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Reporting Participant Characteristics in a Research Paper

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A report on a scientific study using human participants will include a description of the participant characteristics. This is included as a subsection of the “Methods” section, usually called “Participants” or “Participant Characteristics.” The purpose is to give readers information on the number and type of study participants, as a way of clarifying to whom the study findings apply and shedding light on the generalizability of the findings as well as any possible limitations. Accurate reporting is needed for replication studies that might be carried out in the future.

The “Participants” subsection should be fairly short and should tell readers about the population pool, how many participants were included in the study sample, and what kind of sample they represent, such as random, snowball, etc. There is no need to give a lengthy description of the method used to select or recruit the participants, as these topics belong in a separate “Procedures” subsection that is also under “Methods.” The subsection on “Participant Characteristics” only needs to provide facts on the participants themselves.

Report the participants’ genders (how many male and female participants) and ages (the age range and, if appropriate, the standard deviation). In particular, if you are writing for an international audience, specify the country and region or cities where the participants lived. If the study invited only participants with certain characteristics, report this, too. For example, tell readers if the participants all had autism, were left-handed, or had participated in sports within the past year.

Related: Finished preparing the methods sections for your research paper ? Find out why the “Methods” section is so important now!

Next, use your judgment to identify other pieces of information that are relevant to the study. For a detailed tutorial on reporting “Participant Characteristics,” see Alice Frye’s “Method Section: Describing participants.” Frye reminds authors to mention if only people with certain characteristics or backgrounds were included in the study. Did all the participants work at the same company? Were the students at the same school? Did they represent a range of socioeconomic backgrounds? Did they come from both urban and rural backgrounds? Were they physically and emotionally healthy? Similarly, mention if the study sample excluded people with certain characteristics.

If you are going to examine any participant characteristics as factors in the analysis, include a description of these. For instance, if you plan to examine the influence of teachers’ years of experience on their attitude toward new technology, then you should report the range of the teachers’ years of experience. If you plan to study how children’s socioeconomic level relates to their test scores, you should briefly mention that the children in the sample came from low, middle, and high-income backgrounds. Finally, mention whether the participants participated voluntarily. Include information on whether they gave informed consent (if the participants were children, mention that their parents consented to their participation). Also, mention if the participants received any sort of compensation or benefit for their participation, such as money or course credit.

Case Studies and Qualitative Reports

Case studies and qualitative reports may have only a few participants or even a single participant. If there is space to do so, you can write a brief background of each participant in the “Participants” section and include relevant information on the participant’s birthplace, current place of residence, language, and any life experience that is relevant to the study theme. If you have permission to use the participant’s name, do so. Otherwise, use a different name and add a note to readers that the name is a pseudonym. Alternatively, you might label the participants with numbers (e.g., Student 1, Student 2) or letters (e.g., Doctor A, Doctor B, etc.), or use initials to identify them (e.g., KY, JM).

Use Past Tense

Remember to use past tense when writing the “Participants” section . This is because you are describing what the participants’ characteristics were at the time of data collection . By the time your article is published, the participants’ characteristics may have changed. For example, they may be a year older and have more work experience. Their socioeconomic level may have changed since the study. In some cases, participants may even have passed away. While characteristics like gender and race are either unlikely or impossible to change, the whole section is written in the past tense to maintain a consistent style and to avoid making unsupported claims about what the participants’ current status is.

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APA Methods Section – How To Write It With Examples

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APA-Methods-Section-01

The APA methods section is a very important part of your academic paper, displaying how you conducted your research by providing a precise description of the methods and procedures you used for the study. This section ensures transparency, allowing other researchers to see exactly how you conducted your experiments. In APA style , the methods section usually includes subsections on participants, materials or measures, and procedures. This article discusses the APA methods section in detail.

Inhaltsverzeichnis

  • 1 APA Methods Section – In a Nutshell
  • 2 Definition: APA Methods Section
  • 3 APA Methods Section: Structure
  • 4 APA Methods Section: Participants
  • 5 APA Methods Section: Materials
  • 6 APA Methods Section: Procedure

APA Methods Section – In a Nutshell

  • The APA methods section covers the participants, materials, and procedures.
  • Under the ‘Participants’ heading of the APA methods section, you should state the relevant demographic characteristics of your participants.
  • Accurately reporting the facts of the study can help other researchers determine how much the results can be generalized.

Definition: APA Methods Section

The APA methods section describes the procedures you used to carry out your research and explains why particular processes were selected. It allows other researchers to replicate the study and make their own conclusions on the validity of the experiment.

APA Methods Section: Structure

  • The main heading of the APA methods section should be written in bold and should be capitalized. It also has to be centered.
  • All subheadings should be aligned to the left and must be boldfaced. You should select subheadings that are suitable for your essay, and the most commonly used include ‘Participants’, ‘Materials’, and ‘Procedure’.

Heading formats:

APA format has certain requirements for reporting different research designs. You should go through these guidelines to determine what you should mention for research using longitudinal designs , replication studies, and experimental designs .

APA Methods Section: Participants

Under this subheading, you will have to report on the sample characteristics, the procedures used to collect samples, and the sample size selected.

Subject or Participant Characteristics

In academic studies, ‘participants’ refers to the people who take part in a study. If animals are used instead of human beings, the researcher can use the term ‘subjects’. In this subheading of the APA methods section, you have to describe the demographic characteristics of the participants, including their age, sex, race, ethnic group, education level, and gender identity. Depending on the nature of the study, other characteristics may be important. Some of these include:

  • Education levels
  • Language preference
  • Immigration status

By describing the characteristics of the participants, readers will be able to determine how much the results can be generalized. Make sure you use bias-free language when writing this part of the APA methods section.

The study included 100 homosexual men and 100 homosexual women aged between 30 and 50 years from the city of London, UK.

Sampling Procedures

When selecting participants for your study, you will have to use certain sampling procedures. If the study could access all members of the population, you can say that you used random sampling methods. This section of the APA methods section should cover the percentage of respondents who participated in the research, and how they were chosen. You also need to state how participants were compensated and the ethical standard followed.

  • Transgender male students from London were invited to participate in a study.
  • Invites were sent to the students via email, social media posts, and posters in the schools.
  • Each participant received $10 for the time spent in the study.
  • The research obtained ethical approval before the participants were recruited.

Sample Size and Statistical Power

In this part of the APA methods section, you should give details on the sample size and statistical power you aimed at achieving. You should mention whether the final sample was the same as the intended sample. This section should show whether your research had enough statistical power to find any effects.

  • The study aimed at a statistical power of 75% to detect an effect of 10% with an alpha of .05.
  • 200 participants were required, and the study fulfilled these conditions.

APA Methods Section: Materials

Readers also need to know the materials you used for the study. This part of the APA methods section will give other researchers a good picture of the methods used to conduct the study.

Primary and secondary measures

Here, you should indicate the instruments used in the study, as well as the constructs they were meant to measure. Some of these are inventories, scales, tests, software, and hardware. Make sure you cover the following aspects:

  • Reliability
  • The Traumatic Stress Schedule (TSS) was used to measure the exposure to traumatic events.
  • This 10-item chart requires participants to report lifelong exposure to traumatic stress.
  • For example, they could indicate whether they suffered the traumatic death of a loved one.
  • The Davidson Trauma Scale was also used to assess the symptoms of trauma.

Under this subheading of the APA methods section, you should also mention covariates or additional variables that can explain the outcomes.

Quality of measurements

You can mention the strategies you applied to ensure data integrity and reliability. These may include:

  • Training the interviewers
  • Establishing clear data nominalization procedures
  • Rigorous data handling and analysis processes
  • Having multiple people assess the data

If the data was subjectively coded, you should indicate the interrater reliability scores in the APA methods section.

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APA Methods Section: Procedure

This part of the APA methods section indicates the methods you used to carry out the research, process the data, and analyze the results.

Research Design and Data Collection Methods

Data collection is the systematic gathering of observations and measurements, and you have to describe all procedures used in this process. You can use supplementary materials to describe long and complicated data collection methods.

When reporting the research design, you should mention the framework of the study. This could be experimental, longitudinal, correlational, or descriptive. Additionally, you should mention whether you used a between-subjects design or within-subjects design .

In this part of the APA methods section, you should also mention whether any masking methods were used to hide condition assignments from the participants.

  • Participants are told the research takes an hour covers their personal experiences in school.
  • They were assured that the reports would be confidential and were asked to give consent.
  • The participants were asked to fill in questionnaires .
  • The control group was given an unrelated filler task, after which they filled a questionnaire.
  • It was determined the experiences of homosexual and CIS-gendered students varied.

Data diagnostics

This part of the APA method section outlines the steps taken to process the data. It includes:

  • Methods of identifying and controlling outliers
  • Data transformation procedures
  • Methods of compensating for missing values

Analytic strategies

This subheading of the APA methods section describes the analytic strategies used, but you shouldn’t mention the outcomes. The primary and secondary hypotheses use past studies or theoretical frameworks , while exploratory hypotheses focus on the data in the study.

We started by assessing the demographic differences between the two groups. We also performed an independent samples t-test on the test scores .

What are the parts of an APA methods section?

In this section, you should include the study participants, the methods used, and the procedures.

What is included in the APA methods section?

The methods section covers the participants or subject characteristics, the sampling procedures, the sample size, the measures used, the data collection methods, the research design, the data analysis strategy, and the data processing method.

Should I use the Oxford comma when writing the APA methods section?

Yes, the serial comma is required when writing the APA methods section.

Should I use the first person to write the APA methods section?

Yes, the APA language guidelines encourage researchers to use first-person pronouns when writing the methods section.

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Method section

Your method section provides a detailed overview of how you conducted your research. Because your study methods form a large part of your credibility as a researcher and writer, it is imperative that you be clear about what you did to gather information from participants in your study.

With your methods section, as with the sections above, you want to walk your readers through your study almost as if they were a participant. What happened first? What happened next?

The method section includes the following sub-sections.

I. Participants: Discuss who was enrolled in your experiment. Include major demographics that have an impact on the results of the experiment (i.e. if race is a factor, you should provide a breakdown by race). The accepted term for describing a person who participates in research studies is a participant not a subject.

II. Apparatus and materials: The apparatus is any equipment used during data collection (such as computers or eye-tracking devices). Materials include scripts, surveys, or software used for data collection (not data analysis). It is sometimes necessary to provide specific examples of materials or prompts, depending on the nature of your study.

III. Procedure: The procedure includes the step-by-step how of your experiment. The procedure should include:

  • A description of the experimental design and how participants were assigned conditions.
  • Identification of your independent variable(s) (IV), dependent variable(s) (DV), and control variables. Give your variables clear, meaningful names so that your readers are not confused.
  • Important instructions to participants.
  • A step-by-step listing in chronological order of what participants did during the experiment.

Results section

The results section is where you present the results of your research-both narrated for the readers in plain English and accompanied by statistics.

Note : Depending on the requirements or the projected length of your paper, sometimes the results are combined with the discussion section.

Organizing Results

Continue with your story in the results section. How do your results fit with the overall story you are telling? What results are the most compelling? You want to begin your discussion by reminding your readers once again what your hypotheses were and what your overall story is. Then provide each result as it relates to that story. The most important results should go first.

Preliminary discussion: Sometimes it is necessary to provide a preliminary discussion in your results section about your participant groups. In order to convince your readers that your results are meaningful, you must first demonstrate that the conditions of the study were met. For example, if you randomly assigned subjects into groups, are these two groups comparable? You can't discuss the differences in the two groups until you establish that the two groups can be compared.

Provide information on your data analysis: Be sure to describe the analysis you did. If you are using a non-conventional analysis, you also need to provide justification for why you are doing so.

Presenting Results : Bem (2006) recommends the following pattern for presenting findings:

  • Remind readers of the conceptual hypotheses or questions you are asking
  • Remind readers of behaviors measured or operations performed
  • Provide the answer/result in plain English
  • Provide the statistic that supports your plain English answer
  • Elaborate or qualify the overall conclusion if necessary

Writers new to psychology and writing with statistics often dump numbers at their readers without providing a clear narration of what those numbers mean. Please see our Writing with Statistics handout for more information on how to write with statistics.

Discussion section

Your discussion section is where you talk about what your results mean and where you wrap up the overall story you are telling. This is where you interpret your findings, evaluate your hypotheses or research questions, discuss unexpected results, and tie your findings to the previous literature (discussed first in your literature review). Your discussion section should move from specific to general.

Here are some tips for writing your discussion section.

  • Begin by providing an interpretation of your results: what is it that you have learned from your research?
  • Discuss each hypotheses or research question in more depth.
  • Do not repeat what you have already said in your results—instead, focus on adding new information and broadening the perspective of your results to you reader.
  • Discuss how your results compare to previous findings in the literature. If there are differences, discuss why you think these differences exist and what they could mean.
  • Briefly consider your study's limitations, but do not dwell on its flaws.
  • Consider also what new questions your study raises, what questions your study was not able to answer, and what avenues future research could take in this area.

Example: Here is how this works.

References section

References should be in standard APA format. Please see our APA Formatting guide for specific instructions.

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Research Design | Step-by-Step Guide with Examples

Published on 5 May 2022 by Shona McCombes . Revised on 20 March 2023.

A research design is a strategy for answering your research question  using empirical data. Creating a research design means making decisions about:

  • Your overall aims and approach
  • The type of research design you’ll use
  • Your sampling methods or criteria for selecting subjects
  • Your data collection methods
  • The procedures you’ll follow to collect data
  • Your data analysis methods

A well-planned research design helps ensure that your methods match your research aims and that you use the right kind of analysis for your data.

Table of contents

Step 1: consider your aims and approach, step 2: choose a type of research design, step 3: identify your population and sampling method, step 4: choose your data collection methods, step 5: plan your data collection procedures, step 6: decide on your data analysis strategies, frequently asked questions.

  • Introduction

Before you can start designing your research, you should already have a clear idea of the research question you want to investigate.

There are many different ways you could go about answering this question. Your research design choices should be driven by your aims and priorities – start by thinking carefully about what you want to achieve.

The first choice you need to make is whether you’ll take a qualitative or quantitative approach.

Qualitative research designs tend to be more flexible and inductive , allowing you to adjust your approach based on what you find throughout the research process.

Quantitative research designs tend to be more fixed and deductive , with variables and hypotheses clearly defined in advance of data collection.

It’s also possible to use a mixed methods design that integrates aspects of both approaches. By combining qualitative and quantitative insights, you can gain a more complete picture of the problem you’re studying and strengthen the credibility of your conclusions.

Practical and ethical considerations when designing research

As well as scientific considerations, you need to think practically when designing your research. If your research involves people or animals, you also need to consider research ethics .

  • How much time do you have to collect data and write up the research?
  • Will you be able to gain access to the data you need (e.g., by travelling to a specific location or contacting specific people)?
  • Do you have the necessary research skills (e.g., statistical analysis or interview techniques)?
  • Will you need ethical approval ?

At each stage of the research design process, make sure that your choices are practically feasible.

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Within both qualitative and quantitative approaches, there are several types of research design to choose from. Each type provides a framework for the overall shape of your research.

Types of quantitative research designs

Quantitative designs can be split into four main types. Experimental and   quasi-experimental designs allow you to test cause-and-effect relationships, while descriptive and correlational designs allow you to measure variables and describe relationships between them.

With descriptive and correlational designs, you can get a clear picture of characteristics, trends, and relationships as they exist in the real world. However, you can’t draw conclusions about cause and effect (because correlation doesn’t imply causation ).

Experiments are the strongest way to test cause-and-effect relationships without the risk of other variables influencing the results. However, their controlled conditions may not always reflect how things work in the real world. They’re often also more difficult and expensive to implement.

Types of qualitative research designs

Qualitative designs are less strictly defined. This approach is about gaining a rich, detailed understanding of a specific context or phenomenon, and you can often be more creative and flexible in designing your research.

The table below shows some common types of qualitative design. They often have similar approaches in terms of data collection, but focus on different aspects when analysing the data.

Your research design should clearly define who or what your research will focus on, and how you’ll go about choosing your participants or subjects.

In research, a population is the entire group that you want to draw conclusions about, while a sample is the smaller group of individuals you’ll actually collect data from.

Defining the population

A population can be made up of anything you want to study – plants, animals, organisations, texts, countries, etc. In the social sciences, it most often refers to a group of people.

For example, will you focus on people from a specific demographic, region, or background? Are you interested in people with a certain job or medical condition, or users of a particular product?

The more precisely you define your population, the easier it will be to gather a representative sample.

Sampling methods

Even with a narrowly defined population, it’s rarely possible to collect data from every individual. Instead, you’ll collect data from a sample.

To select a sample, there are two main approaches: probability sampling and non-probability sampling . The sampling method you use affects how confidently you can generalise your results to the population as a whole.

Probability sampling is the most statistically valid option, but it’s often difficult to achieve unless you’re dealing with a very small and accessible population.

For practical reasons, many studies use non-probability sampling, but it’s important to be aware of the limitations and carefully consider potential biases. You should always make an effort to gather a sample that’s as representative as possible of the population.

Case selection in qualitative research

In some types of qualitative designs, sampling may not be relevant.

For example, in an ethnography or a case study, your aim is to deeply understand a specific context, not to generalise to a population. Instead of sampling, you may simply aim to collect as much data as possible about the context you are studying.

In these types of design, you still have to carefully consider your choice of case or community. You should have a clear rationale for why this particular case is suitable for answering your research question.

For example, you might choose a case study that reveals an unusual or neglected aspect of your research problem, or you might choose several very similar or very different cases in order to compare them.

Data collection methods are ways of directly measuring variables and gathering information. They allow you to gain first-hand knowledge and original insights into your research problem.

You can choose just one data collection method, or use several methods in the same study.

Survey methods

Surveys allow you to collect data about opinions, behaviours, experiences, and characteristics by asking people directly. There are two main survey methods to choose from: questionnaires and interviews.

Observation methods

Observations allow you to collect data unobtrusively, observing characteristics, behaviours, or social interactions without relying on self-reporting.

Observations may be conducted in real time, taking notes as you observe, or you might make audiovisual recordings for later analysis. They can be qualitative or quantitative.

Other methods of data collection

There are many other ways you might collect data depending on your field and topic.

If you’re not sure which methods will work best for your research design, try reading some papers in your field to see what data collection methods they used.

Secondary data

If you don’t have the time or resources to collect data from the population you’re interested in, you can also choose to use secondary data that other researchers already collected – for example, datasets from government surveys or previous studies on your topic.

With this raw data, you can do your own analysis to answer new research questions that weren’t addressed by the original study.

Using secondary data can expand the scope of your research, as you may be able to access much larger and more varied samples than you could collect yourself.

However, it also means you don’t have any control over which variables to measure or how to measure them, so the conclusions you can draw may be limited.

As well as deciding on your methods, you need to plan exactly how you’ll use these methods to collect data that’s consistent, accurate, and unbiased.

Planning systematic procedures is especially important in quantitative research, where you need to precisely define your variables and ensure your measurements are reliable and valid.

Operationalisation

Some variables, like height or age, are easily measured. But often you’ll be dealing with more abstract concepts, like satisfaction, anxiety, or competence. Operationalisation means turning these fuzzy ideas into measurable indicators.

If you’re using observations , which events or actions will you count?

If you’re using surveys , which questions will you ask and what range of responses will be offered?

You may also choose to use or adapt existing materials designed to measure the concept you’re interested in – for example, questionnaires or inventories whose reliability and validity has already been established.

Reliability and validity

Reliability means your results can be consistently reproduced , while validity means that you’re actually measuring the concept you’re interested in.

For valid and reliable results, your measurement materials should be thoroughly researched and carefully designed. Plan your procedures to make sure you carry out the same steps in the same way for each participant.

If you’re developing a new questionnaire or other instrument to measure a specific concept, running a pilot study allows you to check its validity and reliability in advance.

Sampling procedures

As well as choosing an appropriate sampling method, you need a concrete plan for how you’ll actually contact and recruit your selected sample.

That means making decisions about things like:

  • How many participants do you need for an adequate sample size?
  • What inclusion and exclusion criteria will you use to identify eligible participants?
  • How will you contact your sample – by mail, online, by phone, or in person?

If you’re using a probability sampling method, it’s important that everyone who is randomly selected actually participates in the study. How will you ensure a high response rate?

If you’re using a non-probability method, how will you avoid bias and ensure a representative sample?

Data management

It’s also important to create a data management plan for organising and storing your data.

Will you need to transcribe interviews or perform data entry for observations? You should anonymise and safeguard any sensitive data, and make sure it’s backed up regularly.

Keeping your data well organised will save time when it comes to analysing them. It can also help other researchers validate and add to your findings.

On their own, raw data can’t answer your research question. The last step of designing your research is planning how you’ll analyse the data.

Quantitative data analysis

In quantitative research, you’ll most likely use some form of statistical analysis . With statistics, you can summarise your sample data, make estimates, and test hypotheses.

Using descriptive statistics , you can summarise your sample data in terms of:

  • The distribution of the data (e.g., the frequency of each score on a test)
  • The central tendency of the data (e.g., the mean to describe the average score)
  • The variability of the data (e.g., the standard deviation to describe how spread out the scores are)

The specific calculations you can do depend on the level of measurement of your variables.

Using inferential statistics , you can:

  • Make estimates about the population based on your sample data.
  • Test hypotheses about a relationship between variables.

Regression and correlation tests look for associations between two or more variables, while comparison tests (such as t tests and ANOVAs ) look for differences in the outcomes of different groups.

Your choice of statistical test depends on various aspects of your research design, including the types of variables you’re dealing with and the distribution of your data.

Qualitative data analysis

In qualitative research, your data will usually be very dense with information and ideas. Instead of summing it up in numbers, you’ll need to comb through the data in detail, interpret its meanings, identify patterns, and extract the parts that are most relevant to your research question.

Two of the most common approaches to doing this are thematic analysis and discourse analysis .

There are many other ways of analysing qualitative data depending on the aims of your research. To get a sense of potential approaches, try reading some qualitative research papers in your field.

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.

Operationalisation means turning abstract conceptual ideas into measurable observations.

For example, the concept of social anxiety isn’t directly observable, but it can be operationally defined in terms of self-rating scores, behavioural avoidance of crowded places, or physical anxiety symptoms in social situations.

Before collecting data , it’s important to consider how you will operationalise the variables that you want to measure.

The research methods you use depend on the type of data you need to answer your research question .

  • If you want to measure something or test a hypothesis , use quantitative methods . If you want to explore ideas, thoughts, and meanings, use qualitative methods .
  • If you want to analyse a large amount of readily available data, use secondary data. If you want data specific to your purposes with control over how they are generated, collect primary data.
  • If you want to establish cause-and-effect relationships between variables , use experimental methods. If you want to understand the characteristics of a research subject, use descriptive methods.

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  • How to Write Your Methods

how to write participants in research example

Ensure understanding, reproducibility and replicability

What should you include in your methods section, and how much detail is appropriate?

Why Methods Matter

The methods section was once the most likely part of a paper to be unfairly abbreviated, overly summarized, or even relegated to hard-to-find sections of a publisher’s website. While some journals may responsibly include more detailed elements of methods in supplementary sections, the movement for increased reproducibility and rigor in science has reinstated the importance of the methods section. Methods are now viewed as a key element in establishing the credibility of the research being reported, alongside the open availability of data and results.

A clear methods section impacts editorial evaluation and readers’ understanding, and is also the backbone of transparency and replicability.

For example, the Reproducibility Project: Cancer Biology project set out in 2013 to replicate experiments from 50 high profile cancer papers, but revised their target to 18 papers once they understood how much methodological detail was not contained in the original papers.

how to write participants in research example

What to include in your methods section

What you include in your methods sections depends on what field you are in and what experiments you are performing. However, the general principle in place at the majority of journals is summarized well by the guidelines at PLOS ONE : “The Materials and Methods section should provide enough detail to allow suitably skilled investigators to fully replicate your study. ” The emphases here are deliberate: the methods should enable readers to understand your paper, and replicate your study. However, there is no need to go into the level of detail that a lay-person would require—the focus is on the reader who is also trained in your field, with the suitable skills and knowledge to attempt a replication.

A constant principle of rigorous science

A methods section that enables other researchers to understand and replicate your results is a constant principle of rigorous, transparent, and Open Science. Aim to be thorough, even if a particular journal doesn’t require the same level of detail . Reproducibility is all of our responsibility. You cannot create any problems by exceeding a minimum standard of information. If a journal still has word-limits—either for the overall article or specific sections—and requires some methodological details to be in a supplemental section, that is OK as long as the extra details are searchable and findable .

Imagine replicating your own work, years in the future

As part of PLOS’ presentation on Reproducibility and Open Publishing (part of UCSF’s Reproducibility Series ) we recommend planning the level of detail in your methods section by imagining you are writing for your future self, replicating your own work. When you consider that you might be at a different institution, with different account logins, applications, resources, and access levels—you can help yourself imagine the level of specificity that you yourself would require to redo the exact experiment. Consider:

  • Which details would you need to be reminded of? 
  • Which cell line, or antibody, or software, or reagent did you use, and does it have a Research Resource ID (RRID) that you can cite?
  • Which version of a questionnaire did you use in your survey? 
  • Exactly which visual stimulus did you show participants, and is it publicly available? 
  • What participants did you decide to exclude? 
  • What process did you adjust, during your work? 

Tip: Be sure to capture any changes to your protocols

You yourself would want to know about any adjustments, if you ever replicate the work, so you can surmise that anyone else would want to as well. Even if a necessary adjustment you made was not ideal, transparency is the key to ensuring this is not regarded as an issue in the future. It is far better to transparently convey any non-optimal methods, or methodological constraints, than to conceal them, which could result in reproducibility or ethical issues downstream.

Visual aids for methods help when reading the whole paper

Consider whether a visual representation of your methods could be appropriate or aid understanding your process. A visual reference readers can easily return to, like a flow-diagram, decision-tree, or checklist, can help readers to better understand the complete article, not just the methods section.

Ethical Considerations

In addition to describing what you did, it is just as important to assure readers that you also followed all relevant ethical guidelines when conducting your research. While ethical standards and reporting guidelines are often presented in a separate section of a paper, ensure that your methods and protocols actually follow these guidelines. Read more about ethics .

Existing standards, checklists, guidelines, partners

While the level of detail contained in a methods section should be guided by the universal principles of rigorous science outlined above, various disciplines, fields, and projects have worked hard to design and develop consistent standards, guidelines, and tools to help with reporting all types of experiment. Below, you’ll find some of the key initiatives. Ensure you read the submission guidelines for the specific journal you are submitting to, in order to discover any further journal- or field-specific policies to follow, or initiatives/tools to utilize.

Tip: Keep your paper moving forward by providing the proper paperwork up front

Be sure to check the journal guidelines and provide the necessary documents with your manuscript submission. Collecting the necessary documentation can greatly slow the first round of peer review, or cause delays when you submit your revision.

Randomized Controlled Trials – CONSORT The Consolidated Standards of Reporting Trials (CONSORT) project covers various initiatives intended to prevent the problems of  inadequate reporting of randomized controlled trials. The primary initiative is an evidence-based minimum set of recommendations for reporting randomized trials known as the CONSORT Statement . 

Systematic Reviews and Meta-Analyses – PRISMA The Preferred Reporting Items for Systematic Reviews and Meta-Analyses ( PRISMA ) is an evidence-based minimum set of items focusing  on the reporting of  reviews evaluating randomized trials and other types of research.

Research using Animals – ARRIVE The Animal Research: Reporting of In Vivo Experiments ( ARRIVE ) guidelines encourage maximizing the information reported in research using animals thereby minimizing unnecessary studies. (Original study and proposal , and updated guidelines , in PLOS Biology .) 

Laboratory Protocols Protocols.io has developed a platform specifically for the sharing and updating of laboratory protocols , which are assigned their own DOI and can be linked from methods sections of papers to enhance reproducibility. Contextualize your protocol and improve discovery with an accompanying Lab Protocol article in PLOS ONE .

Consistent reporting of Materials, Design, and Analysis – the MDAR checklist A cross-publisher group of editors and experts have developed, tested, and rolled out a checklist to help establish and harmonize reporting standards in the Life Sciences . The checklist , which is available for use by authors to compile their methods, and editors/reviewers to check methods, establishes a minimum set of requirements in transparent reporting and is adaptable to any discipline within the Life Sciences, by covering a breadth of potentially relevant methodological items and considerations. If you are in the Life Sciences and writing up your methods section, try working through the MDAR checklist and see whether it helps you include all relevant details into your methods, and whether it reminded you of anything you might have missed otherwise.

Summary Writing tips

The main challenge you may find when writing your methods is keeping it readable AND covering all the details needed for reproducibility and replicability. While this is difficult, do not compromise on rigorous standards for credibility!

how to write participants in research example

  • Keep in mind future replicability, alongside understanding and readability.
  • Follow checklists, and field- and journal-specific guidelines.
  • Consider a commitment to rigorous and transparent science a personal responsibility, and not just adhering to journal guidelines.
  • Establish whether there are persistent identifiers for any research resources you use that can be specifically cited in your methods section.
  • Deposit your laboratory protocols in Protocols.io, establishing a permanent link to them. You can update your protocols later if you improve on them, as can future scientists who follow your protocols.
  • Consider visual aids like flow-diagrams, lists, to help with reading other sections of the paper.
  • Be specific about all decisions made during the experiments that someone reproducing your work would need to know.

how to write participants in research example

Don’t

  • Summarize or abbreviate methods without giving full details in a discoverable supplemental section.
  • Presume you will always be able to remember how you performed the experiments, or have access to private or institutional notebooks and resources.
  • Attempt to hide constraints or non-optimal decisions you had to make–transparency is the key to ensuring the credibility of your research.
  • How to Write a Great Title
  • How to Write an Abstract
  • How to Report Statistics
  • How to Write Discussions and Conclusions
  • How to Edit Your Work

The contents of the Peer Review Center are also available as a live, interactive training session, complete with slides, talking points, and activities. …

The contents of the Writing Center are also available as a live, interactive training session, complete with slides, talking points, and activities. …

There’s a lot to consider when deciding where to submit your work. Learn how to choose a journal that will help your study reach its audience, while reflecting your values as a researcher…

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How to Write a Methods Section for a Psychology Paper

Tips and Examples of an APA Methods Section

Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

how to write participants in research example

Emily is a board-certified science editor who has worked with top digital publishing brands like Voices for Biodiversity, Study.com, GoodTherapy, Vox, and Verywell.

how to write participants in research example

Verywell / Brianna Gilmartin 

The methods section of an APA format psychology paper provides the methods and procedures used in a research study or experiment . This part of an APA paper is critical because it allows other researchers to see exactly how you conducted your research.

Method refers to the procedure that was used in a research study. It included a precise description of how the experiments were performed and why particular procedures were selected. While the APA technically refers to this section as the 'method section,' it is also often known as a 'methods section.'

The methods section ensures the experiment's reproducibility and the assessment of alternative methods that might produce different results. It also allows researchers to replicate the experiment and judge the study's validity.

This article discusses how to write a methods section for a psychology paper, including important elements to include and tips that can help.

What to Include in a Method Section

So what exactly do you need to include when writing your method section? You should provide detailed information on the following:

  • Research design
  • Participants
  • Participant behavior

The method section should provide enough information to allow other researchers to replicate your experiment or study.

Components of a Method Section

The method section should utilize subheadings to divide up different subsections. These subsections typically include participants, materials, design, and procedure.

Participants 

In this part of the method section, you should describe the participants in your experiment, including who they were (and any unique features that set them apart from the general population), how many there were, and how they were selected. If you utilized random selection to choose your participants, it should be noted here.

For example: "We randomly selected 100 children from elementary schools near the University of Arizona."

At the very minimum, this part of your method section must convey:

  • Basic demographic characteristics of your participants (such as sex, age, ethnicity, or religion)
  • The population from which your participants were drawn
  • Any restrictions on your pool of participants
  • How many participants were assigned to each condition and how they were assigned to each group (i.e., randomly assignment , another selection method, etc.)
  • Why participants took part in your research (i.e., the study was advertised at a college or hospital, they received some type of incentive, etc.)

Information about participants helps other researchers understand how your study was performed, how generalizable the result might be, and allows other researchers to replicate the experiment with other populations to see if they might obtain the same results.

In this part of the method section, you should describe the materials, measures, equipment, or stimuli used in the experiment. This may include:

  • Testing instruments
  • Technical equipment
  • Any psychological assessments that were used
  • Any special equipment that was used

For example: "Two stories from Sullivan et al.'s (1994) second-order false belief attribution tasks were used to assess children's understanding of second-order beliefs."

For standard equipment such as computers, televisions, and videos, you can simply name the device and not provide further explanation.

Specialized equipment should be given greater detail, especially if it is complex or created for a niche purpose. In some instances, such as if you created a special material or apparatus for your study, you might need to include an illustration of the item in the appendix of your paper.

In this part of your method section, describe the type of design used in the experiment. Specify the variables as well as the levels of these variables. Identify:

  • The independent variables
  • Dependent variables
  • Control variables
  • Any extraneous variables that might influence your results.

Also, explain whether your experiment uses a  within-groups  or between-groups design.

For example: "The experiment used a 3x2 between-subjects design. The independent variables were age and understanding of second-order beliefs."

The next part of your method section should detail the procedures used in your experiment. Your procedures should explain:

  • What the participants did
  • How data was collected
  • The order in which steps occurred

For example: "An examiner interviewed children individually at their school in one session that lasted 20 minutes on average. The examiner explained to each child that he or she would be told two short stories and that some questions would be asked after each story. All sessions were videotaped so the data could later be coded."

Keep this subsection concise yet detailed. Explain what you did and how you did it, but do not overwhelm your readers with too much information.

Tips for How to Write a Methods Section

In addition to following the basic structure of an APA method section, there are also certain things you should remember when writing this section of your paper. Consider the following tips when writing this section:

  • Use the past tense : Always write the method section in the past tense.
  • Be descriptive : Provide enough detail that another researcher could replicate your experiment, but focus on brevity. Avoid unnecessary detail that is not relevant to the outcome of the experiment.
  • Use an academic tone : Use formal language and avoid slang or colloquial expressions. Word choice is also important. Refer to the people in your experiment or study as "participants" rather than "subjects."
  • Use APA format : Keep a style guide on hand as you write your method section. The Publication Manual of the American Psychological Association is the official source for APA style.
  • Make connections : Read through each section of your paper for agreement with other sections. If you mention procedures in the method section, these elements should be discussed in the results and discussion sections.
  • Proofread : Check your paper for grammar, spelling, and punctuation errors.. typos, grammar problems, and spelling errors. Although a spell checker is a handy tool, there are some errors only you can catch.

After writing a draft of your method section, be sure to get a second opinion. You can often become too close to your work to see errors or lack of clarity. Take a rough draft of your method section to your university's writing lab for additional assistance.

A Word From Verywell

The method section is one of the most important components of your APA format paper. The goal of your paper should be to clearly detail what you did in your experiment. Provide enough detail that another researcher could replicate your study if they wanted.

Finally, if you are writing your paper for a class or for a specific publication, be sure to keep in mind any specific instructions provided by your instructor or by the journal editor. Your instructor may have certain requirements that you need to follow while writing your method section.

Frequently Asked Questions

While the subsections can vary, the three components that should be included are sections on the participants, the materials, and the procedures.

  • Describe who the participants were in the study and how they were selected.
  • Define and describe the materials that were used including any equipment, tests, or assessments
  • Describe how the data was collected

To write your methods section in APA format, describe your participants, materials, study design, and procedures. Keep this section succinct, and always write in the past tense. The main heading of this section should be labeled "Method" and it should be centered, bolded, and capitalized. Each subheading within this section should be bolded, left-aligned and in title case.

The purpose of the methods section is to describe what you did in your experiment. It should be brief, but include enough detail that someone could replicate your experiment based on this information. Your methods section should detail what you did to answer your research question. Describe how the study was conducted, the study design that was used and why it was chosen, and how you collected the data and analyzed the results.

Erdemir F. How to write a materials and methods section of a scientific article ? Turk J Urol . 2013;39(Suppl 1):10-5. doi:10.5152/tud.2013.047

Kallet RH. How to write the methods section of a research paper . Respir Care . 2004;49(10):1229-32. PMID: 15447808.

American Psychological Association.  Publication Manual of the American Psychological Association  (7th ed.). Washington DC: The American Psychological Association; 2019.

American Psychological Association. APA Style Journal Article Reporting Standards . Published 2020.

By Kendra Cherry, MSEd Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

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Issue Cover

Article Contents

Introduction, describing the distribution of values, descriptive statistics in text, descriptive statistics in tables, describing loss of participants in a study, comparing baseline characteristics in rcts, conclusions, acknowledgements, conflicts of interest.

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Describing the participants in a study

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R. M. Pickering, Describing the participants in a study, Age and Ageing , Volume 46, Issue 4, July 2017, Pages 576–581, https://doi.org/10.1093/ageing/afx054

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This paper reviews the use of descriptive statistics to describe the participants included in a study. It discusses the practicalities of incorporating statistics in papers for publication in Age and Aging , concisely and in ways that are easy for readers to understand and interpret.

Most papers reporting analysis of clinical data will at some point use statistics to describe the socio-demographic characteristics and medical history of the study participants. An important reason for doing this is to give the reader some idea of the extent to which study findings can be generalised to their own local situation. The production of descriptive statistics is a straightforward matter, most statistical packages producing all the statistics one could possibly desire, and a choice has to be made over which ones to present. These then have to be included in a paper in a manner that is easy for readers to assimilate. There may be constraints on the amount of space available, and it is in any case a good idea to make statistical display as concise as possible. This article reviews the statistics that might be used to describe a sample of older people, and gives tips on how best to do this in a paper for publication in Age and Aging . It builds on a previously published paper [ 1 ].

The values observed in a group of subjects, when measurements of a quantitative characteristic are made, are called the distribution of values. Graphical displays can be used to show the detail of the distribution in a variety of ways, but they take up a considerable amount of space. A precis of two key features of the distribution, its centre and its spread, is usually presented using descriptive statistics. The centre of a distribution can be described by its mean or median, and the spread by its standard deviation (SD), range, or inter-quartile range (IQR). Definitions and properties of these statistics are given in statistical textbooks [ 2 ].

Figure 1 a shows an idealised symmetric distribution for a quantitative variable. The mean might be used here to describe where the centre of the distribution lies and the SD to give an idea of how spread out values are around the centre. SDs are particularly appropriate where a symmetric distribution approximately follows the bell-shaped pattern shown in Figure 1 a which is called the normal distribution. For such a distribution the large majority, 95%, of values observed in a sample will fall between the values two SDs above and below the mean, called the normal range. Presentation of the mean and SD invites the reader to calculate the normal range and think of it as covering most of the distribution of values. Another reason for presenting the SD is that it is required in calculations of sample size for approximately normally distributed outcomes, and can be used by readers in planning future studies. A graphical display of approximately normally distributed real data (age at admission amongst 373 study participants) is shown in Figure 1 c: with relatively small sample size a smooth distribution such as that shown in Figure 1 a cannot be achieved. The mean (82.9) and SD (6.8) of the age distribution lead to the normal range 69.3–96.5 years, which can be seen in Figure 1 c to cover most of the ages in the sample: 14 subjects fall below 69.3 and 7 fall above 96.5, so that the range actually covers 352 (94.4%) of the 373 participants, close to the anticipated 95%. For familiar measurements, such as age, there is additional value in presenting the range, the minimum and maximum values attained. Knowing that the study included people aged between 65 and 101 years is immediately meaningful, whereas the value of the SD is more difficult to interpret.

Idealised and real data distributions. (a) Symmetrical distribution. (b) Skewed distribution. (c) Dotplot (each dot representing one value) of an approximate symmetrical distribution indicating the normal range: age in years at admission (n = 373). (d) Dotplot (each dot representing one value) of a skewed distribution with outliers emphasised and indicating mean and median: hours in A&E (n = 348).

Idealised and real data distributions. (a) Symmetrical distribution. (b) Skewed distribution. (c) Dotplot (each dot representing one value) of an approximate symmetrical distribution indicating the normal range: age in years at admission ( n = 373). (d) Dotplot (each dot representing one value) of a skewed distribution with outliers emphasised and indicating mean and median: hours in A&E ( n = 348).

When a distribution is skewed (Figure 1 b) just one or two extreme values, ‘outliers’, in one of the tails of the distribution (to the right in Figure 1 b) pull the mean away from the obvious central value. An alternative statistic describing central location is the median, defined as the point with 50% of the sample falling above it and 50% below. Figure 1 d shows the distribution of real data (hours in A&E amongst 348 study participants) following a skewed distribution. A few excessively long A&E stays pull the mean to the higher value of 4.9 h compared to the median of 4.4 h: the effect would be greater with a higher proportion of subjects having long stays. The median is often recommended as the preferred statistic to describe the centre of a skewed distribution, but the mean can be helpful. If the attribute being described takes only a limited number of values, the medians of two groups can take the same value in spite of substantial differences in the tails. In these circumstances, the mean can be sensitive to an overall shift in distribution while the median is not. When a comparison of cost based on length of stay is to be made, presenting means of the skewed distributions facilitates calculation of cost savings per subject by applying unit cost to the difference in means. Figure 1 b suggests that the value with highest frequency might be a useful descriptor of the centre of a distribution. In practice, this can prove awkward: depending on the precision of measurement there may be no value occurring more than once.

It is clear from Figure 1 b that no single number can adequately describe the spread of a skewed distribution because spread is greater in one direction than the other. The range (from 1.7 to 40.3 h in A&E in our skewed example) could be used. Another possibility is the IQR (from 3.5 to 5.4 h in A&E) covering the central 50% of the distribution. The SD may be presented even though a distribution is skewed, and could be useful to readers for approximate power calculations, but the normal range derived from the mean and SD will be misleading. With mean(SD) = 4.9(3.2), the lower limit of the normal range of hours in A&E is the impossible negative value of –1.5 h, while the upper limit of 11.3 h lies well below the extreme values exhibited in Figure 1 d.

Descriptive statistics may be presented in text, for example [ 3 ]:

Participants’ ages ranged from 50 to 87 years ( M  = 66.1, SD = 7.8) with 56% identified as female, 64% married or partnered, 23% reported being retired or not working, 55% had post-secondary and higher education, and <20% reported living alone. Over 60% of the participants identified as NZ European. The mean of net personal annual income was $34,615. The participants reported the diagnosis of an average of 2.63 (±2.07) chronic health conditions, with 50% reported having three or more chronic health conditions.

There are perhaps too many attributes (age, gender, marital status, employment status, educational level, living arrangements, nationality, personal income and number of chronic conditions) being described in the excerpt above: it would be easier to assimilate this information from a table.

Characteristics of subjects at admission and their operations before (1998/99) and after (2000/01) implementation of a care pathway [ 4 ]. Figures are number (% of non-missing values) unless otherwise stated

The distributions of the two quantitative variables in Table 1 are described by mean (SD) and range. The statistics being presented should be stated in the context of the table, here in the left hand column, and could differ across variables. If the same statistics are presented for all the variables in a table they can be indicated in the column headings or title. From the mean (SD) and range in each phase, we can see that the age distribution is reasonably symmetrical because the mean falls close to the centre of the range, and the mean ± 2 SD approach the limits of the range. The distribution of hours in A&E is skewed to the right but has been summarised with the same statistics. We can see that the distribution is skewed because the mean is much closer to the minimum than the maximum, and, if the normal range is calculated, the upper limit does not approach the high values in either phase. For these reasons, the normal range should not be interpreted as covering 95% of values. These conclusions from descriptive statistics alone can be verified in Figure 1 c and d.

A choice arises when describing the distribution of an ordinal variable indicating ordered response categories, such as ambulation score in Table 1 . If the variable takes many distinct values, it can be treated as a quantitative variable and described in terms of centre and spread: ordinal variables often extend from the minimum to maximum possible values and in this case stating the range is not helpful. The meaning of the extremes should be stated in the context of the table to aid interpretation of results. Ordinal variables taking only a few distinct values are better treated as categorical variables and number (%) presented for each category. With only five categories the latter approach was adopted for ambulation score. Display as a categorical variable can be facilitated by combining infrequently occurring adjacent values.

In the original study, 3,182 of 5,719 admissions were screened and 2,286 were eligible. Six hundred and ten patients were not available on the hospital units when the RA [Research Assistant] arrived to complete the CAM [Confusion Assessment Method]; 1,582 patients assented to complete the CAM and 94 patients did not assent; the CAM was not completed for 728 patients because an informant was not available to confirm an acute change and fluctuation in mental status prior to admission or enrolment. The CAM was completed for 854 patients; 375 had delirium; 278 were enroled. Of the 278 enroled patients, 172 were discharged before the follow-up assessment, 73 were still hospitalised, 8 withdrew from the study and 27 died. Of the 172 discharged patients, delirium recovery status was determined for 152, 16 withdrew from the study after discharge and 4 died.

The authors start with the 5,719 admissions and report the numbers lost at successive stages, to arrive at the analysis sample of 152. It may be easier to assimilate the detail of the process from tabular or graphical presentation. The CONSORT guidelines [ 6 ] concerning the reporting of Randomised Controlled Trials (RCTs) recommend that progress of participants through a trial be presented as a flow chart, and an example is shown in Figure 2 . These charts are unequivocally helpful and are now presented in studies other than RCTs.

Recruitment and attrition rates in an RCT of WiiActive exercises in community dwelling older adults [7].

Recruitment and attrition rates in an RCT of WiiActive exercises in community dwelling older adults [ 7 ].

In addition to loss of participants at each time point as shown in a flow chart, information on specific variables may be missing even though a participant was available at the study point in question. Taking Table 1 as an example, there were 395 and 373 admissions during the 1998/99 and 2000/01 phases, respectively, as stated in the column headings, but the number of participants providing information varies considerably across the characteristics in the table. The reader should be able to establish how many cases contribute to each result, and to this end wherever the number available is lower than the total for the phase, it is stated below the descriptive statistics. For example, ambulation score was only available for 390 of the 395 participants in the 1998/99 phase. The percentages presented for ambulation score were calculated amongst cases where information was available, and this was done for all percentages in the table as indicated in the title. Alternatively, missing values in a categorical variable may be treated as a category in their own right. Where there is a large amount of missing information, this may be the best way of handling the situation with percentages calculated from the total sample size as denominator. Stating the numbers available allows the reader to check this point. Only participants whose operation was delayed by more than 48 h, gave a ‘reason why operation was delayed’ in the table, and from the stated numbers the reader can see that a reason was not given for all delayed cases.

In reports of RCTs, a table describing baseline characteristics in each trial arm demonstrates whether or not randomisation was successful in producing similar groups, as well as addressing the generalisability issue. If there are differences at baseline, comparison of outcome may be confounded. Statistical tests of significance should not be used to decide whether any differences need to be taken into account [ 8 , 9 ]. If the allocation was properly randomised, we know that any differences at baseline must be due to chance. The question facing the researcher is whether or not the magnitude of a difference at baseline is sufficient to confound comparison of outcome, and this depends on the strength of the relationship between the potential confounder and the outcome, as well the baseline difference. A statistical test for baseline differences does not address this question; furthermore, there may be insufficient numbers available to detect quite large baseline differences. Statistics describing baseline characteristics are used to judge whether any differences are large enough to be important. If they are, additional analyses of outcome controlled for characteristics that differ at baseline may be performed. On the other hand, in non-randomised studies, groups are likely to differ, and statistical significance tests can be used to evaluate the evidence that the selection process of patients to each intervention results in different groups. In this situation a primary analysis controlled for many predictors of outcome would probably have been planned, and should be carried out irrespective of any differences, or lack of them, between study groups.

Describing the main features of the distribution of important characteristics of the participants included in a study is the first step in most papers reporting statistical analysis. It is important in establishing the generalisability of research findings, and in the context of comparative studies, flags the need for controlled analysis. Usually space constraints limit the presentation of many descriptive statistics, and in any case, too many statistics can confuse rather than enhance insight. The attrition of subjects during a study should also be described, so that study subjects can be related to the patient base from which they were drawn.

Descriptive statistics are used to describe the participants in a study so that readers can assess the generalisability of study findings to their own clinical practice.

They need to be appropriate to the variable or participant characteristic they aim to describe, and presented in a fashion that is easy for readers to understand.

When many patient characteristics are being described, the detail of the statistics used and number of participants contributing to analysis are best incorporated in tabular presentation.

The author would like to thank Dr Helen Roberts for kindly granting permission to use data from the care pathway study [ 4 ] to produce Figure 1 c and d.

None declared.

Pickering RM . Describing the subjects in a study . Palliat Med 2001 ; 15 : 69 – 75 .

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Altman DG . Practical Statistics for Medical research . London : Chapman & Hall , 1991 .

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Yeung P , Breheny M . Using the capability approach to understand the determinants of subjective well-being among community-dwelling older people in New Zealand . Age Aging 2016 ; 45 : 292 – 8 .

Roberts HC , Pickering RM , Onslow E et al.  . The effectiveness of implementing a care pathway for femoral neck fracture in older people: a prospective controlled before and after study . Age Aging 2004 ; 33 : 178 – 84 .

Cole MG , McCusker JM , Bailey R et al.  . Partial and no recovery from delirium after hospital discharge predict increased adverse events . Age Aging 2017 ; 46 : 90 – 5 .

Schulz KF , Altman DG , Moher D , for the CONSORT Group . CONSORT 2010 statement: updated guidelines for reporting parallel-group randomised trials . BMJ 2010 ; 340 : 698 – 702 .

Kwok BC , Pua YH . Effects of WiiActive exercises on fear of falling and functional outcomes in community-dwelling older adults: a randomised control trial . Age Aging 2016 ; 45 : 621 – 28 .

Assman SF , Pocock SJ , Enos LE , Kasten LE . Subgroup analysis and other (mis)uses of baseline data in clinical trials . Lancet 2000 ; 355 : 1064 – 9 .

Altman DG . Comparability of randomized groups . Statistician 1985 ; 34 : 125 – 36 .

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  • Advice on writing an information sheet and consent form

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Writing a Participant Information Sheet and Consent Form

Recruitment documents help people make informed choices about whether to participate in a research study. Find out how to write a Participant Information Sheet, example forms and further guidance.

Writing a Participant Information Sheet

Participant Information Sheets must be designed to assist participants to make informed choices. Potential recruits must be given sufficient information to allow them to decide whether or not they want to take part. The process of obtaining consent and the accompanying documentation must be approved by a research ethics committee and, where only verbal consent to research is contemplated include consideration of an appropriate process for witnessing the consent.

Researchers must take the steps necessary to ensure that all participants in the research understand the process in which they are to be engaged, including why their participation is necessary, how it will be used, and how and to whom it will be reported so that the prospective participant can make an informed decision about whether they really do want to take part.

It is highly recommended that the information provided is presented on headed paper and is accurate, clear and simple so that someone with a reading age of 8 would understand the contents (use short words, sentences and paragraphs). The information should be specific to the proposed research and appropriate for the social and cultural context in which is it being given. It is important to avoid technical terms, jargon and abbreviations, bias, coercion or any inappropriate inducements.

What should the Participant Information Sheet include:

  • A friendly invitation to participate.
  • A brief and simple explanation of the purposes of the research and a statement explaining how the participant was chosen and how many other participants will be involved in the study.
  • A statement that participation is voluntary; refusal to participate will involve no penalty or loss of benefits to which the participant is otherwise entitled; and the participant may discontinue participation at any time without penalty or loss of benefits.
  • A thorough explanation of the expected duration of participation in the research and the procedures to be followed.
  • A description of any reasonably foreseeable risks or discomforts and any benefits to the participant. For research involving more than minimal risk, an explanation as to whether any compensation or any medical treatments are available if injury occurs and, if so, what they consist of, or where further information may be obtained.
  • A statement describing the extent, if any, to which confidentiality of records identifying the participant will be maintained.
  • It is considered good practice for researchers to debrief participants at the conclusion of the research and to provide them with copies of any reports or other publications arising from their participation.
  • If appropriate, a statement indicating that the data might be used for additional or subsequent research.
  • An explanation of who to contact for answers to pertinent questions about the research and the rights of the participant and who to contact in the event of a research-related injury to the participant.
  • If applicable, a statement declaring that each researcher who may have access to children (aged under 18) or vulnerable adults has undergone a satisfactory criminal records check.
  • Remember to thank your participant for considering taking part in the study and include a statement indicating that the research study has been approved by the UCL Research Ethics Committee.

Language and layout

It is highly recommended that the information provided is presented on headed paper and is accurate, clear, and simple. The information should be specific to the proposed research and appropriate for the social and cultural context in which is it being given. It is important to avoid technical terms, jargon, and abbreviations, bias, coercion, or any inappropriate inducements.

The following points should be considered when writing an information sheet:

  • Use clear, non-technical language. We recommend that you refer to the  Plain English Campaign
  • Use appropriate language for the target audience. For example, consider the different ways needed to communicate with primary school children as opposed to their teachers, or people with expertise in the area of study as opposed to people with no such knowledge
  • Divide the text into paragraphs for ease of reading
  • Consider using sub-headings for clarity, such as questions and answers
  • Make sure the font and font size are legible.

Ask someone else to review your information sheet before it is circulated.

  • Template Participant Information Sheet  (Word)
  • Template Consent Form  (Word)
  • Guidance on obtaining consent from research participants online (for online and in-person study designs)

Authors: Dr Pippa Lally, Behavioural Science and Health, and Jack Hindley, Information Services Division, UCL

  • Recording & Obtaining Consent

UCL Research Ethics Committee Guidance Note 2: Extract from Nuffield Council on Bioethics website

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Research Method

Home » Informed Consent in Research – Types, Templates and Examples

Informed Consent in Research – Types, Templates and Examples

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Informed Consent in Research

Informed Consent in Research

Informed consent is a process of communication between a researcher and a potential participant in which the researcher provides adequate information about the study, its risks and benefits, and the participant voluntarily agrees to participate. It is a cornerstone of ethical research involving human subjects and is intended to protect the rights and welfare of participants.

Types of Informed Consent in Research

There are different types of informed consent in research , which may vary depending on the nature of the study, the type of participants, and the context. Some of the common types of informed consent in research include:

Written Consent

This is the most common type of informed consent, where participants are provided with a written document that explains the study and its requirements. The document typically includes information about the purpose of the study, procedures involved, risks and benefits, confidentiality, and participant rights. Participants are asked to sign the document as an indication of their willingness to participate.

Oral Consent

In some cases, oral consent may be used when a written document is not practical or feasible. Oral consent involves explaining the study and its requirements to participants verbally and obtaining their consent. This method may be used for studies with illiterate or visually impaired participants or when conducting research remotely.

Implied Consent

Implied consent is used in studies where participants’ actions are taken as an indication of their willingness to participate. For example, a participant may be considered to have given implied consent if they show up for a scheduled appointment for the study.

Opt-out Consent

This method is used when participants are given the opportunity to decline participation in a study. Participants are provided with information about the study and are given the option to opt-out if they do not wish to participate. This method is commonly used in population-based studies or surveys.

Assent is used in studies involving minors or participants who are unable to provide informed consent due to cognitive impairment or disability. Assent involves obtaining the agreement of the participant to participate in the study, along with the consent of a legally authorized representative.

Informed Consent Format in Research

Here’s a basic format for informed consent that can be customized for specific research studies:

  • Introduction : Begin by introducing yourself and the purpose of the study. Clearly state that participation is voluntary and that participants can withdraw at any time without penalty.
  • Study Overview : Provide a brief overview of the study, including its purpose, methods, and expected outcomes.
  • Procedures : Describe the procedures involved in the study in clear, concise language. Include information about the types of data that will be collected, how they will be collected, and how long the study will take.
  • Risks and Benefits : Outline the potential risks and benefits of participating in the study. Be honest and upfront about any discomfort, inconvenience, or potential harm that may be involved, as well as any potential benefits.
  • Confidentiality and Privacy : Explain how participant data will be collected, stored, and used, and what measures will be taken to ensure confidentiality and privacy.
  • Voluntary Participation: Emphasize that participation is voluntary and that participants can withdraw at any time without penalty. Explain how to withdraw from the study and who to contact if participants have questions or concerns.
  • Compensation and Incentives: If applicable, explain any compensation or incentives that will be offered to participants for their participation.
  • Contact Information: Provide contact information for the researcher or a representative from the research team who can answer questions and address concerns.
  • Signature : Ask participants to sign and date the consent form to indicate their voluntary agreement to participate in the study.

Informed Consent Templates in Research

Here is an example of an informed consent template that can be used in research studies:

Introduction

You are being invited to participate in a research study. Before you decide whether or not to participate, it is important for you to understand why the research is being done, what your participation will involve, and what risks and benefits may be associated with your participation.

Purpose of the Study

The purpose of this study is [insert purpose of study].

If you agree to participate, you will be asked to [insert procedures involved in the study].

Risks and Benefits

There are several potential risks and benefits associated with participation in this study. Some of the risks include [insert potential risks of participation]. Some of the benefits include [insert potential benefits of participation].

Confidentiality

Your participation in this study will be kept confidential to the extent allowed by law. All data collected during the study will be stored in a secure location and only accessed by authorized personnel. Your name and other identifying information will not be included in any reports or publications resulting from this study.

Voluntary Participation

Your participation in this study is completely voluntary. You have the right to withdraw from the study at any time without penalty. If you choose not to participate or if you withdraw from the study, there will be no negative consequences.

Contact Information

If you have any questions or concerns about the study, you can contact the investigator(s) at [insert contact information]. If you have questions about your rights as a research participant, you may contact [insert name of institutional review board and contact information].

Statement of Consent

By signing below, you acknowledge that you have read and understood the information provided in this consent form and that you freely and voluntarily consent to participate in this study.

Participant Signature: _____________________________________ Date: _____________

Investigator Signature: ____________________________________ Date: _____________

Examples of Informed Consent in Research

Here’s an example of informed consent in research:

Title : The Effects of Yoga on Stress and anxiety levels in college students

Introduction :

We are conducting a research study to investigate the effects of yoga on stress and anxiety levels in college students. We are inviting you to participate in this study.

If you agree to participate, you will be asked to attend four yoga classes per week for six weeks. Before and after the six-week period, you will be asked to complete surveys about your stress and anxiety levels. Additionally, we will measure your heart rate variability at the beginning and end of the six-week period.

Risks and Benefits:

There are no known risks associated with participating in this study. However, the benefits of practicing yoga may include decreased stress and anxiety levels, increased flexibility and strength, and improved overall well-being.

Confidentiality:

All information collected during this study will be kept strictly confidential. Your name will not be used in any reports or publications resulting from this study.

Voluntary Participation:

Participation in this study is completely voluntary. You are free to withdraw from the study at any time without penalty.

Contact Information:

If you have any questions or concerns about this study, you may contact the principal investigator at (phone number/email address).

By signing this form, I acknowledge that I have read and understood the above information and agree to participate in this study.

Participant Signature: ___________________________

Date: ___________________________

Researcher Signature: ___________________________

Importance of Informed Consent in Research

Here are some reasons why informed consent is important in research:

  • Protection of participants’ rights : Informed consent ensures that participants understand the nature and purpose of the research, the risks and benefits of participating, and their rights as participants. It empowers them to make an informed decision about whether to participate or not.
  • Ethical responsibility : Researchers have an ethical responsibility to respect the autonomy of participants and to protect them from harm. Informed consent is a crucial way to uphold these principles.
  • Legality : Informed consent is a legal requirement in most countries. It is necessary to protect researchers from legal liability and to ensure that research is conducted in accordance with ethical standards.
  • Trust : Informed consent helps build trust between researchers and participants. When participants understand the research process and their role in it, they are more likely to trust the researchers and the study.
  • Quality of research : Informed consent ensures that participants are fully informed about the research and its purpose, which can lead to more accurate and reliable data. This, in turn, can improve the quality of research outcomes.

Purpose of Informed Consent in Research

Informed consent is a critical component of research ethics, and it serves several important purposes, including:

  • Respect for autonomy: Informed consent respects an individual’s right to make decisions about their own health and well-being. It recognizes that individuals have the right to choose whether or not to participate in research, based on their own values, beliefs, and preferences.
  • Protection of participants : Informed consent helps protect research participants from potential harm or risks that may arise from their involvement in a study. By providing participants with information about the study, its risks and benefits, and their rights, they are able to make an informed decision about whether to participate.
  • Transparency: Informed consent promotes transparency in the research process. It ensures that participants are fully informed about the research, including its purpose, methods, and potential outcomes, which helps to build trust between researchers and participants.
  • Legal and ethical requirements: Informed consent is a legal and ethical requirement in most research studies. It ensures that researchers obtain voluntary and informed agreement from participants to participate in the study, which helps to protect the rights and welfare of research participants.

Advantages of Informed Consent in Research

The advantages of informed consent in research are numerous, and some of the most significant benefits include:

  • Protecting participants’ autonomy: Informed consent allows participants to exercise their right to self-determination and make decisions about whether to participate in a study or not. It also ensures that participants are fully informed about the risks, benefits, and implications of participating in the study.
  • Promoting transparency and trust: Informed consent helps build trust between researchers and participants by providing clear and accurate information about the study’s purpose, procedures, and potential outcomes. This transparency promotes open communication and a positive research experience for all parties involved.
  • Reducing the risk of harm: Informed consent ensures that participants are fully aware of any potential risks or side effects associated with the study. This knowledge enables them to make informed decisions about their participation and reduces the likelihood of harm or negative consequences.
  • Ensuring ethical standards are met : Informed consent is a fundamental ethical requirement for conducting research involving human participants. By obtaining informed consent, researchers demonstrate their commitment to upholding ethical principles and standards in their research practices.
  • Facilitating future research : Informed consent enables researchers to collect high-quality data that can be used for future research purposes. It also allows participants to make an informed decision about whether they are willing to participate in future studies.

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  • The Scientist University

How to Write a Good Introduction Section

A strong narrative is as integral a part of science writing as it is for any other form of communication..

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Nathan Ni holds a PhD from Queens University. He is a science editor for The Scientist’s Creative Services Team who strives to better understand and communicate the relationships between health and disease.

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A person sitting at a laboratory bench, typing on a laptop while looking at notes on a clipboard.

First impressions are important. Scientists need to make their work stand out among a sea of others. However, many mistakenly believe that first impressions are formed based only on titles and abstracts. In actuality, the introduction section is critical to making a real impression on the audience. The introduction is where authors outline their research topic and describe their study. It is where they provide background information and showcase their writing and argumentation styles. For these reasons, the introduction engages the audience in a deeper way than the formalities and rigidities of the title and abstract can afford. To use a fishing analogy: if the title and the abstract serve as the hook and the bait, then the introduction is the process of actually reeling the fish into the boat.

Good Introductions Are Important Guides

In contrast to the constraints placed on the title and abstract, the introduction is the first real opportunity for the scientist to engage with their audience and showcase and convey their passions and motivations for the study in question. This opportunity is somewhat of a double-edged sword. Study authors inevitably have a treasure trove of knowledge and expertise when it comes to their projects and their fields. However, they must remember that the audience does not necessarily have this background information—and that they are only engaging with their audience for a finite amount of time. Despite the urge to excitedly write about all of the different aspects and intricacies of the project, it is very important that authors keep their introductions simple and well organized. 

Therefore, the introduction should move from broad scopes to narrow focuses as the audience reads further. The author should direct the reader along this journey, focusing on topics with direct relevance to what was investigated in the study. A broad fact introduced early on should be linked or paired with a more specific fact along the same lines of thought, eventually culminating in how this information led to the motivation behind the study itself. It is vital to not go off on tangents or talk about things that are too esoteric. A confused audience is an audience that tends not to read further.

Applying Common Principles Across Well-Known and Niche Subjects

Writers can apply these principles in more specialized manuscripts focusing on a single entity rather than a well-known pathology. Consider the following example from a manuscript by cell biologist Luis R. Cruz-Vera’s research team from the University of Alabama in Huntsville, published in the Journal of Biological Chemistry. 1

Here, they divide the opening paragraph of their introduction into four distinct sections. First, they explain what ribosome arresting peptides (RAPs) are and what they do.

Ribosome arresting peptides (RAPs) are nascent polypeptides that act in cis on the translating ribosome to control the expression of genes by inducing ribosome arrest during translation elongation or termination. RAPs commonly sense external forces or low molecular weight compounds in the environment that spatially and temporally contribute to the expression of genes. 

Then they introduce the two different types of RAPs.

RAPs such as SecM that sense external forces on the ribosome are typically large, because these nascent peptides have a domain that functions outside of the ribosome. In contrast, those that sense small molecules inside of the ribosome, such as TnaC are smaller. 

They describe how each type works via a different mechanism.

Typically, larger RAPs interact with cellular factors that can control their capacity for arresting ribosomes. Because of their size and proximity to ribosomal components, large RAPs clearly show two structural domains, a sensor domain and an arresting domain. At the moment of the arrest for the large RAPs, the sensor domain is located outside the ribosome exit tunnel, whereas the arresting domain remains inside the tunnel. The short RAPs currently characterized interact with the compounds that they sense by using the ribosome exit tunnel as a binding surface. For these short RAPs, it has been determined that conserved amino acid residues are necessary to induce arrest by either directly binding the effector molecule or by acting at the peptidyl-transferase center (PTC) during ribosome arrest. 

And finally, they conclude by highlighting a knowledge gap in how small RAPs operate versus what is already known about large RAPs.

However, because the size of short RAPs ranges from only a few to a couple of dozen amino acids, as in the case of TnaC, it has remained unclear whether short RAPs are constituted by the two independent sensor and stalling domains, as it has been observed with larger RAPs.

In this way, the authors make a natural progression from “why this topic is important” to “what is known about this topic,” setting the stage for “what is unknown about this topic and why it should be studied.” 

Gradually Moving from Broad to Narrow

A three-step funnel explaining how the introduction guides the reader from summary to specific. The first phase should lay out the question that needs to be answered. The second phase should delve deeper into that question, and the final phase should tie what is already known with what is explored in this study.

These principles can be further transferred towards the introductory section as a whole. The first paragraph should serve as an introduction to the field and the topic. The middle paragraph(s) provide exposition and detail regarding what is known and unknown, and what has already been done and still remains to do, and the final paragraph outlines the study and its principle findings, providing a transition into either the materials and methods or the results section. 

For example, this work by radiation oncologist Eric Deutsch’s group at Université Paris-Saclay, published in PLoS One , 2 opens by succinctly explaining a scientific problem: “ the threat of extensive dispersion of radioactive isotopes within populated areas that would have an unfortunate effect on human health has increased drastically .” It then offers the call to action necessitated by this problem: “ the development of a decorporating agent capable of effectively mitigating the effects of a wide range of isotopes is critical .”

In the next two paragraphs, the study authors provide information on how and why dispersion of radioactive isotopes are a problem—“ the FDA has approved only three compounds (only one of which is used as a preventative therapy) for the treatment of exposure to specific radioactive elements ”—and highlights the strengths and weaknesses of what is currently available. They then introduce the focal point of their own work, chitosan@DOTAGA, within this context, explaining its potential as a solution to the problem they previously introduced: “ After oral administration to rodents over several days, no signs of acute or chronic toxicity were observed, and DOTAGA did not enter the blood stream and was fully eliminated from the gastrointestinal tract within 24 hours of administration. ”

Finally, the introduction concludes by listing the study objective—“ explore the potential of this polymer for use in the decorporation of a wide range of radioactive isotopes ”—and the motivations and rationale behind the study objective—“ there are no suitable countermeasures available for uranium poisoning. […] This innovative approach aims to directly chelate the radioactive cations, specifically uranium, within the gastrointestinal tract prior to their systemic absorption, which ensures their prompt elimination and mitigation of the associated toxicities. ”

The Introduction Engages with the Reader

The introduction section is often overlooked in favor of the title and the abstract, but it serves two important functions. First, it gives the audience all of the information that it needs to contextualize the yet-to-be-presented data within the context of the problem that needs to be solved or the scientific question that needs to be addressed. Second, and more importantly, it justifies the importance of the study, of its initiative, rationale, and purpose. The introduction is the author’s best—and arguably only real—opportunity to convince the audience that their study is worth reading.  

Looking for more information on scientific writing? Check out  The Scientist’s   TS SciComm  section. Looking for some help putting together a manuscript, a figure, a poster, or anything else?    The Scientist’s   Scientific Services  may have the professional help that you need.

  • Judd HNG, et al. Functional domains of a ribosome arresting peptide are affected by surrounding nonconserved residues . J Biol Chem . 2024;300(3):105780.
  • Durand A, et al. Enhancing radioprotection: A chitosan-based chelating polymer is a versatile radioprotective agent for prophylactic and therapeutic interventions against radionuclide contamination . PLoS One . 2024;19(4):e0292414.

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    The present study followed a qualitative research design based on ethnographic. methods. This approach was chosen given that the purpose of the research was to. describe and analyze part of the culture of a specific community, specifically "by. identifying and describing the participants' practices and beliefs" (Gay & Airasian, 2002).

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