what to include in research methods

How To Choose Your Research Methodology

Qualitative vs quantitative vs mixed methods.

By: Derek Jansen (MBA). Expert Reviewed By: Dr Eunice Rautenbach | June 2021

Without a doubt, one of the most common questions we receive at Grad Coach is “ How do I choose the right methodology for my research? ”. It’s easy to see why – with so many options on the research design table, it’s easy to get intimidated, especially with all the complex lingo!

In this post, we’ll explain the three overarching types of research – qualitative, quantitative and mixed methods – and how you can go about choosing the best methodological approach for your research.

Overview: Choosing Your Methodology

Understanding the options – Qualitative research – Quantitative research – Mixed methods-based research

Choosing a research methodology – Nature of the research – Research area norms – Practicalities

Free Webinar: Research Methodology 101

1. Understanding the options

Before we jump into the question of how to choose a research methodology, it’s useful to take a step back to understand the three overarching types of research – qualitative , quantitative and mixed methods -based research. Each of these options takes a different methodological approach.

Qualitative research utilises data that is not numbers-based. In other words, qualitative research focuses on words , descriptions , concepts or ideas – while quantitative research makes use of numbers and statistics. Qualitative research investigates the “softer side” of things to explore and describe, while quantitative research focuses on the “hard numbers”, to measure differences between variables and the relationships between them.

Importantly, qualitative research methods are typically used to explore and gain a deeper understanding of the complexity of a situation – to draw a rich picture . In contrast to this, quantitative methods are usually used to confirm or test hypotheses . In other words, they have distinctly different purposes. The table below highlights a few of the key differences between qualitative and quantitative research – you can learn more about the differences here.

  • Uses an inductive approach
  • Is used to build theories
  • Takes a subjective approach
  • Adopts an open and flexible approach
  • The researcher is close to the respondents
  • Interviews and focus groups are oftentimes used to collect word-based data.
  • Generally, draws on small sample sizes
  • Uses qualitative data analysis techniques (e.g. content analysis , thematic analysis , etc)
  • Uses a deductive approach
  • Is used to test theories
  • Takes an objective approach
  • Adopts a closed, highly planned approach
  • The research is disconnected from respondents
  • Surveys or laboratory equipment are often used to collect number-based data.
  • Generally, requires large sample sizes
  • Uses statistical analysis techniques to make sense of the data

Mixed methods -based research, as you’d expect, attempts to bring these two types of research together, drawing on both qualitative and quantitative data. Quite often, mixed methods-based studies will use qualitative research to explore a situation and develop a potential model of understanding (this is called a conceptual framework), and then go on to use quantitative methods to test that model empirically.

In other words, while qualitative and quantitative methods (and the philosophies that underpin them) are completely different, they are not at odds with each other. It’s not a competition of qualitative vs quantitative. On the contrary, they can be used together to develop a high-quality piece of research. Of course, this is easier said than done, so we usually recommend that first-time researchers stick to a single approach , unless the nature of their study truly warrants a mixed-methods approach.

The key takeaway here, and the reason we started by looking at the three options, is that it’s important to understand that each methodological approach has a different purpose – for example, to explore and understand situations (qualitative), to test and measure (quantitative) or to do both. They’re not simply alternative tools for the same job. 

Right – now that we’ve got that out of the way, let’s look at how you can go about choosing the right methodology for your research.

Methodology choices in research

2. How to choose a research methodology

To choose the right research methodology for your dissertation or thesis, you need to consider three important factors . Based on these three factors, you can decide on your overarching approach – qualitative, quantitative or mixed methods. Once you’ve made that decision, you can flesh out the finer details of your methodology, such as the sampling , data collection methods and analysis techniques (we discuss these separately in other posts ).

The three factors you need to consider are:

  • The nature of your research aims, objectives and research questions
  • The methodological approaches taken in the existing literature
  • Practicalities and constraints

Let’s take a look at each of these.

Factor #1: The nature of your research

As I mentioned earlier, each type of research (and therefore, research methodology), whether qualitative, quantitative or mixed, has a different purpose and helps solve a different type of question. So, it’s logical that the key deciding factor in terms of which research methodology you adopt is the nature of your research aims, objectives and research questions .

But, what types of research exist?

Broadly speaking, research can fall into one of three categories:

  • Exploratory – getting a better understanding of an issue and potentially developing a theory regarding it
  • Confirmatory – confirming a potential theory or hypothesis by testing it empirically
  • A mix of both – building a potential theory or hypothesis and then testing it

As a rule of thumb, exploratory research tends to adopt a qualitative approach , whereas confirmatory research tends to use quantitative methods . This isn’t set in stone, but it’s a very useful heuristic. Naturally then, research that combines a mix of both, or is seeking to develop a theory from the ground up and then test that theory, would utilize a mixed-methods approach.

Exploratory vs confirmatory research

Let’s look at an example in action.

If your research aims were to understand the perspectives of war veterans regarding certain political matters, you’d likely adopt a qualitative methodology, making use of interviews to collect data and one or more qualitative data analysis methods to make sense of the data.

If, on the other hand, your research aims involved testing a set of hypotheses regarding the link between political leaning and income levels, you’d likely adopt a quantitative methodology, using numbers-based data from a survey to measure the links between variables and/or constructs .

So, the first (and most important thing) thing you need to consider when deciding which methodological approach to use for your research project is the nature of your research aims , objectives and research questions. Specifically, you need to assess whether your research leans in an exploratory or confirmatory direction or involves a mix of both.

The importance of achieving solid alignment between these three factors and your methodology can’t be overstated. If they’re misaligned, you’re going to be forcing a square peg into a round hole. In other words, you’ll be using the wrong tool for the job, and your research will become a disjointed mess.

If your research is a mix of both exploratory and confirmatory, but you have a tight word count limit, you may need to consider trimming down the scope a little and focusing on one or the other. One methodology executed well has a far better chance of earning marks than a poorly executed mixed methods approach. So, don’t try to be a hero, unless there is a very strong underpinning logic.

Need a helping hand?

what to include in research methods

Factor #2: The disciplinary norms

Choosing the right methodology for your research also involves looking at the approaches used by other researchers in the field, and studies with similar research aims and objectives to yours. Oftentimes, within a discipline, there is a common methodological approach (or set of approaches) used in studies. While this doesn’t mean you should follow the herd “just because”, you should at least consider these approaches and evaluate their merit within your context.

A major benefit of reviewing the research methodologies used by similar studies in your field is that you can often piggyback on the data collection techniques that other (more experienced) researchers have developed. For example, if you’re undertaking a quantitative study, you can often find tried and tested survey scales with high Cronbach’s alphas. These are usually included in the appendices of journal articles, so you don’t even have to contact the original authors. By using these, you’ll save a lot of time and ensure that your study stands on the proverbial “shoulders of giants” by using high-quality measurement instruments .

Of course, when reviewing existing literature, keep point #1 front of mind. In other words, your methodology needs to align with your research aims, objectives and questions. Don’t fall into the trap of adopting the methodological “norm” of other studies just because it’s popular. Only adopt that which is relevant to your research.

Factor #3: Practicalities

When choosing a research methodology, there will always be a tension between doing what’s theoretically best (i.e., the most scientifically rigorous research design ) and doing what’s practical , given your constraints . This is the nature of doing research and there are always trade-offs, as with anything else.

But what constraints, you ask?

When you’re evaluating your methodological options, you need to consider the following constraints:

  • Data access
  • Equipment and software
  • Your knowledge and skills

Let’s look at each of these.

Constraint #1: Data access

The first practical constraint you need to consider is your access to data . If you’re going to be undertaking primary research , you need to think critically about the sample of respondents you realistically have access to. For example, if you plan to use in-person interviews , you need to ask yourself how many people you’ll need to interview, whether they’ll be agreeable to being interviewed, where they’re located, and so on.

If you’re wanting to undertake a quantitative approach using surveys to collect data, you’ll need to consider how many responses you’ll require to achieve statistically significant results. For many statistical tests, a sample of a few hundred respondents is typically needed to develop convincing conclusions.

So, think carefully about what data you’ll need access to, how much data you’ll need and how you’ll collect it. The last thing you want is to spend a huge amount of time on your research only to find that you can’t get access to the required data.

Constraint #2: Time

The next constraint is time. If you’re undertaking research as part of a PhD, you may have a fairly open-ended time limit, but this is unlikely to be the case for undergrad and Masters-level projects. So, pay attention to your timeline, as the data collection and analysis components of different methodologies have a major impact on time requirements . Also, keep in mind that these stages of the research often take a lot longer than originally anticipated.

Another practical implication of time limits is that it will directly impact which time horizon you can use – i.e. longitudinal vs cross-sectional . For example, if you’ve got a 6-month limit for your entire research project, it’s quite unlikely that you’ll be able to adopt a longitudinal time horizon. 

Constraint #3: Money

As with so many things, money is another important constraint you’ll need to consider when deciding on your research methodology. While some research designs will cost near zero to execute, others may require a substantial budget .

Some of the costs that may arise include:

  • Software costs – e.g. survey hosting services, analysis software, etc.
  • Promotion costs – e.g. advertising a survey to attract respondents
  • Incentive costs – e.g. providing a prize or cash payment incentive to attract respondents
  • Equipment rental costs – e.g. recording equipment, lab equipment, etc.
  • Travel costs
  • Food & beverages

These are just a handful of costs that can creep into your research budget. Like most projects, the actual costs tend to be higher than the estimates, so be sure to err on the conservative side and expect the unexpected. It’s critically important that you’re honest with yourself about these costs, or you could end up getting stuck midway through your project because you’ve run out of money.

Budgeting for your research

Constraint #4: Equipment & software

Another practical consideration is the hardware and/or software you’ll need in order to undertake your research. Of course, this variable will depend on the type of data you’re collecting and analysing. For example, you may need lab equipment to analyse substances, or you may need specific analysis software to analyse statistical data. So, be sure to think about what hardware and/or software you’ll need for each potential methodological approach, and whether you have access to these.

Constraint #5: Your knowledge and skillset

The final practical constraint is a big one. Naturally, the research process involves a lot of learning and development along the way, so you will accrue knowledge and skills as you progress. However, when considering your methodological options, you should still consider your current position on the ladder.

Some of the questions you should ask yourself are:

  • Am I more of a “numbers person” or a “words person”?
  • How much do I know about the analysis methods I’ll potentially use (e.g. statistical analysis)?
  • How much do I know about the software and/or hardware that I’ll potentially use?
  • How excited am I to learn new research skills and gain new knowledge?
  • How much time do I have to learn the things I need to learn?

Answering these questions honestly will provide you with another set of criteria against which you can evaluate the research methodology options you’ve shortlisted.

So, as you can see, there is a wide range of practicalities and constraints that you need to take into account when you’re deciding on a research methodology. These practicalities create a tension between the “ideal” methodology and the methodology that you can realistically pull off. This is perfectly normal, and it’s your job to find the option that presents the best set of trade-offs.

Recap: Choosing a methodology

In this post, we’ve discussed how to go about choosing a research methodology. The three major deciding factors we looked at were:

  • Exploratory
  • Confirmatory
  • Combination
  • Research area norms
  • Hardware and software
  • Your knowledge and skillset

If you have any questions, feel free to leave a comment below. If you’d like a helping hand with your research methodology, check out our 1-on-1 research coaching service , or book a free consultation with a friendly Grad Coach.

what to include in research methods

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Dr. Zara

Very useful and informative especially for beginners

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Hi I am Anna ,

I am a PHD candidate in the area of cyber security, maybe we can link up

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I struggle so much with designs of the research for sure!

Joyce

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Research methods--quantitative, qualitative, and more: overview.

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About Research Methods

This guide provides an overview of research methods, how to choose and use them, and supports and resources at UC Berkeley. 

As Patten and Newhart note in the book Understanding Research Methods , "Research methods are the building blocks of the scientific enterprise. They are the "how" for building systematic knowledge. The accumulation of knowledge through research is by its nature a collective endeavor. Each well-designed study provides evidence that may support, amend, refute, or deepen the understanding of existing knowledge...Decisions are important throughout the practice of research and are designed to help researchers collect evidence that includes the full spectrum of the phenomenon under study, to maintain logical rules, and to mitigate or account for possible sources of bias. In many ways, learning research methods is learning how to see and make these decisions."

The choice of methods varies by discipline, by the kind of phenomenon being studied and the data being used to study it, by the technology available, and more.  This guide is an introduction, but if you don't see what you need here, always contact your subject librarian, and/or take a look to see if there's a library research guide that will answer your question. 

Suggestions for changes and additions to this guide are welcome! 

START HERE: SAGE Research Methods

Without question, the most comprehensive resource available from the library is SAGE Research Methods.  HERE IS THE ONLINE GUIDE  to this one-stop shopping collection, and some helpful links are below:

  • SAGE Research Methods
  • Little Green Books  (Quantitative Methods)
  • Little Blue Books  (Qualitative Methods)
  • Dictionaries and Encyclopedias  
  • Case studies of real research projects
  • Sample datasets for hands-on practice
  • Streaming video--see methods come to life
  • Methodspace- -a community for researchers
  • SAGE Research Methods Course Mapping

Library Data Services at UC Berkeley

Library Data Services Program and Digital Scholarship Services

The LDSP offers a variety of services and tools !  From this link, check out pages for each of the following topics:  discovering data, managing data, collecting data, GIS data, text data mining, publishing data, digital scholarship, open science, and the Research Data Management Program.

Be sure also to check out the visual guide to where to seek assistance on campus with any research question you may have!

Library GIS Services

Other Data Services at Berkeley

D-Lab Supports Berkeley faculty, staff, and graduate students with research in data intensive social science, including a wide range of training and workshop offerings Dryad Dryad is a simple self-service tool for researchers to use in publishing their datasets. It provides tools for the effective publication of and access to research data. Geospatial Innovation Facility (GIF) Provides leadership and training across a broad array of integrated mapping technologies on campu Research Data Management A UC Berkeley guide and consulting service for research data management issues

General Research Methods Resources

Here are some general resources for assistance:

  • Assistance from ICPSR (must create an account to access): Getting Help with Data , and Resources for Students
  • Wiley Stats Ref for background information on statistics topics
  • Survey Documentation and Analysis (SDA) .  Program for easy web-based analysis of survey data.

Consultants

  • D-Lab/Data Science Discovery Consultants Request help with your research project from peer consultants.
  • Research data (RDM) consulting Meet with RDM consultants before designing the data security, storage, and sharing aspects of your qualitative project.
  • Statistics Department Consulting Services A service in which advanced graduate students, under faculty supervision, are available to consult during specified hours in the Fall and Spring semesters.

Related Resourcex

  • IRB / CPHS Qualitative research projects with human subjects often require that you go through an ethics review.
  • OURS (Office of Undergraduate Research and Scholarships) OURS supports undergraduates who want to embark on research projects and assistantships. In particular, check out their "Getting Started in Research" workshops
  • Sponsored Projects Sponsored projects works with researchers applying for major external grants.
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Choosing the Right Research Methodology: A Guide for Researchers

  • 3 minute read
  • 51.4K views

Table of Contents

Choosing an optimal research methodology is crucial for the success of any research project. The methodology you select will determine the type of data you collect, how you collect it, and how you analyse it. Understanding the different types of research methods available along with their strengths and weaknesses, is thus imperative to make an informed decision.

Understanding different research methods:

There are several research methods available depending on the type of study you are conducting, i.e., whether it is laboratory-based, clinical, epidemiological, or survey based . Some common methodologies include qualitative research, quantitative research, experimental research, survey-based research, and action research. Each method can be opted for and modified, depending on the type of research hypotheses and objectives.

Qualitative vs quantitative research:

When deciding on a research methodology, one of the key factors to consider is whether your research will be qualitative or quantitative. Qualitative research is used to understand people’s experiences, concepts, thoughts, or behaviours . Quantitative research, on the contrary, deals with numbers, graphs, and charts, and is used to test or confirm hypotheses, assumptions, and theories. 

Qualitative research methodology:

Qualitative research is often used to examine issues that are not well understood, and to gather additional insights on these topics. Qualitative research methods include open-ended survey questions, observations of behaviours described through words, and reviews of literature that has explored similar theories and ideas. These methods are used to understand how language is used in real-world situations, identify common themes or overarching ideas, and describe and interpret various texts. Data analysis for qualitative research typically includes discourse analysis, thematic analysis, and textual analysis. 

Quantitative research methodology:

The goal of quantitative research is to test hypotheses, confirm assumptions and theories, and determine cause-and-effect relationships. Quantitative research methods include experiments, close-ended survey questions, and countable and numbered observations. Data analysis for quantitative research relies heavily on statistical methods.

Analysing qualitative vs quantitative data:

The methods used for data analysis also differ for qualitative and quantitative research. As mentioned earlier, quantitative data is generally analysed using statistical methods and does not leave much room for speculation. It is more structured and follows a predetermined plan. In quantitative research, the researcher starts with a hypothesis and uses statistical methods to test it. Contrarily, methods used for qualitative data analysis can identify patterns and themes within the data, rather than provide statistical measures of the data. It is an iterative process, where the researcher goes back and forth trying to gauge the larger implications of the data through different perspectives and revising the analysis if required.

When to use qualitative vs quantitative research:

The choice between qualitative and quantitative research will depend on the gap that the research project aims to address, and specific objectives of the study. If the goal is to establish facts about a subject or topic, quantitative research is an appropriate choice. However, if the goal is to understand people’s experiences or perspectives, qualitative research may be more suitable. 

Conclusion:

In conclusion, an understanding of the different research methods available, their applicability, advantages, and disadvantages is essential for making an informed decision on the best methodology for your project. If you need any additional guidance on which research methodology to opt for, you can head over to Elsevier Author Services (EAS). EAS experts will guide you throughout the process and help you choose the perfect methodology for your research goals.

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Research Methods: What are research methods?

  • What are research methods?
  • Searching specific databases

What are research methods

Research methods are the strategies, processes or techniques utilized in the collection of data or evidence for analysis in order to uncover new information or create better understanding of a topic.

There are different types of research methods which use different tools for data collection.

Types of research

  • Qualitative Research
  • Quantitative Research
  • Mixed Methods Research

Qualitative Research gathers data about lived experiences, emotions or behaviours, and the meanings individuals attach to them. It assists in enabling researchers to gain a better understanding of complex concepts, social interactions or cultural phenomena. This type of research is useful in the exploration of how or why things have occurred, interpreting events and describing actions.

Quantitative Research gathers numerical data which can be ranked, measured or categorised through statistical analysis. It assists with uncovering patterns or relationships, and for making generalisations. This type of research is useful for finding out how many, how much, how often, or to what extent.

Mixed Methods Research integrates both Q ualitative and Quantitative Research . It provides a holistic approach combining and analysing the statistical data with deeper contextualised insights. Using Mixed Methods also enables Triangulation,  or verification, of the data from two or more sources.

Finding Mixed Methods research in the Databases 

“mixed model*” OR “mixed design*” OR “multiple method*” OR multimethod* OR triangulat*

Data collection tools

Techniques or tools used for gathering research data include:

Qualitative Techniques or Tools Quantitative Techniques or Tools
: these can be structured, semi-structured or unstructured in-depth sessions with the researcher and a participant. Surveys or questionnaires: which ask the same questions to large numbers of participants or use Likert scales which measure opinions as numerical data.
: with several participants discussing a particular topic or a set of questions. Researchers can be facilitators or observers. Observation: which can either involve counting the number of times a specific phenomenon occurs, or the coding of observational data in order to translate it into numbers.
: On-site, in-context or role-play options. Document screening: sourcing numerical data from financial reports or counting word occurrences.
: Interrogation of correspondence (letters, diaries, emails etc) or reports. Experiments: testing hypotheses in laboratories, testing cause and effect relationships, through field experiments, or via quasi- or natural experiments.
: Remembrances or memories of experiences told to the researcher.  

SAGE research methods

  • SAGE research methods online This link opens in a new window Research methods tool to help researchers gather full-text resources, design research projects, understand a particular method and write up their research. Includes access to collections of video, business cases and eBooks,

Help and Information

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Here's What You Need to Understand About Research Methodology

Deeptanshu D

Table of Contents

Research methodology involves a systematic and well-structured approach to conducting scholarly or scientific inquiries. Knowing the significance of research methodology and its different components is crucial as it serves as the basis for any study.

Typically, your research topic will start as a broad idea you want to investigate more thoroughly. Once you’ve identified a research problem and created research questions , you must choose the appropriate methodology and frameworks to address those questions effectively.

What is the definition of a research methodology?

Research methodology is the process or the way you intend to execute your study. The methodology section of a research paper outlines how you plan to conduct your study. It covers various steps such as collecting data, statistical analysis, observing participants, and other procedures involved in the research process

The methods section should give a description of the process that will convert your idea into a study. Additionally, the outcomes of your process must provide valid and reliable results resonant with the aims and objectives of your research. This thumb rule holds complete validity, no matter whether your paper has inclinations for qualitative or quantitative usage.

Studying research methods used in related studies can provide helpful insights and direction for your own research. Now easily discover papers related to your topic on SciSpace and utilize our AI research assistant, Copilot , to quickly review the methodologies applied in different papers.

Analyze and understand research methodologies faster with SciSpace Copilot

The need for a good research methodology

While deciding on your approach towards your research, the reason or factors you weighed in choosing a particular problem and formulating a research topic need to be validated and explained. A research methodology helps you do exactly that. Moreover, a good research methodology lets you build your argument to validate your research work performed through various data collection methods, analytical methods, and other essential points.

Just imagine it as a strategy documented to provide an overview of what you intend to do.

While undertaking any research writing or performing the research itself, you may get drifted in not something of much importance. In such a case, a research methodology helps you to get back to your outlined work methodology.

A research methodology helps in keeping you accountable for your work. Additionally, it can help you evaluate whether your work is in sync with your original aims and objectives or not. Besides, a good research methodology enables you to navigate your research process smoothly and swiftly while providing effective planning to achieve your desired results.

What is the basic structure of a research methodology?

Usually, you must ensure to include the following stated aspects while deciding over the basic structure of your research methodology:

1. Your research procedure

Explain what research methods you’re going to use. Whether you intend to proceed with quantitative or qualitative, or a composite of both approaches, you need to state that explicitly. The option among the three depends on your research’s aim, objectives, and scope.

2. Provide the rationality behind your chosen approach

Based on logic and reason, let your readers know why you have chosen said research methodologies. Additionally, you have to build strong arguments supporting why your chosen research method is the best way to achieve the desired outcome.

3. Explain your mechanism

The mechanism encompasses the research methods or instruments you will use to develop your research methodology. It usually refers to your data collection methods. You can use interviews, surveys, physical questionnaires, etc., of the many available mechanisms as research methodology instruments. The data collection method is determined by the type of research and whether the data is quantitative data(includes numerical data) or qualitative data (perception, morale, etc.) Moreover, you need to put logical reasoning behind choosing a particular instrument.

4. Significance of outcomes

The results will be available once you have finished experimenting. However, you should also explain how you plan to use the data to interpret the findings. This section also aids in understanding the problem from within, breaking it down into pieces, and viewing the research problem from various perspectives.

5. Reader’s advice

Anything that you feel must be explained to spread more awareness among readers and focus groups must be included and described in detail. You should not just specify your research methodology on the assumption that a reader is aware of the topic.  

All the relevant information that explains and simplifies your research paper must be included in the methodology section. If you are conducting your research in a non-traditional manner, give a logical justification and list its benefits.

6. Explain your sample space

Include information about the sample and sample space in the methodology section. The term "sample" refers to a smaller set of data that a researcher selects or chooses from a larger group of people or focus groups using a predetermined selection method. Let your readers know how you are going to distinguish between relevant and non-relevant samples. How you figured out those exact numbers to back your research methodology, i.e. the sample spacing of instruments, must be discussed thoroughly.

For example, if you are going to conduct a survey or interview, then by what procedure will you select the interviewees (or sample size in case of surveys), and how exactly will the interview or survey be conducted.

7. Challenges and limitations

This part, which is frequently assumed to be unnecessary, is actually very important. The challenges and limitations that your chosen strategy inherently possesses must be specified while you are conducting different types of research.

The importance of a good research methodology

You must have observed that all research papers, dissertations, or theses carry a chapter entirely dedicated to research methodology. This section helps maintain your credibility as a better interpreter of results rather than a manipulator.

A good research methodology always explains the procedure, data collection methods and techniques, aim, and scope of the research. In a research study, it leads to a well-organized, rationality-based approach, while the paper lacking it is often observed as messy or disorganized.

You should pay special attention to validating your chosen way towards the research methodology. This becomes extremely important in case you select an unconventional or a distinct method of execution.

Curating and developing a strong, effective research methodology can assist you in addressing a variety of situations, such as:

  • When someone tries to duplicate or expand upon your research after few years.
  • If a contradiction or conflict of facts occurs at a later time. This gives you the security you need to deal with these contradictions while still being able to defend your approach.
  • Gaining a tactical approach in getting your research completed in time. Just ensure you are using the right approach while drafting your research methodology, and it can help you achieve your desired outcomes. Additionally, it provides a better explanation and understanding of the research question itself.
  • Documenting the results so that the final outcome of the research stays as you intended it to be while starting.

Instruments you could use while writing a good research methodology

As a researcher, you must choose which tools or data collection methods that fit best in terms of the relevance of your research. This decision has to be wise.

There exists many research equipments or tools that you can use to carry out your research process. These are classified as:

a. Interviews (One-on-One or a Group)

An interview aimed to get your desired research outcomes can be undertaken in many different ways. For example, you can design your interview as structured, semi-structured, or unstructured. What sets them apart is the degree of formality in the questions. On the other hand, in a group interview, your aim should be to collect more opinions and group perceptions from the focus groups on a certain topic rather than looking out for some formal answers.

In surveys, you are in better control if you specifically draft the questions you seek the response for. For example, you may choose to include free-style questions that can be answered descriptively, or you may provide a multiple-choice type response for questions. Besides, you can also opt to choose both ways, deciding what suits your research process and purpose better.

c. Sample Groups

Similar to the group interviews, here, you can select a group of individuals and assign them a topic to discuss or freely express their opinions over that. You can simultaneously note down the answers and later draft them appropriately, deciding on the relevance of every response.

d. Observations

If your research domain is humanities or sociology, observations are the best-proven method to draw your research methodology. Of course, you can always include studying the spontaneous response of the participants towards a situation or conducting the same but in a more structured manner. A structured observation means putting the participants in a situation at a previously decided time and then studying their responses.

Of all the tools described above, it is you who should wisely choose the instruments and decide what’s the best fit for your research. You must not restrict yourself from multiple methods or a combination of a few instruments if appropriate in drafting a good research methodology.

Types of research methodology

A research methodology exists in various forms. Depending upon their approach, whether centered around words, numbers, or both, methodologies are distinguished as qualitative, quantitative, or an amalgamation of both.

1. Qualitative research methodology

When a research methodology primarily focuses on words and textual data, then it is generally referred to as qualitative research methodology. This type is usually preferred among researchers when the aim and scope of the research are mainly theoretical and explanatory.

The instruments used are observations, interviews, and sample groups. You can use this methodology if you are trying to study human behavior or response in some situations. Generally, qualitative research methodology is widely used in sociology, psychology, and other related domains.

2. Quantitative research methodology

If your research is majorly centered on data, figures, and stats, then analyzing these numerical data is often referred to as quantitative research methodology. You can use quantitative research methodology if your research requires you to validate or justify the obtained results.

In quantitative methods, surveys, tests, experiments, and evaluations of current databases can be advantageously used as instruments If your research involves testing some hypothesis, then use this methodology.

3. Amalgam methodology

As the name suggests, the amalgam methodology uses both quantitative and qualitative approaches. This methodology is used when a part of the research requires you to verify the facts and figures, whereas the other part demands you to discover the theoretical and explanatory nature of the research question.

The instruments for the amalgam methodology require you to conduct interviews and surveys, including tests and experiments. The outcome of this methodology can be insightful and valuable as it provides precise test results in line with theoretical explanations and reasoning.

The amalgam method, makes your work both factual and rational at the same time.

Final words: How to decide which is the best research methodology?

If you have kept your sincerity and awareness intact with the aims and scope of research well enough, you must have got an idea of which research methodology suits your work best.

Before deciding which research methodology answers your research question, you must invest significant time in reading and doing your homework for that. Taking references that yield relevant results should be your first approach to establishing a research methodology.

Moreover, you should never refrain from exploring other options. Before setting your work in stone, you must try all the available options as it explains why the choice of research methodology that you finally make is more appropriate than the other available options.

You should always go for a quantitative research methodology if your research requires gathering large amounts of data, figures, and statistics. This research methodology will provide you with results if your research paper involves the validation of some hypothesis.

Whereas, if  you are looking for more explanations, reasons, opinions, and public perceptions around a theory, you must use qualitative research methodology.The choice of an appropriate research methodology ultimately depends on what you want to achieve through your research.

Frequently Asked Questions (FAQs) about Research Methodology

1. how to write a research methodology.

You can always provide a separate section for research methodology where you should specify details about the methods and instruments used during the research, discussions on result analysis, including insights into the background information, and conveying the research limitations.

2. What are the types of research methodology?

There generally exists four types of research methodology i.e.

  • Observation
  • Experimental
  • Derivational

3. What is the true meaning of research methodology?

The set of techniques or procedures followed to discover and analyze the information gathered to validate or justify a research outcome is generally called Research Methodology.

4. Where lies the importance of research methodology?

Your research methodology directly reflects the validity of your research outcomes and how well-informed your research work is. Moreover, it can help future researchers cite or refer to your research if they plan to use a similar research methodology.

what to include in research methods

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Home » Research Methodology – Types, Examples and writing Guide

Research Methodology – Types, Examples and writing Guide

Table of Contents

Research Methodology

Research Methodology

Definition:

Research Methodology refers to the systematic and scientific approach used to conduct research, investigate problems, and gather data and information for a specific purpose. It involves the techniques and procedures used to identify, collect , analyze , and interpret data to answer research questions or solve research problems . Moreover, They are philosophical and theoretical frameworks that guide the research process.

Structure of Research Methodology

Research methodology formats can vary depending on the specific requirements of the research project, but the following is a basic example of a structure for a research methodology section:

I. Introduction

  • Provide an overview of the research problem and the need for a research methodology section
  • Outline the main research questions and objectives

II. Research Design

  • Explain the research design chosen and why it is appropriate for the research question(s) and objectives
  • Discuss any alternative research designs considered and why they were not chosen
  • Describe the research setting and participants (if applicable)

III. Data Collection Methods

  • Describe the methods used to collect data (e.g., surveys, interviews, observations)
  • Explain how the data collection methods were chosen and why they are appropriate for the research question(s) and objectives
  • Detail any procedures or instruments used for data collection

IV. Data Analysis Methods

  • Describe the methods used to analyze the data (e.g., statistical analysis, content analysis )
  • Explain how the data analysis methods were chosen and why they are appropriate for the research question(s) and objectives
  • Detail any procedures or software used for data analysis

V. Ethical Considerations

  • Discuss any ethical issues that may arise from the research and how they were addressed
  • Explain how informed consent was obtained (if applicable)
  • Detail any measures taken to ensure confidentiality and anonymity

VI. Limitations

  • Identify any potential limitations of the research methodology and how they may impact the results and conclusions

VII. Conclusion

  • Summarize the key aspects of the research methodology section
  • Explain how the research methodology addresses the research question(s) and objectives

Research Methodology Types

Types of Research Methodology are as follows:

Quantitative Research Methodology

This is a research methodology that involves the collection and analysis of numerical data using statistical methods. This type of research is often used to study cause-and-effect relationships and to make predictions.

Qualitative Research Methodology

This is a research methodology that involves the collection and analysis of non-numerical data such as words, images, and observations. This type of research is often used to explore complex phenomena, to gain an in-depth understanding of a particular topic, and to generate hypotheses.

Mixed-Methods Research Methodology

This is a research methodology that combines elements of both quantitative and qualitative research. This approach can be particularly useful for studies that aim to explore complex phenomena and to provide a more comprehensive understanding of a particular topic.

Case Study Research Methodology

This is a research methodology that involves in-depth examination of a single case or a small number of cases. Case studies are often used in psychology, sociology, and anthropology to gain a detailed understanding of a particular individual or group.

Action Research Methodology

This is a research methodology that involves a collaborative process between researchers and practitioners to identify and solve real-world problems. Action research is often used in education, healthcare, and social work.

Experimental Research Methodology

This is a research methodology that involves the manipulation of one or more independent variables to observe their effects on a dependent variable. Experimental research is often used to study cause-and-effect relationships and to make predictions.

Survey Research Methodology

This is a research methodology that involves the collection of data from a sample of individuals using questionnaires or interviews. Survey research is often used to study attitudes, opinions, and behaviors.

Grounded Theory Research Methodology

This is a research methodology that involves the development of theories based on the data collected during the research process. Grounded theory is often used in sociology and anthropology to generate theories about social phenomena.

Research Methodology Example

An Example of Research Methodology could be the following:

Research Methodology for Investigating the Effectiveness of Cognitive Behavioral Therapy in Reducing Symptoms of Depression in Adults

Introduction:

The aim of this research is to investigate the effectiveness of cognitive-behavioral therapy (CBT) in reducing symptoms of depression in adults. To achieve this objective, a randomized controlled trial (RCT) will be conducted using a mixed-methods approach.

Research Design:

The study will follow a pre-test and post-test design with two groups: an experimental group receiving CBT and a control group receiving no intervention. The study will also include a qualitative component, in which semi-structured interviews will be conducted with a subset of participants to explore their experiences of receiving CBT.

Participants:

Participants will be recruited from community mental health clinics in the local area. The sample will consist of 100 adults aged 18-65 years old who meet the diagnostic criteria for major depressive disorder. Participants will be randomly assigned to either the experimental group or the control group.

Intervention :

The experimental group will receive 12 weekly sessions of CBT, each lasting 60 minutes. The intervention will be delivered by licensed mental health professionals who have been trained in CBT. The control group will receive no intervention during the study period.

Data Collection:

Quantitative data will be collected through the use of standardized measures such as the Beck Depression Inventory-II (BDI-II) and the Generalized Anxiety Disorder-7 (GAD-7). Data will be collected at baseline, immediately after the intervention, and at a 3-month follow-up. Qualitative data will be collected through semi-structured interviews with a subset of participants from the experimental group. The interviews will be conducted at the end of the intervention period, and will explore participants’ experiences of receiving CBT.

Data Analysis:

Quantitative data will be analyzed using descriptive statistics, t-tests, and mixed-model analyses of variance (ANOVA) to assess the effectiveness of the intervention. Qualitative data will be analyzed using thematic analysis to identify common themes and patterns in participants’ experiences of receiving CBT.

Ethical Considerations:

This study will comply with ethical guidelines for research involving human subjects. Participants will provide informed consent before participating in the study, and their privacy and confidentiality will be protected throughout the study. Any adverse events or reactions will be reported and managed appropriately.

Data Management:

All data collected will be kept confidential and stored securely using password-protected databases. Identifying information will be removed from qualitative data transcripts to ensure participants’ anonymity.

Limitations:

One potential limitation of this study is that it only focuses on one type of psychotherapy, CBT, and may not generalize to other types of therapy or interventions. Another limitation is that the study will only include participants from community mental health clinics, which may not be representative of the general population.

Conclusion:

This research aims to investigate the effectiveness of CBT in reducing symptoms of depression in adults. By using a randomized controlled trial and a mixed-methods approach, the study will provide valuable insights into the mechanisms underlying the relationship between CBT and depression. The results of this study will have important implications for the development of effective treatments for depression in clinical settings.

How to Write Research Methodology

Writing a research methodology involves explaining the methods and techniques you used to conduct research, collect data, and analyze results. It’s an essential section of any research paper or thesis, as it helps readers understand the validity and reliability of your findings. Here are the steps to write a research methodology:

  • Start by explaining your research question: Begin the methodology section by restating your research question and explaining why it’s important. This helps readers understand the purpose of your research and the rationale behind your methods.
  • Describe your research design: Explain the overall approach you used to conduct research. This could be a qualitative or quantitative research design, experimental or non-experimental, case study or survey, etc. Discuss the advantages and limitations of the chosen design.
  • Discuss your sample: Describe the participants or subjects you included in your study. Include details such as their demographics, sampling method, sample size, and any exclusion criteria used.
  • Describe your data collection methods : Explain how you collected data from your participants. This could include surveys, interviews, observations, questionnaires, or experiments. Include details on how you obtained informed consent, how you administered the tools, and how you minimized the risk of bias.
  • Explain your data analysis techniques: Describe the methods you used to analyze the data you collected. This could include statistical analysis, content analysis, thematic analysis, or discourse analysis. Explain how you dealt with missing data, outliers, and any other issues that arose during the analysis.
  • Discuss the validity and reliability of your research : Explain how you ensured the validity and reliability of your study. This could include measures such as triangulation, member checking, peer review, or inter-coder reliability.
  • Acknowledge any limitations of your research: Discuss any limitations of your study, including any potential threats to validity or generalizability. This helps readers understand the scope of your findings and how they might apply to other contexts.
  • Provide a summary: End the methodology section by summarizing the methods and techniques you used to conduct your research. This provides a clear overview of your research methodology and helps readers understand the process you followed to arrive at your findings.

When to Write Research Methodology

Research methodology is typically written after the research proposal has been approved and before the actual research is conducted. It should be written prior to data collection and analysis, as it provides a clear roadmap for the research project.

The research methodology is an important section of any research paper or thesis, as it describes the methods and procedures that will be used to conduct the research. It should include details about the research design, data collection methods, data analysis techniques, and any ethical considerations.

The methodology should be written in a clear and concise manner, and it should be based on established research practices and standards. It is important to provide enough detail so that the reader can understand how the research was conducted and evaluate the validity of the results.

Applications of Research Methodology

Here are some of the applications of research methodology:

  • To identify the research problem: Research methodology is used to identify the research problem, which is the first step in conducting any research.
  • To design the research: Research methodology helps in designing the research by selecting the appropriate research method, research design, and sampling technique.
  • To collect data: Research methodology provides a systematic approach to collect data from primary and secondary sources.
  • To analyze data: Research methodology helps in analyzing the collected data using various statistical and non-statistical techniques.
  • To test hypotheses: Research methodology provides a framework for testing hypotheses and drawing conclusions based on the analysis of data.
  • To generalize findings: Research methodology helps in generalizing the findings of the research to the target population.
  • To develop theories : Research methodology is used to develop new theories and modify existing theories based on the findings of the research.
  • To evaluate programs and policies : Research methodology is used to evaluate the effectiveness of programs and policies by collecting data and analyzing it.
  • To improve decision-making: Research methodology helps in making informed decisions by providing reliable and valid data.

Purpose of Research Methodology

Research methodology serves several important purposes, including:

  • To guide the research process: Research methodology provides a systematic framework for conducting research. It helps researchers to plan their research, define their research questions, and select appropriate methods and techniques for collecting and analyzing data.
  • To ensure research quality: Research methodology helps researchers to ensure that their research is rigorous, reliable, and valid. It provides guidelines for minimizing bias and error in data collection and analysis, and for ensuring that research findings are accurate and trustworthy.
  • To replicate research: Research methodology provides a clear and detailed account of the research process, making it possible for other researchers to replicate the study and verify its findings.
  • To advance knowledge: Research methodology enables researchers to generate new knowledge and to contribute to the body of knowledge in their field. It provides a means for testing hypotheses, exploring new ideas, and discovering new insights.
  • To inform decision-making: Research methodology provides evidence-based information that can inform policy and decision-making in a variety of fields, including medicine, public health, education, and business.

Advantages of Research Methodology

Research methodology has several advantages that make it a valuable tool for conducting research in various fields. Here are some of the key advantages of research methodology:

  • Systematic and structured approach : Research methodology provides a systematic and structured approach to conducting research, which ensures that the research is conducted in a rigorous and comprehensive manner.
  • Objectivity : Research methodology aims to ensure objectivity in the research process, which means that the research findings are based on evidence and not influenced by personal bias or subjective opinions.
  • Replicability : Research methodology ensures that research can be replicated by other researchers, which is essential for validating research findings and ensuring their accuracy.
  • Reliability : Research methodology aims to ensure that the research findings are reliable, which means that they are consistent and can be depended upon.
  • Validity : Research methodology ensures that the research findings are valid, which means that they accurately reflect the research question or hypothesis being tested.
  • Efficiency : Research methodology provides a structured and efficient way of conducting research, which helps to save time and resources.
  • Flexibility : Research methodology allows researchers to choose the most appropriate research methods and techniques based on the research question, data availability, and other relevant factors.
  • Scope for innovation: Research methodology provides scope for innovation and creativity in designing research studies and developing new research techniques.

Research Methodology Vs Research Methods

Research MethodologyResearch Methods
Research methodology refers to the philosophical and theoretical frameworks that guide the research process. refer to the techniques and procedures used to collect and analyze data.
It is concerned with the underlying principles and assumptions of research.It is concerned with the practical aspects of research.
It provides a rationale for why certain research methods are used.It determines the specific steps that will be taken to conduct research.
It is broader in scope and involves understanding the overall approach to research.It is narrower in scope and focuses on specific techniques and tools used in research.
It is concerned with identifying research questions, defining the research problem, and formulating hypotheses.It is concerned with collecting data, analyzing data, and interpreting results.
It is concerned with the validity and reliability of research.It is concerned with the accuracy and precision of data.
It is concerned with the ethical considerations of research.It is concerned with the practical considerations of research.

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Home » What are Research Methods?

What are Research Methods?

Imagine you’re starting on a journey of discovery, and research methods are your compass, map, and tools. These methods guide us in exploring the vast landscape of knowledge, ensuring our journey is structured, reliable, and fruitful.

Table of Contents

Research Methods

Research Methods

Research Methods are systematic strategies, steps, and tools that researchers use to gather, analyze, and interpret data about a particular topic. It’s like cooking a new recipe; you need the right ingredients (data), a good method (research design), and the proper tools (instruments like surveys or experiments) to create a delightful dish (knowledge).

Types of Research Methods

Qualitative research.

This is akin to painting a portrait. It focuses on understanding concepts, thoughts, and experiences through detailed, descriptive data. Imagine sitting down with someone and listening to their story to grasp the depth of their experiences. Tools for this might include interviews , observations , and textual analysis .

Quantitative Research

Now, imagine yourself counting stars in the sky. This method deals with numbers and statistical analysis. It seeks to quantify the problem by generating numerical data or data that can be transformed into usable statistics. Surveys with multiple-choice questions or experiments where you measure and compare are typical tools here.

Mixed Methods

Sometimes, a single perspective isn’t enough. Mixed methods blend the colors of both qualitative and quantitative research, offering a more comprehensive picture. It’s like using both a microscope and a telescope; you get the detail and the big picture.

Steps in the Research Process

Identifying the Problem : Every journey begins with recognizing where you want to go. What’s the question you’re burning to answer? This step involves defining the scope and purpose of your research.

Literature Review : Before you set out, you need to map the terrain by exploring what others have discovered before you. This involves reading and summarizing existing research on your topic.

Designing the Study : Here’s where you plan your route. Will you conduct interviews? Send out surveys? Observe behaviors? This step involves deciding on your research method, participants, and tools.

Collecting Data : Time to hit the road and gather your data. This is the hands-on part of your research, where you implement your chosen methods to collect information.

Analyzing Data : With your treasures in hand, you now sift through your findings, looking for patterns, themes, or statistical relationships. This step often involves software for qualitative or quantitative analysis.

Interpreting Results : What have you discovered? This stage is about making sense of your data, connecting the dots, and understanding what your findings mean in the context of your research question.

Reporting and Sharing Findings : The final step is to share your journey’s story. This could be a research paper, a presentation, or any format that communicates your discoveries to others.

Ethics in Research

Imagine you’re a guest in someone’s home; you must be respectful and considerate. Similarly, ethical considerations are paramount in research. This means ensuring confidentiality, obtaining informed consent, and treating all subjects (people, animals, the environment) with respect and dignity.

Research methods are the compass, map, and tools that guide us through the terrain of knowledge. They enable us to ask important questions, systematically gather and analyze data, and contribute valuable insights to our understanding of the world. As you start on your research journey, embrace the adventure, respect the process, and look forward to the discoveries that await you.

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Basics of Methodology

Research is a process of inquiry that is carried out in a pondered, organized, and strategic manner. In order to obtain high quality results, it is important to understand methodology.

Research methodology refers to how your project will be designed, what you will observe or measure, and how you will collect and analyze data. The methods you choose must be appropriate for your field and for the specific research questions you are setting out to answer.

A strong understanding of methodology will help you:

  • apply appropriate research techniques
  • design effective data collection instruments
  • analyze and interpret your data
  • develop well-founded conclusions

Below, you will find resources that mostly cover general aspects of research methodology. In the left column, you will find resources that specifically cover qualitative, quantitative, and mixed methods research.

General Works on Methodology

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Qualitative Research

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Quantitative Research

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Mixed Methods Research

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What is research methodology?

what to include in research methods

The basics of research methodology

Why do you need a research methodology, what needs to be included, why do you need to document your research method, what are the different types of research instruments, qualitative / quantitative / mixed research methodologies, how do you choose the best research methodology for you, frequently asked questions about research methodology, related articles.

When you’re working on your first piece of academic research, there are many different things to focus on, and it can be overwhelming to stay on top of everything. This is especially true of budding or inexperienced researchers.

If you’ve never put together a research proposal before or find yourself in a position where you need to explain your research methodology decisions, there are a few things you need to be aware of.

Once you understand the ins and outs, handling academic research in the future will be less intimidating. We break down the basics below:

A research methodology encompasses the way in which you intend to carry out your research. This includes how you plan to tackle things like collection methods, statistical analysis, participant observations, and more.

You can think of your research methodology as being a formula. One part will be how you plan on putting your research into practice, and another will be why you feel this is the best way to approach it. Your research methodology is ultimately a methodological and systematic plan to resolve your research problem.

In short, you are explaining how you will take your idea and turn it into a study, which in turn will produce valid and reliable results that are in accordance with the aims and objectives of your research. This is true whether your paper plans to make use of qualitative methods or quantitative methods.

The purpose of a research methodology is to explain the reasoning behind your approach to your research - you'll need to support your collection methods, methods of analysis, and other key points of your work.

Think of it like writing a plan or an outline for you what you intend to do.

When carrying out research, it can be easy to go off-track or depart from your standard methodology.

Tip: Having a methodology keeps you accountable and on track with your original aims and objectives, and gives you a suitable and sound plan to keep your project manageable, smooth, and effective.

With all that said, how do you write out your standard approach to a research methodology?

As a general plan, your methodology should include the following information:

  • Your research method.  You need to state whether you plan to use quantitative analysis, qualitative analysis, or mixed-method research methods. This will often be determined by what you hope to achieve with your research.
  • Explain your reasoning. Why are you taking this methodological approach? Why is this particular methodology the best way to answer your research problem and achieve your objectives?
  • Explain your instruments.  This will mainly be about your collection methods. There are varying instruments to use such as interviews, physical surveys, questionnaires, for example. Your methodology will need to detail your reasoning in choosing a particular instrument for your research.
  • What will you do with your results?  How are you going to analyze the data once you have gathered it?
  • Advise your reader.  If there is anything in your research methodology that your reader might be unfamiliar with, you should explain it in more detail. For example, you should give any background information to your methods that might be relevant or provide your reasoning if you are conducting your research in a non-standard way.
  • How will your sampling process go?  What will your sampling procedure be and why? For example, if you will collect data by carrying out semi-structured or unstructured interviews, how will you choose your interviewees and how will you conduct the interviews themselves?
  • Any practical limitations?  You should discuss any limitations you foresee being an issue when you’re carrying out your research.

In any dissertation, thesis, or academic journal, you will always find a chapter dedicated to explaining the research methodology of the person who carried out the study, also referred to as the methodology section of the work.

A good research methodology will explain what you are going to do and why, while a poor methodology will lead to a messy or disorganized approach.

You should also be able to justify in this section your reasoning for why you intend to carry out your research in a particular way, especially if it might be a particularly unique method.

Having a sound methodology in place can also help you with the following:

  • When another researcher at a later date wishes to try and replicate your research, they will need your explanations and guidelines.
  • In the event that you receive any criticism or questioning on the research you carried out at a later point, you will be able to refer back to it and succinctly explain the how and why of your approach.
  • It provides you with a plan to follow throughout your research. When you are drafting your methodology approach, you need to be sure that the method you are using is the right one for your goal. This will help you with both explaining and understanding your method.
  • It affords you the opportunity to document from the outset what you intend to achieve with your research, from start to finish.

A research instrument is a tool you will use to help you collect, measure and analyze the data you use as part of your research.

The choice of research instrument will usually be yours to make as the researcher and will be whichever best suits your methodology.

There are many different research instruments you can use in collecting data for your research.

Generally, they can be grouped as follows:

  • Interviews (either as a group or one-on-one). You can carry out interviews in many different ways. For example, your interview can be structured, semi-structured, or unstructured. The difference between them is how formal the set of questions is that is asked of the interviewee. In a group interview, you may choose to ask the interviewees to give you their opinions or perceptions on certain topics.
  • Surveys (online or in-person). In survey research, you are posing questions in which you ask for a response from the person taking the survey. You may wish to have either free-answer questions such as essay-style questions, or you may wish to use closed questions such as multiple choice. You may even wish to make the survey a mixture of both.
  • Focus Groups.  Similar to the group interview above, you may wish to ask a focus group to discuss a particular topic or opinion while you make a note of the answers given.
  • Observations.  This is a good research instrument to use if you are looking into human behaviors. Different ways of researching this include studying the spontaneous behavior of participants in their everyday life, or something more structured. A structured observation is research conducted at a set time and place where researchers observe behavior as planned and agreed upon with participants.

These are the most common ways of carrying out research, but it is really dependent on your needs as a researcher and what approach you think is best to take.

It is also possible to combine a number of research instruments if this is necessary and appropriate in answering your research problem.

There are three different types of methodologies, and they are distinguished by whether they focus on words, numbers, or both.

Data typeWhat is it?Methodology

Quantitative

This methodology focuses more on measuring and testing numerical data. What is the aim of quantitative research?

When using this form of research, your objective will usually be to confirm something.

Surveys, tests, existing databases.

For example, you may use this type of methodology if you are looking to test a set of hypotheses.

Qualitative

Qualitative research is a process of collecting and analyzing both words and textual data.

This form of research methodology is sometimes used where the aim and objective of the research are exploratory.

Observations, interviews, focus groups.

Exploratory research might be used where you are trying to understand human actions i.e. for a study in the sociology or psychology field.

Mixed-method

A mixed-method approach combines both of the above approaches.

The quantitative approach will provide you with some definitive facts and figures, whereas the qualitative methodology will provide your research with an interesting human aspect.

Where you can use a mixed method of research, this can produce some incredibly interesting results. This is due to testing in a way that provides data that is both proven to be exact while also being exploratory at the same time.

➡️ Want to learn more about the differences between qualitative and quantitative research, and how to use both methods? Check out our guide for that!

If you've done your due diligence, you'll have an idea of which methodology approach is best suited to your research.

It’s likely that you will have carried out considerable reading and homework before you reach this point and you may have taken inspiration from other similar studies that have yielded good results.

Still, it is important to consider different options before setting your research in stone. Exploring different options available will help you to explain why the choice you ultimately make is preferable to other methods.

If proving your research problem requires you to gather large volumes of numerical data to test hypotheses, a quantitative research method is likely to provide you with the most usable results.

If instead you’re looking to try and learn more about people, and their perception of events, your methodology is more exploratory in nature and would therefore probably be better served using a qualitative research methodology.

It helps to always bring things back to the question: what do I want to achieve with my research?

Once you have conducted your research, you need to analyze it. Here are some helpful guides for qualitative data analysis:

➡️  How to do a content analysis

➡️  How to do a thematic analysis

➡️  How to do a rhetorical analysis

Research methodology refers to the techniques used to find and analyze information for a study, ensuring that the results are valid, reliable and that they address the research objective.

Data can typically be organized into four different categories or methods: observational, experimental, simulation, and derived.

Writing a methodology section is a process of introducing your methods and instruments, discussing your analysis, providing more background information, addressing your research limitations, and more.

Your research methodology section will need a clear research question and proposed research approach. You'll need to add a background, introduce your research question, write your methodology and add the works you cited during your data collecting phase.

The research methodology section of your study will indicate how valid your findings are and how well-informed your paper is. It also assists future researchers planning to use the same methodology, who want to cite your study or replicate it.

Rhetorical analysis illustration

what to include in research methods

What is Research Methodology? Definition, Types, and Examples

what to include in research methods

Research methodology 1,2 is a structured and scientific approach used to collect, analyze, and interpret quantitative or qualitative data to answer research questions or test hypotheses. A research methodology is like a plan for carrying out research and helps keep researchers on track by limiting the scope of the research. Several aspects must be considered before selecting an appropriate research methodology, such as research limitations and ethical concerns that may affect your research.

The research methodology section in a scientific paper describes the different methodological choices made, such as the data collection and analysis methods, and why these choices were selected. The reasons should explain why the methods chosen are the most appropriate to answer the research question. A good research methodology also helps ensure the reliability and validity of the research findings. There are three types of research methodology—quantitative, qualitative, and mixed-method, which can be chosen based on the research objectives.

What is research methodology ?

A research methodology describes the techniques and procedures used to identify and analyze information regarding a specific research topic. It is a process by which researchers design their study so that they can achieve their objectives using the selected research instruments. It includes all the important aspects of research, including research design, data collection methods, data analysis methods, and the overall framework within which the research is conducted. While these points can help you understand what is research methodology, you also need to know why it is important to pick the right methodology.

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Having a good research methodology in place has the following advantages: 3

  • Helps other researchers who may want to replicate your research; the explanations will be of benefit to them.
  • You can easily answer any questions about your research if they arise at a later stage.
  • A research methodology provides a framework and guidelines for researchers to clearly define research questions, hypotheses, and objectives.
  • It helps researchers identify the most appropriate research design, sampling technique, and data collection and analysis methods.
  • A sound research methodology helps researchers ensure that their findings are valid and reliable and free from biases and errors.
  • It also helps ensure that ethical guidelines are followed while conducting research.
  • A good research methodology helps researchers in planning their research efficiently, by ensuring optimum usage of their time and resources.

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Types of research methodology.

There are three types of research methodology based on the type of research and the data required. 1

  • Quantitative research methodology focuses on measuring and testing numerical data. This approach is good for reaching a large number of people in a short amount of time. This type of research helps in testing the causal relationships between variables, making predictions, and generalizing results to wider populations.
  • Qualitative research methodology examines the opinions, behaviors, and experiences of people. It collects and analyzes words and textual data. This research methodology requires fewer participants but is still more time consuming because the time spent per participant is quite large. This method is used in exploratory research where the research problem being investigated is not clearly defined.
  • Mixed-method research methodology uses the characteristics of both quantitative and qualitative research methodologies in the same study. This method allows researchers to validate their findings, verify if the results observed using both methods are complementary, and explain any unexpected results obtained from one method by using the other method.

What are the types of sampling designs in research methodology?

Sampling 4 is an important part of a research methodology and involves selecting a representative sample of the population to conduct the study, making statistical inferences about them, and estimating the characteristics of the whole population based on these inferences. There are two types of sampling designs in research methodology—probability and nonprobability.

  • Probability sampling

In this type of sampling design, a sample is chosen from a larger population using some form of random selection, that is, every member of the population has an equal chance of being selected. The different types of probability sampling are:

  • Systematic —sample members are chosen at regular intervals. It requires selecting a starting point for the sample and sample size determination that can be repeated at regular intervals. This type of sampling method has a predefined range; hence, it is the least time consuming.
  • Stratified —researchers divide the population into smaller groups that don’t overlap but represent the entire population. While sampling, these groups can be organized, and then a sample can be drawn from each group separately.
  • Cluster —the population is divided into clusters based on demographic parameters like age, sex, location, etc.
  • Convenience —selects participants who are most easily accessible to researchers due to geographical proximity, availability at a particular time, etc.
  • Purposive —participants are selected at the researcher’s discretion. Researchers consider the purpose of the study and the understanding of the target audience.
  • Snowball —already selected participants use their social networks to refer the researcher to other potential participants.
  • Quota —while designing the study, the researchers decide how many people with which characteristics to include as participants. The characteristics help in choosing people most likely to provide insights into the subject.

What are data collection methods?

During research, data are collected using various methods depending on the research methodology being followed and the research methods being undertaken. Both qualitative and quantitative research have different data collection methods, as listed below.

Qualitative research 5

  • One-on-one interviews: Helps the interviewers understand a respondent’s subjective opinion and experience pertaining to a specific topic or event
  • Document study/literature review/record keeping: Researchers’ review of already existing written materials such as archives, annual reports, research articles, guidelines, policy documents, etc.
  • Focus groups: Constructive discussions that usually include a small sample of about 6-10 people and a moderator, to understand the participants’ opinion on a given topic.
  • Qualitative observation : Researchers collect data using their five senses (sight, smell, touch, taste, and hearing).

Quantitative research 6

  • Sampling: The most common type is probability sampling.
  • Interviews: Commonly telephonic or done in-person.
  • Observations: Structured observations are most commonly used in quantitative research. In this method, researchers make observations about specific behaviors of individuals in a structured setting.
  • Document review: Reviewing existing research or documents to collect evidence for supporting the research.
  • Surveys and questionnaires. Surveys can be administered both online and offline depending on the requirement and sample size.

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What are data analysis methods.

The data collected using the various methods for qualitative and quantitative research need to be analyzed to generate meaningful conclusions. These data analysis methods 7 also differ between quantitative and qualitative research.

Quantitative research involves a deductive method for data analysis where hypotheses are developed at the beginning of the research and precise measurement is required. The methods include statistical analysis applications to analyze numerical data and are grouped into two categories—descriptive and inferential.

Descriptive analysis is used to describe the basic features of different types of data to present it in a way that ensures the patterns become meaningful. The different types of descriptive analysis methods are:

  • Measures of frequency (count, percent, frequency)
  • Measures of central tendency (mean, median, mode)
  • Measures of dispersion or variation (range, variance, standard deviation)
  • Measure of position (percentile ranks, quartile ranks)

Inferential analysis is used to make predictions about a larger population based on the analysis of the data collected from a smaller population. This analysis is used to study the relationships between different variables. Some commonly used inferential data analysis methods are:

  • Correlation: To understand the relationship between two or more variables.
  • Cross-tabulation: Analyze the relationship between multiple variables.
  • Regression analysis: Study the impact of independent variables on the dependent variable.
  • Frequency tables: To understand the frequency of data.
  • Analysis of variance: To test the degree to which two or more variables differ in an experiment.

Qualitative research involves an inductive method for data analysis where hypotheses are developed after data collection. The methods include:

  • Content analysis: For analyzing documented information from text and images by determining the presence of certain words or concepts in texts.
  • Narrative analysis: For analyzing content obtained from sources such as interviews, field observations, and surveys. The stories and opinions shared by people are used to answer research questions.
  • Discourse analysis: For analyzing interactions with people considering the social context, that is, the lifestyle and environment, under which the interaction occurs.
  • Grounded theory: Involves hypothesis creation by data collection and analysis to explain why a phenomenon occurred.
  • Thematic analysis: To identify important themes or patterns in data and use these to address an issue.

How to choose a research methodology?

Here are some important factors to consider when choosing a research methodology: 8

  • Research objectives, aims, and questions —these would help structure the research design.
  • Review existing literature to identify any gaps in knowledge.
  • Check the statistical requirements —if data-driven or statistical results are needed then quantitative research is the best. If the research questions can be answered based on people’s opinions and perceptions, then qualitative research is most suitable.
  • Sample size —sample size can often determine the feasibility of a research methodology. For a large sample, less effort- and time-intensive methods are appropriate.
  • Constraints —constraints of time, geography, and resources can help define the appropriate methodology.

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How to write a research methodology .

A research methodology should include the following components: 3,9

  • Research design —should be selected based on the research question and the data required. Common research designs include experimental, quasi-experimental, correlational, descriptive, and exploratory.
  • Research method —this can be quantitative, qualitative, or mixed-method.
  • Reason for selecting a specific methodology —explain why this methodology is the most suitable to answer your research problem.
  • Research instruments —explain the research instruments you plan to use, mainly referring to the data collection methods such as interviews, surveys, etc. Here as well, a reason should be mentioned for selecting the particular instrument.
  • Sampling —this involves selecting a representative subset of the population being studied.
  • Data collection —involves gathering data using several data collection methods, such as surveys, interviews, etc.
  • Data analysis —describe the data analysis methods you will use once you’ve collected the data.
  • Research limitations —mention any limitations you foresee while conducting your research.
  • Validity and reliability —validity helps identify the accuracy and truthfulness of the findings; reliability refers to the consistency and stability of the results over time and across different conditions.
  • Ethical considerations —research should be conducted ethically. The considerations include obtaining consent from participants, maintaining confidentiality, and addressing conflicts of interest.

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Frequently Asked Questions

Q1. What are the key components of research methodology?

A1. A good research methodology has the following key components:

  • Research design
  • Data collection procedures
  • Data analysis methods
  • Ethical considerations

Q2. Why is ethical consideration important in research methodology?

A2. Ethical consideration is important in research methodology to ensure the readers of the reliability and validity of the study. Researchers must clearly mention the ethical norms and standards followed during the conduct of the research and also mention if the research has been cleared by any institutional board. The following 10 points are the important principles related to ethical considerations: 10

  • Participants should not be subjected to harm.
  • Respect for the dignity of participants should be prioritized.
  • Full consent should be obtained from participants before the study.
  • Participants’ privacy should be ensured.
  • Confidentiality of the research data should be ensured.
  • Anonymity of individuals and organizations participating in the research should be maintained.
  • The aims and objectives of the research should not be exaggerated.
  • Affiliations, sources of funding, and any possible conflicts of interest should be declared.
  • Communication in relation to the research should be honest and transparent.
  • Misleading information and biased representation of primary data findings should be avoided.

what to include in research methods

Q3. What is the difference between methodology and method?

A3. Research methodology is different from a research method, although both terms are often confused. Research methods are the tools used to gather data, while the research methodology provides a framework for how research is planned, conducted, and analyzed. The latter guides researchers in making decisions about the most appropriate methods for their research. Research methods refer to the specific techniques, procedures, and tools used by researchers to collect, analyze, and interpret data, for instance surveys, questionnaires, interviews, etc.

Research methodology is, thus, an integral part of a research study. It helps ensure that you stay on track to meet your research objectives and answer your research questions using the most appropriate data collection and analysis tools based on your research design.

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  • Research methodologies. Pfeiffer Library website. Accessed August 15, 2023. https://library.tiffin.edu/researchmethodologies/whatareresearchmethodologies
  • Types of research methodology. Eduvoice website. Accessed August 16, 2023. https://eduvoice.in/types-research-methodology/
  • The basics of research methodology: A key to quality research. Voxco. Accessed August 16, 2023. https://www.voxco.com/blog/what-is-research-methodology/
  • Sampling methods: Types with examples. QuestionPro website. Accessed August 16, 2023. https://www.questionpro.com/blog/types-of-sampling-for-social-research/
  • What is qualitative research? Methods, types, approaches, examples. Researcher.Life blog. Accessed August 15, 2023. https://researcher.life/blog/article/what-is-qualitative-research-methods-types-examples/
  • What is quantitative research? Definition, methods, types, and examples. Researcher.Life blog. Accessed August 15, 2023. https://researcher.life/blog/article/what-is-quantitative-research-types-and-examples/
  • Data analysis in research: Types & methods. QuestionPro website. Accessed August 16, 2023. https://www.questionpro.com/blog/data-analysis-in-research/#Data_analysis_in_qualitative_research
  • Factors to consider while choosing the right research methodology. PhD Monster website. Accessed August 17, 2023. https://www.phdmonster.com/factors-to-consider-while-choosing-the-right-research-methodology/
  • What is research methodology? Research and writing guides. Accessed August 14, 2023. https://paperpile.com/g/what-is-research-methodology/
  • Ethical considerations. Business research methodology website. Accessed August 17, 2023. https://research-methodology.net/research-methodology/ethical-considerations/

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Research Methods Guide: Research Design & Method

  • Introduction
  • Survey Research
  • Interview Research
  • Data Analysis
  • Resources & Consultation

Tutorial Videos: Research Design & Method

Research Methods (sociology-focused)

Qualitative vs. Quantitative Methods (intro)

Qualitative vs. Quantitative Methods (advanced)

what to include in research methods

FAQ: Research Design & Method

What is the difference between Research Design and Research Method?

Research design is a plan to answer your research question.  A research method is a strategy used to implement that plan.  Research design and methods are different but closely related, because good research design ensures that the data you obtain will help you answer your research question more effectively.

Which research method should I choose ?

It depends on your research goal.  It depends on what subjects (and who) you want to study.  Let's say you are interested in studying what makes people happy, or why some students are more conscious about recycling on campus.  To answer these questions, you need to make a decision about how to collect your data.  Most frequently used methods include:

  • Observation / Participant Observation
  • Focus Groups
  • Experiments
  • Secondary Data Analysis / Archival Study
  • Mixed Methods (combination of some of the above)

One particular method could be better suited to your research goal than others, because the data you collect from different methods will be different in quality and quantity.   For instance, surveys are usually designed to produce relatively short answers, rather than the extensive responses expected in qualitative interviews.

What other factors should I consider when choosing one method over another?

Time for data collection and analysis is something you want to consider.  An observation or interview method, so-called qualitative approach, helps you collect richer information, but it takes time.  Using a survey helps you collect more data quickly, yet it may lack details.  So, you will need to consider the time you have for research and the balance between strengths and weaknesses associated with each method (e.g., qualitative vs. quantitative).

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  • What Is a Research Methodology? | Steps & Tips

What Is a Research Methodology? | Steps & Tips

Published on 25 February 2019 by Shona McCombes . Revised on 10 October 2022.

Your research methodology discusses and explains the data collection and analysis methods you used in your research. A key part of your thesis, dissertation, or research paper, the methodology chapter explains what you did and how you did it, allowing readers to evaluate the reliability and validity of your research.

It should include:

  • The type of research you conducted
  • How you collected and analysed your data
  • Any tools or materials you used in the research
  • Why you chose these methods
  • Your methodology section should generally be written in the past tense .
  • Academic style guides in your field may provide detailed guidelines on what to include for different types of studies.
  • Your citation style might provide guidelines for your methodology section (e.g., an APA Style methods section ).

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Table of contents

How to write a research methodology, why is a methods section important, step 1: explain your methodological approach, step 2: describe your data collection methods, step 3: describe your analysis method, step 4: evaluate and justify the methodological choices you made, tips for writing a strong methodology chapter, frequently asked questions about methodology.

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Your methods section is your opportunity to share how you conducted your research and why you chose the methods you chose. It’s also the place to show that your research was rigorously conducted and can be replicated .

It gives your research legitimacy and situates it within your field, and also gives your readers a place to refer to if they have any questions or critiques in other sections.

You can start by introducing your overall approach to your research. You have two options here.

Option 1: Start with your “what”

What research problem or question did you investigate?

  • Aim to describe the characteristics of something?
  • Explore an under-researched topic?
  • Establish a causal relationship?

And what type of data did you need to achieve this aim?

  • Quantitative data , qualitative data , or a mix of both?
  • Primary data collected yourself, or secondary data collected by someone else?
  • Experimental data gathered by controlling and manipulating variables, or descriptive data gathered via observations?

Option 2: Start with your “why”

Depending on your discipline, you can also start with a discussion of the rationale and assumptions underpinning your methodology. In other words, why did you choose these methods for your study?

  • Why is this the best way to answer your research question?
  • Is this a standard methodology in your field, or does it require justification?
  • Were there any ethical considerations involved in your choices?
  • What are the criteria for validity and reliability in this type of research ?

Once you have introduced your reader to your methodological approach, you should share full details about your data collection methods .

Quantitative methods

In order to be considered generalisable, you should describe quantitative research methods in enough detail for another researcher to replicate your study.

Here, explain how you operationalised your concepts and measured your variables. Discuss your sampling method or inclusion/exclusion criteria, as well as any tools, procedures, and materials you used to gather your data.

Surveys Describe where, when, and how the survey was conducted.

  • How did you design the questionnaire?
  • What form did your questions take (e.g., multiple choice, Likert scale )?
  • Were your surveys conducted in-person or virtually?
  • What sampling method did you use to select participants?
  • What was your sample size and response rate?

Experiments Share full details of the tools, techniques, and procedures you used to conduct your experiment.

  • How did you design the experiment ?
  • How did you recruit participants?
  • How did you manipulate and measure the variables ?
  • What tools did you use?

Existing data Explain how you gathered and selected the material (such as datasets or archival data) that you used in your analysis.

  • Where did you source the material?
  • How was the data originally produced?
  • What criteria did you use to select material (e.g., date range)?

The survey consisted of 5 multiple-choice questions and 10 questions measured on a 7-point Likert scale.

The goal was to collect survey responses from 350 customers visiting the fitness apparel company’s brick-and-mortar location in Boston on 4–8 July 2022, between 11:00 and 15:00.

Here, a customer was defined as a person who had purchased a product from the company on the day they took the survey. Participants were given 5 minutes to fill in the survey anonymously. In total, 408 customers responded, but not all surveys were fully completed. Due to this, 371 survey results were included in the analysis.

Qualitative methods

In qualitative research , methods are often more flexible and subjective. For this reason, it’s crucial to robustly explain the methodology choices you made.

Be sure to discuss the criteria you used to select your data, the context in which your research was conducted, and the role you played in collecting your data (e.g., were you an active participant, or a passive observer?)

Interviews or focus groups Describe where, when, and how the interviews were conducted.

  • How did you find and select participants?
  • How many participants took part?
  • What form did the interviews take ( structured , semi-structured , or unstructured )?
  • How long were the interviews?
  • How were they recorded?

Participant observation Describe where, when, and how you conducted the observation or ethnography .

  • What group or community did you observe? How long did you spend there?
  • How did you gain access to this group? What role did you play in the community?
  • How long did you spend conducting the research? Where was it located?
  • How did you record your data (e.g., audiovisual recordings, note-taking)?

Existing data Explain how you selected case study materials for your analysis.

  • What type of materials did you analyse?
  • How did you select them?

In order to gain better insight into possibilities for future improvement of the fitness shop’s product range, semi-structured interviews were conducted with 8 returning customers.

Here, a returning customer was defined as someone who usually bought products at least twice a week from the store.

Surveys were used to select participants. Interviews were conducted in a small office next to the cash register and lasted approximately 20 minutes each. Answers were recorded by note-taking, and seven interviews were also filmed with consent. One interviewee preferred not to be filmed.

Mixed methods

Mixed methods research combines quantitative and qualitative approaches. If a standalone quantitative or qualitative study is insufficient to answer your research question, mixed methods may be a good fit for you.

Mixed methods are less common than standalone analyses, largely because they require a great deal of effort to pull off successfully. If you choose to pursue mixed methods, it’s especially important to robustly justify your methods here.

Next, you should indicate how you processed and analysed your data. Avoid going into too much detail: you should not start introducing or discussing any of your results at this stage.

In quantitative research , your analysis will be based on numbers. In your methods section, you can include:

  • How you prepared the data before analysing it (e.g., checking for missing data , removing outliers , transforming variables)
  • Which software you used (e.g., SPSS, Stata or R)
  • Which statistical tests you used (e.g., two-tailed t test , simple linear regression )

In qualitative research, your analysis will be based on language, images, and observations (often involving some form of textual analysis ).

Specific methods might include:

  • Content analysis : Categorising and discussing the meaning of words, phrases and sentences
  • Thematic analysis : Coding and closely examining the data to identify broad themes and patterns
  • Discourse analysis : Studying communication and meaning in relation to their social context

Mixed methods combine the above two research methods, integrating both qualitative and quantitative approaches into one coherent analytical process.

Above all, your methodology section should clearly make the case for why you chose the methods you did. This is especially true if you did not take the most standard approach to your topic. In this case, discuss why other methods were not suitable for your objectives, and show how this approach contributes new knowledge or understanding.

In any case, it should be overwhelmingly clear to your reader that you set yourself up for success in terms of your methodology’s design. Show how your methods should lead to results that are valid and reliable, while leaving the analysis of the meaning, importance, and relevance of your results for your discussion section .

  • Quantitative: Lab-based experiments cannot always accurately simulate real-life situations and behaviours, but they are effective for testing causal relationships between variables .
  • Qualitative: Unstructured interviews usually produce results that cannot be generalised beyond the sample group , but they provide a more in-depth understanding of participants’ perceptions, motivations, and emotions.
  • Mixed methods: Despite issues systematically comparing differing types of data, a solely quantitative study would not sufficiently incorporate the lived experience of each participant, while a solely qualitative study would be insufficiently generalisable.

Remember that your aim is not just to describe your methods, but to show how and why you applied them. Again, it’s critical to demonstrate that your research was rigorously conducted and can be replicated.

1. Focus on your objectives and research questions

The methodology section should clearly show why your methods suit your objectives  and convince the reader that you chose the best possible approach to answering your problem statement and research questions .

2. Cite relevant sources

Your methodology can be strengthened by referencing existing research in your field. This can help you to:

  • Show that you followed established practice for your type of research
  • Discuss how you decided on your approach by evaluating existing research
  • Present a novel methodological approach to address a gap in the literature

3. Write for your audience

Consider how much information you need to give, and avoid getting too lengthy. If you are using methods that are standard for your discipline, you probably don’t need to give a lot of background or justification.

Regardless, your methodology should be a clear, well-structured text that makes an argument for your approach, not just a list of technical details and procedures.

Methodology refers to the overarching strategy and rationale of your research. Developing your methodology involves studying the research methods used in your field and the theories or principles that underpin them, in order to choose the approach that best matches your objectives.

Methods are the specific tools and procedures you use to collect and analyse data (e.g. interviews, experiments , surveys , statistical tests ).

In a dissertation or scientific paper, the methodology chapter or methods section comes after the introduction and before the results , discussion and conclusion .

Depending on the length and type of document, you might also include a literature review or theoretical framework before the methodology.

Quantitative research deals with numbers and statistics, while qualitative research deals with words and meanings.

Quantitative methods allow you to test a hypothesis by systematically collecting and analysing data, while qualitative methods allow you to explore ideas and experiences in depth.

A sample is a subset of individuals from a larger population. Sampling means selecting the group that you will actually collect data from in your research.

For example, if you are researching the opinions of students in your university, you could survey a sample of 100 students.

Statistical sampling allows you to test a hypothesis about the characteristics of a population. There are various sampling methods you can use to ensure that your sample is representative of the population as a whole.

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Research Methodologies

  • What are research designs?
  • What are research methodologies?

What are research methods?

Quantitative research methods, qualitative research methods, mixed method approach, selecting the best research method.

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Research methods are different from research methodologies because they are the ways in which you will collect the data for your research project.  The best method for your project largely depends on your topic, the type of data you will need, and the people or items from which you will be collecting data.  The following boxes below contain a list of quantitative, qualitative, and mixed research methods.

  • Closed-ended questionnaires/survey: These types of questionnaires or surveys are like "multiple choice" tests, where participants must select from a list of premade answers.  According to the content of the question, they must select the one that they agree with the most.  This approach is the simplest form of quantitative research because the data is easy to combine and quantify.
  • Structured interviews: These are a common research method in market research because the data can be quantified.  They are strictly designed for little "wiggle room" in the interview process so that the data will not be skewed.  You can conduct structured interviews in-person, online, or over the phone (Dawson, 2019).

Constructing Questionnaires

When constructing your questions for a survey or questionnaire, there are things you can do to ensure that your questions are accurate and easy to understand (Dawson, 2019):

  • Keep the questions brief and simple.
  • Eliminate any potential bias from your questions.  Make sure that they do not word things in a way that favor one perspective over another.
  • If your topic is very sensitive, you may want to ask indirect questions rather than direct ones.  This prevents participants from being intimidated and becoming unwilling to share their true responses.
  • If you are using a closed-ended question, try to offer every possible answer that a participant could give to that question.
  • Do not ask questions that assume something of the participant.  The question "How often do you exercise?" assumes that the participant exercises (when they may not), so you would want to include a question that asks if they exercise at all before asking them how often.
  • Try and keep the questionnaire as short as possible.  The longer a questionnaire takes, the more likely the participant will not complete it or get too tired to put truthful answers.
  • Promise confidentiality to your participants at the beginning of the questionnaire.

Quantitative Research Measures

When you are considering a quantitative approach to your research, you need to identify why types of measures you will use in your study.  This will determine what type of numbers you will be using to collect your data.  There are four levels of measurement:

  • Nominal: These are numbers where the order of the numbers do not matter.  They aim to identify separate information.  One example is collecting zip codes from research participants.  The order of the numbers does not matter, but the series of numbers in each zip code indicate different information (Adamson and Prion, 2013).
  • Ordinal: Also known as rankings because the order of these numbers matter.  This is when items are given a specific rank according to specific criteria.  A common example of ordinal measurements include ranking-based questionnaires, where participants are asked to rank items from least favorite to most favorite.  Another common example is a pain scale, where a patient is asked to rank their pain on a scale from 1 to 10 (Adamson and Prion, 2013).
  • Interval: This is when the data are ordered and the distance between the numbers matters to the researcher (Adamson and Prion, 2013).  The distance between each number is the same.  An example of interval data is test grades.
  • Ratio: This is when the data are ordered and have a consistent distance between numbers, but has a "zero point."  This means that there could be a measurement of zero of whatever you are measuring in your study (Adamson and Prion, 2013).  An example of ratio data is measuring the height of something because the "zero point" remains constant in all measurements.  The height of something could also be zero.

Focus Groups

This is when a select group of people gather to talk about a particular topic.  They can also be called discussion groups or group interviews (Dawson, 2019).  They are usually lead by a moderator  to help guide the discussion and ask certain questions.  It is critical that a moderator allows everyone in the group to get a chance to speak so that no one dominates the discussion.  The data that are gathered from focus groups tend to be thoughts, opinions, and perspectives about an issue.

Advantages of Focus Groups

  • Only requires one meeting to get different types of responses.
  • Less researcher bias due to participants being able to speak openly.
  • Helps participants overcome insecurities or fears about a topic.
  • The researcher can also consider the impact of participant interaction.

Disadvantages of Focus Groups

  • Participants may feel uncomfortable to speak in front of an audience, especially if the topic is sensitive or controversial.
  • Since participation is voluntary, not every participant may contribute equally to the discussion.
  • Participants may impact what others say or think.
  • A researcher may feel intimidated by running a focus group on their own.
  • A researcher may need extra funds/resources to provide a safe space to host the focus group.
  • Because the data is collective, it may be difficult to determine a participant's individual thoughts about the research topic.

Observation

There are two ways to conduct research observations:

  • Direct Observation: The researcher observes a participant in an environment.  The researcher often takes notes or uses technology to gather data, such as a voice recorder or video camera.  The researcher does not interact or interfere with the participants.  This approach is often used in psychology and health studies (Dawson, 2019).
  • Participant Observation:  The researcher interacts directly with the participants to get a better understanding of the research topic.  This is a common research method when trying to understand another culture or community.  It is important to decide if you will conduct a covert (participants do not know they are part of the research) or overt (participants know the researcher is observing them) observation because it can be unethical in some situations (Dawson, 2019).

Open-Ended Questionnaires

These types of questionnaires are the opposite of "multiple choice" questionnaires because the answer boxes are left open for the participant to complete.  This means that participants can write short or extended answers to the questions.  Upon gathering the responses, researchers will often "quantify" the data by organizing the responses into different categories.  This can be time consuming because the researcher needs to read all responses carefully.

Semi-structured Interviews

This is the most common type of interview where researchers aim to get specific information so they can compare it to other interview data.  This requires asking the same questions for each interview, but keeping their responses flexible.  This means including follow-up questions if a subject answers a certain way.  Interview schedules are commonly used to aid the interviewers, which list topics or questions that will be discussed at each interview (Dawson, 2019).

Theoretical Analysis

Often used for nonhuman research, theoretical analysis is a qualitative approach where the researcher applies a theoretical framework to analyze something about their topic.  A theoretical framework gives the researcher a specific "lens" to view the topic and think about it critically. it also serves as context to guide the entire study.  This is a popular research method for analyzing works of literature, films, and other forms of media.  You can implement more than one theoretical framework with this method, as many theories complement one another.

Common theoretical frameworks for qualitative research are (Grant and Osanloo, 2014):

  • Behavioral theory
  • Change theory
  • Cognitive theory
  • Content analysis
  • Cross-sectional analysis
  • Developmental theory
  • Feminist theory
  • Gender theory
  • Marxist theory
  • Queer theory
  • Systems theory
  • Transformational theory

Unstructured Interviews

These are in-depth interviews where the researcher tries to understand an interviewee's perspective on a situation or issue.  They are sometimes called life history interviews.  It is important not to bombard the interviewee with too many questions so they can freely disclose their thoughts (Dawson, 2019).

  • Open-ended and closed-ended questionnaires: This approach means implementing elements of both questionnaire types into your data collection.  Participants may answer some questions with premade answers and write their own answers to other questions.  The advantage to this method is that you benefit from both types of data collection to get a broader understanding of you participants.  However, you must think carefully about how you will analyze this data to arrive at a conclusion.

Other mixed method approaches that incorporate quantitative and qualitative research methods depend heavily on the research topic.  It is strongly recommended that you collaborate with your academic advisor before finalizing a mixed method approach.

How do you determine which research method would be best for your proposal?  This heavily depends on your research objective.  According to Dawson (2019), there are several questions to ask yourself when determining the best research method for your project:

  • Are you good with numbers and mathematics?
  • Would you be interested in conducting interviews with human subjects?
  • Would you enjoy creating a questionnaire for participants to complete?
  • Do you prefer written communication or face-to-face interaction?
  • What skills or experiences do you have that might help you with your research?  Do you have any experiences from past research projects that can help with this one?
  • How much time do you have to complete the research?  Some methods take longer to collect data than others.
  • What is your budget?  Do you have adequate funding to conduct the research in the method you  want?
  • How much data do you need?  Some research topics need only a small amount of data while others may need significantly larger amounts.
  • What is the purpose of your research? This can provide a good indicator as to what research method will be most appropriate.
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  • Last Updated: Aug 2, 2022 2:36 PM
  • URL: https://library.tiffin.edu/researchmethodologies

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How to use and assess qualitative research methods

Loraine busetto.

1 Department of Neurology, Heidelberg University Hospital, Im Neuenheimer Feld 400, 69120 Heidelberg, Germany

Wolfgang Wick

2 Clinical Cooperation Unit Neuro-Oncology, German Cancer Research Center, Heidelberg, Germany

Christoph Gumbinger

Associated data.

Not applicable.

This paper aims to provide an overview of the use and assessment of qualitative research methods in the health sciences. Qualitative research can be defined as the study of the nature of phenomena and is especially appropriate for answering questions of why something is (not) observed, assessing complex multi-component interventions, and focussing on intervention improvement. The most common methods of data collection are document study, (non-) participant observations, semi-structured interviews and focus groups. For data analysis, field-notes and audio-recordings are transcribed into protocols and transcripts, and coded using qualitative data management software. Criteria such as checklists, reflexivity, sampling strategies, piloting, co-coding, member-checking and stakeholder involvement can be used to enhance and assess the quality of the research conducted. Using qualitative in addition to quantitative designs will equip us with better tools to address a greater range of research problems, and to fill in blind spots in current neurological research and practice.

The aim of this paper is to provide an overview of qualitative research methods, including hands-on information on how they can be used, reported and assessed. This article is intended for beginning qualitative researchers in the health sciences as well as experienced quantitative researchers who wish to broaden their understanding of qualitative research.

What is qualitative research?

Qualitative research is defined as “the study of the nature of phenomena”, including “their quality, different manifestations, the context in which they appear or the perspectives from which they can be perceived” , but excluding “their range, frequency and place in an objectively determined chain of cause and effect” [ 1 ]. This formal definition can be complemented with a more pragmatic rule of thumb: qualitative research generally includes data in form of words rather than numbers [ 2 ].

Why conduct qualitative research?

Because some research questions cannot be answered using (only) quantitative methods. For example, one Australian study addressed the issue of why patients from Aboriginal communities often present late or not at all to specialist services offered by tertiary care hospitals. Using qualitative interviews with patients and staff, it found one of the most significant access barriers to be transportation problems, including some towns and communities simply not having a bus service to the hospital [ 3 ]. A quantitative study could have measured the number of patients over time or even looked at possible explanatory factors – but only those previously known or suspected to be of relevance. To discover reasons for observed patterns, especially the invisible or surprising ones, qualitative designs are needed.

While qualitative research is common in other fields, it is still relatively underrepresented in health services research. The latter field is more traditionally rooted in the evidence-based-medicine paradigm, as seen in " research that involves testing the effectiveness of various strategies to achieve changes in clinical practice, preferably applying randomised controlled trial study designs (...) " [ 4 ]. This focus on quantitative research and specifically randomised controlled trials (RCT) is visible in the idea of a hierarchy of research evidence which assumes that some research designs are objectively better than others, and that choosing a "lesser" design is only acceptable when the better ones are not practically or ethically feasible [ 5 , 6 ]. Others, however, argue that an objective hierarchy does not exist, and that, instead, the research design and methods should be chosen to fit the specific research question at hand – "questions before methods" [ 2 , 7 – 9 ]. This means that even when an RCT is possible, some research problems require a different design that is better suited to addressing them. Arguing in JAMA, Berwick uses the example of rapid response teams in hospitals, which he describes as " a complex, multicomponent intervention – essentially a process of social change" susceptible to a range of different context factors including leadership or organisation history. According to him, "[in] such complex terrain, the RCT is an impoverished way to learn. Critics who use it as a truth standard in this context are incorrect" [ 8 ] . Instead of limiting oneself to RCTs, Berwick recommends embracing a wider range of methods , including qualitative ones, which for "these specific applications, (...) are not compromises in learning how to improve; they are superior" [ 8 ].

Research problems that can be approached particularly well using qualitative methods include assessing complex multi-component interventions or systems (of change), addressing questions beyond “what works”, towards “what works for whom when, how and why”, and focussing on intervention improvement rather than accreditation [ 7 , 9 – 12 ]. Using qualitative methods can also help shed light on the “softer” side of medical treatment. For example, while quantitative trials can measure the costs and benefits of neuro-oncological treatment in terms of survival rates or adverse effects, qualitative research can help provide a better understanding of patient or caregiver stress, visibility of illness or out-of-pocket expenses.

How to conduct qualitative research?

Given that qualitative research is characterised by flexibility, openness and responsivity to context, the steps of data collection and analysis are not as separate and consecutive as they tend to be in quantitative research [ 13 , 14 ]. As Fossey puts it : “sampling, data collection, analysis and interpretation are related to each other in a cyclical (iterative) manner, rather than following one after another in a stepwise approach” [ 15 ]. The researcher can make educated decisions with regard to the choice of method, how they are implemented, and to which and how many units they are applied [ 13 ]. As shown in Fig.  1 , this can involve several back-and-forth steps between data collection and analysis where new insights and experiences can lead to adaption and expansion of the original plan. Some insights may also necessitate a revision of the research question and/or the research design as a whole. The process ends when saturation is achieved, i.e. when no relevant new information can be found (see also below: sampling and saturation). For reasons of transparency, it is essential for all decisions as well as the underlying reasoning to be well-documented.

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Iterative research process

While it is not always explicitly addressed, qualitative methods reflect a different underlying research paradigm than quantitative research (e.g. constructivism or interpretivism as opposed to positivism). The choice of methods can be based on the respective underlying substantive theory or theoretical framework used by the researcher [ 2 ].

Data collection

The methods of qualitative data collection most commonly used in health research are document study, observations, semi-structured interviews and focus groups [ 1 , 14 , 16 , 17 ].

Document study

Document study (also called document analysis) refers to the review by the researcher of written materials [ 14 ]. These can include personal and non-personal documents such as archives, annual reports, guidelines, policy documents, diaries or letters.

Observations

Observations are particularly useful to gain insights into a certain setting and actual behaviour – as opposed to reported behaviour or opinions [ 13 ]. Qualitative observations can be either participant or non-participant in nature. In participant observations, the observer is part of the observed setting, for example a nurse working in an intensive care unit [ 18 ]. In non-participant observations, the observer is “on the outside looking in”, i.e. present in but not part of the situation, trying not to influence the setting by their presence. Observations can be planned (e.g. for 3 h during the day or night shift) or ad hoc (e.g. as soon as a stroke patient arrives at the emergency room). During the observation, the observer takes notes on everything or certain pre-determined parts of what is happening around them, for example focusing on physician-patient interactions or communication between different professional groups. Written notes can be taken during or after the observations, depending on feasibility (which is usually lower during participant observations) and acceptability (e.g. when the observer is perceived to be judging the observed). Afterwards, these field notes are transcribed into observation protocols. If more than one observer was involved, field notes are taken independently, but notes can be consolidated into one protocol after discussions. Advantages of conducting observations include minimising the distance between the researcher and the researched, the potential discovery of topics that the researcher did not realise were relevant and gaining deeper insights into the real-world dimensions of the research problem at hand [ 18 ].

Semi-structured interviews

Hijmans & Kuyper describe qualitative interviews as “an exchange with an informal character, a conversation with a goal” [ 19 ]. Interviews are used to gain insights into a person’s subjective experiences, opinions and motivations – as opposed to facts or behaviours [ 13 ]. Interviews can be distinguished by the degree to which they are structured (i.e. a questionnaire), open (e.g. free conversation or autobiographical interviews) or semi-structured [ 2 , 13 ]. Semi-structured interviews are characterized by open-ended questions and the use of an interview guide (or topic guide/list) in which the broad areas of interest, sometimes including sub-questions, are defined [ 19 ]. The pre-defined topics in the interview guide can be derived from the literature, previous research or a preliminary method of data collection, e.g. document study or observations. The topic list is usually adapted and improved at the start of the data collection process as the interviewer learns more about the field [ 20 ]. Across interviews the focus on the different (blocks of) questions may differ and some questions may be skipped altogether (e.g. if the interviewee is not able or willing to answer the questions or for concerns about the total length of the interview) [ 20 ]. Qualitative interviews are usually not conducted in written format as it impedes on the interactive component of the method [ 20 ]. In comparison to written surveys, qualitative interviews have the advantage of being interactive and allowing for unexpected topics to emerge and to be taken up by the researcher. This can also help overcome a provider or researcher-centred bias often found in written surveys, which by nature, can only measure what is already known or expected to be of relevance to the researcher. Interviews can be audio- or video-taped; but sometimes it is only feasible or acceptable for the interviewer to take written notes [ 14 , 16 , 20 ].

Focus groups

Focus groups are group interviews to explore participants’ expertise and experiences, including explorations of how and why people behave in certain ways [ 1 ]. Focus groups usually consist of 6–8 people and are led by an experienced moderator following a topic guide or “script” [ 21 ]. They can involve an observer who takes note of the non-verbal aspects of the situation, possibly using an observation guide [ 21 ]. Depending on researchers’ and participants’ preferences, the discussions can be audio- or video-taped and transcribed afterwards [ 21 ]. Focus groups are useful for bringing together homogeneous (to a lesser extent heterogeneous) groups of participants with relevant expertise and experience on a given topic on which they can share detailed information [ 21 ]. Focus groups are a relatively easy, fast and inexpensive method to gain access to information on interactions in a given group, i.e. “the sharing and comparing” among participants [ 21 ]. Disadvantages include less control over the process and a lesser extent to which each individual may participate. Moreover, focus group moderators need experience, as do those tasked with the analysis of the resulting data. Focus groups can be less appropriate for discussing sensitive topics that participants might be reluctant to disclose in a group setting [ 13 ]. Moreover, attention must be paid to the emergence of “groupthink” as well as possible power dynamics within the group, e.g. when patients are awed or intimidated by health professionals.

Choosing the “right” method

As explained above, the school of thought underlying qualitative research assumes no objective hierarchy of evidence and methods. This means that each choice of single or combined methods has to be based on the research question that needs to be answered and a critical assessment with regard to whether or to what extent the chosen method can accomplish this – i.e. the “fit” between question and method [ 14 ]. It is necessary for these decisions to be documented when they are being made, and to be critically discussed when reporting methods and results.

Let us assume that our research aim is to examine the (clinical) processes around acute endovascular treatment (EVT), from the patient’s arrival at the emergency room to recanalization, with the aim to identify possible causes for delay and/or other causes for sub-optimal treatment outcome. As a first step, we could conduct a document study of the relevant standard operating procedures (SOPs) for this phase of care – are they up-to-date and in line with current guidelines? Do they contain any mistakes, irregularities or uncertainties that could cause delays or other problems? Regardless of the answers to these questions, the results have to be interpreted based on what they are: a written outline of what care processes in this hospital should look like. If we want to know what they actually look like in practice, we can conduct observations of the processes described in the SOPs. These results can (and should) be analysed in themselves, but also in comparison to the results of the document analysis, especially as regards relevant discrepancies. Do the SOPs outline specific tests for which no equipment can be observed or tasks to be performed by specialized nurses who are not present during the observation? It might also be possible that the written SOP is outdated, but the actual care provided is in line with current best practice. In order to find out why these discrepancies exist, it can be useful to conduct interviews. Are the physicians simply not aware of the SOPs (because their existence is limited to the hospital’s intranet) or do they actively disagree with them or does the infrastructure make it impossible to provide the care as described? Another rationale for adding interviews is that some situations (or all of their possible variations for different patient groups or the day, night or weekend shift) cannot practically or ethically be observed. In this case, it is possible to ask those involved to report on their actions – being aware that this is not the same as the actual observation. A senior physician’s or hospital manager’s description of certain situations might differ from a nurse’s or junior physician’s one, maybe because they intentionally misrepresent facts or maybe because different aspects of the process are visible or important to them. In some cases, it can also be relevant to consider to whom the interviewee is disclosing this information – someone they trust, someone they are otherwise not connected to, or someone they suspect or are aware of being in a potentially “dangerous” power relationship to them. Lastly, a focus group could be conducted with representatives of the relevant professional groups to explore how and why exactly they provide care around EVT. The discussion might reveal discrepancies (between SOPs and actual care or between different physicians) and motivations to the researchers as well as to the focus group members that they might not have been aware of themselves. For the focus group to deliver relevant information, attention has to be paid to its composition and conduct, for example, to make sure that all participants feel safe to disclose sensitive or potentially problematic information or that the discussion is not dominated by (senior) physicians only. The resulting combination of data collection methods is shown in Fig.  2 .

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Possible combination of data collection methods

Attributions for icons: “Book” by Serhii Smirnov, “Interview” by Adrien Coquet, FR, “Magnifying Glass” by anggun, ID, “Business communication” by Vectors Market; all from the Noun Project

The combination of multiple data source as described for this example can be referred to as “triangulation”, in which multiple measurements are carried out from different angles to achieve a more comprehensive understanding of the phenomenon under study [ 22 , 23 ].

Data analysis

To analyse the data collected through observations, interviews and focus groups these need to be transcribed into protocols and transcripts (see Fig.  3 ). Interviews and focus groups can be transcribed verbatim , with or without annotations for behaviour (e.g. laughing, crying, pausing) and with or without phonetic transcription of dialects and filler words, depending on what is expected or known to be relevant for the analysis. In the next step, the protocols and transcripts are coded , that is, marked (or tagged, labelled) with one or more short descriptors of the content of a sentence or paragraph [ 2 , 15 , 23 ]. Jansen describes coding as “connecting the raw data with “theoretical” terms” [ 20 ]. In a more practical sense, coding makes raw data sortable. This makes it possible to extract and examine all segments describing, say, a tele-neurology consultation from multiple data sources (e.g. SOPs, emergency room observations, staff and patient interview). In a process of synthesis and abstraction, the codes are then grouped, summarised and/or categorised [ 15 , 20 ]. The end product of the coding or analysis process is a descriptive theory of the behavioural pattern under investigation [ 20 ]. The coding process is performed using qualitative data management software, the most common ones being InVivo, MaxQDA and Atlas.ti. It should be noted that these are data management tools which support the analysis performed by the researcher(s) [ 14 ].

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From data collection to data analysis

Attributions for icons: see Fig. ​ Fig.2, 2 , also “Speech to text” by Trevor Dsouza, “Field Notes” by Mike O’Brien, US, “Voice Record” by ProSymbols, US, “Inspection” by Made, AU, and “Cloud” by Graphic Tigers; all from the Noun Project

How to report qualitative research?

Protocols of qualitative research can be published separately and in advance of the study results. However, the aim is not the same as in RCT protocols, i.e. to pre-define and set in stone the research questions and primary or secondary endpoints. Rather, it is a way to describe the research methods in detail, which might not be possible in the results paper given journals’ word limits. Qualitative research papers are usually longer than their quantitative counterparts to allow for deep understanding and so-called “thick description”. In the methods section, the focus is on transparency of the methods used, including why, how and by whom they were implemented in the specific study setting, so as to enable a discussion of whether and how this may have influenced data collection, analysis and interpretation. The results section usually starts with a paragraph outlining the main findings, followed by more detailed descriptions of, for example, the commonalities, discrepancies or exceptions per category [ 20 ]. Here it is important to support main findings by relevant quotations, which may add information, context, emphasis or real-life examples [ 20 , 23 ]. It is subject to debate in the field whether it is relevant to state the exact number or percentage of respondents supporting a certain statement (e.g. “Five interviewees expressed negative feelings towards XYZ”) [ 21 ].

How to combine qualitative with quantitative research?

Qualitative methods can be combined with other methods in multi- or mixed methods designs, which “[employ] two or more different methods [ …] within the same study or research program rather than confining the research to one single method” [ 24 ]. Reasons for combining methods can be diverse, including triangulation for corroboration of findings, complementarity for illustration and clarification of results, expansion to extend the breadth and range of the study, explanation of (unexpected) results generated with one method with the help of another, or offsetting the weakness of one method with the strength of another [ 1 , 17 , 24 – 26 ]. The resulting designs can be classified according to when, why and how the different quantitative and/or qualitative data strands are combined. The three most common types of mixed method designs are the convergent parallel design , the explanatory sequential design and the exploratory sequential design. The designs with examples are shown in Fig.  4 .

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Three common mixed methods designs

In the convergent parallel design, a qualitative study is conducted in parallel to and independently of a quantitative study, and the results of both studies are compared and combined at the stage of interpretation of results. Using the above example of EVT provision, this could entail setting up a quantitative EVT registry to measure process times and patient outcomes in parallel to conducting the qualitative research outlined above, and then comparing results. Amongst other things, this would make it possible to assess whether interview respondents’ subjective impressions of patients receiving good care match modified Rankin Scores at follow-up, or whether observed delays in care provision are exceptions or the rule when compared to door-to-needle times as documented in the registry. In the explanatory sequential design, a quantitative study is carried out first, followed by a qualitative study to help explain the results from the quantitative study. This would be an appropriate design if the registry alone had revealed relevant delays in door-to-needle times and the qualitative study would be used to understand where and why these occurred, and how they could be improved. In the exploratory design, the qualitative study is carried out first and its results help informing and building the quantitative study in the next step [ 26 ]. If the qualitative study around EVT provision had shown a high level of dissatisfaction among the staff members involved, a quantitative questionnaire investigating staff satisfaction could be set up in the next step, informed by the qualitative study on which topics dissatisfaction had been expressed. Amongst other things, the questionnaire design would make it possible to widen the reach of the research to more respondents from different (types of) hospitals, regions, countries or settings, and to conduct sub-group analyses for different professional groups.

How to assess qualitative research?

A variety of assessment criteria and lists have been developed for qualitative research, ranging in their focus and comprehensiveness [ 14 , 17 , 27 ]. However, none of these has been elevated to the “gold standard” in the field. In the following, we therefore focus on a set of commonly used assessment criteria that, from a practical standpoint, a researcher can look for when assessing a qualitative research report or paper.

Assessors should check the authors’ use of and adherence to the relevant reporting checklists (e.g. Standards for Reporting Qualitative Research (SRQR)) to make sure all items that are relevant for this type of research are addressed [ 23 , 28 ]. Discussions of quantitative measures in addition to or instead of these qualitative measures can be a sign of lower quality of the research (paper). Providing and adhering to a checklist for qualitative research contributes to an important quality criterion for qualitative research, namely transparency [ 15 , 17 , 23 ].

Reflexivity

While methodological transparency and complete reporting is relevant for all types of research, some additional criteria must be taken into account for qualitative research. This includes what is called reflexivity, i.e. sensitivity to the relationship between the researcher and the researched, including how contact was established and maintained, or the background and experience of the researcher(s) involved in data collection and analysis. Depending on the research question and population to be researched this can be limited to professional experience, but it may also include gender, age or ethnicity [ 17 , 27 ]. These details are relevant because in qualitative research, as opposed to quantitative research, the researcher as a person cannot be isolated from the research process [ 23 ]. It may influence the conversation when an interviewed patient speaks to an interviewer who is a physician, or when an interviewee is asked to discuss a gynaecological procedure with a male interviewer, and therefore the reader must be made aware of these details [ 19 ].

Sampling and saturation

The aim of qualitative sampling is for all variants of the objects of observation that are deemed relevant for the study to be present in the sample “ to see the issue and its meanings from as many angles as possible” [ 1 , 16 , 19 , 20 , 27 ] , and to ensure “information-richness [ 15 ]. An iterative sampling approach is advised, in which data collection (e.g. five interviews) is followed by data analysis, followed by more data collection to find variants that are lacking in the current sample. This process continues until no new (relevant) information can be found and further sampling becomes redundant – which is called saturation [ 1 , 15 ] . In other words: qualitative data collection finds its end point not a priori , but when the research team determines that saturation has been reached [ 29 , 30 ].

This is also the reason why most qualitative studies use deliberate instead of random sampling strategies. This is generally referred to as “ purposive sampling” , in which researchers pre-define which types of participants or cases they need to include so as to cover all variations that are expected to be of relevance, based on the literature, previous experience or theory (i.e. theoretical sampling) [ 14 , 20 ]. Other types of purposive sampling include (but are not limited to) maximum variation sampling, critical case sampling or extreme or deviant case sampling [ 2 ]. In the above EVT example, a purposive sample could include all relevant professional groups and/or all relevant stakeholders (patients, relatives) and/or all relevant times of observation (day, night and weekend shift).

Assessors of qualitative research should check whether the considerations underlying the sampling strategy were sound and whether or how researchers tried to adapt and improve their strategies in stepwise or cyclical approaches between data collection and analysis to achieve saturation [ 14 ].

Good qualitative research is iterative in nature, i.e. it goes back and forth between data collection and analysis, revising and improving the approach where necessary. One example of this are pilot interviews, where different aspects of the interview (especially the interview guide, but also, for example, the site of the interview or whether the interview can be audio-recorded) are tested with a small number of respondents, evaluated and revised [ 19 ]. In doing so, the interviewer learns which wording or types of questions work best, or which is the best length of an interview with patients who have trouble concentrating for an extended time. Of course, the same reasoning applies to observations or focus groups which can also be piloted.

Ideally, coding should be performed by at least two researchers, especially at the beginning of the coding process when a common approach must be defined, including the establishment of a useful coding list (or tree), and when a common meaning of individual codes must be established [ 23 ]. An initial sub-set or all transcripts can be coded independently by the coders and then compared and consolidated after regular discussions in the research team. This is to make sure that codes are applied consistently to the research data.

Member checking

Member checking, also called respondent validation , refers to the practice of checking back with study respondents to see if the research is in line with their views [ 14 , 27 ]. This can happen after data collection or analysis or when first results are available [ 23 ]. For example, interviewees can be provided with (summaries of) their transcripts and asked whether they believe this to be a complete representation of their views or whether they would like to clarify or elaborate on their responses [ 17 ]. Respondents’ feedback on these issues then becomes part of the data collection and analysis [ 27 ].

Stakeholder involvement

In those niches where qualitative approaches have been able to evolve and grow, a new trend has seen the inclusion of patients and their representatives not only as study participants (i.e. “members”, see above) but as consultants to and active participants in the broader research process [ 31 – 33 ]. The underlying assumption is that patients and other stakeholders hold unique perspectives and experiences that add value beyond their own single story, making the research more relevant and beneficial to researchers, study participants and (future) patients alike [ 34 , 35 ]. Using the example of patients on or nearing dialysis, a recent scoping review found that 80% of clinical research did not address the top 10 research priorities identified by patients and caregivers [ 32 , 36 ]. In this sense, the involvement of the relevant stakeholders, especially patients and relatives, is increasingly being seen as a quality indicator in and of itself.

How not to assess qualitative research

The above overview does not include certain items that are routine in assessments of quantitative research. What follows is a non-exhaustive, non-representative, experience-based list of the quantitative criteria often applied to the assessment of qualitative research, as well as an explanation of the limited usefulness of these endeavours.

Protocol adherence

Given the openness and flexibility of qualitative research, it should not be assessed by how well it adheres to pre-determined and fixed strategies – in other words: its rigidity. Instead, the assessor should look for signs of adaptation and refinement based on lessons learned from earlier steps in the research process.

Sample size

For the reasons explained above, qualitative research does not require specific sample sizes, nor does it require that the sample size be determined a priori [ 1 , 14 , 27 , 37 – 39 ]. Sample size can only be a useful quality indicator when related to the research purpose, the chosen methodology and the composition of the sample, i.e. who was included and why.

Randomisation

While some authors argue that randomisation can be used in qualitative research, this is not commonly the case, as neither its feasibility nor its necessity or usefulness has been convincingly established for qualitative research [ 13 , 27 ]. Relevant disadvantages include the negative impact of a too large sample size as well as the possibility (or probability) of selecting “ quiet, uncooperative or inarticulate individuals ” [ 17 ]. Qualitative studies do not use control groups, either.

Interrater reliability, variability and other “objectivity checks”

The concept of “interrater reliability” is sometimes used in qualitative research to assess to which extent the coding approach overlaps between the two co-coders. However, it is not clear what this measure tells us about the quality of the analysis [ 23 ]. This means that these scores can be included in qualitative research reports, preferably with some additional information on what the score means for the analysis, but it is not a requirement. Relatedly, it is not relevant for the quality or “objectivity” of qualitative research to separate those who recruited the study participants and collected and analysed the data. Experiences even show that it might be better to have the same person or team perform all of these tasks [ 20 ]. First, when researchers introduce themselves during recruitment this can enhance trust when the interview takes place days or weeks later with the same researcher. Second, when the audio-recording is transcribed for analysis, the researcher conducting the interviews will usually remember the interviewee and the specific interview situation during data analysis. This might be helpful in providing additional context information for interpretation of data, e.g. on whether something might have been meant as a joke [ 18 ].

Not being quantitative research

Being qualitative research instead of quantitative research should not be used as an assessment criterion if it is used irrespectively of the research problem at hand. Similarly, qualitative research should not be required to be combined with quantitative research per se – unless mixed methods research is judged as inherently better than single-method research. In this case, the same criterion should be applied for quantitative studies without a qualitative component.

The main take-away points of this paper are summarised in Table ​ Table1. 1 . We aimed to show that, if conducted well, qualitative research can answer specific research questions that cannot to be adequately answered using (only) quantitative designs. Seeing qualitative and quantitative methods as equal will help us become more aware and critical of the “fit” between the research problem and our chosen methods: I can conduct an RCT to determine the reasons for transportation delays of acute stroke patients – but should I? It also provides us with a greater range of tools to tackle a greater range of research problems more appropriately and successfully, filling in the blind spots on one half of the methodological spectrum to better address the whole complexity of neurological research and practice.

Take-away-points

• Assessing complex multi-component interventions or systems (of change)

• What works for whom when, how and why?

• Focussing on intervention improvement

• Document study

• Observations (participant or non-participant)

• Interviews (especially semi-structured)

• Focus groups

• Transcription of audio-recordings and field notes into transcripts and protocols

• Coding of protocols

• Using qualitative data management software

• Combinations of quantitative and/or qualitative methods, e.g.:

• : quali and quanti in parallel

• : quanti followed by quali

• : quali followed by quanti

• Checklists

• Reflexivity

• Sampling strategies

• Piloting

• Co-coding

• Member checking

• Stakeholder involvement

• Protocol adherence

• Sample size

• Randomization

• Interrater reliability, variability and other “objectivity checks”

• Not being quantitative research

Acknowledgements

Abbreviations.

EVTEndovascular treatment
RCTRandomised Controlled Trial
SOPStandard Operating Procedure
SRQRStandards for Reporting Qualitative Research

Authors’ contributions

LB drafted the manuscript; WW and CG revised the manuscript; all authors approved the final versions.

no external funding.

Availability of data and materials

Ethics approval and consent to participate, consent for publication, competing interests.

The authors declare no competing interests.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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15 Types of Research Methods

15 Types of Research Methods

Chris Drew (PhD)

Dr. Chris Drew is the founder of the Helpful Professor. He holds a PhD in education and has published over 20 articles in scholarly journals. He is the former editor of the Journal of Learning Development in Higher Education. [Image Descriptor: Photo of Chris]

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types of research methods, explained below

Research methods refer to the strategies, tools, and techniques used to gather and analyze data in a structured way in order to answer a research question or investigate a hypothesis (Hammond & Wellington, 2020).

Generally, we place research methods into two categories: quantitative and qualitative. Each has its own strengths and weaknesses, which we can summarize as:

  • Quantitative research can achieve generalizability through scrupulous statistical analysis applied to large sample sizes.
  • Qualitative research achieves deep, detailed, and nuance accounts of specific case studies, which are not generalizable.

Some researchers, with the aim of making the most of both quantitative and qualitative research, employ mixed methods, whereby they will apply both types of research methods in the one study, such as by conducting a statistical survey alongside in-depth interviews to add context to the quantitative findings.

Below, I’ll outline 15 common research methods, and include pros, cons, and examples of each .

Types of Research Methods

Research methods can be broadly categorized into two types: quantitative and qualitative.

  • Quantitative methods involve systematic empirical investigation of observable phenomena via statistical, mathematical, or computational techniques, providing an in-depth understanding of a specific concept or phenomenon (Schweigert, 2021). The strengths of this approach include its ability to produce reliable results that can be generalized to a larger population, although it can lack depth and detail.
  • Qualitative methods encompass techniques that are designed to provide a deep understanding of a complex issue, often in a specific context, through collection of non-numerical data (Tracy, 2019). This approach often provides rich, detailed insights but can be time-consuming and its findings may not be generalizable.

These can be further broken down into a range of specific research methods and designs:

Primarily Quantitative MethodsPrimarily Qualitative methods
Experimental ResearchCase Study
Surveys and QuestionnairesEthnography
Longitudinal StudiesPhenomenology
Cross-Sectional StudiesHistorical research
Correlational ResearchContent analysis
Causal-Comparative ResearchGrounded theory
Meta-AnalysisAction research
Quasi-Experimental DesignObservational research

Combining the two methods above, mixed methods research mixes elements of both qualitative and quantitative research methods, providing a comprehensive understanding of the research problem . We can further break these down into:

  • Sequential Explanatory Design (QUAN→QUAL): This methodology involves conducting quantitative analysis first, then supplementing it with a qualitative study.
  • Sequential Exploratory Design (QUAL→QUAN): This methodology goes in the other direction, starting with qualitative analysis and ending with quantitative analysis.

Let’s explore some methods and designs from both quantitative and qualitative traditions, starting with qualitative research methods.

Qualitative Research Methods

Qualitative research methods allow for the exploration of phenomena in their natural settings, providing detailed, descriptive responses and insights into individuals’ experiences and perceptions (Howitt, 2019).

These methods are useful when a detailed understanding of a phenomenon is sought.

1. Ethnographic Research

Ethnographic research emerged out of anthropological research, where anthropologists would enter into a setting for a sustained period of time, getting to know a cultural group and taking detailed observations.

Ethnographers would sometimes even act as participants in the group or culture, which many scholars argue is a weakness because it is a step away from achieving objectivity (Stokes & Wall, 2017).

In fact, at its most extreme version, ethnographers even conduct research on themselves, in a fascinating methodology call autoethnography .

The purpose is to understand the culture, social structure, and the behaviors of the group under study. It is often useful when researchers seek to understand shared cultural meanings and practices in their natural settings.

However, it can be time-consuming and may reflect researcher biases due to the immersion approach.

Pros of Ethnographic ResearchCons of Ethnographic Research
1. Provides deep cultural insights1. Time-consuming
2. Contextually relevant findings2. Potential researcher bias
3. Explores dynamic social processes3. May

Example of Ethnography

Liquidated: An Ethnography of Wall Street  by Karen Ho involves an anthropologist who embeds herself with Wall Street firms to study the culture of Wall Street bankers and how this culture affects the broader economy and world.

2. Phenomenological Research

Phenomenological research is a qualitative method focused on the study of individual experiences from the participant’s perspective (Tracy, 2019).

It focuses specifically on people’s experiences in relation to a specific social phenomenon ( see here for examples of social phenomena ).

This method is valuable when the goal is to understand how individuals perceive, experience, and make meaning of particular phenomena. However, because it is subjective and dependent on participants’ self-reports, findings may not be generalizable, and are highly reliant on self-reported ‘thoughts and feelings’.

Pros of Phenomenological ResearchCons of Phenomenological Research
1. Provides rich, detailed data1. Limited generalizability
2. Highlights personal experience and perceptions2. Data collection can be time-consuming
3. Allows exploration of complex phenomena3. Requires highly skilled researchers

Example of Phenomenological Research

A phenomenological approach to experiences with technology  by Sebnem Cilesiz represents a good starting-point for formulating a phenomenological study. With its focus on the ‘essence of experience’, this piece presents methodological, reliability, validity, and data analysis techniques that phenomenologists use to explain how people experience technology in their everyday lives.

3. Historical Research

Historical research is a qualitative method involving the examination of past events to draw conclusions about the present or make predictions about the future (Stokes & Wall, 2017).

As you might expect, it’s common in the research branches of history departments in universities.

This approach is useful in studies that seek to understand the past to interpret present events or trends. However, it relies heavily on the availability and reliability of source materials, which may be limited.

Common data sources include cultural artifacts from both material and non-material culture , which are then examined, compared, contrasted, and contextualized to test hypotheses and generate theories.

Pros of Historical ResearchCons of Historical Research
1. 1. Dependent on available sources
2. Can help understand current events or trends2. Potential bias in source materials
3. Allows the study of change over time3. Difficult to replicate

Example of Historical Research

A historical research example might be a study examining the evolution of gender roles over the last century. This research might involve the analysis of historical newspapers, advertisements, letters, and company documents, as well as sociocultural contexts.

4. Content Analysis

Content analysis is a research method that involves systematic and objective coding and interpreting of text or media to identify patterns, themes, ideologies, or biases (Schweigert, 2021).

A content analysis is useful in analyzing communication patterns, helping to reveal how texts such as newspapers, movies, films, political speeches, and other types of ‘content’ contain narratives and biases.

However, interpretations can be very subjective, which often requires scholars to engage in practices such as cross-comparing their coding with peers or external researchers.

Content analysis can be further broken down in to other specific methodologies such as semiotic analysis, multimodal analysis , and discourse analysis .

Pros of Content AnalysisCons of Content Analysis
1. Unobtrusive data collection1. Lacks contextual information
2. Allows for large sample analysis2. Potential coder bias
3. Replicable and reliable if done properly3. May overlook nuances

Example of Content Analysis

How is Islam Portrayed in Western Media?  by Poorebrahim and Zarei (2013) employs a type of content analysis called critical discourse analysis (common in poststructuralist and critical theory research ). This study by Poorebrahum and Zarei combs through a corpus of western media texts to explore the language forms that are used in relation to Islam and Muslims, finding that they are overly stereotyped, which may represent anti-Islam bias or failure to understand the Islamic world.

5. Grounded Theory Research

Grounded theory involves developing a theory  during and after  data collection rather than beforehand.

This is in contrast to most academic research studies, which start with a hypothesis or theory and then testing of it through a study, where we might have a null hypothesis (disproving the theory) and an alternative hypothesis (supporting the theory).

Grounded Theory is useful because it keeps an open mind to what the data might reveal out of the research. It can be time-consuming and requires rigorous data analysis (Tracy, 2019).

Pros of Grounded Theory ResearchCons of Grounded Theory Research
1. Helps with theory development1. Time-consuming
2. Rigorous data analysis2. Requires iterative data collection and analysis
3. Can fill gaps in existing theories3. Requires skilled researchers

Grounded Theory Example

Developing a Leadership Identity   by Komives et al (2005) employs a grounded theory approach to develop a thesis based on the data rather than testing a hypothesis. The researchers studied the leadership identity of 13 college students taking on leadership roles. Based on their interviews, the researchers theorized that the students’ leadership identities shifted from a hierarchical view of leadership to one that embraced leadership as a collaborative concept.

6. Action Research

Action research is an approach which aims to solve real-world problems and bring about change within a setting. The study is designed to solve a specific problem – or in other words, to take action (Patten, 2017).

This approach can involve mixed methods, but is generally qualitative because it usually involves the study of a specific case study wherein the researcher works, e.g. a teacher studying their own classroom practice to seek ways they can improve.

Action research is very common in fields like education and nursing where practitioners identify areas for improvement then implement a study in order to find paths forward.

Pros of Action ResearchCons of Action Research
1. Addresses real-world problems and seeks to find solutions.1. It is time-consuming and often hard to implement into a practitioner’s already busy schedule
2. Integrates research and action in an action-research cycle.2. Requires collaboration between researcher, practitioner, and research participants.
3. Can bring about positive change in isolated instances, such as in a school or nursery setting.3. Complexity of managing dual roles (where the researcher is also often the practitioner)

Action Research Example

Using Digital Sandbox Gaming to Improve Creativity Within Boys’ Writing   by Ellison and Drew was a research study one of my research students completed in his own classroom under my supervision. He implemented a digital game-based approach to literacy teaching with boys and interviewed his students to see if the use of games as stimuli for storytelling helped draw them into the learning experience.

7. Natural Observational Research

Observational research can also be quantitative (see: experimental research), but in naturalistic settings for the social sciences, researchers tend to employ qualitative data collection methods like interviews and field notes to observe people in their day-to-day environments.

This approach involves the observation and detailed recording of behaviors in their natural settings (Howitt, 2019). It can provide rich, in-depth information, but the researcher’s presence might influence behavior.

While observational research has some overlaps with ethnography (especially in regard to data collection techniques), it tends not to be as sustained as ethnography, e.g. a researcher might do 5 observations, every second Monday, as opposed to being embedded in an environment.

Pros of Qualitative Observational ResearchCons of Qualitative Observational Research
1. Captures behavior in natural settings, allowing for interesting insights into authentic behaviors. 1. Researcher’s presence may influence behavior
2. Can provide rich, detailed data through the researcher’s vignettes.2. Can be time-consuming
3. Non-invasive because researchers want to observe natural activities rather than interfering with research participants.3. Requires skilled and trained observers

Observational Research Example

A researcher might use qualitative observational research to study the behaviors and interactions of children at a playground. The researcher would document the behaviors observed, such as the types of games played, levels of cooperation , and instances of conflict.

8. Case Study Research

Case study research is a qualitative method that involves a deep and thorough investigation of a single individual, group, or event in order to explore facets of that phenomenon that cannot be captured using other methods (Stokes & Wall, 2017).

Case study research is especially valuable in providing contextualized insights into specific issues, facilitating the application of abstract theories to real-world situations (Patten, 2017).

However, findings from a case study may not be generalizable due to the specific context and the limited number of cases studied (Walliman, 2021).

Pros of Case Study ResearchCons of Case Study Research
1. Provides detailed insights1. Limited generalizability
2. Facilitates the study of complex phenomena2. Can be time-consuming
3. Can test or generate theories3. Subject to observer bias

See More: Case Study Advantages and Disadvantages

Example of a Case Study

Scholars conduct a detailed exploration of the implementation of a new teaching method within a classroom setting. The study focuses on how the teacher and students adapt to the new method, the challenges encountered, and the outcomes on student performance and engagement. While the study provides specific and detailed insights of the teaching method in that classroom, it cannot be generalized to other classrooms, as statistical significance has not been established through this qualitative approach.

Quantitative Research Methods

Quantitative research methods involve the systematic empirical investigation of observable phenomena via statistical, mathematical, or computational techniques (Pajo, 2022). The focus is on gathering numerical data and generalizing it across groups of people or to explain a particular phenomenon.

9. Experimental Research

Experimental research is a quantitative method where researchers manipulate one variable to determine its effect on another (Walliman, 2021).

This is common, for example, in high-school science labs, where students are asked to introduce a variable into a setting in order to examine its effect.

This type of research is useful in situations where researchers want to determine causal relationships between variables. However, experimental conditions may not reflect real-world conditions.

Pros of Experimental ResearchCons of Experimental Research
1. Allows for determination of causality1. Might not reflect real-world conditions
2. Allows for the study of phenomena in highly controlled environments to minimize research contamination.2. Can be costly and time-consuming to create a controlled environment.
3. Can be replicated so other researchers can test and verify the results.3. Ethical concerns need to be addressed as the research is directly manipulating variables.

Example of Experimental Research

A researcher may conduct an experiment to determine the effects of a new educational approach on student learning outcomes. Students would be randomly assigned to either the control group (traditional teaching method) or the experimental group (new educational approach).

10. Surveys and Questionnaires

Surveys and questionnaires are quantitative methods that involve asking research participants structured and predefined questions to collect data about their attitudes, beliefs, behaviors, or characteristics (Patten, 2017).

Surveys are beneficial for collecting data from large samples, but they depend heavily on the honesty and accuracy of respondents.

They tend to be seen as more authoritative than their qualitative counterparts, semi-structured interviews, because the data is quantifiable (e.g. a questionnaire where information is presented on a scale from 1 to 10 can allow researchers to determine and compare statistical means, averages, and variations across sub-populations in the study).

Pros of Surveys and QuestionnairesCons of Surveys and Questionnaires
1. Data can be gathered from larger samples than is possible in qualitative research. 1. There is heavy dependence on respondent honesty
2. The data is quantifiable, allowing for comparison across subpopulations2. There is limited depth of response as opposed to qualitative approaches.
3. Can be cost-effective and time-efficient3. Static with no flexibility to explore responses (unlike semi- or unstrcutured interviewing)

Example of a Survey Study

A company might use a survey to gather data about employee job satisfaction across its offices worldwide. Employees would be asked to rate various aspects of their job satisfaction on a Likert scale. While this method provides a broad overview, it may lack the depth of understanding possible with other methods (Stokes & Wall, 2017).

11. Longitudinal Studies

Longitudinal studies involve repeated observations of the same variables over extended periods (Howitt, 2019). These studies are valuable for tracking development and change but can be costly and time-consuming.

With multiple data points collected over extended periods, it’s possible to examine continuous changes within things like population dynamics or consumer behavior. This makes a detailed analysis of change possible.

a visual representation of a longitudinal study demonstrating that data is collected over time on one sample so researchers can examine how variables change over time

Perhaps the most relatable example of a longitudinal study is a national census, which is taken on the same day every few years, to gather comparative demographic data that can show how a nation is changing over time.

While longitudinal studies are commonly quantitative, there are also instances of qualitative ones as well, such as the famous 7 Up study from the UK, which studies 14 individuals every 7 years to explore their development over their lives.

Pros of Longitudinal StudiesCons of Longitudinal Studies
1. Tracks changes over time allowing for comparison of past to present events.1. Is almost by definition time-consuming because time needs to pass between each data collection session.
2. Can identify sequences of events, but causality is often harder to determine.2. There is high risk of participant dropout over time as participants move on with their lives.

Example of a Longitudinal Study

A national census, taken every few years, uses surveys to develop longitudinal data, which is then compared and analyzed to present accurate trends over time. Trends a census can reveal include changes in religiosity, values and attitudes on social issues, and much more.

12. Cross-Sectional Studies

Cross-sectional studies are a quantitative research method that involves analyzing data from a population at a specific point in time (Patten, 2017). They provide a snapshot of a situation but cannot determine causality.

This design is used to measure and compare the prevalence of certain characteristics or outcomes in different groups within the sampled population.

A visual representation of a cross-sectional group of people, demonstrating that the data is collected at a single point in time and you can compare groups within the sample

The major advantage of cross-sectional design is its ability to measure a wide range of variables simultaneously without needing to follow up with participants over time.

However, cross-sectional studies do have limitations . This design can only show if there are associations or correlations between different variables, but cannot prove cause and effect relationships, temporal sequence, changes, and trends over time.

Pros of Cross-Sectional StudiesCons of Cross-Sectional Studies
1. Quick and inexpensive, with no long-term commitment required.1. Cannot determine causality because it is a simple snapshot, with no time delay between data collection points.
2. Good for descriptive analyses.2. Does not allow researchers to follow up with research participants.

Example of a Cross-Sectional Study

Our longitudinal study example of a national census also happens to contain cross-sectional design. One census is cross-sectional, displaying only data from one point in time. But when a census is taken once every few years, it becomes longitudinal, and so long as the data collection technique remains unchanged, identification of changes will be achievable, adding another time dimension on top of a basic cross-sectional study.

13. Correlational Research

Correlational research is a quantitative method that seeks to determine if and to what degree a relationship exists between two or more quantifiable variables (Schweigert, 2021).

This approach provides a fast and easy way to make initial hypotheses based on either positive or  negative correlation trends  that can be observed within dataset.

While correlational research can reveal relationships between variables, it cannot establish causality.

Methods used for data analysis may include statistical correlations such as Pearson’s or Spearman’s.

Pros of Correlational ResearchCons of Correlational Research
1. Reveals relationships between variables1. Cannot determine causality
2. Can use existing data2. May be
3. Can guide further experimental research3. Correlation may be coincidental

Example of Correlational Research

A team of researchers is interested in studying the relationship between the amount of time students spend studying and their academic performance. They gather data from a high school, measuring the number of hours each student studies per week and their grade point averages (GPAs) at the end of the semester. Upon analyzing the data, they find a positive correlation, suggesting that students who spend more time studying tend to have higher GPAs.

14. Quasi-Experimental Design Research

Quasi-experimental design research is a quantitative research method that is similar to experimental design but lacks the element of random assignment to treatment or control.

Instead, quasi-experimental designs typically rely on certain other methods to control for extraneous variables.

The term ‘quasi-experimental’ implies that the experiment resembles a true experiment, but it is not exactly the same because it doesn’t meet all the criteria for a ‘true’ experiment, specifically in terms of control and random assignment.

Quasi-experimental design is useful when researchers want to study a causal hypothesis or relationship, but practical or ethical considerations prevent them from manipulating variables and randomly assigning participants to conditions.

Pros Cons
1. It’s more feasible to implement than true experiments.1. Without random assignment, it’s harder to rule out confounding variables.
2. It can be conducted in real-world settings, making the findings more applicable to the real world.2. The lack of random assignment may of the study.
3. Useful when it’s unethical or impossible to manipulate the independent variable or randomly assign participants.3. It’s more difficult to establish a cause-effect relationship due to the potential for confounding variables.

Example of Quasi-Experimental Design

A researcher wants to study the impact of a new math tutoring program on student performance. However, ethical and practical constraints prevent random assignment to the “tutoring” and “no tutoring” groups. Instead, the researcher compares students who chose to receive tutoring (experimental group) to similar students who did not choose to receive tutoring (control group), controlling for other variables like grade level and previous math performance.

Related: Examples and Types of Random Assignment in Research

15. Meta-Analysis Research

Meta-analysis statistically combines the results of multiple studies on a specific topic to yield a more precise estimate of the effect size. It’s the gold standard of secondary research .

Meta-analysis is particularly useful when there are numerous studies on a topic, and there is a need to integrate the findings to draw more reliable conclusions.

Some meta-analyses can identify flaws or gaps in a corpus of research, when can be highly influential in academic research, despite lack of primary data collection.

However, they tend only to be feasible when there is a sizable corpus of high-quality and reliable studies into a phenomenon.

Pros Cons
Increased Statistical Power: By combining data from multiple studies, meta-analysis increases the statistical power to detect effects.Publication Bias: Studies with null or negative findings are less likely to be published, leading to an overestimation of effect sizes.
Greater Precision: It provides more precise estimates of effect sizes by reducing the influence of random error.Quality of Studies: of a meta-analysis depends on the quality of the studies included.
Resolving Discrepancies: Meta-analysis can help resolve disagreements between different studies on a topic.Heterogeneity: Differences in study design, sample, or procedures can introduce heterogeneity, complicating interpretation of results.

Example of a Meta-Analysis

The power of feedback revisited (Wisniewski, Zierer & Hattie, 2020) is a meta-analysis that examines 435 empirical studies research on the effects of feedback on student learning. They use a random-effects model to ascertain whether there is a clear effect size across the literature. The authors find that feedback tends to impact cognitive and motor skill outcomes but has less of an effect on motivational and behavioral outcomes.

Choosing a research method requires a lot of consideration regarding what you want to achieve, your research paradigm, and the methodology that is most valuable for what you are studying. There are multiple types of research methods, many of which I haven’t been able to present here. Generally, it’s recommended that you work with an experienced researcher or research supervisor to identify a suitable research method for your study at hand.

Hammond, M., & Wellington, J. (2020). Research methods: The key concepts . New York: Routledge.

Howitt, D. (2019). Introduction to qualitative research methods in psychology . London: Pearson UK.

Pajo, B. (2022). Introduction to research methods: A hands-on approach . New York: Sage Publications.

Patten, M. L. (2017). Understanding research methods: An overview of the essentials . New York: Sage

Schweigert, W. A. (2021). Research methods in psychology: A handbook . Los Angeles: Waveland Press.

Stokes, P., & Wall, T. (2017). Research methods . New York: Bloomsbury Publishing.

Tracy, S. J. (2019). Qualitative research methods: Collecting evidence, crafting analysis, communicating impact . London: John Wiley & Sons.

Walliman, N. (2021). Research methods: The basics. London: Routledge.

Chris

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  • What Is Qualitative Research? | Methods & Examples

What Is Qualitative Research? | Methods & Examples

Published on June 19, 2020 by Pritha Bhandari . Revised on June 22, 2023.

Qualitative research involves collecting and analyzing non-numerical data (e.g., text, video, or audio) to understand concepts, opinions, or experiences. It can be used to gather in-depth insights into a problem or generate new ideas for research.

Qualitative research is the opposite of quantitative research , which involves collecting and analyzing numerical data for statistical analysis.

Qualitative research is commonly used in the humanities and social sciences, in subjects such as anthropology, sociology, education, health sciences, history, etc.

  • How does social media shape body image in teenagers?
  • How do children and adults interpret healthy eating in the UK?
  • What factors influence employee retention in a large organization?
  • How is anxiety experienced around the world?
  • How can teachers integrate social issues into science curriculums?

Table of contents

Approaches to qualitative research, qualitative research methods, qualitative data analysis, advantages of qualitative research, disadvantages of qualitative research, other interesting articles, frequently asked questions about qualitative research.

Qualitative research is used to understand how people experience the world. While there are many approaches to qualitative research, they tend to be flexible and focus on retaining rich meaning when interpreting data.

Common approaches include grounded theory, ethnography , action research , phenomenological research, and narrative research. They share some similarities, but emphasize different aims and perspectives.

Qualitative research approaches
Approach What does it involve?
Grounded theory Researchers collect rich data on a topic of interest and develop theories .
Researchers immerse themselves in groups or organizations to understand their cultures.
Action research Researchers and participants collaboratively link theory to practice to drive social change.
Phenomenological research Researchers investigate a phenomenon or event by describing and interpreting participants’ lived experiences.
Narrative research Researchers examine how stories are told to understand how participants perceive and make sense of their experiences.

Note that qualitative research is at risk for certain research biases including the Hawthorne effect , observer bias , recall bias , and social desirability bias . While not always totally avoidable, awareness of potential biases as you collect and analyze your data can prevent them from impacting your work too much.

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Each of the research approaches involve using one or more data collection methods . These are some of the most common qualitative methods:

  • Observations: recording what you have seen, heard, or encountered in detailed field notes.
  • Interviews:  personally asking people questions in one-on-one conversations.
  • Focus groups: asking questions and generating discussion among a group of people.
  • Surveys : distributing questionnaires with open-ended questions.
  • Secondary research: collecting existing data in the form of texts, images, audio or video recordings, etc.
  • You take field notes with observations and reflect on your own experiences of the company culture.
  • You distribute open-ended surveys to employees across all the company’s offices by email to find out if the culture varies across locations.
  • You conduct in-depth interviews with employees in your office to learn about their experiences and perspectives in greater detail.

Qualitative researchers often consider themselves “instruments” in research because all observations, interpretations and analyses are filtered through their own personal lens.

For this reason, when writing up your methodology for qualitative research, it’s important to reflect on your approach and to thoroughly explain the choices you made in collecting and analyzing the data.

Qualitative data can take the form of texts, photos, videos and audio. For example, you might be working with interview transcripts, survey responses, fieldnotes, or recordings from natural settings.

Most types of qualitative data analysis share the same five steps:

  • Prepare and organize your data. This may mean transcribing interviews or typing up fieldnotes.
  • Review and explore your data. Examine the data for patterns or repeated ideas that emerge.
  • Develop a data coding system. Based on your initial ideas, establish a set of codes that you can apply to categorize your data.
  • Assign codes to the data. For example, in qualitative survey analysis, this may mean going through each participant’s responses and tagging them with codes in a spreadsheet. As you go through your data, you can create new codes to add to your system if necessary.
  • Identify recurring themes. Link codes together into cohesive, overarching themes.

There are several specific approaches to analyzing qualitative data. Although these methods share similar processes, they emphasize different concepts.

Qualitative data analysis
Approach When to use Example
To describe and categorize common words, phrases, and ideas in qualitative data. A market researcher could perform content analysis to find out what kind of language is used in descriptions of therapeutic apps.
To identify and interpret patterns and themes in qualitative data. A psychologist could apply thematic analysis to travel blogs to explore how tourism shapes self-identity.
To examine the content, structure, and design of texts. A media researcher could use textual analysis to understand how news coverage of celebrities has changed in the past decade.
To study communication and how language is used to achieve effects in specific contexts. A political scientist could use discourse analysis to study how politicians generate trust in election campaigns.

Qualitative research often tries to preserve the voice and perspective of participants and can be adjusted as new research questions arise. Qualitative research is good for:

  • Flexibility

The data collection and analysis process can be adapted as new ideas or patterns emerge. They are not rigidly decided beforehand.

  • Natural settings

Data collection occurs in real-world contexts or in naturalistic ways.

  • Meaningful insights

Detailed descriptions of people’s experiences, feelings and perceptions can be used in designing, testing or improving systems or products.

  • Generation of new ideas

Open-ended responses mean that researchers can uncover novel problems or opportunities that they wouldn’t have thought of otherwise.

Researchers must consider practical and theoretical limitations in analyzing and interpreting their data. Qualitative research suffers from:

  • Unreliability

The real-world setting often makes qualitative research unreliable because of uncontrolled factors that affect the data.

  • Subjectivity

Due to the researcher’s primary role in analyzing and interpreting data, qualitative research cannot be replicated . The researcher decides what is important and what is irrelevant in data analysis, so interpretations of the same data can vary greatly.

  • Limited generalizability

Small samples are often used to gather detailed data about specific contexts. Despite rigorous analysis procedures, it is difficult to draw generalizable conclusions because the data may be biased and unrepresentative of the wider population .

  • Labor-intensive

Although software can be used to manage and record large amounts of text, data analysis often has to be checked or performed manually.

If you want to know more about statistics , methodology , or research bias , make sure to check out some of our other articles with explanations and examples.

  • Chi square goodness of fit test
  • Degrees of freedom
  • Null hypothesis
  • Discourse analysis
  • Control groups
  • Mixed methods research
  • Non-probability sampling
  • Quantitative research
  • Inclusion and exclusion criteria

Research bias

  • Rosenthal effect
  • Implicit bias
  • Cognitive bias
  • Selection bias
  • Negativity bias
  • Status quo bias

Quantitative research deals with numbers and statistics, while qualitative research deals with words and meanings.

Quantitative methods allow you to systematically measure variables and test hypotheses . Qualitative methods allow you to explore concepts and experiences in more detail.

There are five common approaches to qualitative research :

  • Grounded theory involves collecting data in order to develop new theories.
  • Ethnography involves immersing yourself in a group or organization to understand its culture.
  • Narrative research involves interpreting stories to understand how people make sense of their experiences and perceptions.
  • Phenomenological research involves investigating phenomena through people’s lived experiences.
  • Action research links theory and practice in several cycles to drive innovative changes.

Data collection is the systematic process by which observations or measurements are gathered in research. It is used in many different contexts by academics, governments, businesses, and other organizations.

There are various approaches to qualitative data analysis , but they all share five steps in common:

  • Prepare and organize your data.
  • Review and explore your data.
  • Develop a data coding system.
  • Assign codes to the data.
  • Identify recurring themes.

The specifics of each step depend on the focus of the analysis. Some common approaches include textual analysis , thematic analysis , and discourse analysis .

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The application and evaluation of the lmdi method in building carbon emissions analysis: a comprehensive review.

what to include in research methods

1. Introduction

  • The LMDI method has four advantages and two disadvantages, leading to four directions for future development.
  • The LMDI is applied to examine the driving variances of urban REC, carbon emissions, and CO₂ emissions in China.
  • The analysis of buildings using the LMDI covers three main categories: civil buildings, public buildings, and residential buildings. Public buildings are further subdivided into four categories. The analysis is conducted through the combination of the LMDI and other methods.
  • The analysis of different aspects of building using various LMDI models and other methods.
  • The LMDI method, combined with dynamic material flow analysis and index decomposition analysis, determines Domestic Material Consumption (DMC) and material footprint (MF) under the influence of material and residential intensity effects. This reflects the demand and consumption of materials in a country or region at different stages of development.

2. Methodology

3. analysis of related technical theories of lmdi decomposition, 4. summary of lmdi analysis of urban energy, 4.1. analysis of carbon emissions, 4.2. analysis of driving factors on carbon emissions, 4.3. analysis of driving factors in energy consumption, 5. lmdi analysis of building, 5.1. ldmi analysis of civil architecture, 5.2. lmdi analysis of public architecture, 5.2.1. lmdi analysis of public buildings, 5.2.2. lmdi analysis of educational buildings, 5.2.3. lmdi analysis of commercial building, 5.2.4. lmdi analysis of hotel building, 5.3. lmdi analysis of residential architecture, 6. analysis of lmdi and other methods in building sector, 6.1. analysis of lmdi in building sector, 6.1.1. application of i-pbat model, 6.1.2. key drivers of carbon emissions in building sector, 6.2. analysis of other methods in building sector, 6.2.1. analysis of tapio decoupling model, 6.2.2. bibliometric method, 6.2.3. analysis of system dynamics model and scenario, 6.2.4. dynamic integrated building carbon emission-forecasting model, 6.2.5. assessment of synergistic emission-reduction potential, 7. lmdi analysis of building materials, 8. conclusions and discussion, conflicts of interest, abbreviations.

ALautomation level by area
Bbehavioral
BAbuilding area
BSbuilding structure
CERCPBcarbon reduction
CIcarbon intensity
CLclimate
CO carbon dioxide
CPBCECarbon Emissions in Public Buildings
CSconsumption suppression
DEMATELDecision Making Trial and Evaluation Laboratory
DMCDomestic Material Consumption
Eeconomic
EAeconomic activity
ECenergy consumption
EFcarbon emission
EIenergy intensity
EOeconomic output
ESenergy structure
FARfloor area shape
GDIMGeneralized Divisia Index Method
Iincome
IDAindex decomposition analysis
IPATImpact, Population, Affluence, and Technology
I-PBATImpact, Population, Behaviour, Affluence, and Technology
IRinfrastructure ratio
ISindustrial structure
ISMInterpretive Structural Modeling
LEAPLong-range Energy Alternatives Planning System
LMDILogarithmic Mean Divisia Index
Mbuilding material
MCbuilding material consumption
MCEmachinery efficiency
MEbuilding material efficiency
MFmaterial footprint
MIbuilding material intensity
POPpopulation
PCAper capita area
PCIper capita income
PCGDPper capita GDP
PUpopulation urbanization
RCresidential consumption
RECresidential energy consumption
RTresidential type
RIresidential intensity
SAsocial affluence
SDSystem Dynamics
SDAstructural decomposition analysis
SENstudent enrollment numbers
STIRPATStochastic Impacts by Regression on Population, Affluence, and Technology
TLtechnological level
UCunit cost
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SourceYearMajor FocusMethodology
Zhao, X.L.; Li, N.; et al. [ ]2012Factors Influencing RECLMDI
Liu, Z.G.; Wang, S.S.; et al. [ ]2015Factors Influencing Carbon Emissions in Urban Civil Architecture in China from 1997 to 2007LMDI
Shen, L.Y.; Wu, Y.; et al. [ ]2018EKC Analysis of Carbon Emissions in BeijingEKC + LMDI
Gu, S.; Fu, B.Y.; et al. [ ]2019Factors Influencing CO Emissions in Shanghai from 1995 to 2016 and Forecast of the Decarbonization Potential from 2016 to 2030LMDI + SD
Huang, Y.Z.; Matsumoto, K. [ ]2021Influence of Urbanization on CO Outputs in 30 of China’s Provinces from 1990 to 2016LMDI
Li, H.M., Qiu, P.; et al. [ ]2021Estimation of CO Emissions for Provincial-Level Building Industries and Different Building TypesLMDI
Zhang, Y.; Zhang, Y.X.; et al. [ ]2022Research on Urban Carbon Footprint Drivers and LMDI Decomposition and Forecasting with Three ScenariosLMDI
Gao, G.Y.; Jia, Q.; et al. [ ]2024LMDI Decomposition of CO Emission Factors, Tapio Decoupling Model Analysis, and LEAP Model ForecastingLMDI
SourceYearMajor FocusMethodology
Ma, M.; Shen, L.Y.; et al. [ ]2017LMDI-I Decomposition of Carbon Emissions from Public Buildings in China and STIRPAT Drivers ModelSTIRPAT + LMDI
Yang, S.H.; Liu, J.; et al. [ ]2021Study on the Drivers of Carbon Emissions from Residential Buildings in Four Regions of ChinaLMDI
Ma, M.D.; Yan, R.; et al. [ ]2018Contribution to Drivers of Energy Consumption in Public Buildings and Energy Usage Assessment During the 10th Five-Year Plan PeriodLMDI
SourceYearMajor FocusMethodology
Ma, M.D.; Yan, R.; et al. [ ]2018Analysis of Impact Factors on Public Building Energy Consumption and ESPB Evaluation during the 10th–12th Five-Year Plan PeriodsLMDI
Gan, L.; Liu, Y.; et al. [ ]2022Inequality Analysis of Carbon Output Intensity and Drivers in Public Buildings in China from 2010 to 2019LMDI
Zhang, J.J.; Yan, Z.F.; et al. [ ]2023Analysis of Factors Influencing Carbon Emissions in Public Buildings and the Impact of Economic Growth Level on Operational-Stage Carbon EmissionsLMDI
Zou, Q.; Zeng, G.P.; et al. [ ]2024Major Drivers of Carbon Emissions in Public Buildings in ChangshaSTIRPAT Model + Network Analysis + Spatial Durbin Model
SourceYearMajor FocusMethodology
Zhou, X.; Xu, Z.X.; et al. [ ]2023Analysis of Drivers of Carbon Emissions in Educational Buildings and Definition of Three Typical ScenariosScenario Analysis + LMDI
Laporte, J.P.; Román-Collado, R.; et al. [ ]2024Assessment of Energy Consumption Changes in Chilean Universities from 2017 to 2022STIRPAT
SourceYearMajor FocusMethodology
Zhang, M.; Yan, S.; et al. [ ]2015Study on Factors Influencing Energy Consumption in Commercial Buildings and Decoupling Relationship with Economic DevelopmentLMDI
Ma, M.D.; Cai, W.; et al. [ ]2018Measurement of Decarbonization of Commercial Buildings in ChinaLMDI
Ma, M.D.; Cai, W.G. [ ]2018Kaya Identity Drivers Decomposition of Carbon Footprint in Commercial Buildings in China and Evaluation of CMCCB Values from 2001 to 2015LMDI
Xiang, X.W.; Ma, M.D.; et al. [ ]2022Assessment of Decarbonization Progress in Commercial Buildings Across 16 CountriesLMDI
Ma, M.D.; Feng, W.; et al. [ ]2022Estimation of Decarbonization Levels in Commercial Buildings of China’s Five Major Urban CentersGDI method
SourceYearMajor FocusMethodology
Du, Z.J.; Jiang, X.Y.; et al. [ ]2019Assessment of Energy Consumption in Business Hotel BuildingsSTIRPAT + LMDI
SourceYearMajor FocusMethodology
Lin, B.Q.; Liu, H.X. [ ]2015Identification of Factors Influencing REC and Tapio Decoupling Method for Describing the Decoupling Correlation between REC and Residential Income3D LMDI model
Zhang, M.; Bai, C.Y. [ ]2018Decomposition Analysis of CO Intensity Factors and Assessment of Energy Service Demand for Residential Buildings in China Based on Household SizeLMDI
Ma, M.D.; Ma, X.; et al. [ ]2019Drivers of CO Emissions Under IDALMDI
Balezentis, T. [ ]2020Decoupling Relationships between Drivers of Carbon Footprints in 30 Provinces of China from 2000 to 2015LMDI
Huo, T.F.; Ma, Y.L.; et al. [ ]2021Bottom-Up Analysis of Identifying the Contribution of Energy-Saving Policies to Mesoscale ChangeLMDI
Reuter, M. Narula, K.; et al. [ ]2021Exploration of the Spatiotemporal Rhythm and Driving Mechanisms of Urban Residential Building Carbon Footprints in 30 Provinces of China from 2000 to 2019LMDI
Chen, H.D.; Du, Q.X.; et al. [ ]2023Evaluation of Decarbonization in Residential Buildings in Henan from 2010 to 2020 and Forecast of Carbon Emission Trends and Peak Timing from 2020 to 2050LMDI
Yang, X.; Sima, Y.F.; et al. [ ]2023Research on the Peaks of Carbon Footprints and Decarbonization Path for Residential Buildings in Fujian ProvinceKaya-LMDI
Lin, C.X.; Li, X.J. [ ]2024Comprehensive Assessment Model for CPSIAM and Evaluation of Provincial Total Carbon Emission PeaksKaya-LMDI
Huo, T.F.; Du, Q.X.; et al. [ ]2024Comprehensive Assessment of Carbon Emissions from Lighting and Electrical Appliances in Residential BuildingsLMDI + TD + LEAP
Li, X.J.; Lin, C.X.; et al. [ ]2024Quantification of Factors Influencing Residential Carbon Emissions in Yunnan Province, ChinaLMDI + LEAP
Li, W.Y.; Li, Q.Y.; et al. [ ]2024Identification of Factors Influencing REC and Tapio Decoupling Method for Describing the Decoupling Correlation Between REC and Residential IncomeLMDI
SourceYearMajor FocusMethodology
Gong, Y.Y.; Song, D.Y. [ ]2015Calculation of Full-Life Energy Usage and Carbon Footprints in the Construction Industry of Wuhan CityLCA + LMDI
Lu, Y.J.; Cui, P.; et al. [ ]2016Decomposition Analysis of Incremental Emission Changes and Evaluation of Building Carbon Footprints in China from 1994 to 2012LMDI
Hu, X.C.; Liu, C.L. [ ]2016Factors Influencing Carbon Productivity and a Carbon Productivity Survey of the Australian Building IndustryLMDI
Ma, M.D.; Yan, R.; et al. [ ]2017Evaluation of Energy Consumption per Unit Area and Building Energy Savings in ChinaIPAT-LMDI
Lu, Y.J.; Cui, P.; et al. [ ]2018Three-Dimensional Decomposition of the Total Energy Consumption Changes in the Building IndustryLMDI
Wang, M.; Feng, C. [ ]2018Exploration of the Drivers of Energy-Related CO Emissions in the Building IndustryLMDI
Du, Q.; Lu, X.R.; et al. [ ]2018Analysis of the Industrial Carbon Emissions Characteristics in 30 Provinces of ChinaLMDI
Chen, X.; Shuai, C.Y.; et al. [ ]2020Forecasting Peak Emissions and Investigating the Driving Factors of Carbon Footprints in the Industrial, Building, Transportation, and Agricultural SectorsCKC + LMDI
Li, D.Z.; Huang, G.Y.; et al. [ ]2020Exploring the Factors Influencing Total Carbon Emissions in the Building Industry at the Provincial LevelLMDI
He, J.H.; Yue, Q.; et al. [ ]2020Analysis of the Factors Influencing Carbon Emissions in Three Types of Buildings in China from 2000 to 2005Factor decomposition analysis + LMDI
Zhong, X.Y.; Hu, M.M.; et al. [ ]2021Analysis of the Evolution of Building Energy Consumption Intensity from 1971 to 2014 and Correlation with Economic Growth and the Future Impact of Energy Conservation in 21 Global Territories by 2060LMDI + IAM
Yan, S.H.; Chen, W.G. [ ]2022Decoupling Status and Factors Influencing the Decomposition of CO Emissions under the Construction of the LMDI ModelLMDI
Sun, Z.H.; Ma, Z.L.; et al. [ ]2022Literature Review on Building Carbon Peaks and Carbon NeutralityBibliometric Methods
Jiang, B.Y.; Sun, L.; et al. [ ]2023Introduction of Technological Factors in the Building Sector and and Reconstruction of Impact Variables for CO Emission Fluctuations in Jiangsu Province from 2011 to 2019LMDI
Huo, T.F.; Cong, X.B.; et al. [ ]2023Establishment of an Integrated DEMATEL-ISM ModelDEMATEL-ISM
Shi, Q.W.; Liang, Q.Q.; et al. [ ]2023Simulation of CE Trends Under Economic Dynamics and Building Demand Perspectives, and Exploration of CO Influencing Factors for the Overall and Provincial Building Sector in ChinaLMDI
Zhang, S.X.; Wang, M.P.; et al. [ ]2024Development of a Dynamic Comprehensive Building Carbon Footprint Forecasting Model and Prediction of Building Sector Carbon Emission Trajectories and Probability Distributions for Shandong Province from 2020 to 2050LMDI + SD Model
Zheng, S.M.; He, X.R.; et al. [ ]2024Decoupling Model Study of the Correlation between Building Sector Carbon Emissions and Economic Growth in the Core Economic Region of East ChinaLMDI
Zhao, Q.F.; Wang, T.; et al. [ ]2024Framework Development, Carbon Intensity Methods, and Exploration of CEMPCPSIAM
SourceYearMajor FocusMethodology
Huo, T.F.; Du, Q.X.; et al. [ ]2023STIRPAT-PLS Model Framework Construction and Analysis of Key Factors Affecting Cross-Sector Building Carbon EmissionsSTIRPAT-PLS
Li, Y.; Wang, J.F.; et al. [ ]2023Exploration of Emission Influencing Factors and Future Peak Emission Predictions for China and Its ProvincesGDIM + scenario analysis + Monte Carlo simulation
Xu, F.; Li, X.D.; et al. [ ]20242011–2020 Building Sector Emissions Calculation and Innovative Factor Analysis Model Development for 29 Chinese ProvincesLMDI
SourceYearMajor FocusMethodology
He, H.; Myers, R.J. [ ]2021Building Materials’ Demand DecompositionLMDI
Karakaya, E.; Sarı, E.; et al. [ ]2021Identification of the Primary Factors Influencing the Alterations in DMC and MFLMDI
Application and EvaluationProsCons
Analyzes urban energy use and carbon emissions trends.Handles zero and negative values, provides path-independent results.Requires high-quality data, can be complex to implement at large scales.
Analyzes regional emissions, policy effectiveness, and energy-saving measures.Identifies key drivers of emissions, useful for policy formulation.Limited by data quality, may not capture all local factors.
Evaluates emission reductions, efficiency improvements, and regional disparities.Provides detailed emission reduction insights, supports targeted policy recommendations.May require extensive data for accurate modeling, regional differences can complicate analysis.
Analyzes energy use impacts, policy effectiveness, and technological advancements.Helps in developing specific policies, emphasizes multi-sectoral collaboration.May oversimplify complex interactions, relies on quality data for accurate predictions.
Analyzes global and regional carbon-reduction measures, energy usage patterns.Highlights key factors in emission reductions, supports global and regional comparisons.Different regions and countries have varying decarbonization paths, making comparisons challenging.
Evaluates factors influencing energy use, suggests efficiency improvements.Provides specific recommendations for energy-saving measures, useful for operational improvements.Limited to specific building types, may not account for all operational variations.
Evaluates impacts of material selection, regional characteristics, and development levels.Integrates physical and monetary flows, enhances understanding of material demand drivers.Regional variations can affect analysis, data integration can be complex.
Evaluates decoupling status and effectiveness of policies.Useful for understanding decoupling trends, supports policy evaluation.May not capture all drivers of emissions, focused on economic growth vs. emissions only.
Provides an overview of current research, identifies gaps.Offers comprehensive literature analysis, helps identify future research directions.Limited to existing literature, may miss emerging trends.
Projects emissions under various scenarios, assesses impacts of different policies.Accounts for complex interactions, useful for scenario planning.Can be complex to implement, requires detailed data and modeling expertise.
Forecasts emissions considering various drivers, provides detailed insights.Handles complex systems, integrates multiple factors influencing emissions.High computational demands, data quality issues can affect results.
Forecasts emission reduction potential through collaborative efforts.Identifies potential for significant emission reductions, supports collaborative approaches.Achieving carbon neutrality remains challenging, forecasts may be uncertain.
The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

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Li, Y.; Chen, H.; Yu, P.; Yang, L. The Application and Evaluation of the LMDI Method in Building Carbon Emissions Analysis: A Comprehensive Review. Buildings 2024 , 14 , 2820. https://doi.org/10.3390/buildings14092820

Li Y, Chen H, Yu P, Yang L. The Application and Evaluation of the LMDI Method in Building Carbon Emissions Analysis: A Comprehensive Review. Buildings . 2024; 14(9):2820. https://doi.org/10.3390/buildings14092820

Li, Yangluxi, Huishu Chen, Peijun Yu, and Li Yang. 2024. "The Application and Evaluation of the LMDI Method in Building Carbon Emissions Analysis: A Comprehensive Review" Buildings 14, no. 9: 2820. https://doi.org/10.3390/buildings14092820

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  • Volume 11, Issue 1
  • Research priorities for progressive pulmonary fibrosis in the UK
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  • http://orcid.org/0000-0002-8250-6464 Laura Fabbri 1 , 2 , 3 ,
  • Anne-Marie Russell 4 , 5 ,
  • Nazia Chaudhuri 6 ,
  • Wendy Adams 7 ,
  • Katherine Cowan 8 , 9 ,
  • John Conway 10 ,
  • Wendy Dickinson 11 ,
  • Michael Gibbons 12 ,
  • Simon Hart 13 ,
  • Steve Jones 7 ,
  • Jenny Lynch-Wilson 14 ,
  • Tom McMillan 15 ,
  • Steve Milward 16 ,
  • Maureen Ward 17 ,
  • Louise Elisabeth Wright 7 and
  • http://orcid.org/0000-0002-7929-2119 Gisli Jenkins 1 , 2 , 3
  • 1 National Heart and Lung Institute , Imperial College London Department of Medicine , London , UK
  • 2 Department of Respiratory Medicine , Royal Brompton Hospital , London , UK
  • 3 Nottingham Biomedical Research Centre , National Institute for Health Research , Nottingham , UK
  • 4 College of Medical and Dental Sciences (MDS) University of Birmingham , Birmingham , UK
  • 5 University of Exeter , Exeter , UK
  • 6 University of Ulster Faculty of Life and Health Sciences , Londonderry , UK
  • 7 Action for Pulmonary Fibrosis , Peterborough , UK
  • 8 James Lind Alliance , Southampton , UK
  • 9 Katherine Cowan Consulting Limited , East Sussex , UK
  • 10 Patient Representative , Tooting , UK
  • 11 Carer Representative , Nottingham , UK
  • 12 Respiratory Medicine , Royal Devon & Exeter NHS Foundation Trust , Exeter , UK
  • 13 Respiratory Research Group , Hull York Medical School/University of Hull , Cottingham , UK
  • 14 Hywel Dda University Health Board , Carmarthen , UK
  • 15 Carer Representative , Ballycastle , UK
  • 16 Patient Representative , Bolton , UK
  • 17 Carer Representative , Tameside , UK
  • Correspondence to Dr Laura Fabbri; l.fabbri{at}imperial.ac.uk

Introduction Health research bodies recommend patient involvement and engagement in research and healthcare planning, although their implementation is not yet widespread. This deficiency extends to progressive pulmonary fibrosis (PPF), where crucial aspects remain unknown, including causal mechanisms, curative treatments and optimal symptom management. This study addresses these gaps by seeking stakeholders’ perspectives to guide research and treatment directions.

Method A priority-setting partnership was established to explore stakeholders’ priorities in the diagnosis, treatment, management and care of PPF, including idiopathic pulmonary fibrosis which is the archetypal PPF. Stakeholders included people living with PPF, their carers, relatives and healthcare professionals involved in their management.

Results Through an online open-ended survey, 2542 responses were collected from 638 stakeholders. Thematic analysis identified 48 specific research questions, which were then cross-referenced with academic literature to pinpoint research gaps. Following the evidence check, 44 unanswered questions were shortlisted by 834 stakeholders in a second online survey. Ultimately, a top 10 priority list was established through consensus.

The prioritised research questions include (1) improved diagnosis accuracy and timing, (2) development of new treatments, (3) enhanced accuracy in primary care, (4) optimal timing for drug and non-drug interventions, (5) effective cough treatment, (6) early intervention for PPF, (7) improved survival rates, (8) symptom reduction, (9) impact of interventions on life expectancy and (10) new treatments with reduced side effects.

Conclusion Stakeholders’ priorities can be summarised into five areas: early diagnosis, drug and non-drug treatments, survival and symptom management. Ideally, these topics should guide funding bodies and health policies.

  • interstitial fibrosis
  • idiopathic pulmonary fibrosis

Data availability statement

Data are available on reasonable request.

This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits others to copy, redistribute, remix, transform and build upon this work for any purpose, provided the original work is properly cited, a link to the licence is given, and indication of whether changes were made. See:  https://creativecommons.org/licenses/by/4.0/ .

https://doi.org/10.1136/bmjresp-2024-002368

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WHAT IS ALREADY KNOWN ON THIS TOPIC

Health research bodies recommend the involvement and engagement of stakeholders in research and healthcare planning, but this was not applied to progressive pulmonary fibrosis (PPF), where crucial aspects remain unknown.

WHAT THIS STUDY ADDS

Stakeholders consider early diagnosis, drug and non-drug treatments, survival and symptom management key priority areas for future research in PPF.

HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICY

The highlighted topics should guide the decisions of funding bodies and health policies.

Introduction

Integration of patient and public involvement and engagement (PPIE) was formally identified as an urgent priority about 20 years ago, particularly in the UK, where it represents a founding principle of the National Institute of Health Research (NIHR). 1 Notwithstanding the acknowledged importance of public involvement, its implementation in everyday research has been slow. 2 We know that PPIE can improve healthcare quality, health literacy and patient autonomy, with positive effects on patients’ health and cognitive and emotional empowerment, and it is cost-effective. 3 4

Interstitial lung diseases (ILDs) are a group of fibroinflammatory diseases that lead to inflammation or scar tissue deposition (fibrosis) within the alveolar interstitium. ILDs can be of unknown cause or be associated with other diseases or environmental exposures. 5 They have an incidence of between 1 and 31.5 per 100 000 person-years and a prevalence between 6.3 and 71 per 100 000 people. Some patients can have a chronic and relentless evolution, and the term progressive pulmonary fibrosis (PPF) is used to describe the cases of pulmonary fibrosis (PF) that have a fibrotic phenotype. While recent PPF guidelines refer to ILDs other than idiopathic pulmonary fibrosis (IPF), 6 7 for the purpose of this study, IPF has been included in the definition of PPF as IPF is the archetypal progressive ILD. PPF is associated with worsening respiratory symptoms, a decline in lung function, decreased quality of life and a risk of early death. 8 Many aspects of PPF remain unknown, such as the causal mechanisms, a defined curative treatment or best symptom management. For its severity and poor prognosis, PPF is often compared with cancer. Yet, for years, stakeholders across Europe have reported a lack of services and difficulties in getting a diagnosis, treatment access, holistic care and palliative care, 9 10 care that is more widely available to patients with cancer. 11 12

This study aimed to identify stakeholders’ views on PPF and to prioritise these unknowns to inform policymakers, funders, researchers, industry and others who have the potential to implement the priorities identified.

The priority setting partnership

An established methodology, designed by the James Lind Alliance (JLA), was used. This methodology was developed to bring patients, carers and clinicians together in a priority setting partnership (PSP) to identify uncertainties or unanswered questions about specific health issues. A PSP is a multistep process: data are collected through a first survey and then successively processed to formulate research questions. After a check of the literature, the research questions that still have to be investigated will go through a second survey to be shortlisted. Finally, a ‘top 10’ list of those uncertainties for research is agreed by consensus during a workshop ( figure 1 ). 13

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Schematic representation of James Lind Alliance methodology.

The steering group for our PSP included people diagnosed with PF (n=4), carers (n=3) and healthcare professionals (HCPs) (n=6) with expertise in PPF, who met online 11 times over 2 years. This group led the PSP under the guidance of a JLA’s senior advisor. Steering group members were purposively invited from the charity (Action for Pulmonary Fibrosis) network. The sampling followed a strict balance of group representation (patients, carers, HCPs), geographic and gender distribution. The steering group agreed to limit the scope of the PSP to diagnosis, treatment, management and care of PF. The first survey was limited to the UK, while the second was opened worldwide, although most entries (94%) were received from the UK.

The first survey

Initially, we gathered stakeholders’ questions and uncertainties through an online survey with open-ended questions. The questions, developed with patient partners, reflected the in-scope themes: (a) What questions or concerns about the diagnosis of PF would you like to see answered by research? (b) What questions or concerns about the treatment of PF would you like to see answered by research? (c) What questions or concerns about the care of people affected by PF would you like to see answered by research? Stakeholders included people living with PF, carers, relatives and HCPs involved in their management. A secure Research Electronic Data Capture cloud was used for data collection.

The survey was advertised on social media (Facebook, LinkedIn, Twitter, Instagram), in newsletters, through the patient group networks and support partners and through word of mouth. To ensure the participation of those unfamiliar with technology, paper copies of the survey were mailed to members of patient support groups. Participants had the option to register their interest to receive feedback on the outcomes of the study.

After the closure of the survey, data were anonymised, and a thematic inductive approach was used. LF identified ‘keywords’ themes which were coded generating a codebook. LF and WA identified patterns in the coded data and grouped similar codes to generate overarching themes. The themes were mapped against the preset criteria in and out of scope. From each in-scope theme, a summary research question was generated using consensus agreement from the wider team. In case of disagreement, data were discussed with the independent advisor KC, and decided by three-way consensus. We acknowledge that theme generation can be affected by the perceptions and experiences of individuals analysing data (LF and WA) and include a statement of reflexivity ( online supplemental file 1 ).

Supplemental material

The summary questions were worded in lay language, avoiding jargon, to be understood by lay audiences. The steering group reviewed the list of research questions to determine whether they adequately reflected the survey submissions. Three separate working groups were organised for a first round of reviews, and results were successively discussed collegially and agreed on by steering group consensus. The independent advisor facilitated all meetings in line with the JLA methodology. 13 A targeted literature review was performed to verify the research questions identified in the online survey. We chose a pragmatic approach as a full systematic review was impractical within the timeframe of the PSP. Targeted review criteria were as follows: (a) to ensure retrieval of the most recent literature, searches were restricted from 2015 to 2021, (b) search was limited to English-only articles, studied in humans and restricted to adults, (c) guidelines, systematic reviews, review, articles and articles in-press were included, (d) abstracts, editorials and research letters were excluded. We consulted the databases EMBASE, MEDLINE, CINAHL and Google Scholar. Given the broad scope of our PSP, the research questions that were derived by the above methodology were considered unanswered if there was no systematic review, a recent systematic review indicated insufficient evidence or insufficient evidence outlined in consensus papers. Literature search results were submitted to the JLA Institute for transparency. Results were rediscussed within the steering group. Research questions inadequately covered in the literature were selected for the second survey.

The second survey and the workshop

For the second survey, we asked stakeholders to select up to 10 questions which they considered most important from the 44 derived from the first survey. We used the webpage SurveyMonkey for the poll. 14 The 15 out of 44 top-rated questions selected were subsequently ranked during an online workshop.

Workshop participants were purposively sampled to ensure a balanced representation of people living with PF, carers and HCPs with adequate expertise and representation from all the nations and regions in the UK, as well as gender. The consultation was split over two 3-hour sessions run on consecutive days. Participants were initially divided into four equally representative groups, each supported by a JLA moderator. Each group debated the importance of all questions, evaluating urgency, pros and cons and ranked all 15 questions in order of priority. Results were subsequently merged and rediscussed during a plenary session the following day. The final top 10 ranking was agreed by consensus.

Reporting follows the guideline for priority setting of health research (REPRISE) ( online supplemental file 2 ). 15

Patient and public involvement

Patient and public involvement was the driving force behind this project, which was co-produced by the patient-led charity Action for Pulmonary Fibrosis. Charity representatives had a significant role in designing, recruiting participants and disseminating results. The steering group included people living with the disease and carers, who are also coauthors of this paper.

First survey results

The initial online survey was open from April to May 2021. 638 UK participants completed the survey and generated 2542 single statements/questions. Details about the demographic data are presented in table 1 . HCPs worked in primary (29%), secondary (40%) and tertiary care (21%), and 43% of them had >10 years of experience working with ILDs. Geographic distribution was 81% in England, 6% in Scotland and 5% in Wales and Northern Ireland, respectively.

  • View inline

Demographics (A) participants; (B) self-reported data on underlying ILD; (C) HCPs categories

The in-scope entries were distilled into 48 themes and subsequent research questions. After review and collegial discussion by the steering group, 44 questions ( box 1 ) were shortlisted for the second survey.

Unresolved research questions

What tests and tools (eg, blood tests, lung function, imaging, virtual and artificial technology) can predict the progression of progressive pulmonary fibrosis (PPF)?

How many people live with different types of PPF in the UK?

How can acute deteriorations of PPF be predicted in patients with PPF?

Can new treatments for PPF be developed with reduced side effects? Does how the drug is delivered (eg, oral, nebulised, through a vein) affect potential side effects of the drug in PPF?

Can treatments halt or reverse PPF?

What are the increased medical risks following a diagnosis of PPF during certain medical procedures (eg, anaesthesia), and how can these be reduced or eliminated?

How should exercise programmes and pulmonary rehabilitation be delivered to best improve symptoms and quality of life in PPF?

How can the delivery of portable and home-based oxygen be improved (digital monitors, remote control, lighter weight, quieter, higher flow rates) for patients with PPF?

What is the best time to refer to occupational therapy to benefit quality of life and improve planning for the future for patients with PPF and their carers?

What are the biological changes in human cells that lead to the development of PPF?

What can be done to improve the speed and accuracy of PPF diagnosis in primary care (eg, training, integration of case-based studies in general practice training, awareness campaigns)? 

How can we use new technology (eg, artificial intelligence) to help inform diagnosis and prognosis of PPF?

What is the best time for drug and non-drug interventions (pulmonary rehabilitation, oxygen therapy, psychological support) to start to preserve quality and length of life for patients with PPF?

To what extent do different interventions (medication, pulmonary rehabilitation, oxygen therapy, psychological support) impact length of life in patients with PPF? 

What is the best management of acute deterioration in PPF?

How can treatments be tailored for individual patients with PPF?

What forms of education and training for healthcare professionals could improve the way patients and families are informed of the diagnosis of PPF?

Can non-drug interventions (eg, yoga, singing, relaxation techniques, acupuncture, herbal remedies, etc) improve well-being, symptoms management and survival in PPF?

Does diet help with the management of PPF symptoms?

What treatments (drug, non-drug and aids) can reduce breathlessness and phlegm production in PPF?

Does psychological well-being affect PPF disease progression?

What type of support (psychological, peer, drug) is most effective at reducing feelings of isolation, depression and anxiety in patients, carers and families affected by PPF?

Are there health inequalities in access to care for PPF (eg, ethnic minorities or gender differences)? If so how can these be reduced?

What tests and tools (eg, blood tests, lung function, imaging, virtual and artificial technology) should be used to monitor progression of PPF?

What are the most effective ways to reduce or manage side effects from medications used to treat PPF?

How can other co-existing medical conditions (comorbidities) be managed in people living with PPF?

How can the diagnosis of PPF be improved in terms of accuracy and the time taken (screening programme, early signs and symptoms that could be detected in primary care, blood markers, imaging, biopsy, artificial intelligence, etc)?

What is the optimum timing for lung transplantation in PPF?

What treatments (drug, non-drug and aids) can treat cough in PPF?

Would early treatment delay progression, lung function decline and improve survival in PPF?

Which therapies will improve survival in PPF?

How can palliative care support be more acceptable for people living with PPF, and when should this be proposed? 

Can the likelihood of developing PPF be predicted through genetic screening?

How does geography impact on the quality of care that a person with PPF receives?

What is the most effective multidisciplinary team structure and function to support patients and families affected by PPF?

What are the psychological consequences of a diagnosis of PPF for patients, their families and carers?

Can oxygen improve quality of life and outcomes in PPF?

How can the discussion and management of end of life in PPF be improved so that patients and families feel better prepared and supported?

How can peer support (support groups, befrienders, friends) impact disease management for patients with PPF and their carers?

What support (eg, information and training, financial, psychological, etc) would enable carers of patients with PPF to feel empowered in their role?

To what extent can different interventions (medication, pulmonary rehabilitation, oxygen therapy, psychological support) impact quality of life in patients with PPF? 

How effective are different treatments at treating different types of PPF?

Can drugs used to treat other diseases be effective in treating PPF?

Can treatments other than pirfenidone and nintedanib slow the progression of PPF?

Initial 44 questions identified by the first survey, after the targeted literature review.

Note, the order is random, no priorities.

Second survey results

The second survey was online in April and May 2022. 834 stakeholders took part in this survey and submitted their selections. Details about the demographic data are reported in table 1 . In this survey, HCPs were mainly from tertiary (45%) and secondary (40%) care, and 49% of them had >10 years of experience working with ILDs. Geographical distribution was 77.7% in England, 8.2% in Wales, 6.2% in Scotland, 4.6% in Northern Ireland and 3.2% outside the UK.

Notably, the top 15 ranking questions shortlisted during this survey were equivalent across people living with the disease, carers and HCPs ( table 2 ).

Interim rankings for the top 15 research questions (top questions for each group from the long list of 44)

In June 2022, 15 out of the 44 most voted-for questions were discussed during an online workshop, where the priorities were ranked to define a top 10 ( table 3 ). This was done by 22 stakeholders—7 living with PF, 4 carers, 8 HCPs and 3 who fitted more than one category (eg, carer and HCP). All of them were recruited in the UK.

Top 10 research priorities for progressive pulmonary fibrosis (PPF)

Within the top 10 selections, we identified 5 main themes.

Diagnosis (questions 1 and 3) : stakeholders acknowledged the challenges of getting an early diagnosis. Early detection is desirable and may occur through screening programmes, or tests with high sensitivity and specificity. An important point highlighted is to prioritise the education of primary care HCPs to recognise early signs and red flags for a swift referral to specialist centres. Stakeholders highlighted misdiagnosis causing delays in referral to specialist services, as initial symptoms such as dyspnoea and cough are not specific to PF.

Drug treatments (questions 2, 6 and 10) : new drug development was a pivotal priority, particularly addressing the need for a cure. Research should strive to stop and reverse the fibrotic process. At the time of the survey, in the UK, antifibrotic prescribing for IPF was restricted to those with a forced vital capacity (FVC) between 50% and 80% of predicted values. It was therefore deemed critical by stakeholders to explore the need for more data about the optimal timing to start treatment. Stakeholders wanted to know the correct timing to start treatment to prevent the progression of the disease, reduce the decline in lung functions and improve the survival rate. The uncertainties about timing were also impacted by concerns related to the side effects of treatment and the impact on the patient’s quality of life. Stakeholders identified the need for new treatments or new administration routes with reduced side effects.

Non-pharmacological treatments (questions 4 and 9) : stakeholders highlighted concerns regarding the side effects of drugs and their impact on quality of life as a reason for significant interest in non-pharmacological approaches to management, including pulmonary rehabilitation, oxygen therapy, psychological support and peer support. It was acknowledged that there may be insufficient data on the efficacy and best timing for these approaches, particularly pertinent to people who could not tolerate drug therapy or would like to explore other alternative types of therapy.

Survival (question 7) : poor prognosis was highlighted by stakeholders as a key distressing point, with ‘3–5 years survival’ as a recurrent statistic used in healthcare conversations. Therefore, identifying novel therapies to improve survival was deemed a valid research point on its own, irrespective of current pharmacological and non-pharmacological treatments.

Symptom management (questions 5 and 8) : symptoms caused by PF can be disabling. Productive cough and dyspnoea impact the quality of life and are perceived as a cause of stigma. Stakeholders are interested in any possible treatment, including drug, non-drug or aids that could reduce these symptoms or help manage them.

The research question about the causes of PF, worded as ‘What are the biological changes?’ was not included in the top 10. Other excluded themes discussed during the workshop that were considered necessary but did not reach the priority of the top 10 are the prediction and management of acute exacerbation, the efficacy of genetic screening and how to improve oxygen devices ( table 2 ).

Qualitative work has explored broad concepts related to clinical care pathways, but it is often limited to small groups 15 16 or to countries outside the UK. 16 We acknowledge that patient populations worldwide have similar needs. Still, there are different nuances due to the structure of health service provision and deficits in many areas of health service provision. 17

The design of this project was developed at a time when there was ongoing discussion about grouping ILD based on their phenotypes. In the subsequent years, experts deliberated on this issue, which eventually led to the publication of documents by ATS and ERS, although with some controversy. 18 It is important to mention that we included both IPF and non-IPF fibrotic ILD in our definition of PPF.

Our primary strength is the coproduction with the patient-led groups, allowing us to distribute the survey capillary with broad coverage. To ensure that participants who were less familiar with technology could be included, we were not limited to an online survey and included paper copies. The JLA offers a robust methodology focused on research priorities, ensuring that future research is patient-centred. From our study, the first in the UK with a broad cohort and following the JLA methodology, stakeholders consider that early diagnosis, new drug and non-drug treatments, survival and symptom management require prioritisation.

Early diagnosis was the highest ranked priority. Delays in the diagnostic pathway are a well-recognised problem worldwide. 19–21 The time from the onset of symptoms to diagnosis can reach up to 24 months. 19 Delayed diagnosis has been proven to negatively impact progression-free survival, quality of life and hospitalisation rates in patients with IPF. 19 Delays may happen in several stages of the diagnostic pathway, due to under-reporting of ILD features on diagnostic testing and prolonged time to pulmonology referral even when ILD is reported. 22 As reported by a similar study in Australia, 16 there is an educational need for training for primary care HCPs and also a research interest in new technologies, such as biomarkers, artificial intelligence and imaging, which can be used to detect ILD earlier. 23 24

After diagnosis, finding a treatment to cure fibrosis is a priority. Pirfenidone and nintedanib represented a paradigm shift in managing IPF and progressive fibrotic ILD, but stakeholders require fibrosis to be stopped and reversed—slowing it down is not enough. Future research might consider targeting distinct pathogenetic pathways or focusing on alveolar regenerative medicine. 25 Other approaches to consider are combining treatments or subcategorising patients according to comorbidities and biomarkers for tailored care. 26

The best timing of antifibrotic treatment was deemed a priority specifically related to the NICE requirements about the FVC threshold for an antifibrotic prescription, which applied when we ran the survey. At the time of the survey, FVC had to be between 50% and 80% of the predicted value to be eligible for antifibrotics prescription. To date, in the UK, these limits still apply to pirfenidone, while for nintedanib the 80% threshold has been removed for patients with IPF and its licence has been extended to progressive fibrotic ILD. 27 28 Antifibrotics slow the loss of lung function, and there is evidence that early treatment may also improve survival. However, these data require further investigation, as they may be misinterpreted due to lead-time bias: earlier detection may only move forward the time of a patient’s treatment start without moving back the time of death. 26 29 30

Furthermore, we should not overlook the downside of antifibrotics, which emerged in the priorities listed. Side effects, particularly gastrointestinal ones, can affect up to 30% of patients and impact their quality of life. 31 Although patients try to cope with them, they are the main reason why patients stop pharmacological treatment. 32 33 Reducing and managing side effects is one of the priorities listed.

Besides the pharmacological approach, our stakeholder group also prioritised non-drug management scenarios. The benefits of a holistic approach, including pulmonary rehabilitation, oxygen supplementation, palliative interventions, lung transplant, psychological support and peer support, have not been sufficiently proven and quantified. 34 There is some evidence for pulmonary rehabilitation and oxygen, 35–37 but there are still unanswered questions. This applies especially to symptom management, cough and dyspnoea, which are perceived as invalidating and stigmatising. 38

Some of the priorities listed are similar to those identified by Tikellis et al , 16 particularly those related to the patients’ experience with delayed diagnosis, symptom management, drug side effects and the need for a cure. These similarities suggest that countries with developed healthcare systems have common priorities, and it may not be necessary to repeat local consultation but to dedicate resources for specific service improvements. Differently from the Australian colleagues, we purposefully excluded researchers from the workshop participants to reduce the risk of bias and amplify the voices of stakeholders who do not usually influence the research agenda (as per JLA principles). This may be the reason why stakeholders deprioritised the question about the importance of basic science and translational medicine, not apparent to the general public. This finding should prompt the development of public engagement activities in basic science. Similarly, acute exacerbations were deemed of interest only by HCPs, who are used to managing them, while for patients and carers, acute exacerbations represent only the inevitable end point. Likewise, oxygen devices were considered of interest only for patients with more severe diseases and, therefore, deprioritised during the discussion. An interesting and polarising point of discussion was genetic screenings. Some participants wished this was widely available to test their children, while others had strong positions against it in the context of no cure available. However, a previous study showed that relatives of patients with PF who undergo screening for early disease do not regret the experience. 39

We acknowledge the limits of our investigation. For pragmatic reasons, we predefined the topics to be considered in scope. Despite our best efforts to involve a diverse and representative population, linguistic barriers may have prevented some people from taking part, as surveys and workshops were available only in English. Also, since the participants were all volunteers, there may have been a self-selection bias, with only highly motivated people participating in the research. We campaigned to enrol people living with different types of PF. Still, IPF represented the majority (69% and 62%) of the survey participants and their opinions may have dominated the inputs compared with non-IPF participants. Given the nature of the data (participants inputted their own data; no medical records were consulted), we cannot comment on the severity or progression of their condition or exclude that some participants had a more stable disease, which might not be defined as progressive. The top 10 priorities were agreed on through consensus in a workshop, and participants were purposively invited to balance the different stakeholders’ groups (patients, carers and HCPs), geographic distribution and gender. To reduce bias, researchers were excluded from the recruitment and data collection for the workshop, and the charity Action for Pulmonary Fibrosis invited the participants from their network. We cannot exclude that the sampling of stakeholders influenced the priority list, and a different cohort of participants with different experiences and expertise in PPF may have chosen different priorities.

Our study identified a comprehensive list of topics which have yet to be adequately investigated, including the diagnosis, treatment, management and care of PPF. Stakeholders consider that early diagnosis, new drug and non-drug treatments, survival and symptom management require prioritisation. Our findings should ideally guide funding bodies, health policies and researchers to ensure resources are focused on projects that matter to the people affected by PPF.

Ethics statements

Patient consent for publication.

Not applicable.

Ethics approval

This project was reviewed by the Faculty of Medicine and Health Sciences’ research ethics committee at the University of Nottingham (ethics reference FMHS 101-1020) and considered exempt.

Acknowledgments

The authors would like to thank the family of Mr Ian Foote, steering group member, who prematurely died before the completion of this project. The authors are thankful for all the support offered by the UK, European and International patient charities that advertised our surveys within their network. The authors would also like to thank Lucy Howard and Glenn Hearson from the University of Nottingham for their work in setting up the first survey.

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X @istamina, @IPFdoc

Contributors Study conception and design: LF, A-MR, NC, WA, KC, JC, WD, MG, SH, SJ, JL-W, TMcM, SM, MW, LEW, GJ; data collection: LF, WA, LW, GJ; analysis and interpretation of results: LF, A-MR, NC, WA, KC, JC, WD, MG, SH, SJ, JL-W, TMcM, SM, MW, LEW, GJ; draft manuscript preparation: LF, A-MR, NC, WA, KC, GJ. All authors reviewed the results and approved the final version of the manuscript. LF is responsible for the overall content as guarantor.

Funding This work was supported by the NIHR Research Professorship awarded to Professor GJ (P-2017-08-ST2-014).

Competing interests AMR discloses payment or honoraria for lectures, presentations, speakers bureaus, manuscript writing or educational events from Boehringer Ingelheim, Hoffman La Roche, Irish Lung Fibrosis Association, Aerogen. Support for attending meetings and travel from Boehringer Ingelheim, Hoffman La Roche, Interstitial Lung Disease Interdisciplinary Network. GJ discloses grants or contracts from any entity from AstraZeneca, Biogen, Galecto, GlaxoSmithKline, Nordic Biosciences, RedX, Pliant; consulting fees from Apollo Therapeutics, AstraZeneca, Brainomix. Bristol Myers Squibb, Chiesi, Cohbar, Daewoong, GlaxoSmithKline, Veracyte, Resolution Therapeutics, Pliant; payment or honoraria for lectures, presentations, speakers bureaus, manuscript writing or educational events from Boehringer Ingelheim, Chiesi, Roche, PatientMPower, AstraZeneca; payment for expert testimony from Pinsent Masons; participation on a Data Safety Monitoring Board or Advisory Board with Boehringer Ingelheim, Galapagos, Vicore; leadership or fiduciary role in other board, society, committee or advocacy group, paid or unpaid with NuMedii and Action for Pulmonary Fibrosis.

Patient and public involvement Patients and/or the public were involved in the design, or conduct, or reporting, or dissemination plans of this research. Refer to the 'Methods' section for further details.

Provenance and peer review Not commissioned; externally peer reviewed.

Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.

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