characteristics of an effective research report

Research Report Meaning, Characteristics and Types

Table of contents:-, research report meaning, characteristics of good research report, key characteristics of research report, types of research report, stages in preparation of research report, characteristics of a good report.

A research report is a document that conveys the outcomes of a study or investigation. Its purpose is to communicate the research’s findings, conclusions, and implications to a particular audience. This report aims to offer a comprehensive and unbiased overview of the research process, methodology, and results.

Once the researcher has completed data collection , data processing, developing and testing hypotheses, and interpretation of responses, the next important phase in research is the preparation of the research report. A research report is essential for the communication of research findings to its potential users.

The research report must be free from personal bias, external influences, and subjective factors. i.e., it must be free from one’s liking and disliking. The research report must be prepared to meet impersonal needs.

What is Research Report?

According to Lancaster, “A report is a statement of collected and considered facts, so drawn-ups to give clear and concise information to persons who are not already in possession of the full facts of the subject matter of the report”.

When researchers communicate their results in writing, they create a research report. It includes the research methodology, approaches, data collection precautions, research findings, and recommendations for solving related problems. Managers can put this result into action for more effective decision making .

Generally, top management places a higher emphasis on obtaining the research outcome rather than delving into the research procedure. Hence, the research report acts as a presentation that highlights the procedure and methodology adopted by the researcher.

The research report presents the complete procedure in a comprehensive way that in turn helps the management in making crucial decisions. Creating a research report adheres to a specific format, sequence, and writing style.

Enhance the effectiveness of a research report by incorporating various charts, graphs, diagrams, tables, etc. By using different representation techniques, researchers can convince the audience as well as the management in an effective way.

Characteristics of a good research report are listed below:

• Clarity and Completeness
• Reliability
• Comprehensibility and Readability
• Logical Content

The following paragraphs outline the characteristics of a good research report.

1) Accuracy

Report information must be accurate and based on facts, credible sources and data to establish reliability and trustworthiness. It should not be biased by the personal feelings of the writer. The information presented must be as precise as possible.

2) Simplicity

The language of a research report should be as simple as possible to ensure easy understanding. A good report communicates its message clearly and without ambiguity through its language.

It is a document of practical utility; therefore, it should be grammatically accurate, brief, and easily understood. 

Jargon and technical words should be avoided when writing the report. Even in a technical report, there should be restricted use of technical terms if it is to be presented to laymen.

3) Clarity and Completeness

The report must be straightforward, lucid, and comprehensive in every aspect. Ambiguity should be avoided at all costs. Clarity is achieved through the strategic and practical organization of information. Report writers should divide their report into short paragraphs with headings and insert other suitable signposts to enhance clarity. They should: 

• Approach their task systematically, 
• Clarify their purpose, 
• Define their sources, 
• State their findings and 
• Make necessary recommendations. 

A report should concisely convey the key points without unnecessary length, ensuring that the reader’s patience is not lost and ideas are not confused. Many times, people lack the time to read lengthy reports.

However, a report must also be complete. Sometimes, it is important to have a detailed discussion about the facts. A report is not an essay; therefore, points should be added to it.

5) Appearance

A report requires a visually appealing presentation and, whenever feasible, should be attention-grabbing. An effective report depends on the arrangement, organization, format, layout, typography, printing quality, and paper choice. Big companies often produce very attractive and colourful Annual Reports to showcase their achievements and financial performance.

6) Comprehensibility and Readability

Reports should be clear and straightforward for easy understanding. The style of presentation and the choice of words should be attractive to readers. The writer must present the facts in elegant and grammatically correct English so that the reader is compelled to read the report from beginning to end.

Only then does a report serve its purpose. A report written by different individuals on the same subject matter can vary depending on the intended audience.

7) Reliability

Reports should be reliable and should not create an erroneous impression in the minds of readers due to oversight or neglect. The facts presented in a report should be pertinent.

Every fact in a report must align with the central purpose, but it is also vital to ensure that all pertinent information is included.

Irrelevant facts can make a report confusing, and the exclusion of relevant facts can render it incomplete and likely to mislead.

Report writing should not incur unnecessary expenses. Cost-effective methods should be used to maintain a consistent level of quality when communicating the content.

9) Timelines

Reports can be valuable and practical when they reach the readers promptly. Any delay in the submission of reports renders the preparation of reports futile and sometimes obsolete.

10) Logical Content

The points mentioned in a report should be arranged in a step-by-step logical sequence and not haphazardly. Distinctive points should have self-explanatory headings and sub-headings. The scientific accuracy of facts is very essential for a report.

Planning is necessary before a report is prepared, as reports invariably lead to decision-making, and inaccurate facts may result in unsuccessful decisions.

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A research report serves as a means of communicating research findings to the readers effectively.

• Clarity in Information
• Optimal Length
• Objective and Simple Language
• Clear Thinking and Logical Organization
• Engaging Style
• Clarity in Presentation
• Readability
• Best Composition Practices
• Inferences and Conclusions
• Proper References
• Attractive Appearance

i) Clarity in Information

A well-defined research report must define the what, why, who, whom, when, where, and how of the research study. It must help the readers to understand the focus of the information presented.

ii) Optimal Length

The report should strike a balance, being sufficiently brief and appropriately extended. It should cover the subject matter adequately while maintaining the reader’s interest.

iii) Objective and Simple Language

The report should be written in an objective style, employing simple language. Correctness, precision, and clarity should be prioritized, avoiding wordiness, indirection, and pompous language.

iv) Clear Thinking and Logical Organization

An excellent report integrates clear thinking, logical organization, and sound interpretation of the research findings.

v) Engaging Style

It should not be dull; instead, it should captivate and sustain the reader’s interest.

vi) Accuracy

Accuracy is paramount. The report must present facts objectively, eschewing exaggerations and superlatives.

vii) Clarity in Presentation

Presentation clarity is achieved through familiar words, unambiguous statements, and explicit definitions of new concepts or terms.

viii) Coherence

The logical flow of ideas and a coherent sequence of sentences contribute to a smooth continuity of thought.

ix) Readability

Even technical reports should be easily understandable. Translate technicalities into reader-friendly language.

x) Best Composition Practices

Follow best composition practices, ensuring readability through proper paragraphing, short sentences, and the use of illustrations, examples, section headings, charts, graphs, and diagrams.

xi) Inferences and Conclusions

Draw sound inferences and conclusions from statistical tables without repeating them in verbal form.

xii) Proper References

Footnote references should be correctly formatted, and the bibliography should be reasonably complete.

xiii) Attractive Appearance

The report should be visually appealing, maintaining a neat and clean appearance, whether typed or printed.

xiv) Error-Free

The report should be free from all types of mistakes, including language, factual, spelling, and calculation errors.

In striving for these qualities, the researcher enhances the overall quality of the report.

Research reports are of the following types:

• Technical Report
• Manuscripts for Journal Articles
• Thesis and Dissertations
• Other Types of Research Report

1) Technical Report

Technical reports are reports which contain detailed information about the research problem and its findings. These reports are typically subject to review by individuals interested in research methodology. Such reports include detailed descriptions of used methods for research design such as universe selection , sample preparation, designing questionnaire , identifying potential data sources, etc. These reports provide a complete description of every step, method, and tool used. When crafting technical reports, we assume that users possess knowledge of research methodology, which is why the language used in these reports is technical. Technical reports are valuable in situations where there is a need for statistical analysis of collected data. Researchers also employ it in conducting a series of research studies, where they can repetitively use the methodology.

2) Manuscripts for Journal Articles

When authors prepare a report with a particular layout or design for publishing in an academic or scientific journal, it becomes a “manuscript for journal articles”. Journal articles are a concise and complete presentation of a particular research study. While technical reports present a detailed description of all the activities in research, journal articles are known for presenting only a few critical areas or findings of a study. The readers or audience of journal articles include other researchers, management and executives, strategic analysts and the general public, interested in the topic.

In general, a manuscript for a journal article typically ranges from 10 to 30 pages in length. Sometimes there is a page or word limit for preparing the report. Authors primarily submit manuscripts for journal articles online, although they occasionally send paper copies through regular mail.

3) Thesis and Dissertations

Students working towards a Master’s, PhD, or another higher degree generally produce a thesis or dissertation, which is a form of research report. Like other normal research reports, the thesis or dissertation usually describes the design, tools or methods and results of the student’s research in detail.

These reports typically include a detailed section called the literature review, which encompasses relevant literature and previous studies on the topic. Firstly, the work or research of the student is analysed by a professional researcher or an expert in that particular research field, and then the thesis is written under the guidance of a professional supervisor. Dissertations and theses usually span approximately 120 to 300 pages in length.

Generally, the university or institution decides the length of the dissertation or thesis. A distinctive feature of a thesis or a dissertation is that it is quite economical, as it requires few printed and bound copies of the report. Sometimes electronic copies are required to be submitted along with the hard copy of the thesis or dissertations. Compact discs (CDs) are used to generate the electronic copy.

4) Other Types of Research Report

Along with the above-mentioned types, there are some other types of research reports, which are as follows:

• Popular Report
• Interim Report
• Summary Report
• Research Abstract

i) Popular Report

A popular report is prepared for the use of administrators, executives, or managers. It is simple and attractive in the form of a report. Clear and concise statements are used with less technical or statistical terms. Data representation is kept very simple through minimal use of graphs and charts. It has a different format than that of a technical one by liberally using margins and blank spaces. The style of writing a popular report is journalistic and precise. It is written to facilitate reading rapidly and comprehending quickly.

ii) Interim Report

An interim report is a kind of report which is prepared to show the sponsors, the progress of research work before the final presentation of the report. It is prepared when there is a certain time gap between the data collection and presentation. In this scenario, the completed portion of data analysis along with its findings is described in a particular interim report.

iii) Summary Report

This type of report is related to the interest of the general public. The findings of such a report are helpful for the decision making of general users. The language used for preparing a summary report is comprehensive and simple. The inclusion of numerous graphs and tables enhances the report’s overall clarity and comprehension. The main focus of this report is on the objectives, findings, and implications of the research issue.

iv) Research Abstract

The research abstract is a short presentation of the technical report. All the elements of a particular technical report, such as the research problem, objectives, sampling techniques, etc., are described in the research abstract but the description is concise and easy.

Research reports result from meticulous and deliberate work. Consequently, the preparation of the information can be delineated into the following key stages:

1) Logical Understanding and Subject Analysis: This stage involves a comprehensive grasp and analysis of the subject matter.

2) Planning/Designing the Final Outline: In this phase, the final outline of the report is meticulously planned and designed.

3) Write-Up/Preparation of Rough Draft: The report takes shape during this stage through the composition of a rough draft.

4) Polishing/Finalization of the Research Report: The final stage encompasses refining and polishing the report to achieve its ultimate form.

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Logical understanding and subject analysis.

This initial stage focuses on the subject’s development, which can be achieved through two approaches:

• Logical development and
• Chronological development

Logical development relies on mental connections and associations between different aspects facilitated by rational analysis. Typically, this involves progressing from simple to complex elements. In contrast, chronological development follows a sequence of time or events, with instructions or descriptions often adhering to chronological order.

Designing the Final Outline of the Research Report

This marks the second stage in report writing. Once the subject matter is comprehended, the subsequent step involves structuring the report, arranging its components, and outlining them. This stage is also referred to as the planning  and organization stage. While ideas may flow through the author’s mind, they must create a plan, sketch, or design. These are necessary for achieving a harmonious succession to become more accessible, and the author may be unsure where to commence or conclude. Effective communication of research results hinges not only on language but predominantly on the meticulous planning and organization of the report.

Preparation of the Rough Draft

The third stage involves the writing and drafting of the report. This phase is pivotal for the researcher as they translate their research study into written form, articulating what they have accomplished and how they intend to convey it.

The clarity in communication and reporting during this stage is influenced by several factors, including the audience, the technical complexity of the problem, the researcher’s grasp of facts and techniques, their proficiency in the language (communication skills), the completeness of notes and documentation, and the availability of analyzed results.

Depending on these factors, some authors may produce the report with just one or two drafts. In contrast, others, with less command over language and a lack of clarity about the problem and subject matter, may require more time and multiple drafts (first draft, second draft, third draft, fourth draft, etc.).

Finalization of the Research Report

This marks the last stage, potentially the most challenging phase in all formal writing. Constructing the structure is relatively easy, but refining and adding the finishing touches require considerable time. Consider, for instance, the construction of a house. The work progresses swiftly up to the roofing (structure) stage, but the final touches and completion demand a significant amount of time.

The rough draft, whether it is the second draft or the n th draft, must undergo rewriting and polishing to meet the requirements. The meticulous revision of the rough draft is what distinguishes a mediocre piece of writing from a good one. During the polishing and finalization phase, it is crucial to scrutinize the report for weaknesses in the logical development of the subject and the cohesion of its presentation. Additionally, attention should be given to the mechanics of writing, including language, usage, grammar, spelling, and punctuation.

Good research possesses certain characteristics, which are as follows:

• Empirical Basis
• Logical Approach
• Systematic Nature
• Replicability
• Validity and Verifiability
• Theory and Principle Development

1. Empirical Basis: It implies that any conclusion drawn is grounded in hardcore evidence collected from real-life experiences and observations. This foundation provides external validity to research results.

2. Logical Approach: Good research is logical, guided by the rules of reasoning and analytical processes of induction (general to specific) and deduction (particular to the public). Logical reasoning is integral to making research feasible and meaningful in decision-making.

3. Systematic Nature: Good research is systematic, which adheres to a structured set of rules, following specific steps in a defined sequence. Systematic research encourages creative thinking while avoiding reliance on guesswork and intuition to reach conclusions.

4. Replicability: Scientific research designs, procedures, and results should be replicable. This ensures that anyone apart from the original researcher can assess their validity. Researchers can use or replicate results obtained by others, making the procedures and outcomes of the research both replicable and transmittable.

5. Validity and Verifiability: Good research involves precise observation and accurate description. The researcher selects reliable and valid instruments for data collection, employing statistical measures to portray results accurately. The conclusions drawn are correct and verifiable by both the researcher and others.

6. Theory and Principle Development: It contributes to formulating theories and principles, aiding accurate predictions about the variables under study. By making sound generalizations based on observed samples, researchers extend their findings beyond immediate situations, objects, or groups, formulating generalizations or theories about these factors.

1. What are the key characteristics of research report?

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Home » Research Report – Example, Writing Guide and Types

Research Report – Example, Writing Guide and Types

Table of Contents

Research Report

Definition:

Research Report is a written document that presents the results of a research project or study, including the research question, methodology, results, and conclusions, in a clear and objective manner.

The purpose of a research report is to communicate the findings of the research to the intended audience, which could be other researchers, stakeholders, or the general public.

Components of Research Report

Components of Research Report are as follows:

Introduction

The introduction sets the stage for the research report and provides a brief overview of the research question or problem being investigated. It should include a clear statement of the purpose of the study and its significance or relevance to the field of research. It may also provide background information or a literature review to help contextualize the research.

Literature Review

The literature review provides a critical analysis and synthesis of the existing research and scholarship relevant to the research question or problem. It should identify the gaps, inconsistencies, and contradictions in the literature and show how the current study addresses these issues. The literature review also establishes the theoretical framework or conceptual model that guides the research.

Methodology

The methodology section describes the research design, methods, and procedures used to collect and analyze data. It should include information on the sample or participants, data collection instruments, data collection procedures, and data analysis techniques. The methodology should be clear and detailed enough to allow other researchers to replicate the study.

The results section presents the findings of the study in a clear and objective manner. It should provide a detailed description of the data and statistics used to answer the research question or test the hypothesis. Tables, graphs, and figures may be included to help visualize the data and illustrate the key findings.

The discussion section interprets the results of the study and explains their significance or relevance to the research question or problem. It should also compare the current findings with those of previous studies and identify the implications for future research or practice. The discussion should be based on the results presented in the previous section and should avoid speculation or unfounded conclusions.

The conclusion summarizes the key findings of the study and restates the main argument or thesis presented in the introduction. It should also provide a brief overview of the contributions of the study to the field of research and the implications for practice or policy.

The references section lists all the sources cited in the research report, following a specific citation style, such as APA or MLA.

The appendices section includes any additional material, such as data tables, figures, or instruments used in the study, that could not be included in the main text due to space limitations.

Types of Research Report

Types of Research Report are as follows:

Thesis is a type of research report. A thesis is a long-form research document that presents the findings and conclusions of an original research study conducted by a student as part of a graduate or postgraduate program. It is typically written by a student pursuing a higher degree, such as a Master’s or Doctoral degree, although it can also be written by researchers or scholars in other fields.

Research Paper

Research paper is a type of research report. A research paper is a document that presents the results of a research study or investigation. Research papers can be written in a variety of fields, including science, social science, humanities, and business. They typically follow a standard format that includes an introduction, literature review, methodology, results, discussion, and conclusion sections.

Technical Report

A technical report is a detailed report that provides information about a specific technical or scientific problem or project. Technical reports are often used in engineering, science, and other technical fields to document research and development work.

Progress Report

A progress report provides an update on the progress of a research project or program over a specific period of time. Progress reports are typically used to communicate the status of a project to stakeholders, funders, or project managers.

Feasibility Report

A feasibility report assesses the feasibility of a proposed project or plan, providing an analysis of the potential risks, benefits, and costs associated with the project. Feasibility reports are often used in business, engineering, and other fields to determine the viability of a project before it is undertaken.

Field Report

A field report documents observations and findings from fieldwork, which is research conducted in the natural environment or setting. Field reports are often used in anthropology, ecology, and other social and natural sciences.

Experimental Report

An experimental report documents the results of a scientific experiment, including the hypothesis, methods, results, and conclusions. Experimental reports are often used in biology, chemistry, and other sciences to communicate the results of laboratory experiments.

Case Study Report

A case study report provides an in-depth analysis of a specific case or situation, often used in psychology, social work, and other fields to document and understand complex cases or phenomena.

Literature Review Report

A literature review report synthesizes and summarizes existing research on a specific topic, providing an overview of the current state of knowledge on the subject. Literature review reports are often used in social sciences, education, and other fields to identify gaps in the literature and guide future research.

Research Report Example

Following is a Research Report Example sample for Students:

Title: The Impact of Social Media on Academic Performance among High School Students

This study aims to investigate the relationship between social media use and academic performance among high school students. The study utilized a quantitative research design, which involved a survey questionnaire administered to a sample of 200 high school students. The findings indicate that there is a negative correlation between social media use and academic performance, suggesting that excessive social media use can lead to poor academic performance among high school students. The results of this study have important implications for educators, parents, and policymakers, as they highlight the need for strategies that can help students balance their social media use and academic responsibilities.

Introduction:

Social media has become an integral part of the lives of high school students. With the widespread use of social media platforms such as Facebook, Twitter, Instagram, and Snapchat, students can connect with friends, share photos and videos, and engage in discussions on a range of topics. While social media offers many benefits, concerns have been raised about its impact on academic performance. Many studies have found a negative correlation between social media use and academic performance among high school students (Kirschner & Karpinski, 2010; Paul, Baker, & Cochran, 2012).

Given the growing importance of social media in the lives of high school students, it is important to investigate its impact on academic performance. This study aims to address this gap by examining the relationship between social media use and academic performance among high school students.

Methodology:

The study utilized a quantitative research design, which involved a survey questionnaire administered to a sample of 200 high school students. The questionnaire was developed based on previous studies and was designed to measure the frequency and duration of social media use, as well as academic performance.

The participants were selected using a convenience sampling technique, and the survey questionnaire was distributed in the classroom during regular school hours. The data collected were analyzed using descriptive statistics and correlation analysis.

The findings indicate that the majority of high school students use social media platforms on a daily basis, with Facebook being the most popular platform. The results also show a negative correlation between social media use and academic performance, suggesting that excessive social media use can lead to poor academic performance among high school students.

Discussion:

The results of this study have important implications for educators, parents, and policymakers. The negative correlation between social media use and academic performance suggests that strategies should be put in place to help students balance their social media use and academic responsibilities. For example, educators could incorporate social media into their teaching strategies to engage students and enhance learning. Parents could limit their children’s social media use and encourage them to prioritize their academic responsibilities. Policymakers could develop guidelines and policies to regulate social media use among high school students.

Conclusion:

In conclusion, this study provides evidence of the negative impact of social media on academic performance among high school students. The findings highlight the need for strategies that can help students balance their social media use and academic responsibilities. Further research is needed to explore the specific mechanisms by which social media use affects academic performance and to develop effective strategies for addressing this issue.

Limitations:

One limitation of this study is the use of convenience sampling, which limits the generalizability of the findings to other populations. Future studies should use random sampling techniques to increase the representativeness of the sample. Another limitation is the use of self-reported measures, which may be subject to social desirability bias. Future studies could use objective measures of social media use and academic performance, such as tracking software and school records.

Implications:

The findings of this study have important implications for educators, parents, and policymakers. Educators could incorporate social media into their teaching strategies to engage students and enhance learning. For example, teachers could use social media platforms to share relevant educational resources and facilitate online discussions. Parents could limit their children’s social media use and encourage them to prioritize their academic responsibilities. They could also engage in open communication with their children to understand their social media use and its impact on their academic performance. Policymakers could develop guidelines and policies to regulate social media use among high school students. For example, schools could implement social media policies that restrict access during class time and encourage responsible use.

References:

• Kirschner, P. A., & Karpinski, A. C. (2010). Facebook® and academic performance. Computers in Human Behavior, 26(6), 1237-1245.
• Paul, J. A., Baker, H. M., & Cochran, J. D. (2012). Effect of online social networking on student academic performance. Journal of the Research Center for Educational Technology, 8(1), 1-19.
• Pantic, I. (2014). Online social networking and mental health. Cyberpsychology, Behavior, and Social Networking, 17(10), 652-657.
• Rosen, L. D., Carrier, L. M., & Cheever, N. A. (2013). Facebook and texting made me do it: Media-induced task-switching while studying. Computers in Human Behavior, 29(3), 948-958.

Note*: Above mention, Example is just a sample for the students’ guide. Do not directly copy and paste as your College or University assignment. Kindly do some research and Write your own.

Applications of Research Report

Research reports have many applications, including:

• Communicating research findings: The primary application of a research report is to communicate the results of a study to other researchers, stakeholders, or the general public. The report serves as a way to share new knowledge, insights, and discoveries with others in the field.
• Informing policy and practice : Research reports can inform policy and practice by providing evidence-based recommendations for decision-makers. For example, a research report on the effectiveness of a new drug could inform regulatory agencies in their decision-making process.
• Supporting further research: Research reports can provide a foundation for further research in a particular area. Other researchers may use the findings and methodology of a report to develop new research questions or to build on existing research.
• Evaluating programs and interventions : Research reports can be used to evaluate the effectiveness of programs and interventions in achieving their intended outcomes. For example, a research report on a new educational program could provide evidence of its impact on student performance.
• Demonstrating impact : Research reports can be used to demonstrate the impact of research funding or to evaluate the success of research projects. By presenting the findings and outcomes of a study, research reports can show the value of research to funders and stakeholders.
• Enhancing professional development : Research reports can be used to enhance professional development by providing a source of information and learning for researchers and practitioners in a particular field. For example, a research report on a new teaching methodology could provide insights and ideas for educators to incorporate into their own practice.

How to write Research Report

Here are some steps you can follow to write a research report:

• Identify the research question: The first step in writing a research report is to identify your research question. This will help you focus your research and organize your findings.
• Conduct research : Once you have identified your research question, you will need to conduct research to gather relevant data and information. This can involve conducting experiments, reviewing literature, or analyzing data.
• Organize your findings: Once you have gathered all of your data, you will need to organize your findings in a way that is clear and understandable. This can involve creating tables, graphs, or charts to illustrate your results.
• Write the report: Once you have organized your findings, you can begin writing the report. Start with an introduction that provides background information and explains the purpose of your research. Next, provide a detailed description of your research methods and findings. Finally, summarize your results and draw conclusions based on your findings.
• Proofread and edit: After you have written your report, be sure to proofread and edit it carefully. Check for grammar and spelling errors, and make sure that your report is well-organized and easy to read.
• Include a reference list: Be sure to include a list of references that you used in your research. This will give credit to your sources and allow readers to further explore the topic if they choose.
• Format your report: Finally, format your report according to the guidelines provided by your instructor or organization. This may include formatting requirements for headings, margins, fonts, and spacing.

Purpose of Research Report

The purpose of a research report is to communicate the results of a research study to a specific audience, such as peers in the same field, stakeholders, or the general public. The report provides a detailed description of the research methods, findings, and conclusions.

Some common purposes of a research report include:

• Sharing knowledge: A research report allows researchers to share their findings and knowledge with others in their field. This helps to advance the field and improve the understanding of a particular topic.
• Identifying trends: A research report can identify trends and patterns in data, which can help guide future research and inform decision-making.
• Addressing problems: A research report can provide insights into problems or issues and suggest solutions or recommendations for addressing them.
• Evaluating programs or interventions : A research report can evaluate the effectiveness of programs or interventions, which can inform decision-making about whether to continue, modify, or discontinue them.
• Meeting regulatory requirements: In some fields, research reports are required to meet regulatory requirements, such as in the case of drug trials or environmental impact studies.

When to Write Research Report

A research report should be written after completing the research study. This includes collecting data, analyzing the results, and drawing conclusions based on the findings. Once the research is complete, the report should be written in a timely manner while the information is still fresh in the researcher’s mind.

In academic settings, research reports are often required as part of coursework or as part of a thesis or dissertation. In this case, the report should be written according to the guidelines provided by the instructor or institution.

In other settings, such as in industry or government, research reports may be required to inform decision-making or to comply with regulatory requirements. In these cases, the report should be written as soon as possible after the research is completed in order to inform decision-making in a timely manner.

Overall, the timing of when to write a research report depends on the purpose of the research, the expectations of the audience, and any regulatory requirements that need to be met. However, it is important to complete the report in a timely manner while the information is still fresh in the researcher’s mind.

Characteristics of Research Report

There are several characteristics of a research report that distinguish it from other types of writing. These characteristics include:

• Objective: A research report should be written in an objective and unbiased manner. It should present the facts and findings of the research study without any personal opinions or biases.
• Systematic: A research report should be written in a systematic manner. It should follow a clear and logical structure, and the information should be presented in a way that is easy to understand and follow.
• Detailed: A research report should be detailed and comprehensive. It should provide a thorough description of the research methods, results, and conclusions.
• Accurate : A research report should be accurate and based on sound research methods. The findings and conclusions should be supported by data and evidence.
• Organized: A research report should be well-organized. It should include headings and subheadings to help the reader navigate the report and understand the main points.
• Clear and concise: A research report should be written in clear and concise language. The information should be presented in a way that is easy to understand, and unnecessary jargon should be avoided.
• Citations and references: A research report should include citations and references to support the findings and conclusions. This helps to give credit to other researchers and to provide readers with the opportunity to further explore the topic.

Advantages of Research Report

Research reports have several advantages, including:

• Communicating research findings: Research reports allow researchers to communicate their findings to a wider audience, including other researchers, stakeholders, and the general public. This helps to disseminate knowledge and advance the understanding of a particular topic.
• Providing evidence for decision-making : Research reports can provide evidence to inform decision-making, such as in the case of policy-making, program planning, or product development. The findings and conclusions can help guide decisions and improve outcomes.
• Supporting further research: Research reports can provide a foundation for further research on a particular topic. Other researchers can build on the findings and conclusions of the report, which can lead to further discoveries and advancements in the field.
• Demonstrating expertise: Research reports can demonstrate the expertise of the researchers and their ability to conduct rigorous and high-quality research. This can be important for securing funding, promotions, and other professional opportunities.
• Meeting regulatory requirements: In some fields, research reports are required to meet regulatory requirements, such as in the case of drug trials or environmental impact studies. Producing a high-quality research report can help ensure compliance with these requirements.

Limitations of Research Report

Despite their advantages, research reports also have some limitations, including:

• Time-consuming: Conducting research and writing a report can be a time-consuming process, particularly for large-scale studies. This can limit the frequency and speed of producing research reports.
• Expensive: Conducting research and producing a report can be expensive, particularly for studies that require specialized equipment, personnel, or data. This can limit the scope and feasibility of some research studies.
• Limited generalizability: Research studies often focus on a specific population or context, which can limit the generalizability of the findings to other populations or contexts.
• Potential bias : Researchers may have biases or conflicts of interest that can influence the findings and conclusions of the research study. Additionally, participants may also have biases or may not be representative of the larger population, which can limit the validity and reliability of the findings.
• Accessibility: Research reports may be written in technical or academic language, which can limit their accessibility to a wider audience. Additionally, some research may be behind paywalls or require specialized access, which can limit the ability of others to read and use the findings.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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Research report guide: Definition, types, and tips

Last updated

5 March 2024

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From successful product launches or software releases to planning major business decisions, research reports serve many vital functions. They can summarize evidence and deliver insights and recommendations to save companies time and resources. They can reveal the most value-adding actions a company should take.

However, poorly constructed reports can have the opposite effect! Taking the time to learn established research-reporting rules and approaches will equip you with in-demand skills. You’ll be able to capture and communicate information applicable to numerous situations and industries, adding another string to your resume bow.

• What are research reports?

A research report is a collection of contextual data, gathered through organized research, that provides new insights into a particular challenge (which, for this article, is business-related). Research reports are a time-tested method for distilling large amounts of data into a narrow band of focus.

Their effectiveness often hinges on whether the report provides:

Strong, well-researched evidence

Comprehensive analysis

Well-considered conclusions and recommendations

Though the topic possibilities are endless, an effective research report keeps a laser-like focus on the specific questions or objectives the researcher believes are key to achieving success. Many research reports begin as research proposals, which usually include the need for a report to capture the findings of the study and recommend a course of action.

A description of the research method used, e.g., qualitative, quantitative, or other

Statistical analysis

Causal (or explanatory) research (i.e., research identifying relationships between two variables)

Inductive research, also known as ‘theory-building’

Deductive research, such as that used to test theories

Action research, where the research is actively used to drive change

• Importance of a research report

Research reports can unify and direct a company's focus toward the most appropriate strategic action. Of course, spending resources on a report takes up some of the company's human and financial resources. Choosing when a report is called for is a matter of judgment and experience.

Some development models used heavily in the engineering world, such as Waterfall development, are notorious for over-relying on research reports. With Waterfall development, there is a linear progression through each step of a project, and each stage is precisely documented and reported on before moving to the next.

The pace of the business world is faster than the speed at which your authors can produce and disseminate reports. So how do companies strike the right balance between creating and acting on research reports?

The answer lies, again, in the report's defined objectives. By paring down your most pressing interests and those of your stakeholders, your research and reporting skills will be the lenses that keep your company's priorities in constant focus.

Honing your company's primary objectives can save significant amounts of time and align research and reporting efforts with ever-greater precision.

Some examples of well-designed research objectives are:

Proving whether or not a product or service meets customer expectations

Demonstrating the value of a service, product, or business process to your stakeholders and investors

Improving business decision-making when faced with a lack of time or other constraints

Clarifying the relationship between a critical cause and effect for problematic business processes

Prioritizing the development of a backlog of products or product features

Comparing business or production strategies

Evaluating past decisions and predicting future outcomes

• Features of a research report

Research reports generally require a research design phase, where the report author(s) determine the most important elements the report must contain.

Just as there are various kinds of research, there are many types of reports.

Here are the standard elements of almost any research-reporting format:

Report summary. A broad but comprehensive overview of what readers will learn in the full report. Summaries are usually no more than one or two paragraphs and address all key elements of the report. Think of the key takeaways your primary stakeholders will want to know if they don’t have time to read the full document.

Introduction. Include a brief background of the topic, the type of research, and the research sample. Consider the primary goal of the report, who is most affected, and how far along the company is in meeting its objectives.

Methods. A description of how the researcher carried out data collection, analysis, and final interpretations of the data. Include the reasons for choosing a particular method. The methods section should strike a balance between clearly presenting the approach taken to gather data and discussing how it is designed to achieve the report's objectives.

Data analysis. This section contains interpretations that lead readers through the results relevant to the report's thesis. If there were unexpected results, include here a discussion on why that might be. Charts, calculations, statistics, and other supporting information also belong here (or, if lengthy, as an appendix). This should be the most detailed section of the research report, with references for further study. Present the information in a logical order, whether chronologically or in order of importance to the report's objectives.

Conclusion. This should be written with sound reasoning, often containing useful recommendations. The conclusion must be backed by a continuous thread of logic throughout the report.

• How to write a research paper

With a clear outline and robust pool of research, a research paper can start to write itself, but what's a good way to start a research report?

Research report examples are often the quickest way to gain inspiration for your report. Look for the types of research reports most relevant to your industry and consider which makes the most sense for your data and goals.

The research report outline will help you organize the elements of your report. One of the most time-tested report outlines is the IMRaD structure:

Introduction

...and Discussion

Pay close attention to the most well-established research reporting format in your industry, and consider your tone and language from your audience's perspective. Learn the key terms inside and out; incorrect jargon could easily harm the perceived authority of your research paper.

Along with a foundation in high-quality research and razor-sharp analysis, the most effective research reports will also demonstrate well-developed:

Internal logic

Narrative flow

Conclusions and recommendations

Readability, striking a balance between simple phrasing and technical insight

How to gather research data for your report

The validity of research data is critical. Because the research phase usually occurs well before the writing phase, you normally have plenty of time to vet your data.

However, research reports could involve ongoing research, where report authors (sometimes the researchers themselves) write portions of the report alongside ongoing research.

One such research-report example would be an R&D department that knows its primary stakeholders are eager to learn about a lengthy work in progress and any potentially important outcomes.

However you choose to manage the research and reporting, your data must meet robust quality standards before you can rely on it. Vet any research with the following questions in mind:

Does it use statistically valid analysis methods?

Do the researchers clearly explain their research, analysis, and sampling methods?

Did the researchers provide any caveats or advice on how to interpret their data?

Have you gathered the data yourself or were you in close contact with those who did?

Is the source biased?

Usually, flawed research methods become more apparent the further you get through a research report.

It's perfectly natural for good research to raise new questions, but the reader should have no uncertainty about what the data represents. There should be no doubt about matters such as:

Whether the sampling or analysis methods were based on sound and consistent logic

What the research samples are and where they came from

The accuracy of any statistical functions or equations

Validation of testing and measuring processes

When does a report require design validation?

A robust design validation process is often a gold standard in highly technical research reports. Design validation ensures the objects of a study are measured accurately, which lends more weight to your report and makes it valuable to more specialized industries.

Product development and engineering projects are the most common research-report examples that typically involve a design validation process. Depending on the scope and complexity of your research, you might face additional steps to validate your data and research procedures.

If you’re including design validation in the report (or report proposal), explain and justify your data-collection processes. Good design validation builds greater trust in a research report and lends more weight to its conclusions.

Choosing the right analysis method

Just as the quality of your report depends on properly validated research, a useful conclusion requires the most contextually relevant analysis method. This means comparing different statistical methods and choosing the one that makes the most sense for your research.

Most broadly, research analysis comes down to quantitative or qualitative methods (respectively: measurable by a number vs subjectively qualified values). There are also mixed research methods, which bridge the need for merging hard data with qualified assessments and still reach a cohesive set of conclusions.

Some of the most common analysis methods in research reports include:

Significance testing (aka hypothesis analysis), which compares test and control groups to determine how likely the data was the result of random chance.

Regression analysis , to establish relationships between variables, control for extraneous variables , and support correlation analysis.

Correlation analysis (aka bivariate testing), a method to identify and determine the strength of linear relationships between variables. It’s effective for detecting patterns from complex data, but care must be exercised to not confuse correlation with causation.

With any analysis method, it's important to justify which method you chose in the report. You should also provide estimates of the statistical accuracy (e.g., the p-value or confidence level of quantifiable data) of any data analysis.

This requires a commitment to the report's primary aim. For instance, this may be achieving a certain level of customer satisfaction by analyzing the cause and effect of changes to how service is delivered. Even better, use statistical analysis to calculate which change is most positively correlated with improved levels of customer satisfaction.

• Tips for writing research reports

There's endless good advice for writing effective research reports, and it almost all depends on the subjective aims of the people behind the report. Due to the wide variety of research reports, the best tips will be unique to each author's purpose.

Consider the following research report tips in any order, and take note of the ones most relevant to you:

No matter how in depth or detailed your report might be, provide a well-considered, succinct summary. At the very least, give your readers a quick and effective way to get up to speed.

Pare down your target audience (e.g., other researchers, employees, laypersons, etc.), and adjust your voice for their background knowledge and interest levels

For all but the most open-ended research, clarify your objectives, both for yourself and within the report.

Leverage your team members’ talents to fill in any knowledge gaps you might have. Your team is only as good as the sum of its parts.

Justify why your research proposal’s topic will endure long enough to derive value from the finished report.

Consolidate all research and analysis functions onto a single user-friendly platform. There's no reason to settle for less than developer-grade tools suitable for non-developers.

What's the format of a research report?

The research-reporting format is how the report is structured—a framework the authors use to organize their data, conclusions, arguments, and recommendations. The format heavily determines how the report's outline develops, because the format dictates the overall structure and order of information (based on the report's goals and research objectives).

What's the purpose of a research-report outline?

A good report outline gives form and substance to the report's objectives, presenting the results in a readable, engaging way. For any research-report format, the outline should create momentum along a chain of logic that builds up to a conclusion or interpretation.

What's the difference between a research essay and a research report?

There are several key differences between research reports and essays:

Research report:

Ordered into separate sections

More commercial in nature

Often includes infographics

Heavily descriptive

More self-referential

Usually provides recommendations

Research essay

Does not rely on research report formatting

More academically minded

Normally text-only

Less detailed

Omits discussion of methods

Usually non-prescriptive 

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A Practical Guide to Writing Quantitative and Qualitative Research Questions and Hypotheses in Scholarly Articles

Edward barroga.

1 Department of General Education, Graduate School of Nursing Science, St. Luke’s International University, Tokyo, Japan.

Glafera Janet Matanguihan

2 Department of Biological Sciences, Messiah University, Mechanicsburg, PA, USA.

The development of research questions and the subsequent hypotheses are prerequisites to defining the main research purpose and specific objectives of a study. Consequently, these objectives determine the study design and research outcome. The development of research questions is a process based on knowledge of current trends, cutting-edge studies, and technological advances in the research field. Excellent research questions are focused and require a comprehensive literature search and in-depth understanding of the problem being investigated. Initially, research questions may be written as descriptive questions which could be developed into inferential questions. These questions must be specific and concise to provide a clear foundation for developing hypotheses. Hypotheses are more formal predictions about the research outcomes. These specify the possible results that may or may not be expected regarding the relationship between groups. Thus, research questions and hypotheses clarify the main purpose and specific objectives of the study, which in turn dictate the design of the study, its direction, and outcome. Studies developed from good research questions and hypotheses will have trustworthy outcomes with wide-ranging social and health implications.

INTRODUCTION

Scientific research is usually initiated by posing evidenced-based research questions which are then explicitly restated as hypotheses. 1 , 2 The hypotheses provide directions to guide the study, solutions, explanations, and expected results. 3 , 4 Both research questions and hypotheses are essentially formulated based on conventional theories and real-world processes, which allow the inception of novel studies and the ethical testing of ideas. 5 , 6

It is crucial to have knowledge of both quantitative and qualitative research 2 as both types of research involve writing research questions and hypotheses. 7 However, these crucial elements of research are sometimes overlooked; if not overlooked, then framed without the forethought and meticulous attention it needs. Planning and careful consideration are needed when developing quantitative or qualitative research, particularly when conceptualizing research questions and hypotheses. 4

There is a continuing need to support researchers in the creation of innovative research questions and hypotheses, as well as for journal articles that carefully review these elements. 1 When research questions and hypotheses are not carefully thought of, unethical studies and poor outcomes usually ensue. Carefully formulated research questions and hypotheses define well-founded objectives, which in turn determine the appropriate design, course, and outcome of the study. This article then aims to discuss in detail the various aspects of crafting research questions and hypotheses, with the goal of guiding researchers as they develop their own. Examples from the authors and peer-reviewed scientific articles in the healthcare field are provided to illustrate key points.

DEFINITIONS AND RELATIONSHIP OF RESEARCH QUESTIONS AND HYPOTHESES

A research question is what a study aims to answer after data analysis and interpretation. The answer is written in length in the discussion section of the paper. Thus, the research question gives a preview of the different parts and variables of the study meant to address the problem posed in the research question. 1 An excellent research question clarifies the research writing while facilitating understanding of the research topic, objective, scope, and limitations of the study. 5

On the other hand, a research hypothesis is an educated statement of an expected outcome. This statement is based on background research and current knowledge. 8 , 9 The research hypothesis makes a specific prediction about a new phenomenon 10 or a formal statement on the expected relationship between an independent variable and a dependent variable. 3 , 11 It provides a tentative answer to the research question to be tested or explored. 4

Hypotheses employ reasoning to predict a theory-based outcome. 10 These can also be developed from theories by focusing on components of theories that have not yet been observed. 10 The validity of hypotheses is often based on the testability of the prediction made in a reproducible experiment. 8

Conversely, hypotheses can also be rephrased as research questions. Several hypotheses based on existing theories and knowledge may be needed to answer a research question. Developing ethical research questions and hypotheses creates a research design that has logical relationships among variables. These relationships serve as a solid foundation for the conduct of the study. 4 , 11 Haphazardly constructed research questions can result in poorly formulated hypotheses and improper study designs, leading to unreliable results. Thus, the formulations of relevant research questions and verifiable hypotheses are crucial when beginning research. 12

CHARACTERISTICS OF GOOD RESEARCH QUESTIONS AND HYPOTHESES

Excellent research questions are specific and focused. These integrate collective data and observations to confirm or refute the subsequent hypotheses. Well-constructed hypotheses are based on previous reports and verify the research context. These are realistic, in-depth, sufficiently complex, and reproducible. More importantly, these hypotheses can be addressed and tested. 13

There are several characteristics of well-developed hypotheses. Good hypotheses are 1) empirically testable 7 , 10 , 11 , 13 ; 2) backed by preliminary evidence 9 ; 3) testable by ethical research 7 , 9 ; 4) based on original ideas 9 ; 5) have evidenced-based logical reasoning 10 ; and 6) can be predicted. 11 Good hypotheses can infer ethical and positive implications, indicating the presence of a relationship or effect relevant to the research theme. 7 , 11 These are initially developed from a general theory and branch into specific hypotheses by deductive reasoning. In the absence of a theory to base the hypotheses, inductive reasoning based on specific observations or findings form more general hypotheses. 10

TYPES OF RESEARCH QUESTIONS AND HYPOTHESES

Research questions and hypotheses are developed according to the type of research, which can be broadly classified into quantitative and qualitative research. We provide a summary of the types of research questions and hypotheses under quantitative and qualitative research categories in Table 1 .

Research questions in quantitative research

In quantitative research, research questions inquire about the relationships among variables being investigated and are usually framed at the start of the study. These are precise and typically linked to the subject population, dependent and independent variables, and research design. 1 Research questions may also attempt to describe the behavior of a population in relation to one or more variables, or describe the characteristics of variables to be measured ( descriptive research questions ). 1 , 5 , 14 These questions may also aim to discover differences between groups within the context of an outcome variable ( comparative research questions ), 1 , 5 , 14 or elucidate trends and interactions among variables ( relationship research questions ). 1 , 5 We provide examples of descriptive, comparative, and relationship research questions in quantitative research in Table 2 .

Hypotheses in quantitative research

In quantitative research, hypotheses predict the expected relationships among variables. 15 Relationships among variables that can be predicted include 1) between a single dependent variable and a single independent variable ( simple hypothesis ) or 2) between two or more independent and dependent variables ( complex hypothesis ). 4 , 11 Hypotheses may also specify the expected direction to be followed and imply an intellectual commitment to a particular outcome ( directional hypothesis ) 4 . On the other hand, hypotheses may not predict the exact direction and are used in the absence of a theory, or when findings contradict previous studies ( non-directional hypothesis ). 4 In addition, hypotheses can 1) define interdependency between variables ( associative hypothesis ), 4 2) propose an effect on the dependent variable from manipulation of the independent variable ( causal hypothesis ), 4 3) state a negative relationship between two variables ( null hypothesis ), 4 , 11 , 15 4) replace the working hypothesis if rejected ( alternative hypothesis ), 15 explain the relationship of phenomena to possibly generate a theory ( working hypothesis ), 11 5) involve quantifiable variables that can be tested statistically ( statistical hypothesis ), 11 6) or express a relationship whose interlinks can be verified logically ( logical hypothesis ). 11 We provide examples of simple, complex, directional, non-directional, associative, causal, null, alternative, working, statistical, and logical hypotheses in quantitative research, as well as the definition of quantitative hypothesis-testing research in Table 3 .

Research questions in qualitative research

Unlike research questions in quantitative research, research questions in qualitative research are usually continuously reviewed and reformulated. The central question and associated subquestions are stated more than the hypotheses. 15 The central question broadly explores a complex set of factors surrounding the central phenomenon, aiming to present the varied perspectives of participants. 15

There are varied goals for which qualitative research questions are developed. These questions can function in several ways, such as to 1) identify and describe existing conditions ( contextual research question s); 2) describe a phenomenon ( descriptive research questions ); 3) assess the effectiveness of existing methods, protocols, theories, or procedures ( evaluation research questions ); 4) examine a phenomenon or analyze the reasons or relationships between subjects or phenomena ( explanatory research questions ); or 5) focus on unknown aspects of a particular topic ( exploratory research questions ). 5 In addition, some qualitative research questions provide new ideas for the development of theories and actions ( generative research questions ) or advance specific ideologies of a position ( ideological research questions ). 1 Other qualitative research questions may build on a body of existing literature and become working guidelines ( ethnographic research questions ). Research questions may also be broadly stated without specific reference to the existing literature or a typology of questions ( phenomenological research questions ), may be directed towards generating a theory of some process ( grounded theory questions ), or may address a description of the case and the emerging themes ( qualitative case study questions ). 15 We provide examples of contextual, descriptive, evaluation, explanatory, exploratory, generative, ideological, ethnographic, phenomenological, grounded theory, and qualitative case study research questions in qualitative research in Table 4 , and the definition of qualitative hypothesis-generating research in Table 5 .

Qualitative studies usually pose at least one central research question and several subquestions starting with How or What . These research questions use exploratory verbs such as explore or describe . These also focus on one central phenomenon of interest, and may mention the participants and research site. 15

Hypotheses in qualitative research

Hypotheses in qualitative research are stated in the form of a clear statement concerning the problem to be investigated. Unlike in quantitative research where hypotheses are usually developed to be tested, qualitative research can lead to both hypothesis-testing and hypothesis-generating outcomes. 2 When studies require both quantitative and qualitative research questions, this suggests an integrative process between both research methods wherein a single mixed-methods research question can be developed. 1

FRAMEWORKS FOR DEVELOPING RESEARCH QUESTIONS AND HYPOTHESES

Research questions followed by hypotheses should be developed before the start of the study. 1 , 12 , 14 It is crucial to develop feasible research questions on a topic that is interesting to both the researcher and the scientific community. This can be achieved by a meticulous review of previous and current studies to establish a novel topic. Specific areas are subsequently focused on to generate ethical research questions. The relevance of the research questions is evaluated in terms of clarity of the resulting data, specificity of the methodology, objectivity of the outcome, depth of the research, and impact of the study. 1 , 5 These aspects constitute the FINER criteria (i.e., Feasible, Interesting, Novel, Ethical, and Relevant). 1 Clarity and effectiveness are achieved if research questions meet the FINER criteria. In addition to the FINER criteria, Ratan et al. described focus, complexity, novelty, feasibility, and measurability for evaluating the effectiveness of research questions. 14

The PICOT and PEO frameworks are also used when developing research questions. 1 The following elements are addressed in these frameworks, PICOT: P-population/patients/problem, I-intervention or indicator being studied, C-comparison group, O-outcome of interest, and T-timeframe of the study; PEO: P-population being studied, E-exposure to preexisting conditions, and O-outcome of interest. 1 Research questions are also considered good if these meet the “FINERMAPS” framework: Feasible, Interesting, Novel, Ethical, Relevant, Manageable, Appropriate, Potential value/publishable, and Systematic. 14

As we indicated earlier, research questions and hypotheses that are not carefully formulated result in unethical studies or poor outcomes. To illustrate this, we provide some examples of ambiguous research question and hypotheses that result in unclear and weak research objectives in quantitative research ( Table 6 ) 16 and qualitative research ( Table 7 ) 17 , and how to transform these ambiguous research question(s) and hypothesis(es) into clear and good statements.

a These statements were composed for comparison and illustrative purposes only.

b These statements are direct quotes from Higashihara and Horiuchi. 16

a This statement is a direct quote from Shimoda et al. 17

The other statements were composed for comparison and illustrative purposes only.

CONSTRUCTING RESEARCH QUESTIONS AND HYPOTHESES

To construct effective research questions and hypotheses, it is very important to 1) clarify the background and 2) identify the research problem at the outset of the research, within a specific timeframe. 9 Then, 3) review or conduct preliminary research to collect all available knowledge about the possible research questions by studying theories and previous studies. 18 Afterwards, 4) construct research questions to investigate the research problem. Identify variables to be accessed from the research questions 4 and make operational definitions of constructs from the research problem and questions. Thereafter, 5) construct specific deductive or inductive predictions in the form of hypotheses. 4 Finally, 6) state the study aims . This general flow for constructing effective research questions and hypotheses prior to conducting research is shown in Fig. 1 .

Research questions are used more frequently in qualitative research than objectives or hypotheses. 3 These questions seek to discover, understand, explore or describe experiences by asking “What” or “How.” The questions are open-ended to elicit a description rather than to relate variables or compare groups. The questions are continually reviewed, reformulated, and changed during the qualitative study. 3 Research questions are also used more frequently in survey projects than hypotheses in experiments in quantitative research to compare variables and their relationships.

Hypotheses are constructed based on the variables identified and as an if-then statement, following the template, ‘If a specific action is taken, then a certain outcome is expected.’ At this stage, some ideas regarding expectations from the research to be conducted must be drawn. 18 Then, the variables to be manipulated (independent) and influenced (dependent) are defined. 4 Thereafter, the hypothesis is stated and refined, and reproducible data tailored to the hypothesis are identified, collected, and analyzed. 4 The hypotheses must be testable and specific, 18 and should describe the variables and their relationships, the specific group being studied, and the predicted research outcome. 18 Hypotheses construction involves a testable proposition to be deduced from theory, and independent and dependent variables to be separated and measured separately. 3 Therefore, good hypotheses must be based on good research questions constructed at the start of a study or trial. 12

In summary, research questions are constructed after establishing the background of the study. Hypotheses are then developed based on the research questions. Thus, it is crucial to have excellent research questions to generate superior hypotheses. In turn, these would determine the research objectives and the design of the study, and ultimately, the outcome of the research. 12 Algorithms for building research questions and hypotheses are shown in Fig. 2 for quantitative research and in Fig. 3 for qualitative research.

EXAMPLES OF RESEARCH QUESTIONS FROM PUBLISHED ARTICLES

• EXAMPLE 1. Descriptive research question (quantitative research)
• - Presents research variables to be assessed (distinct phenotypes and subphenotypes)
• “BACKGROUND: Since COVID-19 was identified, its clinical and biological heterogeneity has been recognized. Identifying COVID-19 phenotypes might help guide basic, clinical, and translational research efforts.
• RESEARCH QUESTION: Does the clinical spectrum of patients with COVID-19 contain distinct phenotypes and subphenotypes? ” 19
• EXAMPLE 2. Relationship research question (quantitative research)
• - Shows interactions between dependent variable (static postural control) and independent variable (peripheral visual field loss)
• “Background: Integration of visual, vestibular, and proprioceptive sensations contributes to postural control. People with peripheral visual field loss have serious postural instability. However, the directional specificity of postural stability and sensory reweighting caused by gradual peripheral visual field loss remain unclear.
• Research question: What are the effects of peripheral visual field loss on static postural control ?” 20
• EXAMPLE 3. Comparative research question (quantitative research)
• - Clarifies the difference among groups with an outcome variable (patients enrolled in COMPERA with moderate PH or severe PH in COPD) and another group without the outcome variable (patients with idiopathic pulmonary arterial hypertension (IPAH))
• “BACKGROUND: Pulmonary hypertension (PH) in COPD is a poorly investigated clinical condition.
• RESEARCH QUESTION: Which factors determine the outcome of PH in COPD?
• STUDY DESIGN AND METHODS: We analyzed the characteristics and outcome of patients enrolled in the Comparative, Prospective Registry of Newly Initiated Therapies for Pulmonary Hypertension (COMPERA) with moderate or severe PH in COPD as defined during the 6th PH World Symposium who received medical therapy for PH and compared them with patients with idiopathic pulmonary arterial hypertension (IPAH) .” 21
• EXAMPLE 4. Exploratory research question (qualitative research)
• - Explores areas that have not been fully investigated (perspectives of families and children who receive care in clinic-based child obesity treatment) to have a deeper understanding of the research problem
• “Problem: Interventions for children with obesity lead to only modest improvements in BMI and long-term outcomes, and data are limited on the perspectives of families of children with obesity in clinic-based treatment. This scoping review seeks to answer the question: What is known about the perspectives of families and children who receive care in clinic-based child obesity treatment? This review aims to explore the scope of perspectives reported by families of children with obesity who have received individualized outpatient clinic-based obesity treatment.” 22
• EXAMPLE 5. Relationship research question (quantitative research)
• - Defines interactions between dependent variable (use of ankle strategies) and independent variable (changes in muscle tone)
• “Background: To maintain an upright standing posture against external disturbances, the human body mainly employs two types of postural control strategies: “ankle strategy” and “hip strategy.” While it has been reported that the magnitude of the disturbance alters the use of postural control strategies, it has not been elucidated how the level of muscle tone, one of the crucial parameters of bodily function, determines the use of each strategy. We have previously confirmed using forward dynamics simulations of human musculoskeletal models that an increased muscle tone promotes the use of ankle strategies. The objective of the present study was to experimentally evaluate a hypothesis: an increased muscle tone promotes the use of ankle strategies. Research question: Do changes in the muscle tone affect the use of ankle strategies ?” 23

EXAMPLES OF HYPOTHESES IN PUBLISHED ARTICLES

• EXAMPLE 1. Working hypothesis (quantitative research)
• - A hypothesis that is initially accepted for further research to produce a feasible theory
• “As fever may have benefit in shortening the duration of viral illness, it is plausible to hypothesize that the antipyretic efficacy of ibuprofen may be hindering the benefits of a fever response when taken during the early stages of COVID-19 illness .” 24
• “In conclusion, it is plausible to hypothesize that the antipyretic efficacy of ibuprofen may be hindering the benefits of a fever response . The difference in perceived safety of these agents in COVID-19 illness could be related to the more potent efficacy to reduce fever with ibuprofen compared to acetaminophen. Compelling data on the benefit of fever warrant further research and review to determine when to treat or withhold ibuprofen for early stage fever for COVID-19 and other related viral illnesses .” 24
• EXAMPLE 2. Exploratory hypothesis (qualitative research)
• - Explores particular areas deeper to clarify subjective experience and develop a formal hypothesis potentially testable in a future quantitative approach
• “We hypothesized that when thinking about a past experience of help-seeking, a self distancing prompt would cause increased help-seeking intentions and more favorable help-seeking outcome expectations .” 25
• “Conclusion
• Although a priori hypotheses were not supported, further research is warranted as results indicate the potential for using self-distancing approaches to increasing help-seeking among some people with depressive symptomatology.” 25
• EXAMPLE 3. Hypothesis-generating research to establish a framework for hypothesis testing (qualitative research)
• “We hypothesize that compassionate care is beneficial for patients (better outcomes), healthcare systems and payers (lower costs), and healthcare providers (lower burnout). ” 26
• Compassionomics is the branch of knowledge and scientific study of the effects of compassionate healthcare. Our main hypotheses are that compassionate healthcare is beneficial for (1) patients, by improving clinical outcomes, (2) healthcare systems and payers, by supporting financial sustainability, and (3) HCPs, by lowering burnout and promoting resilience and well-being. The purpose of this paper is to establish a scientific framework for testing the hypotheses above . If these hypotheses are confirmed through rigorous research, compassionomics will belong in the science of evidence-based medicine, with major implications for all healthcare domains.” 26
• EXAMPLE 4. Statistical hypothesis (quantitative research)
• - An assumption is made about the relationship among several population characteristics ( gender differences in sociodemographic and clinical characteristics of adults with ADHD ). Validity is tested by statistical experiment or analysis ( chi-square test, Students t-test, and logistic regression analysis)
• “Our research investigated gender differences in sociodemographic and clinical characteristics of adults with ADHD in a Japanese clinical sample. Due to unique Japanese cultural ideals and expectations of women's behavior that are in opposition to ADHD symptoms, we hypothesized that women with ADHD experience more difficulties and present more dysfunctions than men . We tested the following hypotheses: first, women with ADHD have more comorbidities than men with ADHD; second, women with ADHD experience more social hardships than men, such as having less full-time employment and being more likely to be divorced.” 27
• “Statistical Analysis
• ( text omitted ) Between-gender comparisons were made using the chi-squared test for categorical variables and Students t-test for continuous variables…( text omitted ). A logistic regression analysis was performed for employment status, marital status, and comorbidity to evaluate the independent effects of gender on these dependent variables.” 27

EXAMPLES OF HYPOTHESIS AS WRITTEN IN PUBLISHED ARTICLES IN RELATION TO OTHER PARTS

• EXAMPLE 1. Background, hypotheses, and aims are provided
• “Pregnant women need skilled care during pregnancy and childbirth, but that skilled care is often delayed in some countries …( text omitted ). The focused antenatal care (FANC) model of WHO recommends that nurses provide information or counseling to all pregnant women …( text omitted ). Job aids are visual support materials that provide the right kind of information using graphics and words in a simple and yet effective manner. When nurses are not highly trained or have many work details to attend to, these job aids can serve as a content reminder for the nurses and can be used for educating their patients (Jennings, Yebadokpo, Affo, & Agbogbe, 2010) ( text omitted ). Importantly, additional evidence is needed to confirm how job aids can further improve the quality of ANC counseling by health workers in maternal care …( text omitted )” 28
• “ This has led us to hypothesize that the quality of ANC counseling would be better if supported by job aids. Consequently, a better quality of ANC counseling is expected to produce higher levels of awareness concerning the danger signs of pregnancy and a more favorable impression of the caring behavior of nurses .” 28
• “This study aimed to examine the differences in the responses of pregnant women to a job aid-supported intervention during ANC visit in terms of 1) their understanding of the danger signs of pregnancy and 2) their impression of the caring behaviors of nurses to pregnant women in rural Tanzania.” 28
• EXAMPLE 2. Background, hypotheses, and aims are provided
• “We conducted a two-arm randomized controlled trial (RCT) to evaluate and compare changes in salivary cortisol and oxytocin levels of first-time pregnant women between experimental and control groups. The women in the experimental group touched and held an infant for 30 min (experimental intervention protocol), whereas those in the control group watched a DVD movie of an infant (control intervention protocol). The primary outcome was salivary cortisol level and the secondary outcome was salivary oxytocin level.” 29
• “ We hypothesize that at 30 min after touching and holding an infant, the salivary cortisol level will significantly decrease and the salivary oxytocin level will increase in the experimental group compared with the control group .” 29
• EXAMPLE 3. Background, aim, and hypothesis are provided
• “In countries where the maternal mortality ratio remains high, antenatal education to increase Birth Preparedness and Complication Readiness (BPCR) is considered one of the top priorities [1]. BPCR includes birth plans during the antenatal period, such as the birthplace, birth attendant, transportation, health facility for complications, expenses, and birth materials, as well as family coordination to achieve such birth plans. In Tanzania, although increasing, only about half of all pregnant women attend an antenatal clinic more than four times [4]. Moreover, the information provided during antenatal care (ANC) is insufficient. In the resource-poor settings, antenatal group education is a potential approach because of the limited time for individual counseling at antenatal clinics.” 30
• “This study aimed to evaluate an antenatal group education program among pregnant women and their families with respect to birth-preparedness and maternal and infant outcomes in rural villages of Tanzania.” 30
• “ The study hypothesis was if Tanzanian pregnant women and their families received a family-oriented antenatal group education, they would (1) have a higher level of BPCR, (2) attend antenatal clinic four or more times, (3) give birth in a health facility, (4) have less complications of women at birth, and (5) have less complications and deaths of infants than those who did not receive the education .” 30

Research questions and hypotheses are crucial components to any type of research, whether quantitative or qualitative. These questions should be developed at the very beginning of the study. Excellent research questions lead to superior hypotheses, which, like a compass, set the direction of research, and can often determine the successful conduct of the study. Many research studies have floundered because the development of research questions and subsequent hypotheses was not given the thought and meticulous attention needed. The development of research questions and hypotheses is an iterative process based on extensive knowledge of the literature and insightful grasp of the knowledge gap. Focused, concise, and specific research questions provide a strong foundation for constructing hypotheses which serve as formal predictions about the research outcomes. Research questions and hypotheses are crucial elements of research that should not be overlooked. They should be carefully thought of and constructed when planning research. This avoids unethical studies and poor outcomes by defining well-founded objectives that determine the design, course, and outcome of the study.

Disclosure: The authors have no potential conflicts of interest to disclose.

Author Contributions:

• Conceptualization: Barroga E, Matanguihan GJ.
• Methodology: Barroga E, Matanguihan GJ.
• Writing - original draft: Barroga E, Matanguihan GJ.
• Writing - review & editing: Barroga E, Matanguihan GJ.

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Features of Report Writing: A Brief Overview

Features of Report Writing explores key elements like clarity, accuracy, objectivity, structure, visual aids, evidence, and recommendations. These features ensure effective communication by presenting information, substantiating claims with credible evidence, and providing actionable recommendations.

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Table of Contents  

1) What is Report Writing? 

2) Features of Report Writing 

     a) Clarity  

     b) Accuracy  

     c) Visual aids  

     d) Evidence  

     e) Structure  

     f) Recommendations  

     g) Objectivity 

3) Steps to write a Report 

4) Conclusion 

What is Report Writing ?  

Report Writing is a systematic and structured process of gathering, analysing, and presenting information in a formal document. It is a vital communication tool used across various fields, including academia, business, government, and research. Reports serve the purpose of informing, analysing, and making recommendations based on gathered data and research findings .   

The process typically involves:  

a) Defining the purpose and scope of the Report 

b) Conducting thorough research 

c) Organising the collected data 

d) Presenting the information clearly and concisely 

Reports can vary in complexity, from simple one-page documents to extensive research papers, business proposals, or technical manuals. Effective Report Writing requires a keen understanding of the target audience, as well as the ability to convey complex ideas understandably .   

It involves structuring the content logically, ensuring coherence and consistency, and providing evidence-based conclusions or recommendations. Well-written Reports facilitate informed decision-making, problem-solving, and knowledge dissemination within organisations, making them invaluable tools for conveying critical information and contributing to the overall success of various endeavours. 

Features of Report Writing  

To help you create an effective Report, here are some of its Features of Report Writing:  

Clarity  

Clarity in Report Writing is crucial. It ensures that complex ideas and data are presented straightforwardly and understandably. A clear Report leaves no room for ambiguity, allowing readers to grasp the information effortlessly. Achieving clarity involves:  

a) Using simple and precise language 

b) Structuring sentences and paragraphs logically 

c) Employing visuals like charts or graphs for better comprehension 

When a Report is clear, readers can quickly discern the key points, making it an effective tool for conveying information, aiding decision-making, and facilitating meaningful communication in various professional and academic contexts. 

Accuracy   

Accuracy is a pivotal feature in Report Writing, ensuring the information presented is precise, reliable, and error-free. It demands thorough research, attention to detail, and fact-checking to substantiate claims and findings. Inaccurate data can mislead readers and compromise the Report's credibility .   

Writers must verify sources, use reliable data collection methods, and cross-verify information to maintain the Report's accuracy. Precision in language, adherence to established methodologies, and rigorous analysis contribute to the overall accuracy of the Report. A meticulously accurate Report enhances its reliability and builds trust, making it an invaluable tool for informed decision-making and academic discourse. 

Visual aids  

Visual aids are essential components of effective Report Writing, enhancing understanding and retention of information. Graphs, charts, tables, and images simplify complex data, making it accessible to a broad audience. These visuals provide a clear visual representation of trends, comparisons, and patterns, supplementing textual information.   

They are potent tools for emphasising key points, supporting arguments, and enhancing comprehension. Well-designed visuals make the Report visually appealing and help readers absorb information more efficiently. By presenting data visually, Report writers can engage their audience, simplify complex concepts, and reinforce the main ideas, ensuring the Report's message is communicated effectively.  

Evidence  

Evidence in Report Writing refers to factual data, examples, or expert opinions supporting the document's claims and conclusions. It serves as the foundation upon which reliable arguments and analyses are built. Strong evidence enhances the Report's credibility, persuading readers of the validity of the presented information.   

Researchers often rely on empirical studies, statistical data, surveys, or credible sources to substantiate their findings. They have correctly cited evidence not only validates the Report's assertions but also demonstrates the writer's thorough research and expertise on the topic. Evidence strengthens the Report's integrity, assuring readers that the information presented is well-grounded and trustworthy.    

Structure  

Structure in Report Writing refers to the organised framework that guides the presentation of information. A well-defined structure ensures logical flow, enabling readers to navigate the content seamlessly. It typically includes sections such as introduction, methodology, findings, analysis, conclusions, and recommendations.   

Each section has a specific purpose, contributing to the overall coherence of the Report. The structure provides a roadmap for the writer, ensuring that essential points are covered systematically. Clear headings and subheadings delineate different topics, enhancing readability. A structured Report improves comprehension and reflects the writer's professionalism and attention to detail, making the document more impactful and persuasive to its intended audience. 

Recommendations  

Recommendations in Report Writing are crucial suggestions based on the findings and analysis. These actionable insights offer practical solutions, strategies, or actions that address the issues highlighted in the Report. Recommendations are grounded in evidence, making them credible and valuable for decision-makers.    

Well-crafted recommendations are specific, feasible, and tailored to the context, providing a clear pathway for implementing changes or improvements. They serve as a guide for stakeholders, helping them make informed choices and take adequate measures. The quality and relevance of recommendations often determine the Report's impact, as they empower organisations and individuals to make positive changes based on the Report's insights. 

Objectivity  

Objectivity in Report Writing refers to presenting information and analysis in an unbiased, impartial, and fair manner. It demands writers separate personal opinions or emotions from presenting facts and findings. Objective Reports rely on empirical evidence, verifiable data, and expert opinions, ensuring the content is reliable and credible.   

By maintaining objectivity, the writer establishes trust with the readers, enabling them to form opinions based on the presented information. Objectivity is essential in research and professional contexts, allowing for an accurate representation of reality and fostering a balanced, rational discussion of the topic.  

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Steps to write a Report  

Writing a comprehensive Report involves structured steps that ensure the document is well-organised, informative, and coherent. Here's a detailed overview of the essential steps to write a Report: 

a) Define purpose : Clarify the Report's objectives and scope. 

b) Research : Gather relevant information from credible sources.  

c) Organise : Structure the Report with clear sections and headings. 

d) Write introduction : Provide context, purpose, and research questions. 

e) Methodology : Explain research methods and data collection processes.  

f) Present findings : Display data using visuals, charts, or tables.  

g) Analysis : Interpret results, discuss trends, and draw connections. 

h) Conclusions : Summarise critical points, answering research questions.  

i) Recommendations : Suggest actionable solutions based on findings.  

j) Edit and proofread : Revise for clarity, coherence, and accuracy.  

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Conclusion  

Understanding the art of Report Writing is essential for effective communication. There are some Features of Report Writing which, when followed, can be efficiently prepared. These features include following a structured approach, defining clear objectives, conducting thorough research, and presenting findings logically and objectively. 

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• Research Report: Definition, Types + [Writing Guide]

One of the reasons for carrying out research is to add to the existing body of knowledge. Therefore, when conducting research, you need to document your processes and findings in a research report. 

With a research report, it is easy to outline the findings of your systematic investigation and any gaps needing further inquiry. Knowing how to create a detailed research report will prove useful when you need to conduct research.  

What is a Research Report?

A research report is a well-crafted document that outlines the processes, data, and findings of a systematic investigation. It is an important document that serves as a first-hand account of the research process, and it is typically considered an objective and accurate source of information.

In many ways, a research report can be considered as a summary of the research process that clearly highlights findings, recommendations, and other important details. Reading a well-written research report should provide you with all the information you need about the core areas of the research process.

Features of a Research Report 

So how do you recognize a research report when you see one? Here are some of the basic features that define a research report. 

• It is a detailed presentation of research processes and findings, and it usually includes tables and graphs. 
• It is written in a formal language.
• A research report is usually written in the third person.
• It is informative and based on first-hand verifiable information.
• It is formally structured with headings, sections, and bullet points.
• It always includes recommendations for future actions. 

Types of Research Report 

The research report is classified based on two things; nature of research and target audience.

Nature of Research

• Qualitative Research Report

This is the type of report written for qualitative research . It outlines the methods, processes, and findings of a qualitative method of systematic investigation. In educational research, a qualitative research report provides an opportunity for one to apply his or her knowledge and develop skills in planning and executing qualitative research projects.

A qualitative research report is usually descriptive in nature. Hence, in addition to presenting details of the research process, you must also create a descriptive narrative of the information.

• Quantitative Research Report

A quantitative research report is a type of research report that is written for quantitative research. Quantitative research is a type of systematic investigation that pays attention to numerical or statistical values in a bid to find answers to research questions. 

In this type of research report, the researcher presents quantitative data to support the research process and findings. Unlike a qualitative research report that is mainly descriptive, a quantitative research report works with numbers; that is, it is numerical in nature. 

Target Audience

Also, a research report can be said to be technical or popular based on the target audience. If you’re dealing with a general audience, you would need to present a popular research report, and if you’re dealing with a specialized audience, you would submit a technical report. 

• Technical Research Report

A technical research report is a detailed document that you present after carrying out industry-based research. This report is highly specialized because it provides information for a technical audience; that is, individuals with above-average knowledge in the field of study. 

In a technical research report, the researcher is expected to provide specific information about the research process, including statistical analyses and sampling methods. Also, the use of language is highly specialized and filled with jargon. 

Examples of technical research reports include legal and medical research reports. 

• Popular Research Report

A popular research report is one for a general audience; that is, for individuals who do not necessarily have any knowledge in the field of study. A popular research report aims to make information accessible to everyone. 

It is written in very simple language, which makes it easy to understand the findings and recommendations. Examples of popular research reports are the information contained in newspapers and magazines. 

Importance of a Research Report 

• Knowledge Transfer: As already stated above, one of the reasons for carrying out research is to contribute to the existing body of knowledge, and this is made possible with a research report. A research report serves as a means to effectively communicate the findings of a systematic investigation to all and sundry.  
• Identification of Knowledge Gaps: With a research report, you’d be able to identify knowledge gaps for further inquiry. A research report shows what has been done while hinting at other areas needing systematic investigation. 
• In market research, a research report would help you understand the market needs and peculiarities at a glance. 
• A research report allows you to present information in a precise and concise manner. 
• It is time-efficient and practical because, in a research report, you do not have to spend time detailing the findings of your research work in person. You can easily send out the report via email and have stakeholders look at it. 

Guide to Writing a Research Report

A lot of detail goes into writing a research report, and getting familiar with the different requirements would help you create the ideal research report. A research report is usually broken down into multiple sections, which allows for a concise presentation of information.

Structure and Example of a Research Report

This is the title of your systematic investigation. Your title should be concise and point to the aims, objectives, and findings of a research report. 

• Table of Contents

This is like a compass that makes it easier for readers to navigate the research report.

An abstract is an overview that highlights all important aspects of the research including the research method, data collection process, and research findings. Think of an abstract as a summary of your research report that presents pertinent information in a concise manner. 

An abstract is always brief; typically 100-150 words and goes straight to the point. The focus of your research abstract should be the 5Ws and 1H format – What, Where, Why, When, Who and How. 

• Introduction

Here, the researcher highlights the aims and objectives of the systematic investigation as well as the problem which the systematic investigation sets out to solve. When writing the report introduction, it is also essential to indicate whether the purposes of the research were achieved or would require more work.

In the introduction section, the researcher specifies the research problem and also outlines the significance of the systematic investigation. Also, the researcher is expected to outline any jargons and terminologies that are contained in the research.  

• Literature Review

A literature review is a written survey of existing knowledge in the field of study. In other words, it is the section where you provide an overview and analysis of different research works that are relevant to your systematic investigation. 

It highlights existing research knowledge and areas needing further investigation, which your research has sought to fill. At this stage, you can also hint at your research hypothesis and its possible implications for the existing body of knowledge in your field of study. 

• An Account of Investigation

This is a detailed account of the research process, including the methodology, sample, and research subjects. Here, you are expected to provide in-depth information on the research process including the data collection and analysis procedures. 

In a quantitative research report, you’d need to provide information surveys, questionnaires and other quantitative data collection methods used in your research. In a qualitative research report, you are expected to describe the qualitative data collection methods used in your research including interviews and focus groups. 

In this section, you are expected to present the results of the systematic investigation. 

This section further explains the findings of the research, earlier outlined. Here, you are expected to present a justification for each outcome and show whether the results are in line with your hypotheses or if other research studies have come up with similar results.

• Conclusions

This is a summary of all the information in the report. It also outlines the significance of the entire study. 

• References and Appendices

This section contains a list of all the primary and secondary research sources. 

Tips for Writing a Research Report

• Define the Context for the Report

As is obtainable when writing an essay, defining the context for your research report would help you create a detailed yet concise document. This is why you need to create an outline before writing so that you do not miss out on anything. 

• Define your Audience

Writing with your audience in mind is essential as it determines the tone of the report. If you’re writing for a general audience, you would want to present the information in a simple and relatable manner. For a specialized audience, you would need to make use of technical and field-specific terms. 

• Include Significant Findings

The idea of a research report is to present some sort of abridged version of your systematic investigation. In your report, you should exclude irrelevant information while highlighting only important data and findings. 

• Include Illustrations

Your research report should include illustrations and other visual representations of your data. Graphs, pie charts, and relevant images lend additional credibility to your systematic investigation.

• Choose the Right Title

A good research report title is brief, precise, and contains keywords from your research. It should provide a clear idea of your systematic investigation so that readers can grasp the entire focus of your research from the title. 

• Proofread the Report

Before publishing the document, ensure that you give it a second look to authenticate the information. If you can, get someone else to go through the report, too, and you can also run it through proofreading and editing software. 

How to Gather Research Data for Your Report  

• Understand the Problem

Every research aims at solving a specific problem or set of problems, and this should be at the back of your mind when writing your research report. Understanding the problem would help you to filter the information you have and include only important data in your report. 

• Know what your report seeks to achieve

This is somewhat similar to the point above because, in some way, the aim of your research report is intertwined with the objectives of your systematic investigation. Identifying the primary purpose of writing a research report would help you to identify and present the required information accordingly. 

• Identify your audience

Knowing your target audience plays a crucial role in data collection for a research report. If your research report is specifically for an organization, you would want to present industry-specific information or show how the research findings are relevant to the work that the company does. 

• Create Surveys/Questionnaires

A survey is a research method that is used to gather data from a specific group of people through a set of questions. It can be either quantitative or qualitative. 

A survey is usually made up of structured questions, and it can be administered online or offline. However, an online survey is a more effective method of research data collection because it helps you save time and gather data with ease. 

You can seamlessly create an online questionnaire for your research on Formplus . With the multiple sharing options available in the builder, you would be able to administer your survey to respondents in little or no time. 

Formplus also has a report summary too l that you can use to create custom visual reports for your research.

Step-by-step guide on how to create an online questionnaire using Formplus  

• Sign into Formplus

In the Formplus builder, you can easily create different online questionnaires for your research by dragging and dropping preferred fields into your form. To access the Formplus builder, you will need to create an account on Formplus. 

Once you do this, sign in to your account and click on Create new form to begin. 

• Edit Form Title : Click on the field provided to input your form title, for example, “Research Questionnaire.”
• Edit Form : Click on the edit icon to edit the form.
• Add Fields : Drag and drop preferred form fields into your form in the Formplus builder inputs column. There are several field input options for questionnaires in the Formplus builder. 
• Edit fields
• Click on “Save”
• Form Customization: With the form customization options in the form builder, you can easily change the outlook of your form and make it more unique and personalized. Formplus allows you to change your form theme, add background images, and even change the font according to your needs. 
• Multiple Sharing Options: Formplus offers various form-sharing options, which enables you to share your questionnaire with respondents easily. You can use the direct social media sharing buttons to share your form link to your organization’s social media pages.  You can also send out your survey form as email invitations to your research subjects too. If you wish, you can share your form’s QR code or embed it on your organization’s website for easy access. 

Conclusion  

Always remember that a research report is just as important as the actual systematic investigation because it plays a vital role in communicating research findings to everyone else. This is why you must take care to create a concise document summarizing the process of conducting any research. 

In this article, we’ve outlined essential tips to help you create a research report. When writing your report, you should always have the audience at the back of your mind, as this would set the tone for the document. 

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Home Market Research

Research Reports: Definition and How to Write Them

Reports are usually spread across a vast horizon of topics but are focused on communicating information about a particular topic and a niche target market. The primary motive of research reports is to convey integral details about a study for marketers to consider while designing new strategies.

Certain events, facts, and other information based on incidents need to be relayed to the people in charge, and creating research reports is the most effective communication tool. Ideal research reports are extremely accurate in the offered information with a clear objective and conclusion. These reports should have a clean and structured format to relay information effectively.

What are Research Reports?

Research reports are recorded data prepared by researchers or statisticians after analyzing the information gathered by conducting organized research, typically in the form of surveys or qualitative methods .

A research report is a reliable source to recount details about a conducted research. It is most often considered to be a true testimony of all the work done to garner specificities of research.

The various sections of a research report are:

• Background/Introduction
• Implemented Methods
• Results based on Analysis
• Deliberation

Learn more: Quantitative Research

Components of Research Reports

Research is imperative for launching a new product/service or a new feature. The markets today are extremely volatile and competitive due to new entrants every day who may or may not provide effective products. An organization needs to make the right decisions at the right time to be relevant in such a market with updated products that suffice customer demands.

The details of a research report may change with the purpose of research but the main components of a report will remain constant. The research approach of the market researcher also influences the style of writing reports. Here are seven main components of a productive research report:

• Research Report Summary: The entire objective along with the overview of research are to be included in a summary which is a couple of paragraphs in length. All the multiple components of the research are explained in brief under the report summary.  It should be interesting enough to capture all the key elements of the report.
• Research Introduction: There always is a primary goal that the researcher is trying to achieve through a report. In the introduction section, he/she can cover answers related to this goal and establish a thesis which will be included to strive and answer it in detail.  This section should answer an integral question: “What is the current situation of the goal?”.  After the research design was conducted, did the organization conclude the goal successfully or they are still a work in progress –  provide such details in the introduction part of the research report.
• Research Methodology: This is the most important section of the report where all the important information lies. The readers can gain data for the topic along with analyzing the quality of provided content and the research can also be approved by other market researchers . Thus, this section needs to be highly informative with each aspect of research discussed in detail.  Information needs to be expressed in chronological order according to its priority and importance. Researchers should include references in case they gained information from existing techniques.
• Research Results: A short description of the results along with calculations conducted to achieve the goal will form this section of results. Usually, the exposition after data analysis is carried out in the discussion part of the report.

Learn more: Quantitative Data

• Research Discussion: The results are discussed in extreme detail in this section along with a comparative analysis of reports that could probably exist in the same domain. Any abnormality uncovered during research will be deliberated in the discussion section.  While writing research reports, the researcher will have to connect the dots on how the results will be applicable in the real world.
• Research References and Conclusion: Conclude all the research findings along with mentioning each and every author, article or any content piece from where references were taken.

Learn more: Qualitative Observation

15 Tips for Writing Research Reports

Writing research reports in the manner can lead to all the efforts going down the drain. Here are 15 tips for writing impactful research reports:

• Prepare the context before starting to write and start from the basics:  This was always taught to us in school – be well-prepared before taking a plunge into new topics. The order of survey questions might not be the ideal or most effective order for writing research reports. The idea is to start with a broader topic and work towards a more specific one and focus on a conclusion or support, which a research should support with the facts.  The most difficult thing to do in reporting, without a doubt is to start. Start with the title, the introduction, then document the first discoveries and continue from that. Once the marketers have the information well documented, they can write a general conclusion.
• Keep the target audience in mind while selecting a format that is clear, logical and obvious to them:  Will the research reports be presented to decision makers or other researchers? What are the general perceptions around that topic? This requires more care and diligence. A researcher will need a significant amount of information to start writing the research report. Be consistent with the wording, the numbering of the annexes and so on. Follow the approved format of the company for the delivery of research reports and demonstrate the integrity of the project with the objectives of the company.
• Have a clear research objective: A researcher should read the entire proposal again, and make sure that the data they provide contributes to the objectives that were raised from the beginning. Remember that speculations are for conversations, not for research reports, if a researcher speculates, they directly question their own research.
• Establish a working model:  Each study must have an internal logic, which will have to be established in the report and in the evidence. The researchers’ worst nightmare is to be required to write research reports and realize that key questions were not included.

Learn more: Quantitative Observation

• Gather all the information about the research topic. Who are the competitors of our customers? Talk to other researchers who have studied the subject of research, know the language of the industry. Misuse of the terms can discourage the readers of research reports from reading further.
• Read aloud while writing. While reading the report, if the researcher hears something inappropriate, for example, if they stumble over the words when reading them, surely the reader will too. If the researcher can’t put an idea in a single sentence, then it is very long and they must change it so that the idea is clear to everyone.
• Check grammar and spelling. Without a doubt, good practices help to understand the report. Use verbs in the present tense. Consider using the present tense, which makes the results sound more immediate. Find new words and other ways of saying things. Have fun with the language whenever possible.
• Discuss only the discoveries that are significant. If some data are not really significant, do not mention them. Remember that not everything is truly important or essential within research reports.

Learn more: Qualitative Data

• Try and stick to the survey questions. For example, do not say that the people surveyed “were worried” about an research issue , when there are different degrees of concern.
• The graphs must be clear enough so that they understand themselves. Do not let graphs lead the reader to make mistakes: give them a title, include the indications, the size of the sample, and the correct wording of the question.
• Be clear with messages. A researcher should always write every section of the report with an accuracy of details and language.
• Be creative with titles – Particularly in segmentation studies choose names “that give life to research”. Such names can survive for a long time after the initial investigation.
• Create an effective conclusion: The conclusion in the research reports is the most difficult to write, but it is an incredible opportunity to excel. Make a precise summary. Sometimes it helps to start the conclusion with something specific, then it describes the most important part of the study, and finally, it provides the implications of the conclusions.
• Get a couple more pair of eyes to read the report. Writers have trouble detecting their own mistakes. But they are responsible for what is presented. Ensure it has been approved by colleagues or friends before sending the find draft out.

Learn more: Market Research and Analysis

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How to Write Effective Research Reports

Frankline kibuacha | dec. 02, 2022 | 3 min. read.

A research report is a document that summarizes and provides an analysis of the findings of a research project. It is an important document that serves as a first-hand account of the research process, data, and findings of a research study, and it is typically considered an objective and accurate source of information.

There are a few questions a research report should answer:

• What are you researching?
• What is the goal of your research?
• What are your methods for researching?
• What did you find in your research?
• How does this compare to other findings?
• And what is the impact of this finding on the world?

A research report is normally organized into three broad sections. First, an introduction provides a brief background on the topic and introduces the reader to your perspective. The second section is the body of the report, which should include the research findings and supporting evidence. Finally, the conclusion, which summarizes your arguments and the implications of your study for future research.

Every year, GeoPoll carries out hundreds of research studies and produces reports on several topics, both for clients and internally commissioned studies. In this article, we highlight some tips for writing great reports from our experience.

Tips for writing excellent research reports

• Start from the basics – with an outline – It is a good idea to outline the research context and findings before taking the plunge, as it helps with the flow and structure of the research report. Once you have the broader information well documented, filling the gaps with the content and findings becomes more straightforward and sets the tone for the report.
• Consider the target audience – To guide the report, always keep the target audience in mind and then select a format that is clear, logical and obvious to the audience. A report meant for top decision-makers, for example, could be more concise than one meant for other researchers. Writing for the audience ensures that the research findings help the cause, so consider writing in their language to make it easy to understand at their level.
• Answer the research questions – Every effective research starts with a clear objective. In writing the report, make sure that the data provided contribute to the goal, which is, in reality, the real purpose for conducting the research in the first place.
• Be simple and clear – Research reports need not be complicated. Aim to write the report with an accuracy of details and language that is simplest and clearest to the reader. Use clear titles that clearly describe the following section in a way that readers will want to get into.
• Provide the methodology implemented – Researchers should also include a summary of the methods used to conduct the research, which provides the overall approaches and perspectives of the research process. The methodology details aspects such as the research objectives, the sample used , broken down into demographics such as gender, location, age, and other sample characteristics, data collection modes used, and data analysis methods. Sharing your methodology gives legitimacy to your research.
• Choose graphs correctly – Research reports often feature graphs to bring out data clearly. To fulfill this purpose, the graphs you use in your report must be clear enough so that the readers understand them themselves. Use clear titles, try and include the original question, and choose the best chart types to represent the data.
• Remain relevant – Not everything is genuinely essential to a research report, and you should aim at prioritizing only the significant discoveries. The idea of a research report is to present an abridged yet impactful version of your research, and it’s OK to exclude irrelevant information while highlighting only essential data and findings.
• Grammar and spelling are imperative – Even more important than most writings, research reports need to be written following the best language practices to help to understand the report and not unconsciously water down the seriousness of the information. Read aloud while writing to put yourself in the shoes of the reader. Use grammar and spell-checking tools and engage other people to proofread the report to ensure it reads well for the target audience.
• Choose an impactful title – A good research report title is brief, precise, and provides a clear idea of the underlying research so that readers can grasp the entire focus of your research from the title.
• Shoot for a strong conclusion – The conclusion in the research reports is primarily important because it summarizes the information and recommendations, and often, some readers skim through to the conclusion. Make a precise summary, highlight the findings that stand out, and provide the implications or courses of action derived from the research findings.

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Section 1- Evidence-based practice (EBP)

Chapter 6: Components of a Research Report

Components of a research report.

Partido, B.B.

Elements of  research report

The research report contains four main areas:

• Introduction – What is the issue? What is known? What is not known? What are you trying to find out? This sections ends with the purpose and specific aims of the study.
• Methods – The recipe for the study. If someone wanted to perform the same study, what information would they need? How will you answer your research question? This part usually contains subheadings: Participants, Instruments, Procedures, Data Analysis,
• Results – What was found? This is organized by specific aims and provides the results of the statistical analysis.
• Discussion – How do the results fit in with the existing  literature? What were the limitations and areas of future research?

Formalized Curiosity for Knowledge and Innovation Copyright © by partido1. All Rights Reserved.

Your Article Library

Top 11 characteristics of a good report.

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This article throws light upon the top eleven characteristics of a good report. The characteristics are: 1. Simplicity 2. Clarity 3. Brevity 4. Positivity 5. Punctuation 6. Approach 7. Readability 8. Accuracy 9. Logical Sequence 10. Proper Form 11. Presentation.

Characteristic # 1. Simplicity:

The language shall be as simple as possible so that a report is easily understandable. Jargons and technical words should be avoided. Even in a technical report there shall be restricted use of technical terms if it has to be presented to laymen.

Characteristic # 2. Clarity:

The language shall be lucid and straight, clearly expressing what is intended to be expressed. For that the report has to be written in correct form and following correct steps.

Characteristic # 3. Brevity:

A report shall not be unnecessarily long so that the patience of the reader is not lost and there is no confusion of ideas. But, at the same time, a report must be complete. A report is not an essay.

Characteristic # 4. Positivity:

As far as possible positive statements should be made instead of negative ones. For example, it is better to say what should be done and not what should not be done.

Characteristic # 5. Punctuation :

Punctuations have to be carefully and correctly used otherwise the meaning of sentences may be misunder­stood or misrepresented.

Characteristic # 6. Approach:

There are two types of approaches: (a) Per­son—When a report is written based on personal enquiry or obser­vations, the approach shall be personal and the sentences shall be in the first person and in direct speech, (b) Impersonal—When a report is prepared as a source of information and when it is merely factual (e.g. a report on a meeting), the approach shall be impersonal and the sentences shall be in the third person and in indirect speech.

Characteristic # 7. Readability:

The keynote of a report is readability. The style of presentation and the diction (use of words) shall be such that the readers find it attractive and he is compelled to read the report from the beginning to the end.’ Then only a report serves its purpose. A report on the same subject matter can be written differ­ently for different classes of readers.

Characteristic # 8. Accuracy:

A report shall be accurate when facts are stated in it. It shall not be biased with personal feelings of the writer.

Characteristic # 9. Logical Sequence:

The points in a report shall be arranged with a logical sequence, step by step and not in a haphazard manner. A planning is necessary before a report is prepared.

Characteristic # 10. Proper Form:

A report must be in the proper form. Some­times there are statutory forms to follow.

Characteristic # 11. Presentation:

A report needs an attractive presentation. It depends on the quality of typing or printing as well as quality of paper used. Big companies make very attractive and colourful Annual Reports.

Related Articles:

• Principles of a Good Research Report
• Report Control System in Large Organisations | Preparation of a Report

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Literature Searching

Characteristics of a good research question

The first step in a literature search is to construct a well-defined question.  This helps in ensuring a comprehensive and efficient search of the available literature for relevant publications on your topic.  The well-constructed research question provides guidance for determining search terms and search strategy parameters.

A good or well-constructed research question is:

• Original and of interest to the researcher and the outside world
• It is clear and focused: it provides enough specifics that it is easy to understand its purpose and it is narrow enough that it can be answered. If the question is too broad it may not be possible to answer it thoroughly. If it is too narrow you may not find enough resources or information to develop a strong argument or research hypothesis.  
• The question concept is researchable in terms of time and access to a suitable amount of quality research resources.
• It is analytical rather than descriptive.  The research question should allow you to produce an analysis of an issue or problem rather than a simple description of it.  In other words, it is not answerable with a simple “yes” or “no” but requires a synthesis and analysis of ideas and sources.
• The results are potentially important and may change current ideas and/or practice
• And there is the potential to develop further projects with similar themes

The question you ask should be developed for the discipline you are studying. A question appropriate for Physical Therapy, for instance, is different from an appropriate one in Sociology, Political Science or Microbiology .

The well-constructed question provides guidance for determining search terms and search strategy parameters. The process of developing a good question to research involves taking your topic and breaking each aspect of it down into its component parts. 

One well-established way that can be used both for creating research questions and developing strategies is known as PICO(T). The PICO framework was designed primarily for questions that include clinical interventions and comparisons, however other types of questions may also be able to follow its principles.  If the PICO framework does not precisely fit your question, using its principles can help you to think about what you want to explore even if you do not end up with a true PICO question.

References/Additional Resources

Fandino W. (2019). Formulating a good research question: Pearls and pitfalls.   Indian journal of anaesthesia ,  63 (8), 611–616. 

Vandenbroucke, J. P., & Pearce, N. (2018). From ideas to studies: how to get ideas and sharpen them into research questions .  Clinical epidemiology ,  10 , 253–264.

Ratan, S. K., Anand, T., & Ratan, J. (2019). Formulation of Research Question - Stepwise Approach .  Journal of Indian Association of Pediatric Surgeons ,  24 (1), 15–20.

Lipowski, E.E. (2008). Developing great research questions. American Journal of Health-System Pharmacy, 65(17) , 1667–1670.

FINER Criteria

Another set of criteria for developing a research question was proposed by Hulley (2013) and is known as the FINER criteria. 

FINER stands for:

Feasible – Writing a feasible research question means that it CAN be answered under objective aspects like time, scope, resources, expertise, or funding. Good questions must be amenable to the formulation of clear hypotheses.

Interesting – The question or topic should be of interest to the researcher and the outside world. It should have a clinical and/or educational significance – the “so what?” factor. 

Novel – In scientific literature, novelty defines itself by being an answer to an existing gap in knowledge. Filling one of these gaps is highly rewarding for any researcher as it may represent a real difference in peoples’ lives.

Good research leads to new information. An investigation which simply reiterates what is previously proven is not worth the effort and cost. A question doesn’t have to be completely original. It may ask whether an earlier observation could be replicated, whether the results in one population also apply to others, or whether enhanced measurement methods can make clear the relationship between two variables.  

Ethical – In empirical research, ethics is an absolute MUST. Make sure that safety and confidentiality measures are addressed, and according to the necessary IRB protocols.

Relevant – An idea that is considered relevant in the healthcare community has better chances to be discussed upon by a larger number of researchers and recognized experts, leading to innovation and rapid information dissemination.

The results could potentially be important and may change current ideas and/or practice.

Cummings, S.R., Browner, W.S., & Hulley, S.B. (2013). Conceiving the research question and developing the study plan. In: Designing clinical research (Hulley, S. R. Cummings, W. S. Browner, D. Grady, & T. B. Newman, Eds.; Fourth edition.). Wolters Kluwer/Lippincott Williams & Wilkins. Pp. 14-22.    

• << Previous: Major Steps in a Literature Search
• Next: Types of Research Questions >>

• Research Report
• Post last modified: 11 January 2022
• Reading time: 25 mins read
• Post category: Research Methodology

What is Research Report?

Research reporting is the oral or written presentation of the findings in such detail and form as to be readily understood and assessed by the society, economy or particularly by the researchers.

As earlier said that it is the final stage of the research process and its purpose is to convey to interested persons the whole result of the study. Report writing is common to both academic and managerial situations. In academics, a research report is prepared for comprehensive and application-oriented learning. In businesses or organisations, reports are used for the basis of decision making.

Table of Content

• 1 What is Research Report?
• 2 Research Report Definition
• 3.1 Preliminary Part
• 3.2 Introduction of the Report
• 3.3 Review of Literature
• 3.4 The Research Methodology
• 3.5 Results
• 3.6 Concluding Remarks
• 3.7 Bibliography
• 4 Significance of Report Writing
• 5 Qualities of Good Report
• 6.1 Analysis of the subject matter
• 6.2 Research outline
• 6.3 Preparation of rough draft
• 6.4 Rewriting and polishing
• 6.5 Writing the final draft
• 7 Precautions for Writing Research Reports
• 8.1.1 Technical Report
• 8.1.2 Popular Report
• 8.2.1 Written Report
• 8.2.2 Oral Report

Research Report Definition

According to C. A. Brown , “A report is a communication from someone who has information to someone who wants to use that information.”

According to Goode and Hatt , “The preparation of report is the final stage of research, and it’s purpose is to convey to the interested persons the whole result of the study, in sufficient detail and so arranged as to enable each reader to comprehend the data and to determine for himself the validity of the conclusions.”

It is clear from the above definitions of a research report, it is a brief account of the problem of investigation, the justification of its selection and the procedure of analysis and interpretation. It is only a summary of the entire research proceedings.

In other words, it can be defined as written documents, which presents information in a specialized and concise manner.

Contents of Research Report

Although no hard and fast rules can be laid down, the report must contain the following points.

• Acknowledgement
• Table of contents
• List of tables
• List of graphs
• Introduction
• Background of the research study
• Statement of the problem
• Brief outline of the chapters
• Books review
• Review of articles published in books, journals, periodicals, etc
• Review of articles published in leading newspapers
• Working papers / discusssion paper / study reports
• Articles on authorised websites
• A broad conclusion and indications for further research
• The theoretical framework (variables)
• Model / hypothesis
• Instruments for data collection
• Data collection
• Pilot study
• Processing of data
• Hypothesis / model testing
• Data analysis and interpretation
• Tables and figures
• Conclusions
• Shortcomings
• Suggestions to the problems
• Direction for further research

Preliminary Part

The preliminary part may have seven major components – cover, title, preface, acknowledgement, table of contents, list of tables, list of graphs. Long reports presented in book form have a cover made up of a card sheet. The cover contains title of the research report, the authority to whom the report is submitted, name of the author, etc.

The preface introduces the report to the readers. It gives a very brief introduction of the report. In the acknowledgements author mention names of persons and organisations that have extended co-operation and helped in the various stages of research. Table of contents is essential. It gives the title and page number of each chapter.

Introduction of the Report

The introduction of the research report should clearly and logically bring out the background of the problem addressed in the research. The purpose of the introduction is to introduce the research project to the readers. A clear statement of the problem with specific questions to be answered is presented in the introduction. It contains a brief outline of the chapters.

Review of Literature

The third section reviews the important literature related to the study. A comprehensive review of the research literature referred to must be made. Previous research studies and the important writings in the area under study should be reviewed. Review of literature is helpful to provide a background for the development of the present study.

The researcher may review concerned books, articles published in edited books, journals and periodicals. Researcher may also take review of articles published in leading newspapers. A researcher should study working papers/discussion papers/study reports. It is essential for a broad conclusion and indications for further research.

The Research Methodology

Research methodology is an integral part of the research. It should clearly indicate the universe and the selection of samples, techniques of data collection, analysis and interpretation, statistical techniques, etc.

Results contain pilot study, processing of data, hypothesis/model testing, data analysis and interpretation, tables and figures, etc. This is the heart of the research report. If a pilot study is planned to be used, it’s purpose should be given in the research methodology.

The collected data and the information should be edited, coded, tabulated and analysed with a view to arriving at a valid and authentic conclusion. Tables and figures are used to clarify the significant relationship. The results obtained through tables, graphs should be critically interpreted.

Concluding Remarks

The concluding remarks should discuss the results obtained in the earlier sections, as well as their usefulness and implications. It contains findings, conclusions, shortcomings, suggestions to the problem and direction for future research. Findings are statements of factual information based upon the data analysis.

Conclusions must clearly explain whether the hypothesis have been established and rejected. This part requires great expertise and preciseness. A report should also refer to the limitations of the applicability of the research inferences. It is essential to suggest the theoretical, practical and policy implications of the research. The suggestions should be supported by scientific and logical arguments. The future direction of research based on the work completed should also be outlined.

Bibliography

The bibliography is an alphabetic list of books, journal articles, reports, etc, published or unpublished, read, referred to, examined by the researcher in preparing the report. The bibliography should follow standard formats for books, journal articles, research reports.

The end of the research report may consist of appendices, listed in respect of all technical data. Appendices are for the purpose of providing detailed data or information that would be too cumbersome within the main body of the research report.

Significance of Report Writing

Report writing is an important communication medium in organisations. The most crucial findings might have come out through a research report. Report is common to academics and managers also. Reports are used for comprehensive and application oriented learning in academics. In organisations, reports are used for the basis of decision making. The importance of report writing can be discussed as under.

Through research reports, a manager or an executive can quickly get an idea of a current scenario which improves his information base for making sound decisions affecting future operations of the company or enterprise. The research report acts as a means of communication of various research findings to the interested parties, organisations and general public.

Good report writing play, a significant role of conveying unknown facts about the phenomenon to the concerned parties. This may provide new insights and new opportunities to the people. Research report plays a key role in making effective decisions in marketing, production, banking, materials, human resource development and government also. Good report writing is used for economic planning and optimum utilisation of resources for the development of a nation.

Report writing facilitates the validation of generalisation. A research report is an end product of research. As earlier said that report writing provides useful information in arriving at rational decisions that may reform the business and society. The findings, conclusions, suggestions and recommendations are useful to academicians, scholars and policymakers. Report writing provides reference material for further research in the same or similar areas of research to the concerned parties.

While preparing a research report, a researcher should take some proper precautions. Report writing should be simple, lucid and systematic. Report writing should be written speedily without interrupting the continuity of thought. The report writing should sustain the interest of readers.

Qualities of Good Report

Report writing is a highly skilled job. It is a process of analysing, understanding and consolidating the findings and projecting a meaningful view of the phenomenon studied. A good report writing is essential for effective communication.

Following are the essential qualities of good report:

• A research report is essentially a scientific documentation. It should have a suggestive title, headings and sub-headings, paragraphs arranged in a logical sequence.
• Good research report should include everything that is relevant and exclude everything that is irrelevant. It means that it should contain the facts rather than opinion.
• The language of the report should be simple and unambiguous. It means that it should be free from biases of the researchers derived from the past experience. Confusion, pretentiousness and pomposity should be carefully guarded against. It means that the language of the report should be simple, employing appropriate words, idioms and expressions.
• The report must be free from grammatical mistakes. It must be grammatically accurate. Faulty construction of sentences makes the meaning of the narrative obscure and ambiguous.
• The report has to take into consideration two facts. Firstly, for whom the report is meant and secondly, what is his level of knowledge. The report has to look to the subject matter of the report and the fact as to the level of knowledge of the person for whom it is meant. Because all reports are not meant for research scholars.

Steps in Writing Research Report

Report writing is a time consuming and expensive exercise. Therefore, reports have to be very sharply focused in purpose content and readership. There is no single universally acceptable method of writing a research report.

Following are the general steps in writing a research report:

Analysis of the subject matter

Research outline, preparation of rough draft, rewriting and polishing, writing the final draft.

This is the first and important step in writing a research report. It is concerned with the development of a subject. Subject matter should be written in a clear, logical and concise manner. The style adopted should be open, straightforward and dignified and folk style language should be avoided.

The data, the reliability and validity of the results of the statistical analysis should be in the form of tables, figures and equations. All redundancy in the data or results presented should be eliminated.

The research outline is an organisational framework prepared by the researcher well in advance. It is an aid to logical organisation of material and a reminder of the points to be stressed in the report. In the process of writing, if need be, outline may be revised accordingly.

Time and place of the study, scope and limitations of the study, study design, summary of pilot study, methods of data collection, analysis interpretation, etc., may be included in a research outline.

Having prepared the primary and secondary data, the researcher has to prepare a rough draft. While preparing the rough draft, the researcher should keep the objectives of the research in mind, and focus on one objective at a time. The researcher should make a checklist of the important points that are necessary to be covered in the manuscript. A researcher should use dictionary and relevant reference materials as and when required.

This is an important step in writing a research report. It takes more time than a rough draft. While rewriting and polishing, a researcher should check the report for weakness in logical development or presentation. He should take breaks in between rewriting and polishing since this gives the time to incubate the ideas.

The last and important step is writing the final draft. The language of the report should be simple, employing appropriate words and expressions and should avoid vague expressions such as ‘it seems’ and ‘there may be’ etc.

It should not used personal pronouns, such as I, We, My, Us, etc and should substitute these by such expressions as a researcher, investigator, etc. Before the final drafting of the report, it is advisable that the researcher should prepare a first draft for critical considerations and possible improvements. It will be helpful in writing the final draft. Finally, the report should be logically outlined with the future directions of the research based on the work completed.

Precautions for Writing Research Reports

A research report is a means of conveying the research study to a specific target audience. The following precautions should be taken while preparing a research report:

• Its hould belong enough to cover the subject and short enough to preserve interest.
• It should not be dull and complicated.
• It should be simple, without the usage of abstract terms and technical jargons.
• It should offer ready availability of findings with the help of charts, tables and graphs, as readers prefer quick knowledge of main findings.
• The layout of the report should be in accordance with the objectives of the research study.
• There should be no grammatical errors and writing should adhere to the techniques of report writing in case of quotations, footnotes and documentations.
• It should be original, intellectual and contribute to the solution of a problem or add knowledge to the concerned field.
• Appendices should been listed with respect to all the technical data in the report.
• It should be attractive, neat and clean, whether handwritten or typed.
• The report writer should refrain from confusing the possessive form of the word ‘it’ is with ‘it’s.’ The accurate possessive form of ‘it is’ is ‘its.’ The use of ‘it’s’ is the contractive form of ‘it is.
• A report should not have contractions. Examples are ‘didn’t’ or ‘it’s.’ In report writing, it is best to use the non-contractive form. Therefore, the examples would be replaced by ‘did not’ and ‘it is.’ Using ‘Figure’ instead of ‘Fig.’ and ‘Table’ instead of ‘Tab.’ will spare the reader of having to translate the abbreviations, while reading. If abbreviations are used, use them consistently throughout the report. For example, do not switch among ‘versus,’ and ‘vs’.
• It is advisable to avoid using the word ‘very’ and other such words that try to embellish a description. They do not add any extra meaning and, therefore, should be dropped.
• Repetition hampers lucidity. Report writers must avoid repeating the same word more than once within a sentence.
• When you use the word ‘this’ or ‘these’ make sure you indicate to what you are referring. This reduces the ambiguity in your writing and helps to tie sentences together.
• Do not use the word ‘they’ to refer to a singular person. You can either rewrite the sentence to avoid needing such a reference or use the singular ‘he or she.’

Types of Research Report

Research reports are designed in order to convey and record the information that will be of practical use to the reader. It is organized into distinct units of specific and highly visible information. The kind of audience addressed in the research report decides the type of report.

Research reports can be categorized on the following basis:

Classification on the Basis of Information

Classification on the basis of representation.

Following are the ways through which the results of the research report can be presented on the basis of information contained:

Technical Report

A technical report is written for other researchers. In writing the technical reports, the importance is mainly given to the methods that have been used to collect the information and data, the presumptions that are made and finally, the various presentation techniques that are used to present the findings and data.

Following are main features of a technical report:

• Summary: It covers a brief analysis of the findings of the research in a very few pages. 
• Nature: It contains the reasons for which the research is undertaken, the analysis and the data that is required in order to prepare a report. 
• Methods employed: It contains a description of the methods that were employed in order to collect the data. 
• Data: It covers a brief analysis of the various sources from which the data has been collected with their features and drawbacks 
• Analysis of data and presentation of the findings: It contains the various forms through which the data that has been analysed can be presented. 
• Conclusions: It contains a brief explanation of findings of the research. 
• Bibliography: It contains a detailed analysis of the various bibliographies that have been used in order to conduct a research. 
• Technical appendices: It contains the appendices for the technical matters and for questionnaires and mathematical derivations. 
• Index: The index of the technical report must be provided at the end of the report.

Popular Report

A popular report is formulated when there is a need to draw conclusions of the findings of the research report. One of the main points of consideration that should be kept in mind while formulating a research report is that it must be simple and attractive. It must be written in a very simple manner that is understandable to all. It must also be made attractive by using large prints, various sub-headings and by giving cartoons occasionally.

Following are the main points that must be kept in mind while preparing a popular report:

• Findings and their implications : While preparing a popular report, main importance is given to the findings of the information and the conclusions that can be drawn out of these findings.
• Recommendations for action : If there are any deviations in the report then recommendations are made for taking corrective action in order to rectify the errors.
• Objective of the study : In a popular report, the specific objective for which the research has been undertaken is presented.
• Methods employed : The report must contain the various methods that has been employed in order to conduct a research.
• Results : The results of the research findings must be presented in a suitable and appropriate manner by taking the help of charts and diagrams.
• Technical appendices : The report must contain an in-depth information used to collect the data in the form of appendices.

Following are the ways through which the results of the research report can be presented on the basis of representation:

• Writtenreport
• Oral report

Written Report

A written report plays a vital role in every business operation. The manner in which an organization writes business letters and business reports creates an impression of its standard. Therefore, the organization should emphasize on the improvement of the writing skills of the employees in order to maintain effective relations with their customers.

Writing effective written reports requires a lot of hard work. Therefore, before you begin writing, it is important to know the objective, i.e., the purpose of writing, collection and organization of required data.

Oral Report

At times, oral presentation of the results that are drawn out of research is considered effective, particularly in cases where policy recommendations are to be made. This approach proves beneficial because it provides a medium of interaction between a listener and a speaker. This leads to a better understanding of the findings and their implications.

However, the main drawback of oral presentation is the lack of any permanent records related to the research. Oral presentation of the report is also effective when it is supported with various visual devices, such as slides, wall charts and whiteboards that help in better understanding of the research reports.

Business Ethics

( Click on Topic to Read )

• What is Ethics?
• What is Business Ethics?
• Values, Norms, Beliefs and Standards in Business Ethics
• Indian Ethos in Management
• Ethical Issues in Marketing
• Ethical Issues in HRM
• Ethical Issues in IT
• Ethical Issues in Production and Operations Management
• Ethical Issues in Finance and Accounting
• What is Corporate Governance?
• What is Ownership Concentration?
• What is Ownership Composition?
• Types of Companies in India
• Internal Corporate Governance
• External Corporate Governance
• Corporate Governance in India
• What is Enterprise Risk Management (ERM)?
• What is Assessment of Risk?
• What is Risk Register?
• Risk Management Committee

Corporate social responsibility (CSR)

• Theories of CSR
• Arguments Against CSR
• Business Case for CSR
• Importance of CSR in India
• Drivers of Corporate Social Responsibility
• Developing a CSR Strategy
• Implement CSR Commitments
• CSR Marketplace
• CSR at Workplace
• Environmental CSR
• CSR with Communities and in Supply Chain
• Community Interventions
• CSR Monitoring
• CSR Reporting
• Voluntary Codes in CSR
• What is Corporate Ethics?

Lean Six Sigma

• What is Six Sigma?
• What is Lean Six Sigma?
• Value and Waste in Lean Six Sigma
• Six Sigma Team
• MAIC Six Sigma
• Six Sigma in Supply Chains
• What is Binomial, Poisson, Normal Distribution?
• What is Sigma Level?
• What is DMAIC in Six Sigma?
• What is DMADV in Six Sigma?
• Six Sigma Project Charter
• Project Decomposition in Six Sigma
• Critical to Quality (CTQ) Six Sigma
• Process Mapping Six Sigma
• Flowchart and SIPOC
• Gage Repeatability and Reproducibility
• Statistical Diagram
• Lean Techniques for Optimisation Flow
• Failure Modes and Effects Analysis (FMEA)
• What is Process Audits?
• Six Sigma Implementation at Ford
• IBM Uses Six Sigma to Drive Behaviour Change
• Research Methodology
• What is Research?

What is Hypothesis?

Sampling method.

• Research Methods
• Data Collection in Research
• Methods of Collecting Data
• Application of Business Research
• Levels of Measurement
• What is Sampling?
• Hypothesis Testing
• What is Management?
• Planning in Management
• Decision Making in Management
• What is Controlling?
• What is Coordination?
• What is Staffing?
• Organization Structure
• What is Departmentation?
• Span of Control
• What is Authority?
• Centralization vs Decentralization
• Organizing in Management
• Schools of Management Thought
• Classical Management Approach
• Is Management an Art or Science?
• Who is a Manager?

Operations Research

• What is Operations Research?
• Operation Research Models
• Linear Programming
• Linear Programming Graphic Solution
• Linear Programming Simplex Method
• Linear Programming Artificial Variable Technique
• Duality in Linear Programming
• Transportation Problem Initial Basic Feasible Solution
• Transportation Problem Finding Optimal Solution
• Project Network Analysis with Critical Path Method
• Project Network Analysis Methods
• Project Evaluation and Review Technique (PERT)
• Simulation in Operation Research
• Replacement Models in Operation Research

Operation Management

• What is Strategy?
• What is Operations Strategy?
• Operations Competitive Dimensions
• Operations Strategy Formulation Process
• What is Strategic Fit?
• Strategic Design Process
• Focused Operations Strategy
• Corporate Level Strategy
• Expansion Strategies
• Stability Strategies
• Retrenchment Strategies
• Competitive Advantage
• Strategic Choice and Strategic Alternatives
• What is Production Process?
• What is Process Technology?
• What is Process Improvement?
• Strategic Capacity Management
• Production and Logistics Strategy
• Taxonomy of Supply Chain Strategies
• Factors Considered in Supply Chain Planning
• Operational and Strategic Issues in Global Logistics
• Logistics Outsourcing Strategy
• What is Supply Chain Mapping?
• Supply Chain Process Restructuring
• Points of Differentiation
• Re-engineering Improvement in SCM
• What is Supply Chain Drivers?
• Supply Chain Operations Reference (SCOR) Model
• Customer Service and Cost Trade Off
• Internal and External Performance Measures
• Linking Supply Chain and Business Performance
• Netflix’s Niche Focused Strategy
• Disney and Pixar Merger
• Process Planning at Mcdonald’s

Service Operations Management

• What is Service?
• What is Service Operations Management?
• What is Service Design?
• Service Design Process
• Service Delivery
• What is Service Quality?
• Gap Model of Service Quality
• Juran Trilogy
• Service Performance Measurement
• Service Decoupling
• IT Service Operation
• Service Operations Management in Different Sector

Procurement Management

• What is Procurement Management?
• Procurement Negotiation
• Types of Requisition
• RFX in Procurement
• What is Purchasing Cycle?
• Vendor Managed Inventory
• Internal Conflict During Purchasing Operation
• Spend Analysis in Procurement
• Sourcing in Procurement
• Supplier Evaluation and Selection in Procurement
• Blacklisting of Suppliers in Procurement
• Total Cost of Ownership in Procurement
• Incoterms in Procurement
• Documents Used in International Procurement
• Transportation and Logistics Strategy
• What is Capital Equipment?
• Procurement Process of Capital Equipment
• Acquisition of Technology in Procurement
• What is E-Procurement?
• E-marketplace and Online Catalogues
• Fixed Price and Cost Reimbursement Contracts
• Contract Cancellation in Procurement
• Ethics in Procurement
• Legal Aspects of Procurement
• Global Sourcing in Procurement
• Intermediaries and Countertrade in Procurement

Strategic Management

• What is Strategic Management?
• What is Value Chain Analysis?
• Mission Statement
• Business Level Strategy
• What is SWOT Analysis?
• What is Competitive Advantage?
• What is Vision?
• What is Ansoff Matrix?
• Prahalad and Gary Hammel
• Strategic Management In Global Environment
• Competitor Analysis Framework
• Competitive Rivalry Analysis
• Competitive Dynamics
• What is Competitive Rivalry?
• Five Competitive Forces That Shape Strategy
• What is PESTLE Analysis?
• Fragmentation and Consolidation Of Industries
• What is Technology Life Cycle?
• What is Diversification Strategy?
• What is Corporate Restructuring Strategy?
• Resources and Capabilities of Organization
• Role of Leaders In Functional-Level Strategic Management
• Functional Structure In Functional Level Strategy Formulation
• Information And Control System
• What is Strategy Gap Analysis?
• Issues In Strategy Implementation
• Matrix Organizational Structure
• What is Strategic Management Process?

Supply Chain

• What is Supply Chain Management?
• Supply Chain Planning and Measuring Strategy Performance
• What is Warehousing?
• What is Packaging?
• What is Inventory Management?
• What is Material Handling?
• What is Order Picking?
• Receiving and Dispatch, Processes
• What is Warehouse Design?
• What is Warehousing Costs?

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The Top 5 Qualities of Every Good Researcher

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Table of Contents

What makes a good researcher? Is it some undefinable, innate genius, or is it something that we can practice and build upon? If it was just the former, then there would be far fewer innovations in the history of humankind than there have been. A careful look at researchers through the ages reveals that they all have certain attributes in common that have helped contribute to their success.

The characteristics of a good researcher:

1. curiosity.

They ask questions. An endless thirst for knowledge is what sets the best of the best apart from the others. Good researchers constantly strive to learn more, not just about their own field, but about other fields as well. The world around us is fascinating, be it the physics behind the way light refracts, or the anthropological constructions of our society. A good researcher keeps exploring the world and keeps searching for answers.

2. Analytical ability and foresight

They look for connections. Information is useless without interpretation. What drives research forward is finding meaning in our observations and data. Good researchers evaluate data from every angle and search for patterns. They explore cause and effect and untangle the tricky web that interconnects everyday phenomena. And then take it one step further to ask, ‘What is the bigger picture? How will the research develop in the future?’

3. Determination

They try, try, and try again. Research can be a frustrating experience. Experiments may not pan out how we expect them to. Even worse, sometimes experiments may run smoothly until they are 95% complete before failing. What sets an average researcher apart from a truly good one? The truly good researcher perseveres. They accept this disappointment, learn from the failure, reevaluate their experiment, and keep moving forward.

4. Collaboration

Teamwork makes the dream work. Contrary to the common perception of the solitary genius in their lab, research is an extremely collaborative process. There is simply too much to do for just one person to do it all. Moreover, research is becoming increasingly multidisciplinary. It is impossible for just one person to have expertise in all these fields. In general, research is conducted in teams , with each researcher having their individual roles and responsibilities. Being able to coordinate, communicate, and get along with team members is a major factor that can contribute to one’s success as a researcher.

5. Communication

They get their message across. Communication skills are an essential asset for every researcher. Not only do they have to communicate with their team members, but they also have to communicate with co-authors, journals, publishers, and funders. Whether it is writing a crisp and effective abstract, presenting at a conference, or writing a persuasive grant proposal to secure research funding, communication appears everywhere in a researcher’s life. The message in the old adage, ‘If a tree falls in the forest, but no one is around to hear it, does it make a sound?’ applies to research too. A discovery could be groundbreaking, but what is the use if the researcher can’t communicate this discovery to the rest of the world?

These are just a few of the skills required by researchers to make it to the top of their field. Other attributes like creativity and time management are also worth mentioning. Nevertheless, having one or more of these top five characteristics will make the research process smoother for you and increase the chances of positive results. Set yourself up for success by building up these skills, focusing on excellence, and asking for help when you need it. Elsevier Author Services is here to aid you at every step of the research journey. From translation services by experts in the field, to preparing your manuscript for publication, to helping you submit the best possible grant proposal, you can trust us to guide you in your journey to doing great research.

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Understanding the Characteristics of a Good Report

Imagine the impact a well-structured, engaging, and informative report can have on your organization’s decision-making process. A good report is more than just a collection of facts and figures – it’s a powerful communication tool that can shape the future of a company. In this blog post, we will explore the characteristics of a good report and how they contribute to effective communication. Let’s dive in and unlock the secrets to creating compelling reports that drive results.

Key Takeaways

A successful report must possess clarity, accuracy, conciseness, coherence, and relevance to effectively facilitate informed decision-making.

Data visualization is essential for good reports in order to effectively convey complex data.

Auditors are responsible for verifying the correctness and reliability of financial information to ensure quality reporting.

Essential Elements of a High-Quality Report

A high-quality report is like a well-crafted symphony, where each element harmoniously blends with the others to create a masterpiece. The five essential characteristics of a good report are:

Conciseness

These components contribute to a comprehensive understanding of the subject matter, allowing stakeholders to make informed decisions based on reliable and credible information.

Have you ever read a report that left you more confused than enlightened? Clarity is the cornerstone of a good report, ensuring that the information is easily understood by the reader. A clear report eliminates ambiguity and uses language that is straightforward and succinct. This is particularly important when presenting a company’s financial position, as unclear information can lead to misinterpretation and costly mistakes.

To further elaborate, clarity in a report also involves the use of clear headings and subheadings that guide the reader through the document. It includes the use of bullet points and numbered lists to present information in an organized and digestible way. It also means avoiding overly complex sentences and paragraphs that can be difficult to follow.

In addition, clear reports also make good use of visual aids such as charts, graphs, and diagrams. These can help to break up large blocks of text and can often communicate information more effectively than words alone. They can also make the report more engaging and pleasing to the eye.

Furthermore, a clear report is one that is free of errors. This includes not only factual errors but also grammatical errors and typos. Such mistakes can detract from the clarity of the report and can give the impression that the report is not reliable or trustworthy.

In sum, clarity is about more than just using simple language. It’s about presenting information in a way that is organized, engaging, and error-free, making the report as easy to understand as possible.

Clear reports favor straightforward language, steer clear of jargon, and incorporate visual aids such as graphs and charts when suitable. These methods not only enhance the reader’s understanding of the company’s financial reports but also facilitate the decision-making process by presenting information in a digestible manner.

Imagine the chaos that would ensue if a company’s financial statements were riddled with inaccuracies and errors.

Accuracy is crucial in a report, as it ensures that the information presented is reliable and trustworthy. Inaccurate information can lead to erroneous decisions, jeopardizing the attainment of the organization’s objectives.

In the context of audit reports, accuracy ensures that the financial statements are presented fairly and accurately, allowing stakeholders to make informed decisions based on dependable data. Accuracy in a report requires meticulous fact-checking, thorough evidence gathering, and obtaining reasonable assurance of fair financial statement presentation. These measures not only ensure the credibility and trustworthiness of the report but also contribute to the formation of a reliable auditor’s opinion.

Have you ever struggled through a lengthy report, only to lose interest halfway through? Conciseness is an essential characteristic of a good report, helping to maintain the reader’s engagement and focus on key points without unnecessary information. A concise report is like a well-tailored suit – it fits perfectly and communicates the desired message with precision.

Concise reports:

Employ active voice

Avoid technical language

Utilize plain language to effectively communicate the message

Avoid reiteration

Focus on the essential points

Allow your reader to grasp the company’s financial position without being overwhelmed by excessive details.

A report with a disjointed flow and inconsistent formatting is like trying to navigate a maze – it’s confusing and disorienting. Coherence in a report ensures that the information flows logically and consistently, making it easier for the reader to follow the narrative. A coherent report is like a well-planned journey, where each step follows the previous one, leading the reader to a clear destination.

A coherent report leverages the following practices for organization and readability:

Use headings and subheadings to clearly structure the report.

Maintain consistent formatting throughout the document.

Utilize transitions between sections to aid the reader’s comprehension.

By adopting these practices and following the applicable financial reporting framework, you’ll create a report that is structured, easy to navigate, and effectively communicates the company’s financial position.

Furthermore, these practices also ensure that your report is not just a dry presentation of facts and figures, but a compelling narrative that engages the reader. It will not only provide valuable insights into the company’s financial status but also highlight key trends and patterns, facilitating a deeper understanding of the company’s performance.

This way, the report becomes a powerful tool for decision-making, enabling stakeholders to make well-informed decisions that can shape the future of the company.

Including irrelevant information in a report is like adding unnecessary ingredients to a recipe – it detracts from the overall flavor and confuses the palate.

Relevance in a report ensures that the information presented is directly related to the topic and serves a purpose in the overall narrative. A relevant report is like a well-curated art exhibition – each piece contributes to the overall theme and enhances the viewer’s experience.

A relevant report prioritizes accurate data, and sources that directly relate to the topic, and presents information in a logical sequence. By adhering to these principles, you’ll create a report that effectively communicates the company’s financial position, allowing stakeholders to make informed decisions based on pertinent information.

The Role of Data Visualization in Good Reports

Data visualization is like a powerful telescope that brings the stars within reach, transforming complex information into easily digestible visuals. In good reports, data visualization plays a significant role, as it helps to convey intricate data in a comprehensible and effective manner.

Incorporating visuals like charts, graphs, and maps into data visualization enhances reporting efficacy, making the information more digestible and engaging for the reader.

Choosing the Right Visuals

Selecting the right visuals for a report is like choosing the perfect outfit for an important event – it must be appropriate, appealing, and effectively communicate your message. The right visuals not only enhance the overall presentation of the report but also ensure that the data is effectively communicated to the audience.

When selecting visuals, consider the audience, the data being presented, and the format that best suits the information. For example, bar graphs are ideal for comparing quantities, while pie charts are suitable for illustrating proportions. By choosing the right visuals, you’ll create a report that is both engaging and informative, allowing the reader to quickly discern essential insights and trends.

Design Principles for Effective Visuals

Design principles for effective visuals are like the foundation of a sturdy building – they provide structure, stability, and aesthetic appeal.

In a report, adhering to design principles ensures that the visuals enhance the message and facilitate understanding. Effective visuals are like a well-crafted painting – they capture the viewer’s attention and convey a clear message.

Design principles for effective visuals encompass:

Simplicity: Easy to understand and focuses on the key points

Consistency: Maintains the same style and formatting throughout the report

Clarity: Information is easily interpreted, allowing the reader to quickly identify patterns and trends.

By applying these design principles, you’ll create visuals that not only enhance the report’s content but also facilitate effective communication of the data.

The Auditor’s Role in Ensuring Quality Reporting

Auditors are like the watchful guardians of a company’s financial health, providing objective opinions on its financial status and compliance with regulations. Their role in ensuring quality reporting is crucial, as they:

Verify the accuracy and reliability of the financial information presented in the report

Identify any potential errors or irregularities

Assess the company’s internal controls and risk management processes

Provide recommendations for improvement

Help maintain transparency and accountability in financial reporting

Auditors, by complying with generally accepted accounting principles and generally accepted auditing standards, bolster the credibility of financial statements and aid stakeholders in making informed decisions.

Types of Audit Opinions

Imagine an art critic evaluating a gallery – their opinion will vary depending on the quality and presentation of the artwork. Similarly, auditors provide different types of audit reports based on their assessment of a company’s financial reporting. These opinions include:

Clean (unqualified) opinion

Qualified opinion

Disclaimer opinion

Adverse opinion

Each auditor’s opinion reflects the evaluation of the organization’s financial statements and adherence to regulations, providing a thorough analysis of the company’s financial statements.

This analysis is the result of an extensive audit process that includes examining the company’s financial records, interviewing key personnel, and assessing internal controls. The auditor’s opinion is not just a simple conclusion but a comprehensive evaluation that takes into account the company’s operational environment, its internal control systems, and its adherence to relevant laws and regulations.

This rigorous process ensures that the auditor’s opinion is based on a complete and accurate view of the company’s financial health, providing stakeholders with valuable insights that can guide their decision-making process.

A clean opinion signifies satisfactory financial reporting, while a qualified opinion indicates potential issues or deviations from generally accepted accounting principles. A disclaimer of opinion is issued when the auditor is unable to provide any opinion on the financial statements, and an adverse opinion indicates substantial misstatements and potential fraud.

Understanding these audit opinion types empowers stakeholders to assess a company’s financial position more accurately and make knowledgeable decisions.

The Auditor’s Responsibility for Quality Reporting

Auditors are like skilled detectives, meticulously examining a company’s financial records to uncover inaccuracies and inconsistencies. Their responsibility for quality reporting involves:

Verifying the correctness and reliability of the financial information presented in the audit report

Adopting a quality control system

Being vigilant towards financial reporting areas prone to fraudulent schemes

These measures can enhance an auditor’s contribution to the credibility of financial statements and their independent opinion on the independent auditor’s report. By meticulously verifying the accuracy of the financial data, identifying potential discrepancies, and maintaining vigilance towards areas prone to fraudulent activities, auditors play a vital role in ensuring the integrity of financial reporting.

The auditor’s independent opinion serves as a testament to the accuracy and reliability of the financial statements, thereby fostering trust among stakeholders and facilitating informed decision-making.

This role of the auditor, coupled with their adherence to stringent auditing standards, significantly bolsters the credibility of the financial statements, making them a vital asset in the eyes of the stakeholders.

Additionally, auditors possess expertise in:

Evaluating internal systems and processes for collecting, analyzing, and reporting information

Providing an impartial view of the financial report

Bolstering the credibility of the financial statements

Their role in ensuring quality reporting is significant, as they help organizations make well-informed decisions and sustain trust with their stakeholders.

Case Study: A Well-Structured Report Example

Let’s explore a case study of a well-structured report that effectively incorporates the key characteristics of a good report. This case study will serve as a practical example, demonstrating how these principles and characteristics are applied in a real-world context.

It will provide a comprehensive understanding of how clarity, accuracy, conciseness, coherence, and relevance can be seamlessly integrated into a report to produce a compelling and informative document. We will delve into the specifics of how each characteristic is manifested in the report, highlighting the strategies used to ensure the report is clear, accurate, concise, coherent, and relevant. This examination of a well-structured report will provide you with valuable insights and practical techniques that you can apply to your own report-writing endeavors.

Imagine a tech company that releases an annual report to its stakeholders, providing a comprehensive overview of its financial performance and achievements throughout the year. The report is organized into sections, including an executive summary, financial statements, and a detailed analysis of the company’s growth and challenges.

The report exhibits the following qualities in its presentation:

The language is straightforward and easy to understand, with graphs and charts to support the financial data. The information presented is accurate, concise, and directly related to the company’s financial position. The report flows logically from one section to the next, allowing the reader to easily follow the narrative and understand the company’s financial position.

This case study demonstrates the power of a well-structured report in effectively communicating complex information to stakeholders. The incorporation of key characteristics of a good report allowed the tech company to offer a comprehensive and engaging performance overview, enabling stakeholders to make informed decisions grounded in reliable and credible information.

Summary and Conclusion

In summary, high-quality reporting is essential for providing accurate and reliable information to stakeholders, allowing organizations to make informed decisions and sustain trust. The characteristics of a good report – clarity, accuracy, conciseness, coherence, and relevance – contribute to effective communication and facilitate comprehension of the subject matter. By incorporating these principles in your own report writing, you’ll create compelling reports that drive results and shape the future of your organization. Remember, a well-crafted report is like a powerful telescope, bringing complex information within reach and transforming it into easily digestible insights.

Frequently Asked Questions

What are the principles of a good report.

The principles of a good report include accuracy, selectiveness, comprehensiveness, cost consideration, objectivity, preciseness, simplicity, and the use of proper language. Sentences should be short and clear, jargon should be avoided, and the text should be broken up into sections to make it easier to read.

What are the 4 types of audit reports?

Audit reports come in four varieties: Clean Report or Unqualified Opinion, Qualified Report or Qualified Opinion, Disclaimer Report or Disclaimer of Opinion, and Adverse Audit Report or Adverse Opinion.

What is an audit report and examples?

An audit report is an independent opinion from an auditor about whether the company’s financial statements are in accordance with generally accepted accounting principles and free from material misstatement. It includes opinions on the Income Statement, Balance Sheet, Cashflows, and Shareholders’ equity statement, and is usually found in companies’ annual reports just before the financial page.

What is the purpose of an audit report?

The purpose of an audit report is to provide assurance that the financial statements presented by a company are in compliance with GAAP and free from material misstatement.

What are the 5 characteristics of a report?

A report should be clear, accurate, concise, coherent, and relevant for it to be effective.

Different Types Of Evidence: Important Documents, Interviews, And Other Information

Duties Of An Expert Witness

History Of Forensic Accounting: The Ethical History Of Forensic Accounting

Listening And Observing In An Interview: Why Interviewing Starts With Good Listening And Observation

Forensic Accountant Responsibilities: The Important Duties Of A Forensic Accountant

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Michael Nielsen

Principles of Effective Research

Note: The entire essay is here in postscript format .

By Michael A. Nielsen

This essay is intended as a letter to both myself and others, to hold up in the sharpest possible terms an ideal of research I believe is worth working toward. I’ve deliberately limited the essay to 10 pages, hoping that the resulting omissions are compensated by the forced brevity. This is a rather personal essay; it’s not the sort of thing I’d usually make publicly available. I’ve made the essay public in order to heighten my commitment to the project, and in the hope that other people will find it stimulating, and perhaps offer some thoughts of their own.

A few words of warning. My primary audience is myself, and some of the advice is specific to my career situation [*], and therefore may not be directly applicable to others. And, of course, it’s all just my opinion anyway. I hope, however, that it’ll still be stimulating and helpful.

[*] I’m a theoretical physicist; I lead a small research group at a large Australian University; I have a permanent position, with no teaching duties for the next few years; I have several colleagues on the faculty with closely related interests.

The philosophy underlying the essay is based on a famous quote attributed to Aristotle: “We are what we repeatedly do. Excellence, then, is not an act but a habit.” Underlying all our habits are models (often unconscious) of how the world works. I’m writing this essay to develop an improved personal model of how to be an effective researcher, a model that can be used as the basis for concrete actions leading to the development of new habits.

Fundamental principles

The fundamental principles of effective research are extremely similar to those for effectiveness in any other part of life. Although the principles are common sense, that doesn’t mean they’re common practice, nor does it mean that they’re easy to internalize. Personally, I find it a constant battle to act in accord with these principles, a battle requiring ongoing reflection, rediscovery and renewed commitment.

Integrating research into the rest of your life

Research is, of course, only a part of life, and must be understood in relation to the rest of life. The foundation of effective research is a strong motivation or desire to do research. If research is not incredibly exciting, rewarding and enjoyable, at least some of the time, then why not do something else that is? For the purposes of this essay, I’ll assume that you already have a strong desire to do research [*].

[*] People sometimes act or talk as though desire and motivation cannot be changed. Within limits, I think that’s wrong, and we can mold our own motivations. But that’s a subject for another essay.

Motivation and desire alone are not enough. You also need to have the rest of your life in order to be an effective researcher. Make sure you’re fit. Look after your health. Spend high quality time with your family. Have fun. These things require a lot of thought and effort to get right. If you don’t get them right, not only will your life as a whole be less good, your research will suffer. So get these things right, and make sure they’re integrated with your research life.

As an example, I once spent three years co-authoring a technical book, and for the final eighteen months I concentrated on the book almost exclusively, to the neglect of my health, relationships, and other research. It is tempting to ask the question “Was the neglect worth the benefits?” But that is the wrong question, for while the neglect paid short-term dividends in increased productivity, over the total period of writing the book I believe it probably cost me productivity, and it certainly did after the book was complete. So not only did I become less fit and healthy, and see my relationships suffer, the book took longer to complete than if I’d had my life in better order.

Principles of personal behaviour: proactivity, vision, and discipline

I believe that the foundation of effective research is to internalize a strong vision of what you want to achieve, to work proactively towards that vision, taking personal responsibility for successes and failures. You need to develop disciplined work habits, and to achieve balance between self-development and the actual creative research process .

Proactivity and personal responsibility

Effective people are proactive and take personal responsibility for the events in their lives. They form a vision of how they want their life to be, and work toward achieving that vision. They identify problems in their lives, and work toward solutions to those problems.

Isn’t this obvious, banal advice? I heard a story years ago in which a representative from McDonald’s was asked what gave McDonald’s the edge in the fast food industry. They replied that McDonald’s took care of the little things, like making sure that their restaurants and surrounds were always extremely clean. Representatives of other fast food companies replied incredulously that surely that was not the reason McDonald’s did so well, for “anyone could do that”. “But only McDonald’s does” was the response. The heart of personal effectiveness is not necessarily any special knowledge or secret: it is doing the basics consistently well.

When it comes to proactivity and responsibility, it seems to be incredibly difficult to internalize these principles and act on them consistently. Almost everyone says and thinks they are proactive and responsible, but how many of us truly respond to the force of external circumstance in the most proactive manner?

My belief is that the reason it is difficult to be consistently proactive and responsible is that over the short term it is often significantly easier to abdicate responsibility and behave in a reactive fashion. In my opinion, there are three basic ways this can occur.

The first way is to blame external circumstances for our problems. “We don’t have enough grant money.” “I have to teach too much.” “My supervisor is no good.” “My students are no good.” “I don’t have enough time for research.” When challenged on what actions we are taking to rectify the situation, we will claim that it’s the fault of other people, or of circumstances beyond our control, relieving ourselves of the burden of doing anything to solve the problem.

In short, we abdicate responsibility, preferring to blame others. This is easier over the short term, since it’s easier to complain than it is to take action, but is not a recipe for long-term happiness or effectiveness. Furthermore, we will usually deny that it is within our power to take actions to improve our situation. After all, if it was in our power, it would be us who is responsible, and our entire worldview is based upon blaming others for our own problems.

The second way of abdicating responsibility is to get caught up in displacement activities. These may give us a short-term fix, especially if they win us the approbation of other people, perhaps for responding to requests that they label urgent. Over the long run such displacement activities are ultimately unfulfilling, representing time lost from our lives.

The third way of abdicating responsibility is by getting down on yourself, worrying and feeling bad for not overcoming one’s difficulties. Winston Churchill spoke of the “black dog” of depression that overtook him during times when his political career was in eclipse. Personally, I sometimes get really down when things are not going well, and get caught up in a cycle of worry and analysis, without constructively addressing my problems. Of course, the right way to respond to a bad situation is not to beat yourself up, but rather to admit that, yes, things are going badly, to figure out exactly what problems you are facing, write out possible solutions, prioritize and implement them, without getting too worried or hamstrung by the whole process.

Why are these three options so attractive? Why do we so often choose to respond in this way to the challenges of life rather than taking things on with a proactive attitude that acknowledges that we’re responsible for our own life? What all three options share in common is that over the short-term abdicating responsibility for our problems is easier than taking responsibility for meeting the challenges of life.

A specific example that I believe speaks to many of us is when we’re having some sort of difficulty or conflict with another person. How many of us put off confronting the problem, preferring instead to hope that the problem will resolve itself? Yet, properly managed – a difficult thing to do, most likely requiring considerable preparation and aforethought – it’s nearly always better to talk with the person about the problem until you arrive at a mutual understanding of both your points of view, both sets of interests, and can resolve the issue on a basis of shared trust.

How can we learn to become proactive? I don’t know of any easy way. One powerful way is to be inspired by examples of proactive people. This can either be through direct personal contact, or indirectly through biographies, history, movies and so on. I like to set aside regular time for such activities. Another powerful tool for learning proactivity is to remind ourselves regularly of the costs and benefits of proactivity and responsibility versus reactivity and irresponsibility. These costs and benefits are easy to forget, unless you’re constantly being reminded that complaints, self-doubt, blame of others and of self are actually the easy short-term way out, and that chances are that you can construct a better life for yourself, at the cost of needing to do some hard work over the short term.

In the context of research, this means constantly reminding yourself that you are the person ultimately responsible for your research effectiveness. Not the institution you find yourself in. Not your colleagues, or supervisor. Not the society you are living in. All these things influence your research career, and may be either a help or a hindrance (more on that later), but in the final analysis if things are not working well it is up to you to take charge and change them.

Effective people have a vision of what they’d like to achieve. Ideally, such a vision incorporates both long-term values and goals, as well as shorter-term goals. A good vision answers questions like: What sort of researcher would I like to become? What areas of research am I interested in? How am I going to achieve competence in those areas? Why are those areas interesting? How am I going to continue growing and expanding my horizons? What short-term steps will I take to achieve those goals? How will I balance the long-term goals with the short-term realities of the situation I find myself in? For example, if you’re in a temporary job and need to get another job soon, it’s probably not such a great idea to devote all your time to learning some new subject, without any visible outcome.

A vision is not something you develop overnight. You need to work at it, putting time aside for the process, and learning to integrate it into your everyday life. It’s a challenging process, but over the long run it’s also extremely rewarding. History shows that great actions usually are the outcome of great purpose, even if the action that resulted was not the original purpose. Your vision doesn’t always need to be of a great purpose; it’s good to work on the little stuff, some of the time. But you should occasionally set yourself some big, ambitious goal, a goal that gets you excited, that makes you want to get up in the morning, and where you’ve developed a confidence in your own mind that you have a chance of achieving that goal. Such a great purpose inspires in a way that the humdrum cannot; it makes things exciting and worthwhile if you feel you’re working towards some genuinely worthy end. I believe this is particularly important in the more abstract parts of research (like theoretical physics), where it can require some work to make a personal, emotional connection to one’s own research. Having a clear vision of a great end is one very good way of making such a connection. When you don’t do this, you can get stuck in the rut of the everyday; you need to get out of that rut, to develop a bigger vision.

Finally, a good vision is not inflexible. It’s something that gets changed as you go along, never lightly, but frequently. The importance of having the vision is that it informs your everyday and every week decisions, giving you a genuinely exciting goal to work towards.

Self-discipline

Effective people are self-disciplined . They work both hard and smart, in the belief that you reap what you sow. How does one achieve such self-discipline? It’s a difficult problem. Wayne Bennett, one of the most successful coaches in the history of the sport of Rugby League, sums the problem up well when he says “I’ve had more trouble with myself than any other man I’ve ever met”.

It is a tempting but ultimately counterproductive fallacy to believe that self-discipline is merely a matter of will , of deciding what it is that you want to do, and then doing it. Many other factors affect self-discipline, and it’s important to understand those other factors. Furthermore, if you believe that it’s all a matter of willpower then you’re likely to get rather depressed when you fall short, sapping your confidenc, and resulting in less disciplined behaviour.

I now describe three factors important in achieving self-discipline.

The first factor is having clarity about what one wants to achieve, why one wants to achieve it, and how to go about achieving it. It’s easy to work hard if you’re clear about these three things, and you’re excited about what you’re doing. Conversely, I think the main cause of aimlessness and procrastination is when you lack clarity on one or more of these points.

The second factor affecting self-discipline is one’s social environment. Researchers are typically under little immediate social pressure to produce research results. Contrast this with the example of professional athletes, who often have an entire support system of coaches, managers and trainers in place, focused around the task of increasing their effectiveness. When a researcher stays out late, sleeps in, and gets a late start, no-one minds; when a professional athlete does, they’re likely to receive a blast from their coach.

Access to a social environment which encourages and supports the development of research skills and research excellence can make an enormous difference to all aspect of one’s research, including self-discipline. The key is to be accountable to other people. Some simple ways of achieving such accountability are to take on students, to collaborate with colleagues, or to set up mentoring relationships with colleagues.

The third factor affecting self-discipline is a special kind of honesty, honesty to oneself, about oneself. It’s extremely easy to kid ourselves about what we do and who we are. A colleague once told me of a friend of his who for some time used a stopwatch to keep track of how much research work he did each week. He was shocked to discover that after factoring in all the other activities he engaged in each day – interruptions, email, surfing the net, the phone, fruitless meetings, chatting with friends, and so on – he was averaging only half an hour of research per day. I wouldn’t be surprised if this was typical of many researchers. The good news, of course, is that building this kind of awareness lays the foundation for personal change, for achieving congruence between our behavioural goals and how we actually behave, in short, for achieving self-discipline.

Aspects of research: self-development and the creative process

Research involves two main aspects, self-development and the creative process of research. We’ll discuss the specifics of each aspect below, but for now I want to concentrate on the problem of achieving balance between the two, for I believe it is a common and significant mistake to concentrate too much on one aspect to the exclusion of the other.

People who concentrate mostly on self-development usually make early exits from their research careers. They may be brilliant and knowledgeable, but they fail to realize their responsibility to make a contribution to the wider community. The academic system usually ensures that this failure is recognized, and they consequently have great difficulty getting jobs. Although this is an important problem, in this essay I will focus mostly on the converse problem, the problem of focusing too much on creative research, to the exclusion of self-development.

There are a lot of incentives for people to concentrate on creative research to the exclusion of self-development. Throughout one’s research career, but particularly early on, there are many advantages to publishing lots of papers. Within limits, this is a good thing, especially for young researchers: it brings you into the community of researchers; it gives you the opportunity to learn how to write well, and give good presentations; it can help keep you motivated. I believe all researchers should publish at least a few papers each year, essentially as an obligation to the research and wider community; they should make some contribution, even if only a small one, on a relatively unimportant topic.

However, some people end up obsessed with writing as many papers as possible, as quickly as possible. While the short-term rewards of this are attractive (jobs, grants, reputation and prizes), the long-term costs are significant. In particular, it can lead to stagnation, and plateauing as a researcher. To achieve one’s full potential requires a balancing act: making a significant and regular enough research contribution to enable oneself to get and keep good jobs, while continuing to develop one’s talents, constantly renewing and replenishing oneself. In particular, once one has achieved a certain amount of job security (a long-term or permanent job) it may make sense to shift the balance so that self-development takes on a larger role.

For many people (myself included) who have concentrated mainly on making creative research contributions earlier in their careers, this can be a difficult adjustment to make, as it requires changing one’s sense of what is important. Furthermore, there is a constant pull towards concentrating on research over self-development, since there are often short-term incentives to sacrifice self-development for research (“I’ve got to get this paper out now”), but rarely vice versa. To balance these tendencies, we need to remember that nobody, no matter how talented, is born an effective researcher; that distinction can only be obtained after a considerable amount of hard work and personal change, and there is no reason to suppose that just because one is now able to publish lots of papers that one has peaked as a researcher.

In my opinion, creative research is best viewed as an extension of self-development, especially an extension of a well-developed reading program. I don’t believe the two can be completely pried apart, as the two interact in interesting non-linear ways. I’m now going to talk in a little more detail about both processes, keeping in mind that the ultimate goal of research is new ideas, insights, tools and technologies, and this goal must inform the process of self-development.

Developing research strengths

The foundation is a plan for the development of research strengths. What are you interested in? Given your interests, what are you going to try to learn? The plan needs to be driven by your research goals, but should balance short-term and long-term considerations. Some time should be spent on things that appear very likely to lead to short-term research payoff. Equally well, some time needs to be allocated to the development of strengths that may not have much immediate pay-off, but over the longer-term will have a considerable payoff.

In targeting areas of development, an important goal to keep in mind is that you want to develop unique combinations of abilities. You need to develop unique combinations of talents which give you a comparative advantage over other people. Do what you can do better than anybody ; to mangle a quote from Lincoln, nobody can be better than everybody all of the time, but anybody can be better than everybody some of the time.

In my opinion the reason most people fail to do great research is that they are not willing to pay the price in self-development. Say some new field opens up that combines field X and field Y. Researchers from each of these fields flock to the new field. My experience is that virtually none of the researchers in either field will systematically learn the other field in any sort of depth. The few who do put in this effort often achieve spectacular results.

Finally, a note on how to go about developing some new research strength. A mistake I’m prone to make, and I know some others are as well, is to feel as though some degree of completeness is required in understanding a research field. In fact, in any given research field there are usually only a tiny number of papers that are really worth reading. You are almost certainly better off reading deeply in the ten most important papers of a research field than you are skimming the top five hundred.

These ideas carry over to the problem of staying current in your fields of interest: I believe that you can stay quite current by (a) quickly skimming a great deal of work, to keep track of what is known, and what sort of problems people are thinking about, and (b) based on that skimming, picking a dozen or so papers each year to read deeply, in the belief that they contain the most important research results of the year. This is not the only deep reading you’ll need to do; you’ll also need to do some which is related to the immediate problems that you’re working on. But you certainly should do some such deep reading.

Develop a high-quality research environment

There is a considerable amount of research showing that people consistently underestimate the effect of the environment on personal effectiveness. This is particularly important in an academic environment where there are usually many short-term social pressures that are not directly related to research effectiveness – teaching, writing letters of recommendation and referee reports, committee work, academic politics. By contrast, in most institutions there are few short-term social pressures to do great research work.

Some of the highest-leverage work you can do involves improving your environment so that social pressures work for you as a researcher, rather than against you. Discussing this in detail would require another essay of length at least equal to that of the present one, but I will make a few remarks.

The first is that improving your environment is something anyone can do; students, in particular, often underestimate the magnitude of the changes they can bring about. Anyone can start a seminar series, develop a discussion area, create a lounge, organize a small workshop, or organize a reading group. Furthermore, although all these things are hard to do well, if you’re willing to do critical evaluations, experiment and try radical changes, preferably in partnership with equally committed people, things are likely to improve a great deal.

Second, institutions have long memories, so changes that you make in your environment will stick around for a long time. This means that once something is working well, chances are it’ll continue to work well without much help from you – and you can move on to improve some other aspect of your environment. Furthermore, each positive change you make actually improves your leverage with other people. I’ve known undergraduate students who had made so many creative positive contributions to their departments that their influence with canny senior faculty was comparable to the influence of other senior faculty.

The creative process

The problem-solver and the problem-creator.

Different people have different styles of creative work. I want to discuss two different styles that I think are particularly useful in understanding the creative process. I call these the problem-solver and the problem-creator styles. They’re not really disjoint or exclusive styles of working, but rather idealizations which are useful ways of thinking about how people go about creative work.

The problem-solver: This is the person who works intensively on well-posed technical problems, often problems known (and sometimes well-known) to the entire research community in which they work. The best problem-solvers are often extremely technically proficient and hard-working. Problem-solvers often attach great social cache to the level of difficulty of the problem they solve, without necessarily worrying so much about other indicators of the importance of the problem.

The problem-creator: This is a rarer working style. Problem-creators may often write papers that are technically rather simple, but ask an interesting new question, or pose an old problem in a new way, or demonstrate a simple but fruitful connection that no-one previously realized existed.

Of course, the problem-solver and the problem-creator are idealizations; all researchers exemplify both styles, to some extent. But they are also useful models to clarify our thinking about the creative process. One distinction between the two styles is how proactive one is in identifying problems, with the problem-solver being much more passive, while the problem-creator is extremely proactive. By contrast, the problem-solver needs to be much more proactive in developing their problem-solving skills. Both styles of research can be extremely successful.

Problem-solvers have numerous social advantages in research, and for that reason I believe they tend to be more common. In particular, it is relatively easy to recognize (and then reward) people who solve problems that are of medium or high levels of difficulty. This has rewards both in terms of the immediate esteem of one’s peers – physicists love to trade legends about brilliant colleagues who immediately see through to the solution of some difficult problems or another – and also in the hunt for jobs and other tangible forms of recognition. It takes more time (and thus can be more difficult) to recognize people whose work is technically rather simple, but whose questions may eventually open up whole new lines of enquiry.

The advantage in being a problem-creator is that there is a sizeable comparative advantage in opening up an entirely new problem area, and thus being the first into that problem area. You can work hard to get a basic foundation in the skills needed in that problem area, and then clean up many of the fundamental problems.

The skills of the problem-creator

Our training as physicists focuses pretty heavily on becoming problem-solvers; we tend not to get much training as problem-creators. One reason I’m discussing these two working styles at some length is to dispel the common idea that creative research is necessarily primarily about problem-solving. It’s true that many people have very successful research career as problem-solvers. But you can also consciously decide to invest more time and effort into developing as a problem-creator. I now describe some of the skills involved in problem-creation.

Developing a taste for what’s important: What do you think are the characteristics of important science? What makes one area thrive, while another dies away? What sorts of unifying ideas are the most useful? What have been the most important developments in your field? Why are they important? What were the apparently promising ideas that didn’t pan out? Why didn’t they pan out? You need to be thinking constantly about these issues, both in concrete terms, and also in the abstract, developing both a general feeling for what is important (and what is not), and also some specific beliefs about what is important and what is not in your fields of interest. Richard Hamming describes setting aside time each week for “Great Thoughts”, time in which he would focus on and discuss with others only things that he believed were of the highest importance. Systematically setting aside time to think (and talk with colleagues) about where the important problems are is an excellent way of developing as a problem-creator.

On this topic, let me point out one myth that exerts a powerful influence (often subconsciously) on people: the idea that difficulty is a good indicator of the importance of a problem. It is true that an elegant solution to a difficult problem (even one not a priori important) often contains important ideas. However, I believe that most people consistently over rate the importance of difficulty. Often far more important is what your work enables, the connections that it makes apparent, the unifying themes uncovered, the new questions asked, and so on.

Internal and external standards for what is important: Some of the most thought-provoking advice on physics that I ever heard was at a colloquium given by eminent physicist Max Dresden. He advised young people in the audience not to work towards a Nobel Prize, but instead to aim their research in directions that they personally find fun and interesting. I thought his advice quite sound in some regards: for some people it is extremely tempting to regard external recognition as the be-all and end-all of research success, and the Nobel Prize is perhaps the highest form of external recognition in physics. Dresden is right, in the sense that working with a primary goal of winning a Nobel Prize would be pointless and degrading; far better to work in an area one personally finds enjoyable.

On the other hand, the Nobel Prizes are usually given for very good reasons: they reward some of the most interesting work in all of physics. There is, admittedly, a political element, with certain fields being favoured, and so on. Nonetheless, imagine a world in which one of these discoveries had not been awarded a Prize for some reason. Would you be proud to have your name associated with that discovery, even so, and regard the work on it as time well spent? In every case I can think of, that certainly is the case for me, and I suspect it’s true for most other physicists.

I believe this highlights an interesting point about what makes something interesting and important. A person working toward a Nobel Prize or some other form of external recognition has, in some sense, decided to abdicate their personal decision about what is important and interesting. The external community of physicists (in this case, represented by the Nobel Committee) is what makes their decision: if it might win a Nobel, it’s important.

Balancing this observation, this is not to say that your decision about what is interesting and important should be yours along. People who work in isolation rarely end up making contributions that are all that significant. Your decision about what is important should be informed by others: talk to your peers, find out what they think is important, look in the textbooks and history books and biographies, and, yes, look at what wins prizes (of all sorts).

But at the end of the day you’ve got to form your own independent standards for what is interesting and important and worth doing, and make judgments about where you should be making a contribution, based on those standards. I think better advice from Dresden would have been to aim to produce work of the highest possible caliber, but according to what you have come to believe is important.

Exploring for problems: Obviously, all researchers do some of this. For the problem-solver, the process of exploring for problems often works along the following lines: keep moving around, looking for problems that you consider (a) well-posed, or able to be well-posed after some work on your part, (b) likely to fall within a reasonable time to the arsenal of tools at your disposal (perhaps with some small expansion of that arsenal), and (c) below some minimum thresholds of interest and difficulty. Once you’ve found a problem of this sort, you work hard on the problem, solve it, and publish.

Problem-creators may be rather more systematic about exploring for problems. For example, they may occasionally set time aside to survey the landscape of a field, looking not just for problems, but trying to identify larger patterns. What types of questions do people in the field tend to ask? Can we abstract away patterns in those questions? What other fields might there be links to? What are the few most important problems in the field? Problem-creators set aside time for doing this kind of systematic exploration, and do it in a disciplined way, often with feedback from others.

Surveying the landscape can be particularly revealing. A lot of people work in fashionable subfields of a larger field primarily because there are lots of other people working in that subfield. The problems they work on may be technically complicated, especially after a few years, when the most basic questions have been answered. This is compensated by the fact that it’s extremely comforting to work within a field where there is a standard narrative explaining the importance of the field, some canonical models for what problems are interesting, and a willing audience of people ready to appreciate your work. In addition, working in such subfields gives younger people a chance to show off their technical prowess (sometimes, not unlike elk spoiling for a fight) to peers in a position to recommend them for valuable faculty positions.

Getting ahead of the game: There are many important problems, and sometimes an entire field comes to some agreement about what is important: proving the Riemann Hypothesis, or understanding high temperature superconductivity. Sometimes, however, there is a problem either not appreciated at all, or only dimly appreciated, that is equal in importance to such gems. Consider the creation of the scanning tunneling microscope – the basic idea had been around for years, yet nobody had ever seriously tried to build the device. The inventors put it together on a shoestring, and created one of the major tools of modern physics. Or consider David Deutsch and Richard Feynman’s creation of the field of quantum computing, by framing the right questions (“What would a quantum mechanical computer be capable of?” and “Would it be faster than a classical computer?”). One of the big ways you can get ahead as a researcher is by identifying and then solving problems that are important, but perhaps not terribly difficult, ahead of everyone else.

Identify the messes: In a nice article about how he does research, physicist Steven Weinberg emphasized the importance of identifying the messes. What areas of physics appear to be a state of mess? Funnily enough, one of the signs of this can be that it’s very hard to understand. For a long time – and to some extent this persists today – physics texts on general relativity were very difficult to understand. The tensor calculus in them was often confusing and difficult to understand. There was a good reason for this: the basic definitions in the subject of differential geometry, although laid down in the 19th century, didn’t really reach their modern form until the mid part of the twentieth century, and then took considerable time to migrate to physics. The reason a lot of the discussion of tensor calculus in physics texts is confusing is because, very often, it is confused , being written by people who don’t have quite the right definitions (meaning, in this case, simplest, most elegant and natural) in mind.

When you identify such a mess, the natural inclination of many people is to shy away, to find something that is easier to understand. But a field that is a mess is really an opportunity. Chances are good that there are deep unifying and simplifying concepts still waiting to be understood and developed by someone – perhaps you.

The skills of the problem-solver

As I’ve already said, our technical training as physicists focuses a lot more on problem-solving than problem-creation, so I’m not going to say a lot about the skills needed to be a problem-solver. But I will make a few general remarks that I find helpful.

Clarity, goals, and forward momentum: In my opinion, there is little that is more important in research than building forward momentum. Being clear about some goal, even if that goal is the wrong goal, or the clarity is illusory, is tremendously powerful. For the most part, it’s better to be doing something, rather than nothing, provided , of course, that you set time aside frequently for reflection and reconsideration of your goals. Much of the time in research is spent in a fog, and taking the time to set clear goals can really help lift the fog.

Have multiple formulations: One of the most common mistakes made by researchers is to hold on very closely to a particular problem formulation. They will stick closely to a particular formulation of a problem, without asking if they can achieve insights on related problems. The important thing is to be able to make some progress: if you can find a related problem, or reformulate a problem in a way that permits you to move forward, that is progress.

Spontaneous discovery as the outcome of self-development: For me this is one of the most common ways of making discoveries. Many people’s basic research model is to identify a problem they find interesting, and then spend a lot of time working on just that problem. In fact, if you keep your mind open while engaging in exploration, and are working at the edge of what is known, you’ll often see huge opportunities open wide in front of you, provided you keep developing your range of skills.

Working on important problems

It’s important that you work towards being able to solve important problems. This sounds silly, but people don’t do this for any number of reasons. I want to talk a little about those reasons, and how to avoid them.

Reason 1: Lack of self-development. Many people don’t spend enough time on self-development. If you stop your development at the level which resulted in your first paper, it’s unlikely you’ll solve any major problems. More realistically, for many people self-development is an incidental thing, something that happens while they’re on the treadmill of trying to solve problems, generate papers, and so on, or while teaching. While such people will develop, it’s unlikely that doing so in such an ad hoc way will let them address the most important problems.

Reason 2: The treadmill of small problems. Social factors such as the need to publish, get grants, and so on, encourage people to work only on unimportant problems, without addressing the important problems. This can be a difficult treadmill to get off.

My belief is that the way to start out in a research career is by working primarily on small and relatively tractable problems, where you have a good chance of success. You then continue the process of self-development, gradually working up to more important problems (which also tend to be more difficult, although, as noted above, difficulty is most emphatically not the same as importance). The rare exception is important problems that are also likely to be technically easy; if you’re lucky you may find such a problem early in your career, or be handed one. If so, solve it quickly!

Even later on, when you’ve developed to the point that you can realistically expect to be able to attack important problems, it’s still useful to tackle a mixture of more and less important problems. The reason is that tackling smaller problems ensures that you make a reasonable contribution to science, and that you continue to take an active part in the research community. Even Andrew Wiles continued to publish papers and work on other problems during his work on Fermat’s Last Theorem, albeit at a rather low rate. If he had not, he would have lost contact with an entire research community, and losing such contact would likely have made a significant negative difference to his work on Fermat’s Last Theorem.

Reason 3: The intimidation factor. Even if people have spent enough time on self-development that they have a realistic chance of attacking big problems, they still may not. The reason is that they have a fear of working on something unsuccessfully. Imagine Andrew Wiles feeling if he had worked on Fermat’s Last Theorem for several decades, and completely failed. For most people, the fear of ending up in such a situation is enough to discourage them from doing this.

The great mathematician Andrei Kolmogorov described an interesting trick that he used to get around this problem. Rather than investing all his time and effort on attacking the problem, he’d put the problem into a larger context. He’d announce a seminar series in which he’d lecture on material that he thought would be related to the problem. He’d write a set of lecture notes (often turning into a book) on material related to the problem. That way, he lowered the psychological pressure on himself. Rather than investing all his effort in an attack on the problem – which might ultimately be a complete waste of time – he knew that he’d produce something of value. By making the research process part of a larger endeavour, he ensured that the process was a success no matter how it came out, even if he failed to solve the problem, or was scooped by someone else. It’s a case of not putting all of one’s psychological eggs in one basket.

Richard Feynman described a related trick. He said that when he started working on a problem he would try to convince himself that he had some kooky insight into the problem that it was very unlikely anybody else had. He admitted that very often this belief was erroneous, or that, even if original, his initial insight often wasn’t very good. But he claimed that he found that he could fool himself into thinking that he had the “inside track” on the problem as a result, and this was essential to getting up the forward momentum necessary to really make a big dint in a difficult problem.

Committing to work on an important problem: For the difficult problems, I think commitment is really a process rather than a moment. You may decide to prepare a lecture to talk about a problem. If that is interesting, you enjoy it, and you feel like you have some insight, you might decide to prepare a few lectures. If that goes well, perhaps you’ll start to prepare more lectures, write a review, and maybe make a really big contribution. It’s all about building up more and more insight. Ideally, you’ll do this as part of some larger process, with social support around you.

People who only attack difficult problems: There is a converse to the problem I’ve been talking about, which is people who are only interested in attacking problems that are both difficult and important. This affliction can affect people at any stage of their career, but it manifests itself in somewhat different ways at different stages.

In the case of the beginner, this is like a beginning pole vaulter insisting on putting the bar at 5 meters from the time they begin, rather than starting at some more reasonable height. Unless exceptionally pigheaded, such a person will never learn to vault 5 meters successfully, simply because they will never learn anything from failure at a more realistic starting height. This sounds prima facie ridiculous, but I have seen people burn out by following exactly this strategy.

The case of the more experienced researcher is more difficult. As I’ve emphasized, once you’ve reached an appropriate level of development I think it’s important to spend some time working on the most important problems. But if that’s all you do, there are some very significant drawbacks. In particular, by attacking only the most important and most difficult problems an experienced researcher (a) takes themselves out of circulation, (b) stops making ongoing contributions, (c) loses the habit of success, and (d) risks losing morale, which is so important to research success. I think the solution is to balance one’s work on the more and less important problems: you need to schedule time to do the more important stuff, but should also make sure that you spend some time on less high-risk activities.

In both cases, the explanation is often, at least in part, intellectual macho. Theorists can be a pretty judgmental lot about the value of their own work, and the work of others. This helps lead some into the error of only working on big problems, and not sometimes working on little problems, for the fun of it, for the contact it brings with colleagues, and for the rewarding and enjoyable sense of making a real contribution of some significance.

This essay has been translated into Chinese by Buhua Liu.

10 comments

Excellent stuff! It reads like a researcher’s “Enchiridion.”

I’ve written about some of these issues on my own site, in particular, the need to try to find something important to work on. In my experience, the difficulty of trying to work on large problems is even greater in the industrial setting. Amazingly trivial things are perfectly capable of eating away your days, and your career.

Have you read Robert Root-Bernstein’s book “Discovering”? He addresses the question of how people make important discoveries, and concludes that some of it is (or could be) learned behavior. It’s an odd book, but well worth seeking out. Many of its conclusions are very similar to yours.

Derek: Thanks for the kind words. I’ve never read Epictetus, but I’m quite a fan of Marcus Aurelius’ “Meditations”, so perhaps that’s the influence you’re seeing.

As an academic, I actually did quite a bit of agonizing over whether or not to cite my sources, and ended up deciding not to in the main, viewing this more like a magazine article or opinion piece than a piece of research. One day I’d like to go back and construct a nice annotated bibliography. (Possibly with the book you recommend, which I’ll certainly take a look at.)

A very realistic portrait of the challenges involved in tackling significant problems. Maintaining habits which lead to excellence is very difficult in any field. I find often scientists assume research skills don’t translate into business, but critical thinking and the ability to properly dissect a problem into manageable chunks is a rare and valuable skill.

What an enjoyable and useful look at the process of research. What I find particularly useful is that there is a “balance” in all areas, “nothing in excess,” approach here, i.e. the advice to have home and life in order, in the long-term, to produce quality. Classical, rather than the romantic “burn brightly and fade away.” I am also intrigued by your categories of researcher: the problem solver and problem creator. I find these very accurate descriptions in my own field, English, (more specifically rhetoric and composition) and in my own ideal of how I want to pursue research – the big questions of language and writing research (what is persuasive language? how do we teach writing?) alternate with “smaller,” practical issues of research (what is an effective way to teach this essay, format a bibliography, etc.)

Inspiring read. Thanks.

Ed and Susan: Thankyou to you both for the kind words.

On categories of researcher: I find it remarkable and surprising to hear that this kind of divide holds also in English. I was certainly only thinking of theoretical physics (and, to some extent, mathematics) when I wrote that!

I’m a postgraduate and began to do research in theoretical physics just now .This article is quite helpful and useful for me. Thank you for writing the nice article! I will recommend it to my friends.

This piece definitely resonates with me. I hope your students listen and understand the advantage they have if you communicate this to them early. I believe most people obtain PhDs but are not taught *how* to do research – which is what you discuss; they only solve *some* problem and by osmosis are to pick up the *how*. Most pick this up from many post-docs and jobs if they are lucky enough to work with good researchers, a horribly inefficient process.

You may be interested in looking at what has been written about John Wheeler’s approach to working with his graduate students (I read a summary somewhere, which I now misplaced). You may have more materials and colleagues you can access. It always amazed me that so many of his students did excellent work. It was not that they were all geniuses and he just knew how to pick them; there was definite training here — on how to solve problems of increasing difficulty, and to always work on one short-range, and one long-range problem, at the same time.

One final note: any ideas on scientists in industry? In particular, I found the following pressures eventually lead to a state of brownian motion: the pressure that all work “has to be profitable”, the “instant expert” syndrome and tracking and justifying time by the minute.

Thanks, fc.

On Wheeler: I’d be _extremely_ interested to see the document you refer to. Like you, I am amazed at all that has been accomplished by the people he worked with. I doubt it was chance.

On brownian motion in research: even in academia, I find I sometimes end up feeling the same kind of pressures you mention. Personally, I find one useful solution is to regularly schedule a short period – even just an hour or half an hour a day – in which I isolate myself from other concerns, and just concentrate on one thing that I believe is truly important, deliberately allowing myself to work on it in an unhurried way, without interruptions. No phone, no email, no web, and no working on stuff that is urgent, but neither fun nor important!

Please answer me this question “WHAT DEFINES A GOOD RESEARCH”

is there any importance of research?

Comments are closed.

What Should Be the Characteristics of a Good Research Paper?

by team@blp

In miscellaneous.

When people want to get answers to various issues, they search for information on the problems. From their findings, they expand them, aiming to agree or refute them. Research papers are common assignments in colleges. 

They follow specific research and writing guidelines to answer particular questions or assigned topics . They look into the critical topic of credible research sources and argue their findings in an orderly manner. To be termed as good, the research paper must bear the following characteristics.

In this Article

Gives credit to previous research work on the topic

• It’s hooked on a relevant research question.

It must be based on appropriate, systematic research methods

• The information must be accurate and controlled.
• It must be verifiable and rigorous.

It must be clear and coherent.

It must be dealt with critical analysis., it must be original., it must possess ethical integrity., be careful with the topic you choose, decide the sources you want to use, create your thesis statement , plan your points, write your paper, characteristics of a good research paper.

Writing a research paper aims to discover new knowledge, but the knowledge must have a base. Its base is the research done previously by other scholars. The student must acknowledge the previous research and avoid duplicating it in their writing process.

A college student must engage in deep research work to create a credible research paper. This makes the process lengthy and complex when choosing your topic, selecting sources, and developing its design. In addition, it requires a great deal of knowledge to piece everything together. Fortunately, Studyclerk will give you professional help anytime you need it. If you do not have enough knowledge and time to write a paper on your own, you can ask for  research paper help  by StudyClerk, where experienced paper writers will write your paper in no time. You can trust their expert writers to handle your assignment well and get a well-written paper in a short time.

It’s hooked on a relevant research question .

All the time a student spends researching multiple sources is to answer a specific research question. The question must be relevant to the current needs. This question guides them into the information they use or the line of argument they take.

The methodology of research a student chooses will determine the value of the information they get or give. The methods must be valid and credible to provide reliable outcomes. Whether the student chooses a qualitative, quantitative, or mixed approach, they must all be valuable and relevant. 

The information must be accurate and controlled .

A good research paper cannot be generalized information but specific, scientific information. That is why they must include references and record tests or information accurately. Moreover, they must keep the information controlled by staying within the topic from the first step of research to the last. 

It must be verifiable and rigorous .

The student must use information or write arguments that can be verified. If it’s a test, it must be replicable by another researcher. The sources must be verifiable and accurate. Without rigorous deep  research strategies , the paper cannot be good. They must put a lot of labor into both the writing and research processes to ensure the information is credible, clear, concise, original, and precise. 

The paper should be written clearly, concisely with logical progression from one section to another. This includes having a well-structured introduction, body, and conclusion. Each section should be coherent and contribute directly to the reader’s understanding of the research question, findings, and implications.

A good research paper involves not just reporting facts and data, but also critically analyzing them. This means evaluating the strengths and limitations of the research, discussing the implications of findings, and situating the results within the broader field of study. The analysis should engage with different perspectives and theories, showing an awareness of the complexity of the topic.

While it builds on previous research, a good research paper offers new insights or approaches to the topic. This could be through presenting new findings, developing a novel theoretical approach, or offering a unique combination of existing knowledge. Originality, especially the research statement , is crucial for advancing knowledge and adding value to the field.

Ethical considerations are paramount in research. A good research paper adheres to ethical standards when it comes to data collection, reporting, and analysis. This includes obtaining necessary permissions for using data, respecting participant privacy in the case of human subjects, and being transparent about any conflicts of interest.

How to write a good research paper

To write a good research paper, you must first understand what kind of question you have been assigned. Then, you will choose the best topic that you will love to write about. The following points will help you write a good research paper.

You must select a topic you love. Go for a topic that will be easier to research, which will give you a broader area of study. 

Your instructor doesn’t restrict you on the sources you must use. Broaden your mind so that you don’t limit yourself to specific sources of information. Sometimes you will get helpful information from sources you slightest thought as good.

Write your central statement to base your position on the research. Make it coherent contentious, and let it be a summary of your arguments.

Create an outline that will guide you when arguing your points

• Start  with the most vital points and smooth the flow.
• Pay attention to  paragraph structure  and let your arguments be clear.
• Finish with a compelling conclusion, and don’t forget to cite your sources.

A research paper requires extensive research methods to get solid points for supporting your stand. First, the sources you use must be verifiable by any other researcher. You must ensure your research work is original for your paper to be credible. Third, each point should be coherent with each paragraph. Finally, your research findings must be tagged on the research question and provide answers that apply to the current society. 

Author’s Bio

Helen Birk is an online freelance writer who holds an outstanding record of helping numerous students do their academic assignments. She is an expert in essays and thesis writing, and students simply love her for her high-quality work. In addition, she enjoys cycling, doing pencil sketching, and listening to spiritual podcasts in her free time.

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Top 22 Qualities | Characteristics | Essentials of a good and Ideal Report

A report should contain all the information which are required by the interested parties. Hence, some principles are followed while drafting a report. These principles are simply guidelines.

The accountant should not feel that he has to conform to a set of rules that places him in a straight jacket. However, there are few guides that he should keep in mind. The rules will not be valid in all cases because of the difference in capabilities of top management to digest information and because of variations in the form in which management wants that information.

Therefore, a report is prepared by considering the following points.

Table of Contents

• 1.1 1. Suitable Title
• 1.2 2. Simple
• 1.3 3. Promptness
• 1.4 4. Comparability
• 1.5 5. Consistency
• 1.6 6. Precise and Accurate
• 1.7 7. Relevant Information
• 1.8 8. Presented to Required Person or Group or Department
• 1.9 9. Routine Details
• 1.10 10. Timeliness
• 1.11 11. Adaptability
• 1.12 12. Ability to Control
• 1.13 13. Economy or Cost Consciousness
• 1.14 14. Effective Communications
• 1.15 15. Principle of Exception
• 1.16 16. Frequency of Reports
• 1.17 17. Media of Presentation
• 1.18 18. Attractiveness
• 1.19 19. Co-ordination of Data
• 1.20 20. Up to Date
• 1.21 21. Number of Reports
• 1.22 22. Good Form and Content
• 2 Infographic on Qualities, Characteristics, Essentials of a good and Ideal Report

Qualities or Characteristics of Good or Essential report

1. suitable title.

A suitable title has to be provided to each report according to the nature of contents. It should also highlight upon its origin and the person for whom it is being prepared.

A report should be readable by an ordinary layman and in known language. Such type of simple style of language is used in the report preparation. As far as possible, scientific or technical language is best left out of reports , unless it becomes unavoidable. In case the reports are of regular nature, it is preferable to get language more or less standardized.

3. Promptness

A report should be prepared and submitted within short span of time or time stipulated by the request letter. Information delayed is information denied. At the same time, accuracy of information should not be given up at the cost of achieving objective of promptness. The following steps may be taken to collect the information as early as possible.

• Accounting records should be kept in such a way that fulfill the requirements of submission of different reports.
• Mechanical devices can be used for record keeping at the maximum to avoid clerical errors and increase productivity.
• Accounting work should be departmentalized in order to prevent bottle necks in reporting.
• In the case of prevailing abnormal or extra-ordinary situation, the employees are asked to report the same immediately.

4. Comparability

Sometimes a report is prepared with some comparative information. In this case, a standard information is compared with actual information. If not so, current year information is compared with last year information. In certain cases, the prospective information is prepared well in advance and the actual information is compared. The main objective of comparability is to highlight significant variations.

5. Consistency

A report should be prepared for many years from the same type of information and statistical data . If so, there is a possibility of preparing a report in consistency. It is possible if same accounting principles and concepts are used for collecting, classifying, tabulating and presenting the information. The usage of report is increased through consistency.

6. Precise and Accurate

A report should be precise, accurate and specific. It can be just a bad reporting practice to supply too much information which over whelms the order; as too little which leaves him guessing. If report is quite long or detailed, then a synopsis should be prepared to cover all significant facts and conclusions.

7. Relevant Information

Relevant accurate data is alone included in the report. If not so, it will involve unnecessary expenditure and the reports will be a waste.

8. Presented to Required Person or Group or Department

The reports should be specific and presented only to the person in need . Sometimes, reports are sent to various departments in a routine way, if so, the reports are prepared in such a way that includes common information.

9. Routine Details

Every report should contain the routine detail s like the period of time of preparing report, the period covered in the report, date of presentation of report, the units of information, the name of the person preparing and presenting it, names of persons to whom it is being submitted. etc.

10. Timeliness

A report should be prepared and presented within the stipulated time . If a report is received late, there is no meaning of preparing such report and no use for management. If the report is presented in time, necessary actions may be taken.

Obviously financial data are more valuable when the events are fresh in the minds of users. The element of time elapsing between the events and the report determines to a large extent, the value of financial reports. Timeliness is generally more important than a high degree of accuracy in the figures.

11. Adaptability

The format and contents of the report should be suitable to the person or group of person s who are going to use the report and the purpose for which it is required. A report can be adoptable if it is prepared and presented according to the needs of the different levels of management (top, middle and lower).

According to Welsch,

“In the design of reports suited to the principal user, consideration must be given to the method of presentation. Those executives, who are going to utilize the reports, have different backgrounds, working methods personalities and personal preferences. Executives having controller-ship background, generally prefer tabulated and detailed data, those having engineering backgrounds frequently prefer graphic presentations, highly summarized data”. (adsbygoogle = window.adsbygoogle || []).push({});

12. Ability to Control

The reports should give full details of variances such favorable and unfavorable. In the case of unfavorable variances, the report should contain a massage about the unfavorable variances which are controllable at that point. If so, corrective controllable actions may be taken by the appropriate level of authority. Moreover, some unfavorable variances which are beyond the control of the executive receiving the report should be mentioned separately or highlighted in the report.

13. Economy or Cost Consciousness

This cost of preparing and presenting the report should also be considered. This cost should not be more than the advantage derived from such reports. The cost of preparing the report should be reasonable so that reporting may be used by all types of concerns.

14. Effective Communications

If the management executives have taken the action on the basis of report and the report influence decisions, there is an effective communication.

In order to be useful to management, accounting information must be communicated to managerial persona l. Communication implies that a person receiving the information understands the nature and significance of material contained in the reports he receives when communication is genuinely effective, management’s actions and decisions are likely to be based on the facts which they receive rather than on untested impressions and guesses.

However, there is a reason to believe that accounting reports to management have not always achieved their intended purpose because the reports were not understood, recipients lacked time required to grasp the meaning or contents of reports was not relevant to problems facing the persons who received them.

15. Principle of Exception

The principle of exception should be followed while preparing and presenting the reports. If so, trouble spots and/or illuminating priority areas are calling for management attention and action. In this case, some benefits are derived such as essential matters only included in the report to the user of the report, more concentration is possible and minimum data is included in the report. Even though, this principle has limited use.

16. Frequency of Reports

The frequency of reports should be decided, well in advance according to the nature of information and its purpose. It means that the reports should be sent regularly when they are demanded or required. Therefore, some reports may be sent daily, some weekly, some once in ten days, some fortnightly, some monthly and so on.

17. Media of Presentation

A report may be prepared for presenting the same in several medias. Therefore, a report may be in written form or oral form or graphic form . An ideal report is presented in the form which carries successful blending of different media.

18. Attractiveness

The style of presenting the report should attract the attention of the user of the report. In meeting this broad requirement for attractiveness in reporting, the accountant assumes the role of an artist . His task is to print a picture that will appeal to the eyes. His report should serve as panorama which is attractive in an artistic sense and therefore one that will be regarded and studied by the potential viewer.

19. Co-ordination of Data

All type of information are collected from various departments including accounting data while preparing the report. In this case, there is a need of coordination of data. It means that data used by different departments should not be unrelated , otherwise a lot of misunderstandings and confusions may arise which would defeat the very purpose of reporting .

20. Up to Date

A report should contain only latest information . Even though, excessive information cannot be included in the report. It means that report should be kept up to date which are necessitated by the changing conditions.

21. Number of Reports

There is no ideal number of reports to be used in an organization. At the same time, a report should be an additional one and should not give birth to be a duplication. Therefore, reports should be prepared and used only for selective areas . The number of reports should be kept as minimum as possible .

22. Good Form and Content

The following points are to be considered while drafting a report.

• A report is prepared in well classified paragraph with suitable heading and sub-heading if possible.
• The title of the report explains the purpose for which the report is prepared and the period covered by the report. For example: Report of the Performance of Sales Representatives of January 2011.
• The title also enables to point out the persons who need the report.
• If statistical figures are to be given only significant figures given in the body of the report and other detailed figures should be given in appendix .
• The reports should contain facts and not opinions . The opinions are given if necessary.
• The report must contain the date of its preparation and date of submission .
• Sometimes a report is prepared on the basis of request made by the management. If so, the report should bear the reference number of such request or letter.
• A report is prepared to satisfy only one purpose. Separate reports be prepared for different subjects .
• The contents of the report should be in a logical sequenc e.

Infographic on Qualities, Characteristics, Essentials of a good and Ideal Report

Related Posts

On the other hand, a research report is a written document that describes an investigative work from beginning to end. The specific details in a report vary according to the type of inquiry.

In addition, specific conventions for writing in each of the scientific disciplines must be taken into account.

Main characteristics of a research report

Clarity of thought and language.

Clarity of thought and language are among the most essential characteristics of a research report. It is important to highlight that research is a thought process that begins even before choosing the topic of study.

The reasoning power of the researcher is the effective tool for the decisions that must be made throughout the process. This process demands a patient, deep and alert thinking.

In this way, clear thinking results in clear writing. As far as possible, sentences should be simple and important points should be highlighted in small paragraphs. This clarity will make the reader easily understand what the author of the report wants to say.

Conceptual clarity

Another characteristic of a research report is its conceptual clarity. The concepts in a study must be defined and explained. In general, the explanations of a dictionary are almost never adequate for research purposes.

Therefore, it is important to be very explicit, even with that terminology that seems to be very simple. It must be taken into account that the same term may have different definitions in different areas of knowledge.

Explicit statement of the research problem

The research report must establish the problem studied explicitly and unambiguously. In the case of Quantitative investigation , the problem statement must specify the variables and the population subject to study.

This approach can be made in declarative or question form. For its part, in qualitative research, the approach is much broader and indicates the general purpose of the study.

Organization and format

Research reports must observe certain standards of format and organization. The details of the format (type and size of source, margins, form of citing sources, presentation of the list of references, among others), are regulated by each institution.

On the other hand, other characteristics, such as the general organization, reflect the expectations of the scientific community. In this way, it is expected that the report contains a general summary, introduction (with the background and motivation of the study), materials and methods, results and the analysis of results.

Use of citations and list of references

It is very common that when conducting an investigation the intellectual property of another author is used. In research reports, an appointment should be suitably included when referring, summarizing, paraphrasing or quoting from another source. There are multiple formats for dating styles, and they vary according to the academic discipline.

In addition, the report must contain the list of references. These offer all the necessary information to locate the sources.

• University of Southern California. (2017, December 08). Organizing Your Social Sciences Research Paper: Academic Writing Style. Retrieved on December 29, 2017, from libguides.usc.edu .
• Locke, L. F.; Silverman, St. J. and Spirduso, W.W. (2004). Reading and Understanding Research. Thousand Oaks: SAGE.
• Cauvery, R.; Sudha, U. K.; Girija, M. and Meena kshi, R. (2003). Research Methodology. New Delhi: S. Chand Publishing.
• Profetto-McGrath, J.; Polit, D. F. and Beck, C. T. (2010). Canadian Essentials of Nursing Research. Philadelphia: Lippincott Williams & Wilkins.
• Ary, D.; Jacobs, L. C. and Sorensen, C. (2009). Introduction to Research in Education. Belmond: Cengage Learning.
• Westervelt, M. (s / f). Research Paper Organization and Content. Retrieved on December 29, 2017, from seas.upenn.edu.
• Penn State University. (2017, October 12). In-text Citation. Retrieved on December 29, 2017, from guides.libraries.psu.edu.
• The University of Tennessee. (s / f). Citing Sources and Avoiding Plagiarism. Retrieved on December 29, 2017, from guides.libraries.psu.edu.

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This paper is in the following e-collection/theme issue:

Published on 17.7.2024 in Vol 26 (2024)

Mapping Digital Public Health Interventions Among Existing Digital Technologies and Internet-Based Interventions to Maintain and Improve Population Health in Practice: Scoping Review

Authors of this article:

• Laura Maaß 1, 2, 3 , MA   ; 
• Konstantinos Angoumis 4, 5 , MSci   ; 
• Merle Freye 2, 6 , PhD   ; 
• Chen-Chia Pan 2, 5, 7 , MA  

1 University of Bremen, SOCIUM Research Center on Inequality and Social Policy, Bremen, Germany

2 Leibniz ScienceCampus Digital Public Health Bremen, Bremen, Germany

3 Digital Health Section, European Public Health Association - EUPHA, Utrecht, Netherlands

4 University of Bielefeld, Bielefeld, Germany

5 Leibniz Institute for Prevention Research and Epidemiology - BIPS, Bremen, Germany

6 University of Bremen, Institute for Information, Health and Medical Law - IGMR, Bremen, Germany

7 University of Bremen, Institute for Public Health and Nursing Research – IPP, Bremen, Germany

Corresponding Author:

Laura Maaß, MA

University of Bremen, SOCIUM Research Center on Inequality and Social Policy

Mary-Somerville-Straße 3

Bremen, 28359

Phone: 49 421 218 58610

Email: [email protected]

Background: The rapid progression and integration of digital technologies into public health have reshaped the global landscape of health care delivery and disease prevention. In pursuit of better population health and health care accessibility, many countries have integrated digital interventions into their health care systems, such as web-based consultations, electronic health records, and telemedicine. Despite the increasing prevalence and relevance of digital technologies in public health and their varying definitions, there has been a shortage of studies examining whether these technologies align with the established definition and core characteristics of digital public health (DiPH) interventions. Hence, the imperative need for a scoping review emerges to explore the breadth of literature dedicated to this subject.

Objective: This scoping review aims to outline DiPH interventions from different implementation stages for health promotion, primary to tertiary prevention, including health care and disease surveillance and monitoring. In addition, we aim to map the reported intervention characteristics, including their technical features and nontechnical elements.

Methods: Original studies or reports of DiPH intervention focused on population health were eligible for this review. PubMed, Web of Science, CENTRAL, IEEE Xplore, and the ACM Full-Text Collection were searched for relevant literature (last updated on October 5, 2022). Intervention characteristics of each identified DiPH intervention, such as target groups, level of prevention or health care, digital health functions, intervention types, and public health functions, were extracted and used to map DiPH interventions. MAXQDA 2022.7 (VERBI GmbH) was used for qualitative data analysis of such interventions’ technical functions and nontechnical characteristics.

Results: In total, we identified and screened 15,701 records, of which 1562 (9.94%) full texts were considered relevant and were assessed for eligibility. Finally, we included 185 (11.84%) publications, which reported 179 different DiPH interventions. Our analysis revealed a diverse landscape of interventions, with telemedical services, health apps, and electronic health records as dominant types. These interventions targeted a wide range of populations and settings, demonstrating their adaptability. The analysis highlighted the multifaceted nature of digital interventions, necessitating precise definitions and standardized terminologies for effective collaboration and evaluation.

Conclusions: Although this scoping review was able to map characteristics and technical functions among 13 intervention types in DiPH, emerging technologies such as artificial intelligence might have been underrepresented in our study. This review underscores the diversity of DiPH interventions among and within intervention groups. Moreover, it highlights the importance of precise terminology for effective planning and evaluation. This review promotes cross-disciplinary collaboration by emphasizing the need for clear definitions, distinct technological functions, and well-defined use cases. It lays the foundation for international benchmarks and comparability within DiPH systems. Further research is needed to map intervention characteristics in this still-evolving field continuously.

Trial Registration: PROSPERO CRD42021265562; https://tinyurl.com/43jksb3k

International Registered Report Identifier (IRRID): RR2-10.2196/33404

Introduction

Digital technologies have become ubiquitous in all facets of life and work [ 1 ]. Within health care, digital solutions offer a promising opportunity to make processes and operational methods more efficient and effective [ 2 , 3 ]. This advancement in health care and public health will empower individuals to engage in self-management and actively manage their overall well-being and health [ 4 ]. Similarly, digital technologies can facilitate the cost-efficient implementation of health promotion, prevention, monitoring, and surveillance measures, making them easy to access [ 5 - 11 ]. These technologies also foster novel care possibilities, enabling sustainable and equitable access to health services across entire populations [ 12 - 16 ]. Therefore, adopting digital health solutions presents a valuable opportunity to strengthen national health care systems. Eventually, these solutions will transform traditional clinical care and public health structures, fundamentally reshaping health systems on a global scale.

However, to our knowledge, no study has yet attempted to comprehensively map out the heterogeneous landscape of digital public health (DiPH) and digital public health interventions (DiPHIs). Despite existing reviews focusing on selected intervention categories [ 17 ], specific target groups such as adolescents [ 18 , 19 ] or patients who are chronically ill with specific medical conditions [ 20 ], a comprehensive mapping of interventions in digital health is still missing. In addition, in all existing reviews, the studies analyzed digital health interventions but not DiPHIs, thereby limiting these interventions to their medical and clinical usability. Therefore, this scoping review aims to fill the research gap and comprehensively map out the heterogeneous landscape of DiPHIs. The development, implementation, integration, and evaluation of evidence- and needs-based DiPH interventions require a clear and shared understanding of the specific characteristics of digital health technologies for public health purposes [ 21 ]. Conversely, the lack of a standardized lexicon creates communication challenges between the subdisciplines of DiPH [ 22 , 23 ], while concurrently hindering comparability between national health systems.

Definition of DiPH

For this review, DiPH is defined as using information and communication technologies (ICTs) such as digital technologies, services, or tools to achieve traditional public health goals [ 24 ] with a population health impact [ 25 ]. According to Winslow [ 26 ], public health aims at “preventing disease, prolonging life, and promoting physical and mental health and efficiency through organized community efforts...” This definition is still used nowadays by the World Health Organization (WHO) to define essential public health functions. This places public health as the leading discipline in health governance, financing, health information systems, communication, coverage, care, education, and health regulations to protect and promote the health of populations [ 27 ].

Hence, we define DiPHI as interventions that address “at least one essential public health function through digital means.” [ 26 ]. To enhance acceptance among the population, DiPHI should consistently follow a needs- and evidence-based design with a participatory and human-centric approach [ 21 , 25 , 28 , 29 ]. The impetus behind their development should not stem solely from technological capabilities but from DiPHIs potential to mitigate disparities and improve access to health services among different groups of a population [ 22 , 25 , 27 ].

Unlike the domain of digital health , which involves the application of health ICT for personalized medicine and telemedicine [ 30 ] and its subfield mobile health , which primarily focuses on patient monitoring and the use of personal digital assistants in the clinical setting [ 31 ], DiPHIs encompass a broader spectrum of services and interventions. These include those in health promotion, such as wearables to promote physical activity; in prevention, such as web-based vaccination registries; in health care, such as telemedicine or electronic health records (EHRs); and in surveillance systems, such as dashboards or tracing systems for infectious disease monitoring on a national level. The goal of DiPHIs is to improve the health and well-being of groups considered vulnerable rather than individuals [ 25 ].

By combining the foundational goals of public health with the capabilities of ICT applications, DiPHIs have the potential to substantially strengthen population health, promote well-being, and advance public health objectives. This impact can be realized at the individual, community, and national levels [ 32 ].

Study Aims and Objective

This scoping review primarily aims to outline a comprehensive range of proposed to implemented DiPHI, including different levels of prevention, health care, and public health research initiatives. Following the aforementioned definition of DiPHI, the second objective is to map the landscape of the existing DiPHI, shedding light on their self-reported digital health functions (based on the evidence standards framework [ESF] for digital health technologies from the National Institute for Health and Care Excellence [NICE] [ 33 ]) and the addressed essential public health functions as defined by the WHO [ 27 ]. Our scoping review will guide future research to address underexplored DiPHI types by identifying research gaps (eg, underrepresented intervention types). The multinational and interdisciplinary comparative analysis of interventions will generate a data set on various interventions, their characteristics, functions, and use cases, which can support researchers or policy makers to make informed decisions for future DiPHIs planning and upscaling.

It is vital to acknowledge that this scoping review, while intended to illustrate the distinctive characteristics of DiPHI, does not seek to provide exhaustive analyses on cost-effectiveness, efficacy, or barriers and facilitators of implementation. The inherent heterogeneity of DiPHI renders it impractical to address these multifaceted aspects within a single literature review [ 13 , 14 ].

Following the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines, we registered our review protocol with the PROSPERO database (CRD42021265562) on August 2, 2021, and details and rationale of the protocol were published in 2022 [ 34 ].

Eligibility Criteria

The standards for eligibility were constructed in the participants, intervention, and study design format. An overview of the inclusion and exclusion criteria is presented in Textbox 1 . Accompanying these criteria, the general requirements of full-text accessibility and the publication language were also considered. The review expanded the publication language limitation to English, German, and Chinese based on the language skills of the reviewer team. Given the scope of our study, which focuses on mapping the characteristics of DiPHI rather than comparing the effectiveness or costs, the review process refrains from specifically incorporating reported outcome variables.

Inclusion criteria

• The study focuses on the community level or above (ie, regional or national) of the general population.
• The paper describes a concrete digital public health intervention (DiPHI) that addresses at least 1 essential public health function through digital means as defined by the World Health Organization (WHO).
• The DiPHI matches our definition of digital public health.
• The DiPHI addresses at least 1 essential public health function as defined by the WHO.
• The DiPHI is paid or reimbursed by the government or health insurance.
• The DiPHI uses the internet or Bluetooth to provide its core function or service.
• The DiPHI is the central research object of the paper.
• All original peer-reviewed studies, reports, books, book chapters, or peer-reviewed conference papers that have a description of a DiPHI as their primary intervention component.
• Full text was available.

Exclusion criteria

• The study population consists of veterans, armed forces, prisoners, inmates, refugees, or asylum seekers.
• The intervention needs to be privately bought by the user without reimbursement by the government or health insurance.
• The intervention focuses on background management processes.
• Study protocols, editorials, commentaries, conference proceedings, or reviews (ie, narrative reviews, scoping reviews, systematic reviews, or meta-analyses).
• Full text was not available.

Literature Search

The initial search followed a comprehensive search strategy conducted on February 19, 2021, in CENTRAL, PubMed, and Web of Science. We ran an additional search following the same search strategy on December 1, 2021, for 2 additional databases: ACM Full-Text Collection and IEEE Xplore. The search results for all 5 databases were updated on October 5, 2022. We applied a consistent search string to all databases with adaption according to index and syntax specifications differences. Given the substantial volume of publications aligning with our inclusion criteria, supplementary manual searches were not undertaken. However, we conducted reference list searches for reviews and meta-analyses describing DiPHIs. No additional references were identified through this approach, as all references were already identified through our systematic search.

The search strategy for all databases was structured around 3 themes connected through “AND.” Terms within the themes are combined through “OR” (refer to Figure 1 for the general overview and Multimedia Appendix 1 for the complete search strategy for all databases, including results per term of the initial search). We decided against searching for concrete interventions such as EHRs, specific health or medical apps, or other interventions to reduce the risk of confirmation bias.

We additionally used Medical Subject Headings wherever appropriate during database searches. All other terms were limited to title, abstract, or keywords. No search limits were applied.

Screening Process

We applied a 3-stage screening strategy (ie, titles, abstracts, and full texts) to identify suitable publications ( Figure 2 ). To reduce the list of reasons for full-text exclusion, the first 3 exclusion criteria mentioned in Textbox 1 were summarized under “wrong setting.” Three authors (LM, MF, and KA) were involved in the screening process for eligibility, and each stage had 2 authors partake in the screening independently. After each screening stage, another author (CCP) resolved any disagreements on study selection with independent decisions. The screening was conducted through the free web and mobile app Rayyan (Rayyan Systems Inc) [ 35 ]. References published in another language than English, Chinese, or German were excluded during full-text screening. Chinese references were screened only by CCP. Cohen κ for full-text screening was 0.77 (identifying a substantial agreement rate according to the study by Landis and Koch [ 36 ]). Full texts were included if the article was published open access, if it was published in a subscription journal licensed by our institution, or if the corresponding author provided a copy. An overview of all excluded full texts, along with the reasons for their exclusion, is included in Multimedia Appendix 2 [ 37 - 39 ].

Data Extraction and Qualitative Content Analysis

Two authors (LM and KA) independently extracted data in an Excel 2019 spreadsheet (Microsoft Corp). The extraction sheet was piloted with the first 10 included publications. The extraction for all data except for the technical functions and nontechnical intervention characteristics (which were extracted as free texts) followed a predefined coding table, which was extended if necessary ( Table 1 ). The extraction for all data was based on qualitative description directly provided by the included texts. Discrepancies in data extraction were resolved through discussion between the 2 authors. Missing data for the included publications or data where only a vaguely formulated description was given in the text were requested from authors via email. Where multiple interventions were described within 1 publication, data for each intervention was extracted in a new row. Target groups were defined and extracted based on the digital health application directory by Lantzsch et al [ 37 ] due to their precise differentiation between healthy users and patient users. Additional target groups (eg, policy makers, health professionals, or researchers) were added in an iterative process. The digital health functions and the intervention types followed the 2019 edition of the NICE ESF for digital health technologies [ 33 ]. The most updated ESF from 2022 reduced its number of individual technical functions and was changed toward a more clinical setting. However, the 2019 framework still included 10 different functions, for example, intervention types covering health promotion, health care, communication, education, and system services. Therefore, we deemed the 2019 version more suitable for our mapping approach. In addition, these functions were supported by the work of Lantzsch et al [ 37 ]. The public health functions were based on the 11 WHO functions [ 27 ]. Building on our previous research, ESF and ESPHF are merged to map DiPH for this study [ 29 ]. Extracting authors selected the option “other” where multiple target groups, functions, or prevention or health care levels appealed.

Target groups were defined and extracted based on the digital health application directory by Lantzsch et al [ 37 ] due to their precise differentiation between healthy users and patient users. Extracting authors selected the option “other” where multiple functions or target groups appealed. This decision displays the only deviation from the registered study protocol for this review [ 34 ] where we did not define different categories within target groups (the study by Lantzsch et al [ 37 ] was published after our study protocol, which underlines the rapidly evolving nature of DiPH). The definitions for prevention and health care (ie, last column in Table 2 ) were based on the WHO definitions ( Table 2 ).

In addition to the previously mentioned topics, we also extracted information on the study design, publication year and type, intervention name, technical features, and nontechnical characteristics. We did not extract data on outcome measures or type of data collection in the included publications because this review aims to conduct an intervention mapping focusing on their characteristics and not on their effectiveness or costs.

a Not applicable.

a WHO: World Health Organization.

For the geographic analysis of interventions, we counted every intervention multiple times if it was implemented internationally. For instance, Adler et al [ 45 ] described an intervention that was implemented in 7 countries. Weighting these interventions per country by the number of countries they were implemented in (here 1/7) would have weakened internationally planned or implemented interventions compared to interventions only targeting 1 country. Therefore, we decided to give full weight to each intervention and count the intervention as 1 for every targeted country. While this approach resulted in an artificially higher number of included interventions, it also ensured that international interventions were not discriminated against based on the geographic analysis.

For the qualitative analysis, we grouped the identified references by intervention types based on our study protocol. We then summarized the extracted data for each intervention type, as illustrated in Table 2 . Additional intervention types were added in an inductive procedure where needed. In addition, we developed an inductive category system based on 5 randomly selected publications per intervention type to describe the technical functions and nontechnical characteristics of different intervention types. The qualitative content analysis through iterative coding was then conducted for all references of 1 intervention type in MAXQDA 2022.7 (VERBI GmbH) by LM. The procedure followed the inductive content analysis procedure described by Vears and Gillam [ 46 ].

In total, we identified 15,701 different publications published until October 5, 2022 (24,767 before deduplication), through our systematic search in 5 scientific databases. Of these, 2987 (19.02%) were assessed for abstract screening and 1609 (10.25%) for full-text screening. The process excluded 1414 records, primarily due to unavailable full-text content and a lack of specificity in describing interventions. Of the screened full texts, the remaining 11.5% (185/1609) were considered eligible for this review. Some of these publications described multiple interventions, whereas, in other cases, the same intervention was presented by >1 publication. Of the 185 publications, 96 (51.9%) were case reports that focused on a detailed intervention design or implementation description, while the aim of the remaining 89 (48.1%) publications lay on the intervention evaluation, most often evaluated through cross-sectional studies (n=37, 20%), trials (n=19, 10.3%), or longitudinal studies (n=18, 9.7%). The characteristics and extracted information of all included 185 references are displayed in Multimedia Appendix 3 [ 38 , 45 , 47 - 229 ] instead of the main manuscript. As sometimes multiple references are reported on the same intervention, this scoping review mapped the characteristics of 179 different DiPHI for the included 185 publications.

Distribution of Interventions Globally

Figure 3 displays the distribution of the included interventions by country. For this analysis, all interventions were weighted equally regardless of the number of countries they were implemented in. As several interventions were implemented in >1 country, this analysis artificially increased the number of observed interventions to 199. Although most interventions (36/199, 18.1%) were from the United States, continent -wise, Europe took the lead with 38.2% (76/199) reported interventions. Ranked third was Asia with 17.6% (35/199), followed by Africa (26/199, 13.1%), Oceania and Australia (9/199, 4.5%), and South America (6/199, 3%). From a gross domestic product point of view (ie, grouped in high, middle, or low-income countries as classified by the World Bank [ 230 ]), most interventions were planned for or implemented in high-income countries (129/199, 64.8%) and were set-up in middle-income countries (58/199, 29.1%). Of the 10 interventions in low-income countries, 3 (30%) targeted Malawi [ 73 - 76 , 82 , 218 ], and 2 (20%) each were applied in Afghanistan and Ethiopia [ 73 - 76 , 91 , 175 , 222 ]. Furthermore, of the 10 interventions, 1 (10%) each was planned or implemented in Mali, Sierra Leone, and Uganda [ 56 , 111 , 190 ].

Intervention Types and Implementation Status at the Time of Publication

Under the classification of intervention by NICE ESF, most interventions (49/179, 27.4%) were centered on telemedical services, including telestroke, telecare, and telemonitoring. According to Timpel et al [ 231 ], these interventions are characterized using ICT to cover a geographic distance in health care delivery from a health professional to a patient or group of patients. The second most frequently counted interventions were health apps and medical apps (28/179, 15.6%), followed by EHR (23/179, 12.8%). The complete overview of intervention types is displayed in Figure 4 , together with their implementation status at the reported time from the included references. As 4 publications reported on the same intervention but at different time phases, all publications were included for this display (eg, Austria’s national EHR ELGA was only planned when Ströher and Honekamp [ 199 ] reported about it, but was already nationally implemented when Herbek et al [ 113 ] and Schaller et al [ 177 ] described the platform). This results in a total of 181 displayed interventions. Interventions in >1 country were categorized as internationally implemented.

Target Population and Intervention Setting

Our analysis showed that DiPHIs tend to focus on an average of 3 distinct groups within the population. These include health professionals, policy makers, public insurance executives, researchers, disaster management professionals, patients, and healthy individuals. Unsurprisingly, health professionals were the most often targeted group, with 140 (78%) of 179 interventions. They were followed by patients who were chronically ill but stable (101/179, 56.4%). Of all interventions, 51.9% (93/179) were aimed at healthy people with or without risk factors for certain health conditions.

Parallel to the observation of the target population, each intervention affected, on average, 2 different settings, that is, level of prevention, health care, or research as defined previously. Most interventions were health care applications (ie, 100/179, 55.9% for primary, 89/179, 49.7% for secondary, and 55/179, 30.7% for tertiary health care). Out of the 179 interventions, while 16 (8.9%) interventions included a research component [ 57 , 84 , 93 , 104 , 128 , 139 , 154 , 163 , 180 , 220 , 221 , 225 ], only 3 (1.7%) focused exclusively on research: the Lone Star Stroke Consortium Telestroke Registry, the SAI Databank for electronic health research and evaluation, and the German COVID-19 data donation app (ie, Corona Datenspende) [ 57 , 93 , 128 ]. For prevention, of the 179 interventions, 13 (7%) exclusively targeted primary prevention (ie, through vaccination registries, behavior change programs, or health education in healthy individuals) [ 55 , 62 , 96 , 98 , 101 , 106 , 126 , 140 , 143 , 188 , 208 , 223 , 226 ]. Of the 179 interventions, 8 (4%) focused only on secondary prevention, as digital screening and surveillance programs [ 48 , 61 , 153 , 161 , 171 , 194 , 201 , 219 ], and 3 (2%) improved the health of patients who were chronically ill on a tertiary prevention level [ 103 , 147 , 202 ]. In contrast, of all included 179 interventions, 10 (6%) were established for primary health care purposes only [ 49 , 67 , 79 , 109 , 124 , 172 , 178 , 186 , 210 , 212 , 228 , 229 ], 17 (9%) were designed for secondary health care through specialists or emergency use cases [ 52 , 54 , 60 , 65 , 78 , 83 , 88 , 95 , 134 , 135 , 173 - 175 , 179 , 189 , 193 , 216 ], and 5 (3%) aimed at tertiary health care in hospital settings [ 70 , 109 , 132 , 157 , 200 ]. Figure 5 gives an overview of the relative size of each target group and the addressed level of prevention, health care, or research per intervention setting.

The Intersection of Digital Health Technologies and Essential Public Health Functions in DiPHIs

The analysis of the distribution of EPHFs and digital health technology functions matches the aforementioned focus on health care in DiPHIs. The heat map, displayed in Figure 6 , highlights that most interventions were found in the cross-section of health care and diagnostic (64/179, 35.8%), treatment (63/179, 35.2%), communication (61/179, 34.1%), and information (57/179, 31.8%) or as system services in health care (42/179, 23.5%). Relatively few interventions, in contrast, were used for calculation (11/179, 6.1%), preventive behavior change (40/179, 22.3%), or public health research (48/179, 26.8%). A subgroup analysis for all intervention types with at least 20 included references is included in Multimedia Appendix 4 . This analysis covers telemedicine, EHR, and health or medical apps, offering an overview of the diversity of topics addressed even within the same intervention category.

Technological Functions and Nontechnical Intervention Characteristics

Given the sample size, we only provide details on the technical functions and nontechnical characteristics of telemedical interventions and EHRs. We chose not to include health apps or medical apps in this analysis due to the considerable heterogeneity in the wide range of purposes and functions of these apps, as discussed in a previous article [ 232 ].

Telemedicine

According to a review by Sood et al [ 233 ], which included 104 publications, telemedicine “...uses communications networks for delivery of health care services and medical education from one geographical location to another, primarily to address challenges like uneven distribution and shortage of infrastructural and human resources.” The category system includes 5 mayor categories and subcategories for which we assessed all 49 telemedical interventions included in our review [ 45 , 47 , 50 , 51 , 60 , 61 , 63 , 65 , 66 , 71 , 85 , 92 , 100 , 101 , 109 , 110 , 115 , 116 , 118 , 119 , 124 , 129 , 134 , 141 , 142 , 145 , 146 , 149 , 151 , 155 , 156 , 159 , 164 , 165 , 174 , 176 , 178 , 179 , 184 , 189 , 193 , 200 , 204 , 206 , 209 - 212 , 227 ]. The results are displayed in Table 3 . Each intervention may exhibit a combination of these features, showcasing how telemedicine is applied in different settings. The most dominant characteristic for included interventions was that the software program was supported by hardware to facilitate clinical care. Besides computers and webcams, this included high-quality cameras, sensors (eg, for blood pressure or blood sugar), ultrasounds, or digital stethoscopes. Nearly half of the interventions (25/49, 51%) described how they used the internet or satellite connections to process and store data. The share of interventions that included a provider-to-provider communication option was slightly lower (17/49, 34%) than those that allowed patient-to-provider communication (23/49, 47%). Nevertheless, 20 (41%) of 49 interventions were characterized by their focus on individual patients, sometimes even through personalized intervention interfaces. However, telemedical interventions may not only focus on clinical care. As stated in the definition, they are also applied to the education context (ie, for patients and health care workers), health promotion, and improving self-efficacy in patients who were chronically ill.

In summary, telemedical interventions exhibit core characteristics that include the use of supporting hardware during consultations, data storage through databases, internet connectivity, bidirectional communication between users, educational modules, user interfaces, and the ability to plan and adjust clinical care plans when needed.

a 3 studies [ 66 , 211 , 227 ] described the same intervention.

b Intervention 1 by Hartvigsen et al [ 109 ].

c Intervention 2 by Hartvigsen et al [ 109 ].

Following the broadly accepted definition by the International Organization for Standardization (2019), an EHR is “a data repository regarding the health and health care of a subject of care where all information is stored on electronic media” [ 234 ]. According to this terminology, we developed a category system with 4 major topics and subcategories, which was applied to the 26 publications that described 23 different EHR systems [ 67 , 69 , 81 , 83 , 87 , 89 - 91 , 104 , 105 , 107 , 113 , 114 , 123 , 125 , 162 , 166 , 177 , 181 , 182 , 185 , 195 , 199 , 205 , 215 , 221 , 224 ]. The results are displayed in Table 4 . Nearly all interventions (18/23, 78%) allowed health care professionals access to the EHR after the patient consented or an active relationship (eg, due to treatment of chronic diseases) existed between the 2 parties. Although not as often described, most EHR systems (14/23, 61%) stated that patients were able to access their data. Data sharing was possible in 61% (14/23) of the interventions, and another 61% (14/23) described data protective procedures for accessing and sharing data. Although fewer times, interoperability with other health care systems was described (11/23, 48%). We observed differences regarding the stored and accessible data. Unsurprisingly, nearly all interventions (21/23, 91%) reported on storing health and clinical data. However, only 30% (7/23) of the interventions included personal data on the record holder or their immunization records. Only 17% (4/23) of the interventions allowed clinicians to upload their notes to the system.

a 3 studies [ 104 , 162 , 215 ] described the same intervention.

b 3 studies [ 113 , 177 , 199 ] described the same intervention.

c 2 studies [ 205 , 221 ] described the same intervention.

Principal Findings

Our scoping review has identified a substantial number of publications, underscoring the substantial interest and activity in DiPH. The wealth of publications illustrates the broad spectrum of interventions being explored and implemented worldwide. This diversity reflects the evolving landscape of health care delivery and disease prevention in the digital age.

The distribution of DiPHIs across countries and continents showcases the worldwide interest in leveraging technology to enhance health care but also points out significant differences in implementation adaptation between high-income and low-income countries. A reason for this imbalance negatively impacting the global digital divide might lie in the inequality regarding the digital advance among developed countries compared to developing countries [ 235 , 236 ]. The prevalence of interventions in high-income countries may partly be attributed to more significant resources and infrastructure [ 237 ]. This divide is highlighted by a lack of funding, inadequate computer availability, and limited internet skills that limit the expansion and applicability of ICT and digital (public) health [ 238 ]. Still, interventions in low-income countries signal the potential for digital technologies to bridge health care gaps in resource-constrained settings and aging societies [ 237 ]. Indeed, the Global Digital Health Monitor covers our findings by displaying overall scores for countries regarding their digital health maturity. Developing countries (especially in Africa) rank lower than their developed counterparts in Europe or North America [ 239 ]. More rigorous public health research and practice efforts are needed to empower developing countries to apply digital tools for health-related purposes. The WHO’s Digital Health Atlas can serve as such an effort where project leads can voluntarily register their digital health intervention free of charge [ 240 ]. Maps such as these will support public health policy, research, and practice in better resource allocation (eg, the map can display already existing subnational initiatives that could be scaled up to the national or international level without creating double-infrastructures), benchmarking between interventions and further developing intervention types. However, the explicit distinction between medically focused digital health interventions and population-centric DiPHIs will be needed for future versions of the atlas.

Our analysis shows that DiPHIs often target multiple population groups and settings. Health professionals are a primary target, reflecting technology integration into health care practice and education. The emphasis on patients who are chronically ill but stable underscores the potential of digital interventions to improve care for this population. Moreover, interventions in diverse prevention, health care, and research settings illustrate their versatility across the health care continuum. This observation was supported by the heat- map representation of EPHFs and ESFs, highlighting a significant concentration of digital interventions in health care–related functions such as diagnostics, treatment, communication, and information. This reflects the predominant role of digital interventions in enhancing clinical care and health care management. However, there is room for further exploration of interventions addressing prevention and public health research functions.

Health apps, telemedical services, and EHRs emerged as the dominant intervention types in our review. Health apps are well known for their heterogeneity [ 232 ], which provides the potential to address all areas of public health, including health promotion, clinical care, and rehabilitation [ 241 ]. Telemedical services stood out as a substantial focus of our included references, aligning with their capacity to extend universal health coverage reach across geographic boundaries and increase health care delivery speed while lowering treatment costs and response times to control disease outbreaks [ 242 ]. EHRs, in contrast, can be essential tools for public health surveillance in providing data on the population’s health status and the health care system’s performance [ 39 , 114 , 243 ]. These findings highlight the multifaceted nature of DiPHIs and their adaptability to various health care needs and contexts in public health.

Overall, the analysis underscores the heterogeneity within DiPHIs, even within the same intervention category, as we have displayed through a qualitative analysis of included publications for telemedical interventions and EHRs. This diversity necessitates precise definitions and standardized terminologies to facilitate effective communication, collaboration, and evaluation. Clear definitions can also aid in benchmarking and comparing interventions across different health care systems. The detailed analysis of technological functions and nontechnical characteristics of both intervention types revealed the complexity and variation within each intervention type. Identifying core characteristics and added features can guide intervention development and enhance our understanding of their capabilities. In 2019, WHO published their recommendations on digital interventions for the clinical setting, which provides a definition for each intervention (eg, client-to-provider telemedicine), synonyms for these tools, and recommendations regarding their use cases [ 244 ]. While this overview serves as a good starting point, it requires extensions for nonclinical settings and an overview of core functions and technical features to allow benchmarking. The heterogeneity in DiPHI forces us to rethink how national health system assessments should be conducted to allow for comparable results. Instead of asking, Does your country have an EHR system?” it is critical to ask for the availability of an intervention with specific characteristics: “ Does your country have an intervention with the following characteristics, targeting these population groups, and being applied for at least one of the following settings?”

As the field continues to evolve, it is essential to prioritize rigorous research and evaluation to assess these interventions’ effectiveness, safety, and impact on population health and health care accessibility. This review serves as a valuable resource for policy makers, researchers, and health care practitioners seeking to navigate the dynamic and diverse field of DiPHIs.

Strengths and Limitations

Originally conceived as a systematic review, our research protocol was registered with PROSPERO to conduct a comprehensive synthesis of the existing literature on DiPHIs. The systematic approach is typically characterized by a rigorous process involving reviewing evidence to answer narrowly defined research questions. However, as our study progressed, we recognized that our research question and the evolving DiPH landscape were better suited for a scoping review methodology. While systematic reviews focus on specific research questions and outcomes, the strengths of scoping reviews for effectively mapping and characterizing interdisciplinary and comprehensive topics (such as the diverse spectrum of DiPHIs in our case, including their characteristics, settings, and target populations) [ 245 ] were more applicable for our study aim. This change allowed us to adapt to the dynamic nature of the field. It provided a broader perspective essential for understanding the multifaceted nature of digital interventions. This transition underscores the importance of selecting the most suitable methodology to achieve comprehensive insights into the subject matter. The selection of our information sources demonstrated the interdisciplinarity of DiPH by combining literature databases from public health and computer science. This rigorous strategy mitigates the risk of missing essential publications. The broader inclusion of publications from 3 languages (ie, English, German, and Chinese) is another strength of our study, given the rising number of publications on digital health and DiPH from German-speaking and Chinese-speaking countries. Throughout the process, a minimum of 2 researchers independently screened all references, adhering to the 4-eye principle. Any disagreements in decisions regarding inclusion or exclusion were resolved by another author (CCP) to ensure the reliability of the results. This study followed the PRISMA-ScR [ 245 ] to provide high-quality, transparent research results. The filled checklist is provided in Multimedia Appendix 5 .

Nevertheless, while this scoping review exhibits numerous strengths, it also presents certain limitations. We did not create publication alerts for the selected databases, limiting our results to references published before October 6, 2022. However, we conducted manual reference list checks for reviews and meta-analyses to identify additional publications that were potentially missed in our search. As no further relevant findings were added from the manual search, we are confident that our scoping review draws a holistic picture of the landscape of DiPHIs globally. Furthermore, we are convinced that the included references are sufficient for an initial intervention mapping of DiPHIs. Nonetheless, it is worth noting that certain intervention types might be underrepresented, such as early warning software, electronic medication plans, electronic prescribing, or emerging intervention types that were not yet reported during our search (eg, artificial intelligence tools). Here, we invite other researchers to build upon our first results and continue the mapping process. Following the PRISMA-ScR [ 245 ], assessing the quality of the included publications was not applicable, which could lead to questions regarding the reporting accuracy of the included publications. Nevertheless, as we focused solely on the functions and use cases of the interventions and not on their outcomes, this limitation remains minor.

Furthermore, the challenge of intervention specificity emerged as a notable consideration. The varying levels of detail in the descriptions of digital interventions in the literature posed difficulties in discerning their precise nature. This lack of specificity hindered the ability to categorize and analyze interventions effectively, as it often left critical questions unanswered. For instance, understanding the core technological functions, nontechnical attributes, determined use cases, and defined user groups of a given digital intervention is essential for its accurate classification and evaluation. Although in our case, data extraction was conducted by 2 authors (LM and KA) independently and authors were contacted in case of uncertainty, the absence of such information generally can impede efforts to compare interventions, assess their impact, and make informed decisions regarding their implementation or scalability. This is why we advocate for clearer reporting standards for digital health and DiPH interventions. Finally, we must point out that although the volume of included publications was substantial, a distinct portion could not be included in our review due to factors such as unavailable full-text content and a lack of specificity in intervention descriptions. This highlights challenges in accessing relevant literature and emphasizes the need for more detailed reporting in published studies, particularly regarding the specifics of digital interventions. In an era where timely access to information is critical, the inaccessibility of full-text articles poses an obstacle to researchers and stakeholders seeking to explore and build upon existing knowledge in DiPHIs.

Further Research

Due to the heterogeneity of DiPHIs, it was not feasible for this scoping review to report detailed information for every intervention type. Therefore, we encourage other researchers to uptake our methodology, conduct reviews on specific intervention types, and refine our initial intervention mapping results. More critically, a shared and multidisciplinary understanding of key terminology in digital health and DiPH is needed. Consequently, consensus finding methods (eg, Delphi approaches) need to be applied to internationally create a shared understanding of DiPHI.

In addition, assessments of the sustainability of DiPHIs are crucial to map the implementation status. As Iwelunmor et al [ 246 ] and Kaboré et al [ 247 ] already highlighted, the sustainability of DiPHIs is an essential component of the whole life cycle of implemented interventions. Therefore, it is crucial to consider whether an intervention has been sustainably implemented or stopped after the initial pilot funding phase has ended. Further research should be conducted to analyze, through a longitudinal design or pre-post comparison, how sustainably DiPHIs are implemented and whether differences between intervention types exist.

Conclusions

This scoping review has shown that DiPHIs are distinctly diverse in their use cases between individual intervention groups and within such groups. Therefore, using precise terminology when planning, implementing, or evaluating DiPHIs is crucial. For instance, instead of phrasing an intervention as an EHR, one should ask for specific technological functions and nontechnical characteristics, determine use cases (from a digital health and public health perspective), and define user groups. This approach facilitates cross-disciplinary collaboration in intervention development and research and fosters international benchmarks and comparability across global DiPH systems. These insights offer valuable guidance for policy makers, researchers, and health care practitioners interested in using the potential of digital interventions to improve population health and health care accessibility.

Acknowledgments

The authors gratefully acknowledge the support of the Leibniz ScienceCampus Bremen Digital Public Health. The study is part of the Leibniz ScienceCampus Bremen Digital Public Health, which is jointly funded by the Leibniz Association (W4/2018), the Federal State of Bremen, and the Leibniz Institute for Prevention Research and Epidemiology (BIPS).

Data Availability

The data sets generated and analyzed during this study are available from the corresponding author on reasonable request.

Authors' Contributions

LM conceptualized and designed the study, including its methodology, with input from CCP. LM served as the principal investigator and project administrator for the entire project. LM, KA, and MF conducted the literature review (data collection), with CCP settling disagreements during the screening process. LM and KA independently conducted the data analysis, with support from CCP. LM and CCP conducted the interpretation of the study data. LM drafted the manuscript, and this paper was revised critically for important intellectual content by all authors. All authors approved the final version of the manuscript.

Conflicts of Interest

None declared.

Complete search strategies for the PubMed, Web of Science, CENTRAL, IEEE Xplore, and ACM Full-Text Collection databases.

Publications excluded during full-text screening.

Overview of the included interventions.

Heat maps of the selected intervention types.

PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) checklist for this manuscript.

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Abbreviations

Edited by T de Azevedo Cardoso; submitted 24.10.23; peer-reviewed by J Köberlein-Neu, P Velmovitsky; comments to author 09.01.24; revised version received 31.01.24; accepted 15.05.24; published 17.07.24.

©Laura Maaß, Konstantinos Angoumis, Merle Freye, Chen-Chia Pan. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 17.07.2024.

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• Published: 18 July 2024

The role of morphometric characteristics in predicting 20-meter sprint performance through machine learning

• Ahmet Kurtoğlu 1 ,
• Özgür Eken 2 ,
• Rukiye Çiftçi 3 ,
• Bekir Çar 4 ,
• Emrah Dönmez 5 ,
• Serhat Kılıçarslan 5 ,
• Mona M. Jamjoom 6 ,
• Nagwan Abdel Samee 7 ,
• Dina S. M. Hassan 7 &
• Noha F. Mahmoud 8  

Scientific Reports volume  14 , Article number:  16593 ( 2024 ) Cite this article

Metrics details

• Computational biology and bioinformatics

The aim of this study was to test the morphometric features affecting 20-m sprint performance in children at the first level of primary education using machine learning (ML) algorithms. In this study, 130 male and 152 female volunteers aged between 6 and 11 years were included. After obtaining demographic information of the participants, skinfold thickness, diameter and circumference measurements, and 20-m sprint performance were determined. The study conducted three distinct experiments to determine the optimal ML technique for predicting outcomes. Initially, the entire feature space was utilized for training the ML models to establish a baseline performance. In the second experiment, only significant features identified through correlation analysis were used for training and testing the models, enhancing the focus on relevant predictors. Lastly, Principal Component Analysis (PCA) was employed to reduce the feature space, aiming to streamline model complexity while retaining data variance. These experiments collectively aimed to evaluate different feature selection and dimensionality reduction techniques, providing insights into the most effective strategies for optimizing predictive performance in the given context. The correlation-based selected features (Age, Height, waist circumference, hip circumference, leg length, thigh length, foot length) has produced a minimum Mean Squared Error (MSE) value of 0.012 for predicting the sprint performance in children. The effective utilization of correlation analysis in the selection of relevant features for our regression model suggests that the features selected exhibit robust linear associations with the target variable and can be relied upon as predictors.

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Introduction.

Different studies have argued that anthropometric characteristics 1 , genetic factors 2 , environmental factors 3 , psychosocial and psychological factors 4 influence basic motoric traits and are naturally characteristics that should be taken into account when selecting talent. In recent years, the connection between morphometric traits and athletic performance has drawn a lot of attention in the fields of sports science and physical fitness testing 5 . Thus, by analyzing the morphometric characteristics that affect basic motoric characteristics, appropriate branch choices can be made at an early age 6 .

Speed is also one of the basic motoric traits and is a fundamental measure of speed and agility, which are important components in many sports and physical activities 7 . Comprehending the elements that influence sprint performance is crucial for enhancing training plans, identifying potential, and fostering whole sports growth 8 , 9 . A study by Gunnar and Pettersen examined the relationship between anthropometric characteristics and sprint performance. Participants consisted of 10–16 year old youth. Body mass index (BMI) in 10–12 year olds and height in 13–16 year olds were among the parameters affecting 10 m and 20 m sprint performance 10 . In the study conducted by Bonato et al 11 in which the effect of anthropometric characteristics on sprint performance in 200 m and 400 athletes was examined, it was concluded that there was a negative relationship between body mass and BMI and sprint performance. Although the results of the observed studies suggest that anthropometric characteristics affect sprint performance, this cannot be separated from two different perspectives on talent selection. One of these perspectives is that only individuals with innate talent can reach the level of an elite athlete, while the other is that every individual can reach the elite level with practice and frequent training 12 . The point where these two different views converge is that talent identification should be done early and children should be directed to branches that are appropriate to their abilities.

Talent screening is practiced in many countries and many different methods are used. In recent years, Machine Learning (ML) and Artificial Intelligence (AI) algorithms have been used in sports sciences for many analyses such as performance analysis, injury prevention and rehabilitation, competition analysis, athlete tracking and data collection, and sports management 13 , 14 , 15 . In recent years, different ML and AI methods have been utilized in talent prediction 16 . The fact that ML applications try to optimize future predictions and decisions by identifying hidden patterns in a data set, determining the complexity in the data set with multilayer neural networks 17 , and making predictions and modeling based on the findings obtained from the data set shows that ML applications should be frequently used in the identification of motor characteristics and talent screening 18 .

When the literature is examined, it is seen that many different test batteries and methods are applied in early childhood talent selection for different branches. In recent years, many studies have been conducted with ML and AI algorithms. However, it has been determined that the number of comprehensive studies examining the anthropometric characteristics that determine speed performance, which is one of the basic motoric characteristics, with ML algorithms is limited. In this context, in our research, we aimed to predict the morphological features that determine 20-m performance in children between the ages of 6–11 years with ML applications. In this way, it is thought that the morphological features that need to be developed and analyzed for maximum sprint performance will be determined and accordingly, children's sprint performance will be predicted and directed to appropriate branches. For this reason, the hypothesis of our research was determined as “Some morphometric characteristics affect 20 m performance”.

In conducting this investigation, we adhered to the conceptual framework shown in Fig.  1 . The primary components of the research study are the collection of data pertaining to twenty-meter sprint performance, preprocessing of the collected data, division of the data into training and testing samples, selection and reduction of relevant features, construction of regression models utilizing traditional Machine Learning, ML, algorithms, and assessment of the predictive model's performance.

The proposed framework for prediction of Sprint Performance using ML technology.

Participants

In this study, 282 participants, 130 males (age: 8.26 ± 1.84 kg, height: 136.51 ± 16.74 cm, weight: 36.61 ± 14.16 kg, BMI 17.77 ± 3.28 kg/m 2 ) and 152 females (age: 8.74 ± 1.83 kg, height: 135.26 ± 12.83 cm, weight: 32.73 ± 10.32 kg, BMI 17.48 ± 2.99 kg/m 2 ), aged between 6 and 11 years, participated in the first levels of primary education. In this study, we focused on participants with normal development at the first level of primary education. Participants reported that they did not have any anxiety and insomnia during the test. In this study, G-Power (version 3.1.9.7, IBM, Düsseldorf) was used to determine the minimum sample 19 . According to this analysis, when α err prob = 0.05; minimum effect size = 0.30; and power (1−β err prob) = 0.80, it was determined that there should be at least 270 participants with an actual power of 80.0%.

In this study, voluntary participants between the ages of 6 and 11, studying at the first level of primary education, showing normal physical, cognitive and affective development were included. Participants were selected from sedentary individuals who did not actively compete in any sports branch other than physical education and sports lessons. Participants who had developmental disorders, needed special education through inclusive education, had chronic diseases, had any disability, or were taking growth hormone, glucocorticoids, antipsychotic or corticosteroid drugs that could change the body structure were not included in the study. Participants who had difficulty understanding the instructions of the researcher during the tests and who persistently refused to perform the tests were excluded from the study.

All participants, parents and teachers were informed about the purpose, rationale and contribution of the research to the literature. Informed consent forms were signed by all researchers and participants and they were informed that they could withdraw from the study at any time. The necessary permissions were obtained from the Health Sciences Non-Interventional Research Ethics Committee (Approval Number: 2024/4892). The data obtained in the study and all test procedures were performed in accordance with the principles set out in the Declaration of Helsinki. The proposed model can be observed in Fig.  1 .

Data collection

Antropometric measurements.

An electronic scale (Tanita BC 420 SMA, Tanita Europe GmbH, Sindelfingen, Germany) was used to measure weight, with an accuracy of 0.1 kg. The children were simply decked up in underwear and a T-shirt. A telescopic height-measuring device (Seca 225 stadiometer, Birmingham, UK) was used to measure the children's height while they were barefoot, to the nearest 0.1 cm. A skinfold caliper (Holtain, Holtain Ltd, Pembrokeshire, United Kingdom, range 0–40 mm) was used to measure the skinfold thickness (mm) twice on the right side of the body, to the nearest 0.2 mm. The following locations were used to measure skinfolds: (1) triceps, located on the back of the arm between the olecranon process and the acromion; (2) biceps, situated slightly above the cubital fossa's center, at the same level as the triceps skinfold; Skinfold thickness (mm) was measured twice on the right side of the body to the nearest 0.2 mm with a skinfold caliper (Holtain, Holtain Ltd, Pembrokeshire, United Kingdom, range 0–40 mm). Skinfold measurements were taken at the following sites: (1) triceps, between the acromion and the olecranon process on the back of the arm; (2) biceps, at the same level as the triceps skinfold, just above the center of the cubital fossa; (3) subscapular, approximately 20 mm below the tip of the scapula, at a 45° angle to the lateral side of the body; (4) suprailiac, approximately 20 mm above the iliac crest and 20 mm toward the medial line; (5) abdominal, midway between the spina iliaca anterior superior and the umbilicus; (6) quadriceps, superior 1/3 of the quadriceps muscle vertically; (7) gastrocnemius, midway medial to the muscle. Circumferences and length of the participants were measured with a tape measure with a precision of 1 cm. In this context; (1) head circumference, frontal and occipital region, (2) neck circumference, just below the larynx, (3) shoulder circumference, just below the acromion, at the end of expiration when the deltoid is most bulging, (4) chest circumference, end of expiration, 4th rib in front, 6th rib on the side, (5) abdominal circumference, umblicus level and subclavian ribs on the sides. costa in front and the 6th costa on the side, (5) abdominal circumference was measured at the level of the umblicus and the trunk circumference at the subcostal level on the sides, (6) thigh, mid-thigh, (7) gastrocnemius, where the gastrocnemius muscle was most bulging, (8) fathom length, standing with arms against the wall and in 90 degrees of abduction, between the fingertips, (9) leg length, between the spina iliaca anterior superior and the medial malleolus, (10) thigh length, between the spina iliaca anterior superior and the medial condyle of the femur, (11) foot length, between the posterior calcaneus and the 2nd phalax.

20 meters sprint performance test

Before the speed tests, 2 pairs of photocells (Smart Speed, Fusion Equipment, AUS) were placed along the running track at 0 and 20 m distances. Participants sprinted twice, starting on their own from a semi-crouched position 0.3 m behind the starting line. The sprint tests were performed on an indoor running track to avoid being affected by weather conditions. The temperature of the area was 22 degrees Celsius. After the familiarization phase, each participant was given two trials. Participants were tested in groups of 10 and after each participant finished the first test, the first participant was taken again for the second test. A rest interval of at least 5 min was ensured between both tests and the best trial was recorded 20 .

Dataset preprocessing and exploration

The subsequent phase involves the preparation of the dataset. The total number of records in the dataset is 282. Table 1 presents a comprehensive statistical summary of the combined dataset. Table 1 presents a comprehensive overview of the data distribution, encompassing many statistical measures such as the number of observations (which is represented by symbol N), average, standard deviation, minimum value, 1st quantile, median, 3rd quantile, and maximum value. The depiction of the variance of diverse variables is facilitated through making use of a scatterplots of the target variable (Sprint Performance) versus all input variables as exemplified in Fig.  2 . In order to facilitate the study of the data records, the entries have undergone normalization using the z-score method. The normalized values exhibit centralization around zero and possess a standard deviation of one. The z-scores of a random variable X, characterized by a mean value of M and a standard deviation ( \({\varvec{sd}}\) ), can be determined using Eq. ( 1 ).

The values of sprint performance against each feature displayed in a scatter-plot graphs.

The effectiveness of forecasting models is significantly impacted by the relevance of the input features. The Pearson correlation coefficient is a dominant approach to assess the relationship between the input variables and determine the extent to which the outcomes are influenced by the feature space. Figure  3 shows the correlation matrix between Sprint performance (the output variable) and the other variables (the input variables). Pearson's Correlation Coefficient is the standard statistical method for analyzing the linear association between two independent random variables. Two vectors’ correlation score, CS, indicates how dependent they are on one another. For any two vectors \({\varvec{x}}1\) and \({\varvec{x}}2\) , we get (Eq.  2 ), which gives us the correlation coefficient where \({\varvec{cov}}\left( {{\varvec{x}}1,{\varvec{x}}2} \right)\) is the covariance between \({\varvec{x}}1\) and \({\varvec{x}}2\user2{ }\) and \({\varvec{\sigma}}\left( {{\varvec{x}}1} \right),\user2{ and \sigma }\left( {{\varvec{x}}2} \right)\) are their variances.

The correlation matrix between Sprint performance (the output variable) and the other variables (the input variables).

The \({\varvec{cs}}\) takes on a value between 1 and + 1, which is linearly dependent on whether or not the input variables \({\varvec{x}}1\) and \({\varvec{x}}2\user2{ }\) are correlated. If they are unrelated, then it would be equal to zero. As depicted in Fig.  3 , the response variable (performance of Sprint) exhibits a stronger correlation with the following input variables including (Age, Height, waist circumference, hip circumference, leg length, thigh length, foot length).

Dataset splitting

The data sets have been partitioned into training and testing instances using a random allocation method, with a ratio of 80% for training and 20% for testing. In the second stage, the experiments were repeated by selecting k = 5 from the cross-validation method. The training examples are utilized for constructing the prediction models, whereas the testing samples are employed for evaluating the correctness of these predictions. The training and testing samples are subsequently inputted into a feature selection step in order to identify the crucial aspects that could potentially impact the accuracy of the prediction.

Feature space

Three distinct tests were undertaken to determine the optimal technique. The initial experiment involved utilizing the entire feature space for training the machine learning prediction models. In the second experiment, we exclusively employed significant features for the purpose of training and testing the regression models. The significant features that have been studied are those extracted using correlation analysis, namely with a correlation score (CS) greater than or equal to 0.4. These features have a higher Pearson Correlation Coefficient with the outcomes. In the third experiment, Principal Component Analysis (PCA) was employed to reduce the feature space. This allowed us to obtain only the primary vectors that were deemed statistically significant for training and testing the prediction models. PCA is a technique that effectively lowers the dimensionality of the feature space by identifying and extracting the most significant patterns that capture the essential information contained within the input features. The result of performing Principal Component Analysis is the identification of the principal components inside the feature space.

ML Prediction models construction and evaluation

Regression is a widely employed supervised machine learning methodology utilized for the purpose of forecasting continuous quantitative outcomes. During the process of regression analysis, the estimation of the relationship between an outcome (also known as the response variable) and a number of input variables (also known as predictors) is conducted using a labelled dataset. Different types of regression analysis can be chosen based on various factors, such as the qualities of the variables, the objective variables being examined, or the specific characteristics and form of the regression curve that represents the relationship between the dependent and independent variables. Linear regression, stepwise regression, decision trees, support vector machines, ensembles, and Gaussian process regressors are illustrative examples of conventional machine learning regression methodologies. A regression model that fits well is characterized by projected values that closely match the actual data values. The mean model, which employs the mean value for each projected outcome, is typically employed in cases where there are no informative predictor variables available. The adequacy of a proposed regression model should thus be superior to that of the mean model.

There are other performance indicators that can be utilized to assess the accuracy of forecasting models, including the R squared (R2) and the Mean Squared Error (MSE), and the Root-Mean-Square Error (RMSE). The coefficient of determination, denoted as R2, quantifies the degree to which the forecasting model is capable of capturing the variability observed in the results. The calculation of R squared is described by Eq. ( 3 ). The second metric, as depicted by Eq.  4 , is the MSE which is a quantitative measure utilized to assess the effectiveness of a regression model. It quantifies the average of the squared discrepancies between the observed and predicted values of the target variable. A lower value of MSE signifies superior model performance, since it signifies a smaller average difference between the anticipated and actual values. The last metric is the RMSE which quantifies the disparities between the observed and anticipated values. It is computed according to Eq. ( 5 ), whereby k represents the sample size, \({\varvec{x}}_{{\varvec{i}}} \user2{ }\) denotes the actual values, \({\varvec{x}}_{{\varvec{i}}}^{\sim }\) represents the forecasted values, and \({\varvec{x}}_{{\varvec{i}}}^{ - }\) signifies the mean of the actual values.

Ethics approval and consent to participate

The study was conducted in accordance with the principles of the Declaration of Helsinki and was aproved by the Ethics Committee of the Institute of Health Sciences of Inonu University approved the study under registration number 2024/4892.

Based on the proposed framework, all input features underwent preprocessing, and numerous strategies for feature extraction were employed to generate different collections of feature combinations. All of the input features stated in Table 1 were used to simulate the Sprint performance in the first experiment carried out under the suggested framework. Tables 2 show the results of analyzing how well various machine learning regression methods, such as linear regression, decision trees, support vector machines, ensembles, and Gaussian process regressor models, were able to predict how well an individual would perform in a twenty-meter sprint after being trained individually using all of the available input features. The values of the root mean squared error and the R squared that were obtained for each regression method are presented in Table 2 . Figure  3 shows a comparison between the predicted value of the response variable (obtained through the various regression methods) and the actual value of the variable. Table 2 displays the findings, which show that the highest prediction performance was achieved by the Gaussian process regression model across all feature sets.

Table 2 presents the results of the analysis, revealing that the Gaussian process regression machine learning model consistently outperformed other regression approaches across all feature sets. The metrics used to assess prediction performance include Root Mean Square Error ( RMSE ) R-squared ( R 2 ) and Mean Squared Error ( MSE ). Notably, the Gaussian process regression demonstrated the highest accuracy with an RMSE of 0.114 and an impressive R 2 value of 0.96. In comparison, Ensembles (Bagged Trees) exhibited higher RMSE (0.224) and lower R 2 (0.85), emphasizing its comparatively weaker predictive capability. The Linear regression and Support Vector Machines (SVM) with a Linear Kernel, also performed well but slightly fell short of the Gaussian process regression model in terms of accuracy. These findings underscore the effectiveness of the Gaussian process regression model approach in predicting the target variable based on the given feature sets. Figure  4 exhibits the behaviour of the comparative prediction values of each method. Figure  4 c and e show that the prediction value does not fit ideally on the regression line compared to the other methods. Table 3 displays the findings, which show that the highest prediction performance was achieved by the Gaussian process regression model using selected features after dimensionality reduction using PCA technique.

A comparison between the predicted value of the response variable (all features).

To confirm the findings, the PCA technique is used to identify the principal components in the feature space (Fig.  5 ). The same set of regression approaches are applied to the identified components. Table 3 hosts the comparison results of RMSE , R 2 and MSE values for the applied regression approaches. The Gaussian process regression model achieves the lowest RMSE and MSE values of 0.405 and 0.164 respectively, and the best R 2 value of 0.51. Alternately, the Decision Trees and Support vector machines (SVM) techniques give the worst MSE value of 0.21, while the lowest R 2 value of 0.38 and the highest RMSE values of 0.453 are obtained when the Decision Trees regression approach is applied. Those results support previous results shown in Table 3 . Figure  4 shows the behavior of the comparative prediction values of each method. Figure  5 a and c show that the linear regression and SVM models have outliner data points that affected the RMSE , R 2 and MSE values. Table 4 displays the findings, which show that the highest prediction performance was achieved by the Linear regression model using selected features from correlation analysis.

A comparison between the predicted value of the response variable after reducing dimensionality using the PCA technique.

According to Table 4 , the R2 and MSE values for the Linear Regression, Decision Trees, SVM, and Gaussian process regressor models are 0.96 and 0.012, respectively. The Linear Regression model achieves a slightly better RMSE value of 0.111 compared to the Decision Trees, while the Gaussian process regression models have an RMSE of 0.112, and the SVM model has an RMSE of 0.113. The best performance is obtained using the Ensembles (Bagged Trees) approach. These results indicate that the correlation features have been accurately identified through hypothesis testing for the entire population. In multiple linear regression, the null hypothesis for a population p is formulated as H0: β1 = 0, β2 = 0, β3 = 0, … βp = 0, which suggests no relationship between the outcome and the p input predictors. The model is considered effective if any β ≠ 0, representing the alternative hypothesis Ha, where Ha: at least one βj ≠ 0 (j = 1, … p). In this study, we used the ANOVA F-statistics test for hypothesis testing, excluding variables with zero variance. In regression-based problems, this test measures the significance level of the estimated coefficients from linear regression models. The significance of each coefficient is determined by calculating four metrics: the sum of squares (SS), the mean sum of squares (MS), the degrees of freedom (DF), the F-statistic, and the p-value. Table 5 shows the results of the test for sprint performance. Based on the F-value and p-value, the null hypothesis is rejected, indicating a linear association between the predicted sprint performance and the variables of gender, age, height, weight, hip circumference, thigh circumference, gastrocnemius circumference, leg length, thigh length, and foot length. The findings presented in Fig.  6 show the relationship between age and 20-m sprint performance. In this graph, it is observed that children's sprint performance improves as their age increases. In particular, the effect of age on sprint time becomes evident starting from early childhood. This finding supports that age is an important determinant of sprint performance and that training programs should be customized according to age.

A comparison between the predicted value of the response variable based on correlation analysis.

The study aimed to explore the relationship between morphometric characteristics and 20-m sprint performance in children at the primary education level, utilizing machine learning algorithms. The inclusion of 282 volunteer participants, comprising 130 males and 152 females aged between 6 and 11 years, allowed for a comprehensive analysis. Demographic details, skinfold thickness, diameter and circumference measurements, along with 20-m sprint performance data, were collected and subjected to rigorous preprocessing techniques, subsequently divided into training and test datasets. Employing machine learning algorithms, a predictive model was generated, revealing that gender, age, various morphometric measurements including height, weight, circumferences, lengths, and skinfold thickness had an impressive accuracy rate of 96% in predicting the 20-m sprint performance. These findings underscore the significant influence of morphometric features on a child’s 20-m sprint performance. The high predictive accuracy, particularly concerning variables like gender, age, and a range of morphometric measurements, suggests their pivotal role in determining sprint capabilities at the primary education stage. The utilization of machine learning algorithms effectively captured the complex interplay between these morphometric traits and athletic performance, demonstrating promising potential for practical application in assessing and enhancing children's physical capabilities.

There are some studies that include morphometric qualifications of the children 1 , 21 , 22 , 23 , 24 , 25 . Aerenhouts et al.’s study (2011) provides valuable insights into the dynamics of sprint performance among junior and senior athletes concerning sprint start and acceleration. The findings underscore the crucial role of acceleration in achieving higher running velocities, particularly in senior athletes 1 . The study highlights the distinction in the developmental progression of sprint capabilities between different age categories and emphasizes the impact of muscularity on acceleration performance, shedding light on the intricacies of sprint performance in athletic contexts. In contrast, the investigation of our study focused on morphometric features predicting 20-m sprint performance in children at the primary education level, utilizing machine learning algorithms. Our study aimed at creating a predictive model for educators and healthcare professionals, offering insights into potential predictors of sprint performance within an educational context, differing notably in its predictive approach and focus on children’s physical education rather than athlete-specific performance dynamics. The study by Papaiakovou et al. 21 examined how chronological age and gender influence sprint performance in children and adolescents. Boys and girls both displayed progressive speed development in sprinting phases. Older boys and girls exhibited significantly higher speeds compared to younger participants. Gender disparities were notable from 15 years onward, suggesting that gender and age collectively impact sprint performance 21 . Conversely, our study aimed to predict 20-m sprint performance in 6–11-year-old children using morphometric features and machine learning algorithms, achieving a 96% predictive accuracy based on various anthropometric and demographic data. These studies differ in their age ranges, focus on specific sprint distances, and methodologies employed for performance prediction. The study by Mendez-Villanueva et al. (2011) explored age-related differences in sprint qualities and their relationship in highly trained young male soccer players. This research examined 10-m sprint (acceleration), flying 20-m sprint (maximum speed), and 10 × 30-m sprint (repeated-sprint) times, investigating the impact of anthropometry and biological maturation on these performances. The study revealed age-based differences in sprint qualities, with performances varying among age groups. In contrast, the our study aimed to predict 20-m sprint performance in 6 to 11-year-old children utilizing morphometric features and machine learning algorithms, achieving 96% predictive accuracy. These studies differ in their focus on sprint qualities in soccer players and children, along with their methodologies for performance prediction. The study by Ramos et al. 24 , 25 aimed to describe and establish normative data for morphological and fitness attributes in 281 young male Portuguese basketball players aged 12–16 years. It encompassed measures of chronological age, maturity parameters, morphological features (body mass, height, skinfolds), and fitness components (sprint, change of direction ability, jump, upper body strength). The study provided descriptive and normative values for these attributes, stratified by age and maturity status, offering a framework for evaluating and adjusting athletes’ performance over time 24 . In contrast, our study focused on predicting 20-m sprint performance in children aged 6–11 using specific morphometric features and machine learning algorithms, achieving a 96% predictive accuracy. These studies differ in their primary objectives; while Ramos et al. aimed to establish normative benchmarks for a range of attributes in young basketball players, our study concentrated on predicting sprint performance in primary education children using machine learning techniques. The study by Zapartidis et al. 22 conducted a comparative analysis of physical fitness and selected anthropometric characteristics between selected (SP) and non-selected (NSP) young handball players for the Greek preliminary national teams, encompassing both male and female players. Their findings highlighted several distinctions between the two groups. In male players, SP individuals exhibited superior ball velocity, standing long jump, 30-m sprint, estimated VO2max, greater height, and arm span. Female SP players had higher values in ball velocity and standing long jump. Moreover, the study revealed variances within different playing positions, such as male backs, wings, and pivots, showcasing the significance of physical and anthropometric attributes in player selection 22 . In contrast, our study aimed to predict 20-m sprint performance in primary education children using machine learning techniques, focusing on morphometric features. It achieved a 96% predictive accuracy based on gender, age, and various morphometric measurements, catering to a distinct research objective. The study conducted by Lago-Peñas et al. 23 , focused on establishing the anthropometric and physiological profiles of young soccer players according to their playing positions and evaluating their relevance for competitive success. It involved 321 young male soccer players and detailed various physical attributes and performance tests for different player positions. Notably, differences in physical characteristics were observed among player positions, correlating with performance in specific tests. Additionally, the study attempted to link these profiles to team success, noting slight physiological performance differences between players from successful and unsuccessful teams, albeit not statistically significant 24 . Conversely, our study aimed to predict 20-m sprint performance in children aged 6–11 using machine learning algorithms, achieving a 96% predictive accuracy based on a range of morphometric features. The difference lies in the focus on predicting sprint performance in young children and the utilization of machine learning techniques, distinct from Lago-Peñas’ emphasis on the physical and performance profiles of soccer players and their relationship to team success 23 . The study by Ramos et al. 24 , 25 delved into the relationship between morphological attributes, physical fitness, and basketball performance in elite young Portuguese players. They evaluated 416 male and female under-14 basketball athletes, examining maturational parameters, morphological attributes, and fitness parameters, linking these attributes with game performance. The research unveiled correlations between specific physical attributes and basketball performance for both genders, identifying key predictors such as height, body composition, strength, agility, and maturation status. Notably, separate regression models were constructed for males and females, offering predictions for basketball performance based on these attributes 22 . Conversely, our research centered on utilizing machine learning algorithms to predict 20-m sprint performance in primary education children aged 6–11, achieving a high accuracy rate of 96%. Unlike Ramos et al.’s emphasis on the relationship between physical attributes, maturation, and basketball performance in elite young players, our study focused on forecasting sprint performance in young children using machine learning and specific morphometric features. The difference in focus highlights the distinct aims and methodologies between the two studies, one exploring performance predictors in elite youth basketball, and the other employing machine learning for sprint prediction in primary education children.

The comprehensive scope of variables considered in this study sheds light on the multifaceted nature of factors influencing sprint performance in children. The accuracy of the predictive model emphasizes the feasibility of utilizing morphometric data to evaluate and potentially improve children's sprinting abilities, offering invaluable insights for educators, coaches, and healthcare professionals working with this demographic. However, while the predictive model exhibited a high accuracy rate, certain limitations need consideration. The study was confined to a specific age range and might not be universally applicable to wider age groups. Moreover, external factors like nutritional habits, genetic predispositions, and additional lifestyle components were not incorporated, potentially impacting the holistic understanding of sprint performance determinants.

In conclusion, this study aimed to investigate the morphometric features influencing 20-m sprint performance in children at the first level of primary education using machine learning (ML) algorithms. The analysis included 282 volunteer participants, aged between 6 and 11 years, comprising 130 males and 152 females. Through a series of experiments, three distinct approaches were employed to determine the optimal ML technique for predicting sprint performance. Initially, the entire feature space was utilized to establish a baseline performance. Subsequently, correlation analysis was employed to identify significant features, enhancing the focus on relevant predictors. Finally, Principal Component Analysis (PCA) was utilized to streamline model complexity while retaining data variance. The results indicated that the correlation-based selected features, including Age, Height, waist circumference, hip circumference, leg length, thigh length, and foot length, yielded a minimum Mean Squared Error (MSE) value of 0.012 for predicting sprint performance in children. This successful application of correlation analysis underscores the robust linear associations between the selected features and the target variable, reaffirming their reliability as predictors. The findings of this study provide a solid foundation for further exploration into the intricate relationship between morphometric characteristics and 20-m sprint performance in children. Addressing the limitations through larger and more diverse sample sizes, inclusion of additional variables, and longitudinal studies could strengthen the generalizability and depth of understanding. Ultimately, this research offers a promising starting point for future investigations in the domain of childhood physical performance, guiding the development of tailored interventions and training programs to optimize children's athletic capabilities.

Data availability

The data presented in this study are available on request from the corresponding author.

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Acknowledgements

The authors would like to express their grateful to Princess Nourah bint Abdulrahman University Researchers Supporting Project number (PNURSP2024R104), Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia.

This research was funded by Princess Nourah bint Abdulrahman University Researchers Supporting Project number (PNURSP2024R104), Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia.

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Department of Physical Education and Sport Teaching, Faculty of Sport Sciences, Bandirma Onyedi Eylul University, Balıkesir, 10200, Turkey

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Author Contributions: Conceptualization, A.K., Ö.E., R.Ç., B.Ç., E.D., S.K.; Data curation, A.K., Ö.E., R.Ç., B.Ç., E.D., S.K.; Formal analysis, A.K., Ö.E., R.Ç., B.Ç., E.D., S.K., M.M.J., N.A.S., D.S.M.H., N.F.M.; Methodology, A.K., Ö.E., R.Ç., B.Ç.; Supervision, A.K., Ö.E., R.Ç., B.Ç., E.D., S.K., M.M.J., N.A.S., D.S.M.H., N.F.M.; Writing—original draft, A.K., Ö.E., R.Ç., B.Ç., E.D., S.K., M.M.J., N.A.S., D.S.M.H., N.F.M. Writing—review & editing, A.K., Ö.E., R.Ç., B.Ç., E.D., S.K., M.M.J., N.A.S., D.S.M.H., N.F.M.

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Kurtoğlu, A., Eken, Ö., Çiftçi, R. et al. The role of morphometric characteristics in predicting 20-meter sprint performance through machine learning. Sci Rep 14 , 16593 (2024). https://doi.org/10.1038/s41598-024-67405-y

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Microbiological characteristics of the lower airway in adults with bronchiectasis: a prospective cohort study

• Jie-lin Duan 1   na1 ,
• Cai-yun Li 4   na1 ,
• Ying Jiang 2 , 3   na1 ,
• Chao Liu 4 ,
• Pan-rui Huang 2 , 3 ,
• Li-fen Gao 2 , 3 ,
• Wei-jie Guan 2 , 3 &
• Lin-Ling Cheng 2 , 3  

Respiratory Research volume  25 , Article number:  283 ( 2024 ) Cite this article

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Metrics details

Microbial infection and colonization are frequently associated with disease progression and poor clinical outcomes in bronchiectasis. Identification of pathogen spectrum is crucial for precision treatment at exacerbation of bronchiectasis.

We conducted a prospective cohort study in patients with bronchiectasis exacerbation onset and stable state. Bronchoalveolar lavage fluid (BALF) was collected for conventional microbiological tests (CMTs) and metagenomic Next-Generation Sequencing (mNGS). Bronchiectasis patients were monitored for documenting the time to the next exacerbation during longitudinal follow-up.

We recruited 168 eligible participants in the exacerbation cohorts, and 38 bronchiectasis patients at stable state at longitudinal follow-up. 141 bronchiectasis patients at exacerbation onset had definite or probable pathogens via combining CMTs with mNGS reports. We identified that Pseudomonas aeruginosa, non-tuberculous mycobacteria , Haemophilus influenzae, Nocardia spp, and Staphylococcus aureus were the top 5 pathogens with a higher detection rate in our cohorts via combination of CMTs and mNGS analysis. We also observed strong correlations of Pseudomonas aeruginosa, Haemophilus influenzae, non-tuberculous mycobacteria with disease severity, including the disease duration, Bronchiectasis Severity Index, and lung function. Moreover, the adjusted pathogenic index of potential pathogenic microorganism negatively correlated ( r  = -0.7280, p  < 0.001) with the time to the next exacerbation in bronchiectasis.

We have revealed the pathogenic microbial spectrum in lower airways and the negative correlation of PPM colonization with the time to the next exacerbation in bronchiectasis. These results suggested that pathogens contribute to the progression of bronchiectasis.

Introduction

Bronchiectasis is a chronic airway disease that is characterized by progressive and irreversible dilatation of bronchus due to the recurrent damage of the bronchial wall [ 1 ]. Clinical presentations of bronchiectasis include chronic cough, purulent phlegm, hemoptysis, and repeated pulmonary infection [ 2 , 3 ]. However, the pathogenesis of bronchiectasis remains elusive. The “Vicious vortex” hypothesis suggests that the changes in the airway microenvironment (such as impaired mucociliary clearance) facilitate the colonization of microorganisms and increase the future risk of infection [ 4 , 5 ]. The failure to clear pathogens could, in turn, induce airway neutrophilic inflammation and progression to airway destruction [ 4 , 5 ].

Recurrent infections play a central role in the pathogenesis of bronchiectasis. Previous studies have demonstrated that bronchiectasis patients with Pseudomonas aeruginosa infection had more severe clinical symptoms, increased exacerbation frequencies, greater disease severity, and worse lung function [ 6 ]. Although effective among bronchiectasis patients, antibiotics cannot readily eradicate a number of potential pathogenic microorganisms (PPMs). Furthermore, the colonization status and higher bacterial loads of PPMs have been linked to poorer clinical outcomes and antibiotic response in patients with bronchiectasis and COPD [ 7 , 8 ].

In light of the pivotal roles of infection in driving the progression of bronchiectasis, it is crucial to identify PPMs and evaluate their abundance within the lower airways. These steps are essential for gaining insights into the pathophysiology of bronchiectasis and for guiding antibiotic treatment at onset of exacerbations. Timely and appropriate use of antibiotics is pivotal for preventing from the deterioration of pulmonary function and progression to exacerbation of bronchiectasis [ 9 ]. In principle, metagenomic next-generation sequencing (mNGS) can detect microorganisms of any known genomic sequences and has been widely used for etiological diagnosis of the respiratory tract, central nervous system, and bloodstream infections, etc. [ 10 , 11 , 12 ]. Moreover, mNGS can cover a broader spectrum of pathogens than conventional microbiological tests (CMTs) such as bacterial and fungal culture, serologic testing, and polymerase chain reaction (PCR), thus better informing the clinicians an appropriate antibiotic choice.

Traditionally, sputum specimens have been used for pathogen testing in bronchiectasis. However, sputum is susceptible to oral contamination and may not accurately reflect the pathogen burden in the lower (particularly distal) respiratory tract. Here, we aimed to evaluate the utility of CMTs and mNGS for detecting pathogens, and outline the characteristics of microorganisms in the lower airways in bronchiectasis. Furthermore, we investigated the association between the type or load of pathogens and prognosis in bronchiectasis.

Study population and samples collection

The patients were enrolled between Dec 17th 2020 and Sept 1st 2022 from the First Affiliated Hospital of Guangzhou Medical University, and followed until Oct 1st 2023 for recording the time to the next exacerbation. All patients have written informed consent. Eligible patients were aged 18 years or older, and had a high-resolution computed tomography (HRCT)-confirmed diagnosis of bronchiectasis. Exacerbations were defined as significantly increased or new-onset respiratory symptoms (chronic cough, infection, fever, purulent sputum, hemoptysis) that needed antibiotics administration as defined by the European Respiratory Society [ 13 ]. Stable state was defined as the absence of new symptoms and no changes in bronchiectasis therapy in the past four weeks [ 14 ]. Patients were excluded if they were unable to tolerate bronchoscopy. Patients with bronchiectasis underwent bronchoscopy of collection of bronchoalveolar lavage fluid (BALF) at onset of exacerbations and during the stable state. The disease severity was evaluated with the bronchiectasis severity index (BSI) and E-FACED score. Lung function was assessed by the forced expiratory volume in one second (FEV 1 ) and the FEV 1 /forced vital capacity (FVC) ratio. Disease duration, the time since the first diagnosis of bronchiectasis by radiology, was recorded during consultation of case history. The diagnosis of exact infectious etiology of each patient was comprehensively made based on a composite reference standard as previous report [ 10 ], including CMTs results, mNGS reports, radiological findings, clinical presentations, therapeutic response to antibiotics, and further adjudication by an independent expert panel involving two independent clinicians.

The CMTs included bacterial/mycoplasma/chlamydia/fungal culture, galactomannan antigen test, (1,3)-β-D-glucan test and cryptococcal polysaccharide antigen test. Sputum and BALF were collected from each patient, transported to the microbiology laboratory, and processed (< 2 h) for culture. Sputum samples with > 25 leukocytes and < 10 squamous epithelial cells (at low-power field) were deemed eligible. Blood/chocolate agar (bioMérieux) and Sabouraud agar were used as the culture media. Multiplex PCR was used for the identification of non-tuberculous mycobacteria.

The internal control (IC) DNA, a double-stranded DNA fragment referred as a spike in control, was synthesized, amplified by PCR (TAKARA PrimeSTAR® HS DNA Polymerase, Cat# R044) and purified using magnetic beads (Matridx, Cat# MD012). All procedures were performed inside a Biosafety cabinet. Qubit fluorometric quantitation was performed on the amplicons (Thermo Fisher, Qubit dsDNA HS Assay Kit, Cat# Q32854). The nucleotide sequences of IC DNA have been reported previously. ICs were added to each BALF sample prior to nucleic acid extraction at a final concentration of 0.02 ng/μL. DNA sequencing library was prepared by enzymatic fragmentation, end repairing, terminal adenylation and adaptor ligation (NGSmaster™ library preparation, Matridx, Cat# MAR002) [ 15 ]. Concentration of DNA libraries was quantified by real-time PCR (KAPA) and pooled. Shotgun sequencing was carried out on illumina Nextseq™ platform. Approximately 20 million of 75 bp single-end reads were generated for each library [ 16 , 17 ]. For each run, a negative control (medium containing 10 6 /mL JURKAT cells) was included for quality control.

Raw sequences were processed by a bioinformatic pipeline, which included: 1) adapter sequences and low-quality bases (Q-score cutoff of 20) were trimmed by Fastp ( https://github.com/OpenGene/fastp ); 2) Host reads were filtered by mapping to the human reference genome (GRCh38.p13) using Burrows Wheeler alignment (BWA, http://bio-bwa.sourceforge.net ) [ 18 ]; 3) After removal of low-complexity reads, the remaining sequences were aligned by BWA to an in-house reference database (curated from NCBI nt database ( ftp://ftp.ncbi.nlm.nih.gov/blast/db/ ) and GenBank ( ftp://ftp.ncbi.nlm.nih.gov/genomes/genbank/)) [ 18 ]. We defined that reads with 90% identity of reference were mapped reads. In addition, reads with multiple locus alignments within the same genus were excluded from the secondary analysis. Only reads mapped to the genome within the same species were considered.

Microbial reads identified from a library were reported if: 1) the sequencing data passed quality control filters (library concentration > 50 pM, Q20 > 85%, Q30 > 80%); 2) negative control in the same sequencing run does not contain the species or the Reads Per Million (RPM) of the sample / RPM of the negative control ≥ 5.

Calculation of the adjusted pathogenic index (API)

To analyze the microbial abundance in BALF, we used the adjusted pathogenic index (API) to reflect the bacterial load of microbial species as described previously [ 19 ]. Briefly, for each library, we chose the reads per million (RPM) mapped reads as the normalization method for mNGS reads as previous report [ 20 ]. RPM was calculated using the formula: gene reads / the total mapped reads (millions). We added spike (IC DNA) to each BALF sample and carried out mNGS testing to evaluate the relationship between spike RPM and nucleated cell count. We observed that spike RPM was inversely correlated with cell count (R 2  = 0.6278), suggesting that cell count in BALF samples correlated to increased human DNA contamination in high cell count samples, and hence reduced spike in recovery. The RPM of the internal control was defined as SRPM (spike reads per million mapped reads).

The API was calculated according to the following formula: API = log 2 [(1,887,800 × RPM / SRPM) + 1] × 1000. Specifically, the factor 1,887,800 originated from 1.8878 μg × 1,000,000. 1.8878 μg represents the amount of spike nucleic acid added per liter of BALF, and 1,000,000 is a coefficient to normalize the ratio of (1,887,800 × RPM / SRPM) similar to 1. The API score is logarithmically transformed to ensure a 5-digit range.

Association between PPM colonization and clinical outcomes in bronchiectasis

The patients at clinical stable state were regularly followed-up to record the time to next exacerbation. According to microbial results from mNGS and CMTs, bronchiectasis patients at clinical stable state were clarified into PPM and non-PPM group according to the presence or absence of PPMs as reported previously [ 21 ]. Briefly, PPMs are those microorganisms that are recognized for causing respiratory infections, like Pseudomonas aeruginosa , Enterobacteriaceae , Haemophilus influenzae , Staphylococcus aureus , Streptococcus pneumoniae , and Moraxella catarrhalis , regardless of their presence in other body areas. Conversely, non-PPMs, like Streptococcus viridans group, Neisseria species , Corynebacterium species , and Candida species , are typically found in the oropharynx or gut and not associated with respiratory infections in healthy individuals [ 21 ]. Then, the correlation of API with the time to the next exacerbation in PPMs or non-PPMs group was analyzed.

Statistical analysis

The SPSS 25.0 (IBM Corporation, USA) package was used for statistical analysis. The quantitative variables were evaluated as mean (standard deviation, SD) or normal distribution or as median (inter-quartile range, IQR) for non-normal distribution. The qualitative or dichotomized variables were evaluated as count (percentage of the total). Associations for the between-group differences were tested using the Kruskal–Wallis or the Wilcoxon matched paired signed-rank test. Pearson’s correlation analysis was used to examine the associations of API in PPM or non-PPM group with the time to next exacerbation.

Study profile and patient characteristics

Between Dec 17th 2020 and Sept 1st 2022, 168 eligible participants (excluding 13 patients who declined follow-up and 4 patients who could not tolerate bronchoscopy) were recruited into the exacerbation cohorts. Meanwhile, 38 bronchiectasis patients (including 13 patients who were enrolled during both the acute exacerbation and the stable state) in stable state were recruited, and were regularly followed-up to monitor the time to the next exacerbation. All participants provided sputum and BALF sample for CMTs as described previously (Fig.  1 and Supplementary Table 1). mNGS was applied for BALF samples only. The exacerbation patients had an average age of 54 (44, 64) years, with a mean disease duration of 10 (3, 20) years. The most common symptoms at exacerbation onset were increased cough and sputum (62/168, 36.9%). The mean FEV 1 and FEV 1 /FVC of exacerbation bronchiectasis was 1.59 (1.03, 2.07) liters and 72.13% (59.01%,81.71%), respectively. The BSI and E-FACED score was 10.0 (7,11.75) and 3.0 (1, 4), respectively. 9.5% of patients were cigarette smokers and 17.9% had a previous history of pulmonary tuberculosis (30/168, 17.9%) (Table  1 ).

The design of the study was illustrated in the flow chart

Pathogen detection by CMTs and mNGS

Potential pathogens were detected via both CMTs and mNGS. 83.9% (141/168) of patients at exacerbation onset were diagnosed as having an infectious etiology according to a composite reference standard. Among these, 96.5% (136/141) of mNGS reports were confirmed by clinical diagnosis. Both CMTs and mNGS could identify bacterial and fungal pathogens, but mNGS showed a higher detection sensitivity for Pseudomonas aeruginosa , non-tuberculous mycobacteria, Haemophilus influenzae , Nocardia spp, and Staphylococcus aureus —all were the top 5 pathogens. In addition, mNGS was more sensitive than CMTs for detecting uncommon respiratory pathogens. For example, mNGS had a 100% detection rate for fastidious ( i.e., Legionella spp., Neisseria subflava ) and anaerobic bacteria ( i.e. , Porphyromonas gingivalis ), but CMTs did not (Fig.  2 A). mNGS also showed higher detection rate than CMTs for Aspergillus fumigatus (87.5% vs. 12.5%) and cytomegalovirus (100% vs. 0%) which were one of the most frequently detected fungal and viral pathogens, respectively, in our cohort (Fig.  2 A).

Clinical utility of mNGS for lower airway pathogen identification. A Microbial findings in the exacerbation cohort using mNGS, conventional microbiological tests (CMTs), or their combination. The left side represents the number of samples with microorganism detection by mNGS and CMTs, or their combination. The right side represents the number of patients with pathogen detection by mNGS and CMTs, or their combination. B Positive and negative rates of pathogen detection by culture, CMTs, and mNGS in the etiology confirmed and unknown groups. C Patients’ etiology and diagnosis. The left side shows the percentage of patients with known or unknown etiology, while the right side indicates the number of patients with known etiology diagnosed via mNGS, CMTs, and clinical manifestations. D Comparison of culture, CMTs, and mNGS relative to a composite reference standard (CRS). Sensitivity, specificity, and accuracy values are displayed below each table

For patients in the exacerbation cohort with a confirmed infectious etiology, the detection rate was 96.45% for mNGS, which was significantly higher compared with that of culture (45.39%) and CMTs (46.10%, including culture and PCR, G/GM test) ( p  < 0.01, Fig.  2 B). mNGS provided additional evidence for infectious etiology in 136 patients. Of these, mNGS alone successfully helped diagnose the infectious etiology in 74 cases, whereas CMTs did not. In contrast, CMTs provided additional evidence for infectious etiology among 65 patients, of whom only 3 had negative mNGS results (Fig.  2 C). By comparing with the composite reference standard, the sensitivity of the mNGS was 96.5% (95% CI [91.49%-98.69%]), which was higher than culture (45.4% [37.1%-54.0%], p  < 0.05) and CMTs (46.1%, [37.7%-54.7%], p  < 0.05). The specificity of the mNGS assay was 74.1% (95% CI [53.4%-88.1%]), which was lower than culture and CMTs (96.3%, [79.1%-99.8%]). The accuracy of culture, CMTs, and mNGS were 53.6%, 54.2% and 92.9%, respectively (Fig.  2 D).

Correlation of pathogen spectrum with disease severity

Accumulating evidence has shown that infections (including Pseudomonas aeruginosa and Haemophilus influenza ) are associated with disease severity of bronchiectasis [ 22 ]. Consistently, we found significant associations between the most frequently detected pathogens in BALF and the clinical characteristics at exacerbation onset. These clinical characteristics included sex, age, body-mass index, duration of disease, radiological severity, BSI, E-FACED score, pulmonary function, smoking, and underlying comorbidities such as asthma, COPD and diabetes. Pseudomonas aeruginosa was detected more frequently in patients with longer disease duration ( p  < 0.001) and greater disease severity evidenced by the number of lobes affected, BSI, E-FACED score and the FEV 1 /FVC ratio (Table  2 ). Notably, non-smokers were more likely to have Pseudomonas aeruginosa colonization or infection than smokers (50.0% vs. 12.5%, p  = 0.004).

Furthermore, Haemophilus influenzae detection was associated with a milder disease severity. 50%, 18.64%, and 5.61% of patients with mild, moderate and severe bronchiectasis, as stratified by the BSI, had Haemophilus influenzae detection ( p  = 0.014). The detection rate of Haemophilus influenzae was significantly lower in patients with a history of asthma than in those without (40% vs. 9.5%, p  = 0.003). There were no significant differences for other clinical indices between Haemophilus influenzae and non- Haemophilus influenzae group (Table  3 ).

We also found a higher detection rate of NTM in patients with a history of inactive pulmonary tuberculosis than those without (20% vs. 6.52%, p  = 0.019). Intriguingly, bronchiectasis patients without NTM showed poorer lung function evidenced by lower FEV 1 pred (%) ( p  = 0.028). As for other clinical parameters, no statistical differences between NTM and non-NTM group were observed (Table  4 ).

Higher API of PPMs correlated with a shorter time to the next exacerbation

We firstly analyzed the major microbial composition in BALF from bronchiectasis patients, and observed a similar microbial composition, while bacterial abundance of each species was different between exacerbation onset and stable state (Fig.  3 A). Previous studies have shown that colonization of PPMs was associated with increased inflammation and poorer clinical outcomes of chronic lung diseases such as COPD [ 7 , 23 ]. Similarly, we found that higher API was significantly associated with shorter time to next exacerbation in bronchiectasis patients with PPMs colonization, but not in non-PPMs group (Fig.  3 B). To mitigate the influence of highly leveraged data points, we performed an outlier exclusion analysis. The correlation remained significant for the PPM group ( r  = -0.7280, P  < 0.001) but not for the non-PPM group ( r  = -0.3327, P  = 0.245). These data suggest that both the colonization and bacterial load of PPMs in BALF was associated with poorer clinical outcomes in bronchiectasis.

The pathogenic index of potential pathogenic microorganisms (PPMs) negatively correlates with the time to next exacerbation. A The composition of top 20 bacterial species measured by mNGS in the lower airways in bronchiectasis patients at exacerbation onset and stable state. B Pearson’s analysis of correlation of adjusted pathogenic index (API) with the time to next exacerbation in bronchiectasis patients with or without PPMs colonization 

Infection has been a common trigger of the pathogenesis and exacerbation of bronchiectasis [ 5 ]. Identifying the probable or definite pathogens is crucial for personalized treatment for exacerbation. Although being the most common sample that be routine clinical used for pathogen identification in bronchiectasis, sputum remains the suboptimal source because the sputum volume is highly variable and suffers from the contamination of oral and upper airway contents. Therefore, lower respiratory tract samples such as BALF are more ideal samples for pathogen identification, while BALF has low microbial biomass and requires higher technical requirements for the operators. Here, we collected BALF samples to identify microbial characteristics in the lower airways in bronchiectasis via mNGS, which has been widely used to rapidly and precisely detect pathogens in patients with lower respiratory tract infection and bronchiectasis [ 10 , 24 ]. Consistently, mNGS yielded superior sensitivity, specificity and accuracy compare with CMTs. Previous studies have shown that Pseudomonas aeruginosa , Haemophilus influenzae , rhinovirus and influenza viruses are the most common pathogens at exacerbation onset of bronchiectasis [ 25 , 26 , 27 ]. In support of these studies, we also found that Pseudomonas aeruginosa , Haemophilus influenza , and other pathogens were frequently detected in BALF from bronchiectasis patients at exacerbation onset, and that Pseudomonas aeruginosa was associated with a longer disease duration. We have also shown that mNGS could be a better diagnostic tool than CTMs in detecting NTM, Nocardia , and Legionella , indicating that these pathogens may be underrepresented in earlier studies and overlooked clinically. To our knowledge, this is the largest cohort study characterizing the microbial spectrum in the lower airways in bronchiectasis patients via collection of BALF samples.

Accumulating evidence has shown that PPMs colonization impairs efferocytosis of alveolar macrophages and is associated with more rapid decline of lung function and poorer clinical outcomes in COPD [ 7 , 28 ]. Consistently, PPM colonization in the lower airways was common in bronchiectasis patients, and was associated with a shorter time to the next exacerbation. Therefore, PPM colonization might be linked to disease progression in bronchiectasis. Immune escape of PPMs in the stable state, as reported previously, would predispose to the overgrowth and transition into the pathogenic state, resulting in exacerbation of COPD or other chronic lung diseases [ 8 , 21 ]. In support of these findings, we found that a higher load of PPMs (referred to as API) in the lower airways was associated with a significantly shorter time to the next exacerbation in bronchiectasis at stable state. Our data imply that the bacterial burden of colonized PPMs in the lower airways was crucial for predicting the course of exacerbation and deterioration in bronchiectasis patients. Meanwhile, our study provides therapeutic clues that long-term antibiotic treatment should be applied to reduce the loads of PPMs among patients with PPM colonization. This strategy has resulted in the reduced frequency of exacerbation and improved quality of life in bronchiectasis patients [ 29 , 30 ].

Our study has several limitations. First, mNGS provides various useful information and potential pathogenic candidates for pathogens identification, but it remains difficult to distinguish pathogens from colonizing microorganisms. Thus, microbiological and radiological examination and rational adjudication by clinicians are needed to more accurately identify the definite pathogens in bronchiectasis. Additionally, because API is calculated based on the reads of microbial species by mNGS, it is unable to provide an absolute quantification of microbial loads in clinical practice. Therefore, quantitative PCR is necessary to monitor the dynamic changes of bacterial burden of PPMs, which can help to precisely dissect the relationship of PPMs with the disease severity in real-world. Moreover, accurately pinpointing disease duration remains a great challenge in bronchiectasis, as symptoms often appear later in the progression. Although our data showed a positive correlation between disease duration (based on first radiological diagnosis) and colonization by Pseudomonas aeruginosa and NTM, it remains unable to reflect the true onset or exact start of disease. Thus, it is necessary and urgent to establish method for precisely determining disease duration in bronchiectasis.

We have investigated the pathogen spectrum by combination of mNGS and CMTs in a cohort of bronchiectasis patients with exacerbation onset based on BALF samples. Our study has not only shown more accurate characterization of the pathogenic bacteria responsible for exacerbations, but also provides the evidence for the prognostic role of colonization and load of PPMs in bronchiectasis.

Availability of data and materials

The original contributions presented in the study are publicly available. The sequencing data reported in this study was archived in the Sequence Read Archive (SRA) with the accession number (PRJNA1021363).

Abbreviations

Bronchoalveolar lavage fluid

Conventional microbiological tests

Metagenomic Next-Generation Sequencing

Potential pathogenic microorganisms

Adjusted pathogenic index

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Acknowledgements

The authors are very grateful to the patients for participating in this study and donating their biological samples.

This study was supported by the National Natural Science Foundation of China (No. 82170003), Guangzhou Basic Research Program (No. 202102010350).

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Jie-lin Duan, Cai-yun Li and Ying Jiang contributed equally to this work.

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State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Department of Allergy and Clinical Immunology, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, P.R. China

Jie-lin Duan

State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, National Center for Respiratory Medicine, Department of Respiratory and Critical Care Medicine, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, P.R. China

Ying Jiang, Pan-rui Huang, Li-fen Gao, Wei-jie Guan & Lin-Ling Cheng

Guangzhou National Laboratory, Guangzhou, China

Medical Department, Hangzhou Matridx Biotechnology Co., Ltd, Hangzhou, People’s Republic of China

Cai-yun Li & Chao Liu

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Lin-Ling Cheng takes full responsibility for the content of the article including study design, the data and analysis. Jie-lin Duan, Cai-yun Li, Ying Jiang, and Wei-jie Guan drafted and revised the manuscript. Cai-yun Li, Chao Liu, Pan-rui Huang, and Li-fen Gao performed the analyses. All authors contributed to data interpretation and manuscript revision.

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Duan, Jl., Li, Cy., Jiang, Y. et al. Microbiological characteristics of the lower airway in adults with bronchiectasis: a prospective cohort study. Respir Res 25 , 283 (2024). https://doi.org/10.1186/s12931-024-02903-1

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Received : 14 November 2023

Accepted : 02 July 2024

Published : 17 July 2024

DOI : https://doi.org/10.1186/s12931-024-02903-1

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Angel Hsu holds net-zero pledgers accountable

The Carolina researcher and her Data-Driven EnviroLab track climate-change data for the United Nations.

As a graduate student at Yale University, Angel Hsu traveled to Copenhagen for the 2009 United Nations Climate Change Conference, or the Convention of the Parties 15.

“COP 15 completely changed my worldview,” Hsu said. “Why does the U.N. matter? Because it convenes stakeholders — activists, business leaders, local governments, Indigenous groups, academics and policymakers. The U.N. feels very far away from us as people, but it matters.”

Attending COP as a student infused purpose into Hsu’s research. Since then, she has delivered two TED Talks, provided expert testimony to the U.S. Senate, co-authored and contributed to two U.N. reports, served on the National Committee on U.S.–China Relations and become a renowned expert in climate research and sustainability.

An associate professor in the College of Arts and Sciences’ public policy department and the environment, ecology and energy program at UNC-Chapel Hill, Hsu is the founder and director of the Data-Driven EnviroLab. She takes students to COP every year.

“UNC-Chapel Hill is a registered observer organization at COP,” Hsu said. “That is an honor and a privilege. There are so many other universities throughout the world that don’t have this opportunity. That’s why I take students every time I go — because I know how life-changing the experience is for students.”

COP is the world’s only multilateral decision-making forum on climate change, involving nearly every country. Hsu’s Data-Driven EnviroLab, which goes by the initials DDL, is an interdisciplinary research group focused on quantitative approaches to environmental issues, providing important research to COP climate negotiators.

“There is not a lot of accountability because private actors, in many cases, are not being regulated by governments, so the voluntary pledges that they make are not actually enforced,” she said. “The DDL’s data on the Net Zero Tracker  have shown that fossil fuel companies are the most active in pledging that they’re going to go net zero, but none of them has a plan to transition away from fossil fuels. We are trying to provide that accountability.”

Following COP 28, students who attended the conference took part in panel discussions about their experiences and the state of climate policy. According to Hallie Turner ’24, one of the organizers of the event, the purpose of the panel discussion was to “make a complicated series of negotiations engaging and accessible to all who are curious.”

Hsu believes climate policy must extend beyond governments to involve nonstate actors, and that people around the world should understand how their lives are affected by climate change.

Last year, Hsu collaborated with researchers at National University of Singapore, one of Carolina’s four strategic partners, on urban heat management. NUS researchers use Digital Urban Twins, advanced 3D models that simulate various climate scenarios. The tool allows researchers and policymakers to evaluate interventions before implementing them. According to Hsu, urban heat management, such as building modifications and cooling, is hugely important to North Carolina.

“I was really trying to learn from colleagues in Singapore,” Hsu said. “What are they modeling? What questions are they asking? How are they approaching urban heat management?”

The DDL is applying these techniques used in Singapore in the Research Triangle. Through cross-disciplinary collaboration, the DDL aims to address heat stress disparities and promote environmental justice, contributing to the development of resilient, sustainable cities — in North Carolina and worldwide.

“We’re never going to solve the problem if people are not talking about it,” Hsu said. “We need to be having these conversations every single day. Climate change — including climate solutions — needs to be part of our consciousness.”

In a campus email, the provost and vice chancellor for student affairs detailed ongoing efforts to improve the Student Conduct system.

3 Carolina research teams receive UNC System grants

The Research Opportunities Initiative funds, totaling $4.5 million, come from the North Carolina General Assembly.

UNC System shares guidance regarding DEI

UNC-Chapel Hill, along with other system campuses, must submit reports for complying with the policy by Sept. 1.

Brenda Kirby, longtime University secretary, dies at 79

Kirby worked in the Chancellor’s Office for 32 years, serving six chancellors.

Researchers identify potential treatment for Angelman syndrome

A small molecule could lead to effective therapy for the rare genetic disorder, UNC School of Medicine scientists say.

Carolina named ‘new Ivy’ by Forbes

The list highlights institutions “turning out the smart, driven graduates craved by employers of all types.”

Student-Made UNC crafts entrepreneurs

The platform’s student managers work hard behind the scenes to help Tar Heel makers market their creations.

Student researchers map heat on campus

Working with the Sustainable Triangle Field Site, they gather data to provide potential solutions to hotspots.

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