example of findings and discussion in qualitative research

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How to write the analysis and discussion chapters in qualitative (SSAH) research

By charlesworth author services.

• Charlesworth Author Services
• 11 November, 2021

While it is more common for Science, Technology, Engineering and Mathematics (STEM) researchers to write separate, distinct chapters for their data/ results and analysis/ discussion , the same sections can feel less clearly defined for a researcher in Social Sciences, Arts and Humanities (SSAH). This article will look specifically at some useful approaches to writing the analysis and discussion chapters in qualitative/SSAH research.

Note : Most of the differences in approaches to research, writing, analysis and discussion come down, ultimately, to differences in epistemology – how we approach, create and work with knowledge in our respective fields. However, this is a vast topic that deserves a separate discussion.

Look for emerging themes and patterns

The ‘results’ of qualitative research can sometimes be harder to pinpoint than in quantitative research. You’re not dealing with definitive numbers and results in the same way as, say, a scientist conducting experiments that produce measurable data. Instead, most qualitative researchers explore prominent, interesting themes and patterns emerging from their data – that could comprise interviews, textual material or participant observation, for example. 

You may find that your data presents a huge number of themes, issues and topics, all of which you might find equally significant and interesting. In fact, you might find yourself overwhelmed by the many directions that your research could take, depending on which themes you choose to study in further depth. You may even discover issues and patterns that you had not expected , that may necessitate having to change or expand the research focus you initially started off with.

It is crucial at this point not to panic. Instead, try to enjoy the many possibilities that your data is offering you. It can be useful to remind yourself at each stage of exactly what you are trying to find out through this research.

What exactly do you want to know? What knowledge do you want to generate and share within your field?

Then, spend some time reflecting upon each of the themes that seem most interesting and significant, and consider whether they are immediately relevant to your main, overarching research objectives and goals.

Suggestion: Don’t worry too much about structure and flow at the early stages of writing your discussion . It would be a more valuable use of your time to fully explore the themes and issues arising from your data first, while also reading widely alongside your writing (more on this below). As you work more intimately with the data and develop your ideas, the overarching narrative and connections between those ideas will begin to emerge. Trust that you’ll be able to draw those links and craft the structure organically as you write.

Let your data guide you

A key characteristic of qualitative research is that the researchers allow their data to ‘speak’ and guide their research and their writing. Instead of insisting too strongly upon the prominence of specific themes and issues and imposing their opinions and beliefs upon the data, a good qualitative researcher ‘listens’ to what the data has to tell them.

Again, you might find yourself having to address unexpected issues or your data may reveal things that seem completely contradictory to the ideas and theories you have worked with so far. Although this might seem worrying, discovering these unexpected new elements can actually make your research much richer and more interesting. 

Suggestion: Allow yourself to follow those leads and ask new questions as you work through your data. These new directions could help you to answer your research questions in more depth and with greater complexity; or they could even open up other avenues for further study, either in this or future research.

Work closely with the literature

As you analyse and discuss the prominent themes, arguments and findings arising from your data, it is very helpful to maintain a regular and consistent reading practice alongside your writing. Return to the literature that you’ve already been reading so far or begin to check out new texts, studies and theories that might be more appropriate for working with any new ideas and themes arising from your data.

Reading and incorporating relevant literature into your writing as you work through your analysis and discussion will help you to consistently contextualise your research within the larger body of knowledge. It will be easier to stay focused on what you are trying to say through your research if you can simultaneously show what has already been said on the subject and how your research and data supports, challenges or extends those debates. By drawing from existing literature , you are setting up a dialogue between your research and prior work, and highlighting what this research has to add to the conversation.

Suggestion : Although it might sometimes feel tedious to have to blend others’ writing in with yours, this is ultimately the best way to showcase the specialness of your own data, findings and research . Remember that it is more difficult to highlight the significance and relevance of your original work without first showing how that work fits into or responds to existing studies. 

In conclusion

The discussion chapters form the heart of your thesis and this is where your unique contribution comes to the forefront. This is where your data takes centre-stage and where you get to showcase your original arguments, perspectives and knowledge. To do this effectively needs you to explore the original themes and issues arising from and within the data, while simultaneously contextualising these findings within the larger, existing body of knowledge of your specialising field. By striking this balance, you prove the two most important qualities of excellent qualitative research : keen awareness of your field and a firm understanding of your place in it.

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• Knowledge Base
• Dissertation
• How to Write a Results Section | Tips & Examples

How to Write a Results Section | Tips & Examples

Published on August 30, 2022 by Tegan George . Revised on July 18, 2023.

A results section is where you report the main findings of the data collection and analysis you conducted for your thesis or dissertation . You should report all relevant results concisely and objectively, in a logical order. Don’t include subjective interpretations of why you found these results or what they mean—any evaluation should be saved for the discussion section .

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Table of contents

How to write a results section, reporting quantitative research results, reporting qualitative research results, results vs. discussion vs. conclusion, checklist: research results, other interesting articles, frequently asked questions about results sections.

When conducting research, it’s important to report the results of your study prior to discussing your interpretations of it. This gives your reader a clear idea of exactly what you found and keeps the data itself separate from your subjective analysis.

Here are a few best practices:

• Your results should always be written in the past tense.
• While the length of this section depends on how much data you collected and analyzed, it should be written as concisely as possible.
• Only include results that are directly relevant to answering your research questions . Avoid speculative or interpretative words like “appears” or “implies.”
• If you have other results you’d like to include, consider adding them to an appendix or footnotes.
• Always start out with your broadest results first, and then flow into your more granular (but still relevant) ones. Think of it like a shoe store: first discuss the shoes as a whole, then the sneakers, boots, sandals, etc.

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If you conducted quantitative research , you’ll likely be working with the results of some sort of statistical analysis .

Your results section should report the results of any statistical tests you used to compare groups or assess relationships between variables . It should also state whether or not each hypothesis was supported.

The most logical way to structure quantitative results is to frame them around your research questions or hypotheses. For each question or hypothesis, share:

• A reminder of the type of analysis you used (e.g., a two-sample t test or simple linear regression ). A more detailed description of your analysis should go in your methodology section.
• A concise summary of each relevant result, both positive and negative. This can include any relevant descriptive statistics (e.g., means and standard deviations ) as well as inferential statistics (e.g., t scores, degrees of freedom , and p values ). Remember, these numbers are often placed in parentheses.
• A brief statement of how each result relates to the question, or whether the hypothesis was supported. You can briefly mention any results that didn’t fit with your expectations and assumptions, but save any speculation on their meaning or consequences for your discussion  and conclusion.

A note on tables and figures

In quantitative research, it’s often helpful to include visual elements such as graphs, charts, and tables , but only if they are directly relevant to your results. Give these elements clear, descriptive titles and labels so that your reader can easily understand what is being shown. If you want to include any other visual elements that are more tangential in nature, consider adding a figure and table list .

As a rule of thumb:

• Tables are used to communicate exact values, giving a concise overview of various results
• Graphs and charts are used to visualize trends and relationships, giving an at-a-glance illustration of key findings

Don’t forget to also mention any tables and figures you used within the text of your results section. Summarize or elaborate on specific aspects you think your reader should know about rather than merely restating the same numbers already shown.

A two-sample t test was used to test the hypothesis that higher social distance from environmental problems would reduce the intent to donate to environmental organizations, with donation intention (recorded as a score from 1 to 10) as the outcome variable and social distance (categorized as either a low or high level of social distance) as the predictor variable.Social distance was found to be positively correlated with donation intention, t (98) = 12.19, p < .001, with the donation intention of the high social distance group 0.28 points higher, on average, than the low social distance group (see figure 1). This contradicts the initial hypothesis that social distance would decrease donation intention, and in fact suggests a small effect in the opposite direction.

Figure 1: Intention to donate to environmental organizations based on social distance from impact of environmental damage.

In qualitative research , your results might not all be directly related to specific hypotheses. In this case, you can structure your results section around key themes or topics that emerged from your analysis of the data.

For each theme, start with general observations about what the data showed. You can mention:

• Recurring points of agreement or disagreement
• Patterns and trends
• Particularly significant snippets from individual responses

Next, clarify and support these points with direct quotations. Be sure to report any relevant demographic information about participants. Further information (such as full transcripts , if appropriate) can be included in an appendix .

When asked about video games as a form of art, the respondents tended to believe that video games themselves are not an art form, but agreed that creativity is involved in their production. The criteria used to identify artistic video games included design, story, music, and creative teams.One respondent (male, 24) noted a difference in creativity between popular video game genres:

“I think that in role-playing games, there’s more attention to character design, to world design, because the whole story is important and more attention is paid to certain game elements […] so that perhaps you do need bigger teams of creative experts than in an average shooter or something.”

Responses suggest that video game consumers consider some types of games to have more artistic potential than others.

Your results section should objectively report your findings, presenting only brief observations in relation to each question, hypothesis, or theme.

It should not  speculate about the meaning of the results or attempt to answer your main research question . Detailed interpretation of your results is more suitable for your discussion section , while synthesis of your results into an overall answer to your main research question is best left for your conclusion .

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I have completed my data collection and analyzed the results.

I have included all results that are relevant to my research questions.

I have concisely and objectively reported each result, including relevant descriptive statistics and inferential statistics .

I have stated whether each hypothesis was supported or refuted.

I have used tables and figures to illustrate my results where appropriate.

All tables and figures are correctly labelled and referred to in the text.

There is no subjective interpretation or speculation on the meaning of the results.

You've finished writing up your results! Use the other checklists to further improve your thesis.

If you want to know more about AI for academic writing, AI tools, or research bias, make sure to check out some of our other articles with explanations and examples or go directly to our tools!

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The results chapter of a thesis or dissertation presents your research results concisely and objectively.

In quantitative research , for each question or hypothesis , state:

• The type of analysis used
• Relevant results in the form of descriptive and inferential statistics
• Whether or not the alternative hypothesis was supported

In qualitative research , for each question or theme, describe:

• Recurring patterns
• Significant or representative individual responses
• Relevant quotations from the data

Don’t interpret or speculate in the results chapter.

Results are usually written in the past tense , because they are describing the outcome of completed actions.

The results chapter or section simply and objectively reports what you found, without speculating on why you found these results. The discussion interprets the meaning of the results, puts them in context, and explains why they matter.

In qualitative research , results and discussion are sometimes combined. But in quantitative research , it’s considered important to separate the objective results from your interpretation of them.

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How To Write The Discussion Chapter

A Simple Explainer With Examples + Free Template

By: Jenna Crossley (PhD) | Reviewed By: Dr. Eunice Rautenbach | August 2021

If you’re reading this, chances are you’ve reached the discussion chapter of your thesis or dissertation and are looking for a bit of guidance. Well, you’ve come to the right place ! In this post, we’ll unpack and demystify the typical discussion chapter in straightforward, easy to understand language, with loads of examples .

Overview: The Discussion Chapter

• What  the discussion chapter is
• What to include in your discussion
• How to write up your discussion
• A few tips and tricks to help you along the way
• Free discussion template

What (exactly) is the discussion chapter?

The discussion chapter is where you interpret and explain your results within your thesis or dissertation. This contrasts with the results chapter, where you merely present and describe the analysis findings (whether qualitative or quantitative ). In the discussion chapter, you elaborate on and evaluate your research findings, and discuss the significance and implications of your results .

In this chapter, you’ll situate your research findings in terms of your research questions or hypotheses and tie them back to previous studies and literature (which you would have covered in your literature review chapter). You’ll also have a look at how relevant and/or significant your findings are to your field of research, and you’ll argue for the conclusions that you draw from your analysis. Simply put, the discussion chapter is there for you to interact with and explain your research findings in a thorough and coherent manner.

What should I include in the discussion chapter?

First things first: in some studies, the results and discussion chapter are combined into one chapter .  This depends on the type of study you conducted (i.e., the nature of the study and methodology adopted), as well as the standards set by the university.  So, check in with your university regarding their norms and expectations before getting started. In this post, we’ll treat the two chapters as separate, as this is most common.

Basically, your discussion chapter should analyse , explore the meaning and identify the importance of the data you presented in your results chapter. In the discussion chapter, you’ll give your results some form of meaning by evaluating and interpreting them. This will help answer your research questions, achieve your research aims and support your overall conclusion (s). Therefore, you discussion chapter should focus on findings that are directly connected to your research aims and questions. Don’t waste precious time and word count on findings that are not central to the purpose of your research project.

As this chapter is a reflection of your results chapter, it’s vital that you don’t report any new findings . In other words, you can’t present claims here if you didn’t present the relevant data in the results chapter first.  So, make sure that for every discussion point you raise in this chapter, you’ve covered the respective data analysis in the results chapter. If you haven’t, you’ll need to go back and adjust your results chapter accordingly.

If you’re struggling to get started, try writing down a bullet point list everything you found in your results chapter. From this, you can make a list of everything you need to cover in your discussion chapter. Also, make sure you revisit your research questions or hypotheses and incorporate the relevant discussion to address these.  This will also help you to see how you can structure your chapter logically.

Need a helping hand?

How to write the discussion chapter

Now that you’ve got a clear idea of what the discussion chapter is and what it needs to include, let’s look at how you can go about structuring this critically important chapter. Broadly speaking, there are six core components that need to be included, and these can be treated as steps in the chapter writing process.

Step 1: Restate your research problem and research questions

The first step in writing up your discussion chapter is to remind your reader of your research problem , as well as your research aim(s) and research questions . If you have hypotheses, you can also briefly mention these. This “reminder” is very important because, after reading dozens of pages, the reader may have forgotten the original point of your research or been swayed in another direction. It’s also likely that some readers skip straight to your discussion chapter from the introduction chapter , so make sure that your research aims and research questions are clear.

Step 2: Summarise your key findings

Next, you’ll want to summarise your key findings from your results chapter. This may look different for qualitative and quantitative research , where qualitative research may report on themes and relationships, whereas quantitative research may touch on correlations and causal relationships. Regardless of the methodology, in this section you need to highlight the overall key findings in relation to your research questions.

Typically, this section only requires one or two paragraphs , depending on how many research questions you have. Aim to be concise here, as you will unpack these findings in more detail later in the chapter. For now, a few lines that directly address your research questions are all that you need.

Some examples of the kind of language you’d use here include:

• The data suggest that…
• The data support/oppose the theory that…
• The analysis identifies…

These are purely examples. What you present here will be completely dependent on your original research questions, so make sure that you are led by them .

Step 3: Interpret your results

Once you’ve restated your research problem and research question(s) and briefly presented your key findings, you can unpack your findings by interpreting your results. Remember: only include what you reported in your results section – don’t introduce new information.

From a structural perspective, it can be a wise approach to follow a similar structure in this chapter as you did in your results chapter. This would help improve readability and make it easier for your reader to follow your arguments. For example, if you structured you results discussion by qualitative themes, it may make sense to do the same here.

Alternatively, you may structure this chapter by research questions, or based on an overarching theoretical framework that your study revolved around. Every study is different, so you’ll need to assess what structure works best for you.

When interpreting your results, you’ll want to assess how your findings compare to those of the existing research (from your literature review chapter). Even if your findings contrast with the existing research, you need to include these in your discussion. In fact, those contrasts are often the most interesting findings . In this case, you’d want to think about why you didn’t find what you were expecting in your data and what the significance of this contrast is.

Here are a few questions to help guide your discussion:

• How do your results relate with those of previous studies ?
• If you get results that differ from those of previous studies, why may this be the case?
• What do your results contribute to your field of research?
• What other explanations could there be for your findings?

When interpreting your findings, be careful not to draw conclusions that aren’t substantiated . Every claim you make needs to be backed up with evidence or findings from the data (and that data needs to be presented in the previous chapter – results). This can look different for different studies; qualitative data may require quotes as evidence, whereas quantitative data would use statistical methods and tests. Whatever the case, every claim you make needs to be strongly backed up.

Step 4: Acknowledge the limitations of your study

The fourth step in writing up your discussion chapter is to acknowledge the limitations of the study. These limitations can cover any part of your study , from the scope or theoretical basis to the analysis method(s) or sample. For example, you may find that you collected data from a very small sample with unique characteristics, which would mean that you are unable to generalise your results to the broader population.

For some students, discussing the limitations of their work can feel a little bit self-defeating . This is a misconception, as a core indicator of high-quality research is its ability to accurately identify its weaknesses. In other words, accurately stating the limitations of your work is a strength, not a weakness . All that said, be careful not to undermine your own research. Tell the reader what limitations exist and what improvements could be made, but also remind them of the value of your study despite its limitations.

Step 5: Make recommendations for implementation and future research

Now that you’ve unpacked your findings and acknowledge the limitations thereof, the next thing you’ll need to do is reflect on your study in terms of two factors:

• The practical application of your findings
• Suggestions for future research

The first thing to discuss is how your findings can be used in the real world – in other words, what contribution can they make to the field or industry? Where are these contributions applicable, how and why? For example, if your research is on communication in health settings, in what ways can your findings be applied to the context of a hospital or medical clinic? Make sure that you spell this out for your reader in practical terms, but also be realistic and make sure that any applications are feasible.

The next discussion point is the opportunity for future research . In other words, how can other studies build on what you’ve found and also improve the findings by overcoming some of the limitations in your study (which you discussed a little earlier). In doing this, you’ll want to investigate whether your results fit in with findings of previous research, and if not, why this may be the case. For example, are there any factors that you didn’t consider in your study? What future research can be done to remedy this? When you write up your suggestions, make sure that you don’t just say that more research is needed on the topic, also comment on how the research can build on your study.

Step 6: Provide a concluding summary

Finally, you’ve reached your final stretch. In this section, you’ll want to provide a brief recap of the key findings – in other words, the findings that directly address your research questions . Basically, your conclusion should tell the reader what your study has found, and what they need to take away from reading your report.

When writing up your concluding summary, bear in mind that some readers may skip straight to this section from the beginning of the chapter.  So, make sure that this section flows well from and has a strong connection to the opening section of the chapter.

Tips and tricks for an A-grade discussion chapter

Now that you know what the discussion chapter is , what to include and exclude , and how to structure it , here are some tips and suggestions to help you craft a quality discussion chapter.

• When you write up your discussion chapter, make sure that you keep it consistent with your introduction chapter , as some readers will skip from the introduction chapter directly to the discussion chapter. Your discussion should use the same tense as your introduction, and it should also make use of the same key terms.
• Don’t make assumptions about your readers. As a writer, you have hands-on experience with the data and so it can be easy to present it in an over-simplified manner. Make sure that you spell out your findings and interpretations for the intelligent layman.
• Have a look at other theses and dissertations from your institution, especially the discussion sections. This will help you to understand the standards and conventions of your university, and you’ll also get a good idea of how others have structured their discussion chapters. You can also check out our chapter template .
• Avoid using absolute terms such as “These results prove that…”, rather make use of terms such as “suggest” or “indicate”, where you could say, “These results suggest that…” or “These results indicate…”. It is highly unlikely that a dissertation or thesis will scientifically prove something (due to a variety of resource constraints), so be humble in your language.
• Use well-structured and consistently formatted headings to ensure that your reader can easily navigate between sections, and so that your chapter flows logically and coherently.

If you have any questions or thoughts regarding this post, feel free to leave a comment below. Also, if you’re looking for one-on-one help with your discussion chapter (or thesis in general), consider booking a free consultation with one of our highly experienced Grad Coaches to discuss how we can help you.

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37 Comments

Thank you this is helpful!

This is very helpful to me… Thanks a lot for sharing this with us 😊

This has been very helpful indeed. Thank you.

This is actually really helpful, I just stumbled upon it. Very happy that I found it, thank you.

Me too! I was kinda lost on how to approach my discussion chapter. How helpful! Thanks a lot!

This is really good and explicit. Thanks

Thank you, this blog has been such a help.

Thank you. This is very helpful.

Dear sir/madame

Thanks a lot for this helpful blog. Really, it supported me in writing my discussion chapter while I was totally unaware about its structure and method of writing.

With regards

Syed Firoz Ahmad PhD, Research Scholar

I agree so much. This blog was god sent. It assisted me so much while I was totally clueless about the context and the know-how. Now I am fully aware of what I am to do and how I am to do it.

Thanks! This is helpful!

thanks alot for this informative website

Dear Sir/Madam,

Truly, your article was much benefited when i structured my discussion chapter.

Thank you very much!!!

This is helpful for me in writing my research discussion component. I have to copy this text on Microsoft word cause of my weakness that I cannot be able to read the text on screen a long time. So many thanks for this articles.

This was helpful

Thanks Jenna, well explained.

Thank you! This is super helpful.

Thanks very much. I have appreciated the six steps on writing the Discussion chapter which are (i) Restating the research problem and questions (ii) Summarising the key findings (iii) Interpreting the results linked to relating to previous results in positive and negative ways; explaining whay different or same and contribution to field of research and expalnation of findings (iv) Acknowledgeing limitations (v) Recommendations for implementation and future resaerch and finally (vi) Providing a conscluding summary

My two questions are: 1. On step 1 and 2 can it be the overall or you restate and sumamrise on each findings based on the reaerch question? 2. On 4 and 5 do you do the acknowlledgement , recommendations on each research finding or overall. This is not clear from your expalanattion.

Please respond.

This post is very useful. I’m wondering whether practical implications must be introduced in the Discussion section or in the Conclusion section?

Sigh, I never knew a 20 min video could have literally save my life like this. I found this at the right time!!!! Everything I need to know in one video thanks a mil ! OMGG and that 6 step!!!!!! was the cherry on top the cake!!!!!!!!!

Thanks alot.., I have gained much

This piece is very helpful on how to go about my discussion section. I can always recommend GradCoach research guides for colleagues.

Many thanks for this resource. It has been very helpful to me. I was finding it hard to even write the first sentence. Much appreciated.

Thanks so much. Very helpful to know what is included in the discussion section

this was a very helpful and useful information

This is very helpful. Very very helpful. Thanks for sharing this online!

it is very helpfull article, and i will recommend it to my fellow students. Thank you.

Superlative! More grease to your elbows.

Powerful, thank you for sharing.

Wow! Just wow! God bless the day I stumbled upon you guys’ YouTube videos! It’s been truly life changing and anxiety about my report that is due in less than a month has subsided significantly!

Simplified explanation. Well done.

The presentation is enlightening. Thank you very much.

Thanks for the support and guidance

This has been a great help to me and thank you do much

I second that “it is highly unlikely that a dissertation or thesis will scientifically prove something”; although, could you enlighten us on that comment and elaborate more please?

Sure, no problem.

Scientific proof is generally considered a very strong assertion that something is definitively and universally true. In most scientific disciplines, especially within the realms of natural and social sciences, absolute proof is very rare. Instead, researchers aim to provide evidence that supports or rejects hypotheses. This evidence increases or decreases the likelihood that a particular theory is correct, but it rarely proves something in the absolute sense.

Dissertations and theses, as substantial as they are, typically focus on exploring a specific question or problem within a larger field of study. They contribute to a broader conversation and body of knowledge. The aim is often to provide detailed insight, extend understanding, and suggest directions for further research rather than to offer definitive proof. These academic works are part of a cumulative process of knowledge building where each piece of research connects with others to gradually enhance our understanding of complex phenomena.

Furthermore, the rigorous nature of scientific inquiry involves continuous testing, validation, and potential refutation of ideas. What might be considered a “proof” at one point can later be challenged by new evidence or alternative interpretations. Therefore, the language of “proof” is cautiously used in academic circles to maintain scientific integrity and humility.

This was very helpful, thank you!

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Library Guides

Dissertations 5: findings, analysis and discussion: home.

• Results/Findings

Alternative Structures

The time has come to show and discuss the findings of your research. How to structure this part of your dissertation? 

Dissertations can have different structures, as you can see in the dissertation  structure  guide.

Dissertations organised by sections

Many dissertations are organised by sections. In this case, we suggest three options. Note that, if within your course you have been instructed to use a specific structure, you should do that. Also note that sometimes there is considerable freedom on the structure, so you can come up with other structures too. 

A) More common for scientific dissertations and quantitative methods:

- Results chapter 

- Discussion chapter

Example: 

• Introduction
• Literature review
• Methodology
• (Recommendations)

if you write a scientific dissertation, or anyway using quantitative methods, you will have some  objective  results that you will present in the Results chapter. You will then interpret the results in the Discussion chapter.  

B) More common for qualitative methods

- Analysis chapter. This can have more descriptive/thematic subheadings.

- Discussion chapter. This can have more descriptive/thematic subheadings.

• Case study of Company X (fashion brand) environmental strategies 
• Successful elements
• Lessons learnt
• Criticisms of Company X environmental strategies 
• Possible alternatives

C) More common for qualitative methods

- Analysis and discussion chapter. This can have more descriptive/thematic titles.

• Case study of Company X (fashion brand) environmental strategies 

If your dissertation uses qualitative methods, it is harder to identify and report objective data. Instead, it may be more productive and meaningful to present the findings in the same sections where you also analyse, and possibly discuss, them. You will probably have different sections dealing with different themes. The different themes can be subheadings of the Analysis and Discussion (together or separate) chapter(s). 

Thematic dissertations

If the structure of your dissertation is thematic ,  you will have several chapters analysing and discussing the issues raised by your research. The chapters will have descriptive/thematic titles. 

• Background on the conflict in Yemen (2004-present day)
• Classification of the conflict in international law  
• International law violations
• Options for enforcement of international law
• Next: Results/Findings >>
• Last Updated: Aug 4, 2023 2:17 PM
• URL: https://libguides.westminster.ac.uk/c.php?g=696975

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How To Write the Findings Chapter for Qualitative Studies

Writing the findings chapter for qualitative studies is a critical step in the research process. This chapter allows researchers to present their findings, analyze the data collected, and draw conclusions based on the study’s objectives. In this blog post, I’lll explore the purpose, key elements, preparation, writing, and presentation of the findings chapter in qualitative studies.

Introduction: Contextualizing Your Findings

The introductory section serves as the gateway to your qualitative findings chapter. Begin by reiterating your problem statement and research questions, setting the stage for the data that will be presented. Highlighting the purpose of your research is crucial at this point to give context to the reader.

Example: The primary aim of this case study is to explore how educators perceive the integration of artificial intelligence (AI) tools in K-12 education settings. This research seeks to understand the perceptions and experiences of educators who have implemented AI technologies in their classrooms, framed within the context of Technological Pedagogical Content Knowledge (TPACK). In this chapter, data are systematically organized into three overarching themes, each comprising sub-themes that provide a nuanced understanding of the participants’ perspectives. The research questions guiding this investigation were: (1) What are educators’ perceptions of the role of AI tools in K-12 classrooms? (2) How do educators navigate the challenges of integrating AI tools into their teaching practices? The answers to these questions are integral to understanding the complex dynamics of AI implementation in educational contexts.  

Overview of Findings

Following this, offer a brief overview of your main findings. While you should not delve into the details here, giving the reader an idea of what to expect can be helpful. Explain the overall structure of your results chapter and how you’ve organized it to maintain coherence and logical flow.

The Heart of the Matter: The Body of Your Chapter

Presentation.

The body of the chapter is where you lay out your data for the reader. In qualitative research, this usually means dividing your data into themes or categories, which should be clearly described and substantiated with quotes and examples from your dataset. These themes provide the skeletal framework upon which your narrative is built.

Structure and Flow

When planning your qualitative findings chapter, carefully outline the sections and subsections to maintain the flow of the writing and improve readability. You can structure your chapter based on themes, which is often the case in qualitative research, but other formats like chronological or framework-based structures may be more appropriate depending on your specific research design.

✅ Consistency is Key: Make sure each portion of findings adheres to a standardized structure. This enhances consistency and enables the reader to follow your line of reasoning.

Objective and Descriptive Language

While your narrative might touch upon individual experiences and perspectives, remember to maintain an objective tone. Your task is to describe, not interpret—that comes later, in the Discussion chapter. Thus, avoid phrases that suggest interpretation, such as “suggests” or “implies.”

Visual Aids

Tables, figures, and other visual aids can add another layer of comprehension and break up the text, but make sure they can be understood independently of your body text. Label them clearly and use color coding judiciously to indicate differences or hierarchy.

Data Analysis and Interpretation

As you delve into the data, aim to narrate a coherent story. Interpret your findings in light of the literature in the field and your theoretical framework, but remember to clearly differentiate between your descriptions and your interpretations.

✅ References and Appendices: When using quotes or data excerpts, reference them appropriately. Use appendices to present additional data and ensure that you cite them according to the referencing style prescribed by your institution (e.g., APA, Harvard).

Bringing It All Together: The Concluding Summary

This is the section where you summarize your key findings in a concise manner, reiterating points that directly relate to your research questions. It serves as a stepping stone to the Discussion chapter, providing the reader with the essential takeaways. As a rule of thumb, this section should contain no new information.

Additional Tips and Tricks

– Write in the past tense, as you present findings that have already been gathered.

– Review your work multiple times, ensuring each theme or finding is backed by sufficient data.

– Use Microsoft Word’s “heading styles” for consistency.

Final Thoughts

With the right approach, writing the Findings chapter can be an enriching experience that showcases your research and prepares you for discussions and conclusions that follow. The tips and guidelines presented here are meant to make this crucial chapter as clear and impactful as possible, helping you make a valuable contribution to your field of study.

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Author:  Jessica Parker, EdD

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Qualitative Data Analysis

23 Presenting the Results of Qualitative Analysis

Mikaila Mariel Lemonik Arthur

Qualitative research is not finished just because you have determined the main findings or conclusions of your study. Indeed, disseminating the results is an essential part of the research process. By sharing your results with others, whether in written form as scholarly paper or an applied report or in some alternative format like an oral presentation, an infographic, or a video, you ensure that your findings become part of the ongoing conversation of scholarship in your field, forming part of the foundation for future researchers. This chapter provides an introduction to writing about qualitative research findings. It will outline how writing continues to contribute to the analysis process, what concerns researchers should keep in mind as they draft their presentations of findings, and how best to organize qualitative research writing

As you move through the research process, it is essential to keep yourself organized. Organizing your data, memos, and notes aids both the analytical and the writing processes. Whether you use electronic or physical, real-world filing and organizational systems, these systems help make sense of the mountains of data you have and assure you focus your attention on the themes and ideas you have determined are important (Warren and Karner 2015). Be sure that you have kept detailed notes on all of the decisions you have made and procedures you have followed in carrying out research design, data collection, and analysis, as these will guide your ultimate write-up.

First and foremost, researchers should keep in mind that writing is in fact a form of thinking. Writing is an excellent way to discover ideas and arguments and to further develop an analysis. As you write, more ideas will occur to you, things that were previously confusing will start to make sense, and arguments will take a clear shape rather than being amorphous and poorly-organized. However, writing-as-thinking cannot be the final version that you share with others. Good-quality writing does not display the workings of your thought process. It is reorganized and revised (more on that later) to present the data and arguments important in a particular piece. And revision is totally normal! No one expects the first draft of a piece of writing to be ready for prime time. So write rough drafts and memos and notes to yourself and use them to think, and then revise them until the piece is the way you want it to be for sharing.

Bergin (2018) lays out a set of key concerns for appropriate writing about research. First, present your results accurately, without exaggerating or misrepresenting. It is very easy to overstate your findings by accident if you are enthusiastic about what you have found, so it is important to take care and use appropriate cautions about the limitations of the research. You also need to work to ensure that you communicate your findings in a way people can understand, using clear and appropriate language that is adjusted to the level of those you are communicating with. And you must be clear and transparent about the methodological strategies employed in the research. Remember, the goal is, as much as possible, to describe your research in a way that would permit others to replicate the study. There are a variety of other concerns and decision points that qualitative researchers must keep in mind, including the extent to which to include quantification in their presentation of results, ethics, considerations of audience and voice, and how to bring the richness of qualitative data to life.

Quantification, as you have learned, refers to the process of turning data into numbers. It can indeed be very useful to count and tabulate quantitative data drawn from qualitative research. For instance, if you were doing a study of dual-earner households and wanted to know how many had an equal division of household labor and how many did not, you might want to count those numbers up and include them as part of the final write-up. However, researchers need to take care when they are writing about quantified qualitative data. Qualitative data is not as generalizable as quantitative data, so quantification can be very misleading. Thus, qualitative researchers should strive to use raw numbers instead of the percentages that are more appropriate for quantitative research. Writing, for instance, “15 of the 20 people I interviewed prefer pancakes to waffles” is a simple description of the data; writing “75% of people prefer pancakes” suggests a generalizable claim that is not likely supported by the data. Note that mixing numbers with qualitative data is really a type of mixed-methods approach. Mixed-methods approaches are good, but sometimes they seduce researchers into focusing on the persuasive power of numbers and tables rather than capitalizing on the inherent richness of their qualitative data.

A variety of issues of scholarly ethics and research integrity are raised by the writing process. Some of these are unique to qualitative research, while others are more universal concerns for all academic and professional writing. For example, it is essential to avoid plagiarism and misuse of sources. All quotations that appear in a text must be properly cited, whether with in-text and bibliographic citations to the source or with an attribution to the research participant (or the participant’s pseudonym or description in order to protect confidentiality) who said those words. Where writers will paraphrase a text or a participant’s words, they need to make sure that the paraphrase they develop accurately reflects the meaning of the original words. Thus, some scholars suggest that participants should have the opportunity to read (or to have read to them, if they cannot read the text themselves) all sections of the text in which they, their words, or their ideas are presented to ensure accuracy and enable participants to maintain control over their lives.

Audience and Voice

When writing, researchers must consider their audience(s) and the effects they want their writing to have on these audiences. The designated audience will dictate the voice used in the writing, or the individual style and personality of a piece of text. Keep in mind that the potential audience for qualitative research is often much more diverse than that for quantitative research because of the accessibility of the data and the extent to which the writing can be accessible and interesting. Yet individual pieces of writing are typically pitched to a more specific subset of the audience.

Let us consider one potential research study, an ethnography involving participant-observation of the same children both when they are at daycare facility and when they are at home with their families to try to understand how daycare might impact behavior and social development. The findings of this study might be of interest to a wide variety of potential audiences: academic peers, whether at your own academic institution, in your broader discipline, or multidisciplinary; people responsible for creating laws and policies; practitioners who run or teach at day care centers; and the general public, including both people who are interested in child development more generally and those who are themselves parents making decisions about child care for their own children. And the way you write for each of these audiences will be somewhat different. Take a moment and think through what some of these differences might look like.

If you are writing to academic audiences, using specialized academic language and working within the typical constraints of scholarly genres, as will be discussed below, can be an important part of convincing others that your work is legitimate and should be taken seriously. Your writing will be formal. Even if you are writing for students and faculty you already know—your classmates, for instance—you are often asked to imitate the style of academic writing that is used in publications, as this is part of learning to become part of the scholarly conversation. When speaking to academic audiences outside your discipline, you may need to be more careful about jargon and specialized language, as disciplines do not always share the same key terms. For instance, in sociology, scholars use the term diffusion to refer to the way new ideas or practices spread from organization to organization. In the field of international relations, scholars often used the term cascade to refer to the way ideas or practices spread from nation to nation. These terms are describing what is fundamentally the same concept, but they are different terms—and a scholar from one field might have no idea what a scholar from a different field is talking about! Therefore, while the formality and academic structure of the text would stay the same, a writer with a multidisciplinary audience might need to pay more attention to defining their terms in the body of the text.

It is not only other academic scholars who expect to see formal writing. Policymakers tend to expect formality when ideas are presented to them, as well. However, the content and style of the writing will be different. Much less academic jargon should be used, and the most important findings and policy implications should be emphasized right from the start rather than initially focusing on prior literature and theoretical models as you might for an academic audience. Long discussions of research methods should also be minimized. Similarly, when you write for practitioners, the findings and implications for practice should be highlighted. The reading level of the text will vary depending on the typical background of the practitioners to whom you are writing—you can make very different assumptions about the general knowledge and reading abilities of a group of hospital medical directors with MDs than you can about a group of case workers who have a post-high-school certificate. Consider the primary language of your audience as well. The fact that someone can get by in spoken English does not mean they have the vocabulary or English reading skills to digest a complex report. But the fact that someone’s vocabulary is limited says little about their intellectual abilities, so try your best to convey the important complexity of the ideas and findings from your research without dumbing them down—even if you must limit your vocabulary usage.

When writing for the general public, you will want to move even further towards emphasizing key findings and policy implications, but you also want to draw on the most interesting aspects of your data. General readers will read sociological texts that are rich with ethnographic or other kinds of detail—it is almost like reality television on a page! And this is a contrast to busy policymakers and practitioners, who probably want to learn the main findings as quickly as possible so they can go about their busy lives. But also keep in mind that there is a wide variation in reading levels. Journalists at publications pegged to the general public are often advised to write at about a tenth-grade reading level, which would leave most of the specialized terminology we develop in our research fields out of reach. If you want to be accessible to even more people, your vocabulary must be even more limited. The excellent exercise of trying to write using the 1,000 most common English words, available at the Up-Goer Five website ( https://www.splasho.com/upgoer5/ ) does a good job of illustrating this challenge (Sanderson n.d.).

Another element of voice is whether to write in the first person. While many students are instructed to avoid the use of the first person in academic writing, this advice needs to be taken with a grain of salt. There are indeed many contexts in which the first person is best avoided, at least as long as writers can find ways to build strong, comprehensible sentences without its use, including most quantitative research writing. However, if the alternative to using the first person is crafting a sentence like “it is proposed that the researcher will conduct interviews,” it is preferable to write “I propose to conduct interviews.” In qualitative research, in fact, the use of the first person is far more common. This is because the researcher is central to the research project. Qualitative researchers can themselves be understood as research instruments, and thus eliminating the use of the first person in writing is in a sense eliminating information about the conduct of the researchers themselves.

But the question really extends beyond the issue of first-person or third-person. Qualitative researchers have choices about how and whether to foreground themselves in their writing, not just in terms of using the first person, but also in terms of whether to emphasize their own subjectivity and reflexivity, their impressions and ideas, and their role in the setting. In contrast, conventional quantitative research in the positivist tradition really tries to eliminate the author from the study—which indeed is exactly why typical quantitative research avoids the use of the first person. Keep in mind that emphasizing researchers’ roles and reflexivity and using the first person does not mean crafting articles that provide overwhelming detail about the author’s thoughts and practices. Readers do not need to hear, and should not be told, which database you used to search for journal articles, how many hours you spent transcribing, or whether the research process was stressful—save these things for the memos you write to yourself. Rather, readers need to hear how you interacted with research participants, how your standpoint may have shaped the findings, and what analytical procedures you carried out.

Making Data Come Alive

One of the most important parts of writing about qualitative research is presenting the data in a way that makes its richness and value accessible to readers. As the discussion of analysis in the prior chapter suggests, there are a variety of ways to do this. Researchers may select key quotes or images to illustrate points, write up specific case studies that exemplify their argument, or develop vignettes (little stories) that illustrate ideas and themes, all drawing directly on the research data. Researchers can also write more lengthy summaries, narratives, and thick descriptions.

Nearly all qualitative work includes quotes from research participants or documents to some extent, though ethnographic work may focus more on thick description than on relaying participants’ own words. When quotes are presented, they must be explained and interpreted—they cannot stand on their own. This is one of the ways in which qualitative research can be distinguished from journalism. Journalism presents what happened, but social science needs to present the “why,” and the why is best explained by the researcher.

So how do authors go about integrating quotes into their written work? Julie Posselt (2017), a sociologist who studies graduate education, provides a set of instructions. First of all, authors need to remain focused on the core questions of their research, and avoid getting distracted by quotes that are interesting or attention-grabbing but not so relevant to the research question. Selecting the right quotes, those that illustrate the ideas and arguments of the paper, is an important part of the writing process. Second, not all quotes should be the same length (just like not all sentences or paragraphs in a paper should be the same length). Include some quotes that are just phrases, others that are a sentence or so, and others that are longer. We call longer quotes, generally those more than about three lines long, block quotes , and they are typically indented on both sides to set them off from the surrounding text. For all quotes, be sure to summarize what the quote should be telling or showing the reader, connect this quote to other quotes that are similar or different, and provide transitions in the discussion to move from quote to quote and from topic to topic. Especially for longer quotes, it is helpful to do some of this writing before the quote to preview what is coming and other writing after the quote to make clear what readers should have come to understand. Remember, it is always the author’s job to interpret the data. Presenting excerpts of the data, like quotes, in a form the reader can access does not minimize the importance of this job. Be sure that you are explaining the meaning of the data you present.

A few more notes about writing with quotes: avoid patchwriting, whether in your literature review or the section of your paper in which quotes from respondents are presented. Patchwriting is a writing practice wherein the author lightly paraphrases original texts but stays so close to those texts that there is little the author has added. Sometimes, this even takes the form of presenting a series of quotes, properly documented, with nothing much in the way of text generated by the author. A patchwriting approach does not build the scholarly conversation forward, as it does not represent any kind of new contribution on the part of the author. It is of course fine to paraphrase quotes, as long as the meaning is not changed. But if you use direct quotes, do not edit the text of the quotes unless how you edit them does not change the meaning and you have made clear through the use of ellipses (…) and brackets ([])what kinds of edits have been made. For example, consider this exchange from Matthew Desmond’s (2012:1317) research on evictions:

The thing was, I wasn’t never gonna let Crystal come and stay with me from the get go. I just told her that to throw her off. And she wasn’t fittin’ to come stay with me with no money…No. Nope. You might as well stay in that shelter.

A paraphrase of this exchange might read “She said that she was going to let Crystal stay with her if Crystal did not have any money.” Paraphrases like that are fine. What is not fine is rewording the statement but treating it like a quote, for instance writing:

The thing was, I was not going to let Crystal come and stay with me from beginning. I just told her that to throw her off. And it was not proper for her to come stay with me without any money…No. Nope. You might as well stay in that shelter.

But as you can see, the change in language and style removes some of the distinct meaning of the original quote. Instead, writers should leave as much of the original language as possible. If some text in the middle of the quote needs to be removed, as in this example, ellipses are used to show that this has occurred. And if a word needs to be added to clarify, it is placed in square brackets to show that it was not part of the original quote.

Data can also be presented through the use of data displays like tables, charts, graphs, diagrams, and infographics created for publication or presentation, as well as through the use of visual material collected during the research process. Note that if visuals are used, the author must have the legal right to use them. Photographs or diagrams created by the author themselves—or by research participants who have signed consent forms for their work to be used, are fine. But photographs, and sometimes even excerpts from archival documents, may be owned by others from whom researchers must get permission in order to use them.

A large percentage of qualitative research does not include any data displays or visualizations. Therefore, researchers should carefully consider whether the use of data displays will help the reader understand the data. One of the most common types of data displays used by qualitative researchers are simple tables. These might include tables summarizing key data about cases included in the study; tables laying out the characteristics of different taxonomic elements or types developed as part of the analysis; tables counting the incidence of various elements; and 2×2 tables (two columns and two rows) illuminating a theory. Basic network or process diagrams are also commonly included. If data displays are used, it is essential that researchers include context and analysis alongside data displays rather than letting them stand by themselves, and it is preferable to continue to present excerpts and examples from the data rather than just relying on summaries in the tables.

If you will be using graphs, infographics, or other data visualizations, it is important that you attend to making them useful and accurate (Bergin 2018). Think about the viewer or user as your audience and ensure the data visualizations will be comprehensible. You may need to include more detail or labels than you might think. Ensure that data visualizations are laid out and labeled clearly and that you make visual choices that enhance viewers’ ability to understand the points you intend to communicate using the visual in question. Finally, given the ease with which it is possible to design visuals that are deceptive or misleading, it is essential to make ethical and responsible choices in the construction of visualization so that viewers will interpret them in accurate ways.

The Genre of Research Writing

As discussed above, the style and format in which results are presented depends on the audience they are intended for. These differences in styles and format are part of the genre of writing. Genre is a term referring to the rules of a specific form of creative or productive work. Thus, the academic journal article—and student papers based on this form—is one genre. A report or policy paper is another. The discussion below will focus on the academic journal article, but note that reports and policy papers follow somewhat different formats. They might begin with an executive summary of one or a few pages, include minimal background, focus on key findings, and conclude with policy implications, shifting methods and details about the data to an appendix. But both academic journal articles and policy papers share some things in common, for instance the necessity for clear writing, a well-organized structure, and the use of headings.

So what factors make up the genre of the academic journal article in sociology? While there is some flexibility, particularly for ethnographic work, academic journal articles tend to follow a fairly standard format. They begin with a “title page” that includes the article title (often witty and involving scholarly inside jokes, but more importantly clearly describing the content of the article); the authors’ names and institutional affiliations, an abstract , and sometimes keywords designed to help others find the article in databases. An abstract is a short summary of the article that appears both at the very beginning of the article and in search databases. Abstracts are designed to aid readers by giving them the opportunity to learn enough about an article that they can determine whether it is worth their time to read the complete text. They are written about the article, and thus not in the first person, and clearly summarize the research question, methodological approach, main findings, and often the implications of the research.

After the abstract comes an “introduction” of a page or two that details the research question, why it matters, and what approach the paper will take. This is followed by a literature review of about a quarter to a third the length of the entire paper. The literature review is often divided, with headings, into topical subsections, and is designed to provide a clear, thorough overview of the prior research literature on which a paper has built—including prior literature the new paper contradicts. At the end of the literature review it should be made clear what researchers know about the research topic and question, what they do not know, and what this new paper aims to do to address what is not known.

The next major section of the paper is the section that describes research design, data collection, and data analysis, often referred to as “research methods” or “methodology.” This section is an essential part of any written or oral presentation of your research. Here, you tell your readers or listeners “how you collected and interpreted your data” (Taylor, Bogdan, and DeVault 2016:215). Taylor, Bogdan, and DeVault suggest that the discussion of your research methods include the following:

• The particular approach to data collection used in the study;
• Any theoretical perspective(s) that shaped your data collection and analytical approach;
• When the study occurred, over how long, and where (concealing identifiable details as needed);
• A description of the setting and participants, including sampling and selection criteria (if an interview-based study, the number of participants should be clearly stated);
• The researcher’s perspective in carrying out the study, including relevant elements of their identity and standpoint, as well as their role (if any) in research settings; and
• The approach to analyzing the data.

After the methods section comes a section, variously titled but often called “data,” that takes readers through the analysis. This section is where the thick description narrative; the quotes, broken up by theme or topic, with their interpretation; the discussions of case studies; most data displays (other than perhaps those outlining a theoretical model or summarizing descriptive data about cases); and other similar material appears. The idea of the data section is to give readers the ability to see the data for themselves and to understand how this data supports the ultimate conclusions. Note that all tables and figures included in formal publications should be titled and numbered.

At the end of the paper come one or two summary sections, often called “discussion” and/or “conclusion.” If there is a separate discussion section, it will focus on exploring the overall themes and findings of the paper. The conclusion clearly and succinctly summarizes the findings and conclusions of the paper, the limitations of the research and analysis, any suggestions for future research building on the paper or addressing these limitations, and implications, be they for scholarship and theory or policy and practice.

After the end of the textual material in the paper comes the bibliography, typically called “works cited” or “references.” The references should appear in a consistent citation style—in sociology, we often use the American Sociological Association format (American Sociological Association 2019), but other formats may be used depending on where the piece will eventually be published. Care should be taken to ensure that in-text citations also reflect the chosen citation style. In some papers, there may be an appendix containing supplemental information such as a list of interview questions or an additional data visualization.

Note that when researchers give presentations to scholarly audiences, the presentations typically follow a format similar to that of scholarly papers, though given time limitations they are compressed. Abstracts and works cited are often not part of the presentation, though in-text citations are still used. The literature review presented will be shortened to only focus on the most important aspects of the prior literature, and only key examples from the discussion of data will be included. For long or complex papers, sometimes only one of several findings is the focus of the presentation. Of course, presentations for other audiences may be constructed differently, with greater attention to interesting elements of the data and findings as well as implications and less to the literature review and methods.

Concluding Your Work

After you have written a complete draft of the paper, be sure you take the time to revise and edit your work. There are several important strategies for revision. First, put your work away for a little while. Even waiting a day to revise is better than nothing, but it is best, if possible, to take much more time away from the text. This helps you forget what your writing looks like and makes it easier to find errors, mistakes, and omissions. Second, show your work to others. Ask them to read your work and critique it, pointing out places where the argument is weak, where you may have overlooked alternative explanations, where the writing could be improved, and what else you need to work on. Finally, read your work out loud to yourself (or, if you really need an audience, try reading to some stuffed animals). Reading out loud helps you catch wrong words, tricky sentences, and many other issues. But as important as revision is, try to avoid perfectionism in writing (Warren and Karner 2015). Writing can always be improved, no matter how much time you spend on it. Those improvements, however, have diminishing returns, and at some point the writing process needs to conclude so the writing can be shared with the world.

Of course, the main goal of writing up the results of a research project is to share with others. Thus, researchers should be considering how they intend to disseminate their results. What conferences might be appropriate? Where can the paper be submitted? Note that if you are an undergraduate student, there are a wide variety of journals that accept and publish research conducted by undergraduates. Some publish across disciplines, while others are specific to disciplines. Other work, such as reports, may be best disseminated by publication online on relevant organizational websites.

After a project is completed, be sure to take some time to organize your research materials and archive them for longer-term storage. Some Institutional Review Board (IRB) protocols require that original data, such as interview recordings, transcripts, and field notes, be preserved for a specific number of years in a protected (locked for paper or password-protected for digital) form and then destroyed, so be sure that your plans adhere to the IRB requirements. Be sure you keep any materials that might be relevant for future related research or for answering questions people may ask later about your project.

And then what? Well, then it is time to move on to your next research project. Research is a long-term endeavor, not a one-time-only activity. We build our skills and our expertise as we continue to pursue research. So keep at it.

• Find a short article that uses qualitative methods. The sociological magazine Contexts is a good place to find such pieces. Write an abstract of the article.
• Choose a sociological journal article on a topic you are interested in that uses some form of qualitative methods and is at least 20 pages long. Rewrite the article as a five-page research summary accessible to non-scholarly audiences.
• Choose a concept or idea you have learned in this course and write an explanation of it using the Up-Goer Five Text Editor ( https://www.splasho.com/upgoer5/ ), a website that restricts your writing to the 1,000 most common English words. What was this experience like? What did it teach you about communicating with people who have a more limited English-language vocabulary—and what did it teach you about the utility of having access to complex academic language?
• Select five or more sociological journal articles that all use the same basic type of qualitative methods (interviewing, ethnography, documents, or visual sociology). Using what you have learned about coding, code the methods sections of each article, and use your coding to figure out what is common in how such articles discuss their research design, data collection, and analysis methods.
• Return to an exercise you completed earlier in this course and revise your work. What did you change? How did revising impact the final product?
• Find a quote from the transcript of an interview, a social media post, or elsewhere that has not yet been interpreted or explained. Write a paragraph that includes the quote along with an explanation of its sociological meaning or significance.

The style or personality of a piece of writing, including such elements as tone, word choice, syntax, and rhythm.

A quotation, usually one of some length, which is set off from the main text by being indented on both sides rather than being placed in quotation marks.

A classification of written or artistic work based on form, content, and style.

A short summary of a text written from the perspective of a reader rather than from the perspective of an author.

Social Data Analysis Copyright © 2021 by Mikaila Mariel Lemonik Arthur is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

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• v.74(8); 2010 Oct 11

Presenting and Evaluating Qualitative Research

The purpose of this paper is to help authors to think about ways to present qualitative research papers in the American Journal of Pharmaceutical Education . It also discusses methods for reviewers to assess the rigour, quality, and usefulness of qualitative research. Examples of different ways to present data from interviews, observations, and focus groups are included. The paper concludes with guidance for publishing qualitative research and a checklist for authors and reviewers.

INTRODUCTION

Policy and practice decisions, including those in education, increasingly are informed by findings from qualitative as well as quantitative research. Qualitative research is useful to policymakers because it often describes the settings in which policies will be implemented. Qualitative research is also useful to both pharmacy practitioners and pharmacy academics who are involved in researching educational issues in both universities and practice and in developing teaching and learning.

Qualitative research involves the collection, analysis, and interpretation of data that are not easily reduced to numbers. These data relate to the social world and the concepts and behaviors of people within it. Qualitative research can be found in all social sciences and in the applied fields that derive from them, for example, research in health services, nursing, and pharmacy. 1 It looks at X in terms of how X varies in different circumstances rather than how big is X or how many Xs are there? 2 Textbooks often subdivide research into qualitative and quantitative approaches, furthering the common assumption that there are fundamental differences between the 2 approaches. With pharmacy educators who have been trained in the natural and clinical sciences, there is often a tendency to embrace quantitative research, perhaps due to familiarity. A growing consensus is emerging that sees both qualitative and quantitative approaches as useful to answering research questions and understanding the world. Increasingly mixed methods research is being carried out where the researcher explicitly combines the quantitative and qualitative aspects of the study. 3 , 4

Like healthcare, education involves complex human interactions that can rarely be studied or explained in simple terms. Complex educational situations demand complex understanding; thus, the scope of educational research can be extended by the use of qualitative methods. Qualitative research can sometimes provide a better understanding of the nature of educational problems and thus add to insights into teaching and learning in a number of contexts. For example, at the University of Nottingham, we conducted in-depth interviews with pharmacists to determine their perceptions of continuing professional development and who had influenced their learning. We also have used a case study approach using observation of practice and in-depth interviews to explore physiotherapists' views of influences on their leaning in practice. We have conducted in-depth interviews with a variety of stakeholders in Malawi, Africa, to explore the issues surrounding pharmacy academic capacity building. A colleague has interviewed and conducted focus groups with students to explore cultural issues as part of a joint Nottingham-Malaysia pharmacy degree program. Another colleague has interviewed pharmacists and patients regarding their expectations before and after clinic appointments and then observed pharmacist-patient communication in clinics and assessed it using the Calgary Cambridge model in order to develop recommendations for communication skills training. 5 We have also performed documentary analysis on curriculum data to compare pharmacist and nurse supplementary prescribing courses in the United Kingdom.

It is important to choose the most appropriate methods for what is being investigated. Qualitative research is not appropriate to answer every research question and researchers need to think carefully about their objectives. Do they wish to study a particular phenomenon in depth (eg, students' perceptions of studying in a different culture)? Or are they more interested in making standardized comparisons and accounting for variance (eg, examining differences in examination grades after changing the way the content of a module is taught). Clearly a quantitative approach would be more appropriate in the last example. As with any research project, a clear research objective has to be identified to know which methods should be applied.

Types of qualitative data include:

• Audio recordings and transcripts from in-depth or semi-structured interviews
• Structured interview questionnaires containing substantial open comments including a substantial number of responses to open comment items.
• Audio recordings and transcripts from focus group sessions.
• Field notes (notes taken by the researcher while in the field [setting] being studied)
• Video recordings (eg, lecture delivery, class assignments, laboratory performance)
• Case study notes
• Documents (reports, meeting minutes, e-mails)
• Diaries, video diaries
• Observation notes
• Press clippings
• Photographs

RIGOUR IN QUALITATIVE RESEARCH

Qualitative research is often criticized as biased, small scale, anecdotal, and/or lacking rigor; however, when it is carried out properly it is unbiased, in depth, valid, reliable, credible and rigorous. In qualitative research, there needs to be a way of assessing the “extent to which claims are supported by convincing evidence.” 1 Although the terms reliability and validity traditionally have been associated with quantitative research, increasingly they are being seen as important concepts in qualitative research as well. Examining the data for reliability and validity assesses both the objectivity and credibility of the research. Validity relates to the honesty and genuineness of the research data, while reliability relates to the reproducibility and stability of the data.

The validity of research findings refers to the extent to which the findings are an accurate representation of the phenomena they are intended to represent. The reliability of a study refers to the reproducibility of the findings. Validity can be substantiated by a number of techniques including triangulation use of contradictory evidence, respondent validation, and constant comparison. Triangulation is using 2 or more methods to study the same phenomenon. Contradictory evidence, often known as deviant cases, must be sought out, examined, and accounted for in the analysis to ensure that researcher bias does not interfere with or alter their perception of the data and any insights offered. Respondent validation, which is allowing participants to read through the data and analyses and provide feedback on the researchers' interpretations of their responses, provides researchers with a method of checking for inconsistencies, challenges the researchers' assumptions, and provides them with an opportunity to re-analyze their data. The use of constant comparison means that one piece of data (for example, an interview) is compared with previous data and not considered on its own, enabling researchers to treat the data as a whole rather than fragmenting it. Constant comparison also enables the researcher to identify emerging/unanticipated themes within the research project.

STRENGTHS AND LIMITATIONS OF QUALITATIVE RESEARCH

Qualitative researchers have been criticized for overusing interviews and focus groups at the expense of other methods such as ethnography, observation, documentary analysis, case studies, and conversational analysis. Qualitative research has numerous strengths when properly conducted.

Strengths of Qualitative Research

• Issues can be examined in detail and in depth.
• Interviews are not restricted to specific questions and can be guided/redirected by the researcher in real time.
• The research framework and direction can be quickly revised as new information emerges.
• The data based on human experience that is obtained is powerful and sometimes more compelling than quantitative data.
• Subtleties and complexities about the research subjects and/or topic are discovered that are often missed by more positivistic enquiries.
• Data usually are collected from a few cases or individuals so findings cannot be generalized to a larger population. Findings can however be transferable to another setting.

Limitations of Qualitative Research

• Research quality is heavily dependent on the individual skills of the researcher and more easily influenced by the researcher's personal biases and idiosyncrasies.
• Rigor is more difficult to maintain, assess, and demonstrate.
• The volume of data makes analysis and interpretation time consuming.
• It is sometimes not as well understood and accepted as quantitative research within the scientific community
• The researcher's presence during data gathering, which is often unavoidable in qualitative research, can affect the subjects' responses.
• Issues of anonymity and confidentiality can present problems when presenting findings
• Findings can be more difficult and time consuming to characterize in a visual way.

PRESENTATION OF QUALITATIVE RESEARCH FINDINGS

The following extracts are examples of how qualitative data might be presented:

Data From an Interview.

The following is an example of how to present and discuss a quote from an interview.

The researcher should select quotes that are poignant and/or most representative of the research findings. Including large portions of an interview in a research paper is not necessary and often tedious for the reader. The setting and speakers should be established in the text at the end of the quote.

The student describes how he had used deep learning in a dispensing module. He was able to draw on learning from a previous module, “I found that while using the e learning programme I was able to apply the knowledge and skills that I had gained in last year's diseases and goals of treatment module.” (interviewee 22, male)

This is an excerpt from an article on curriculum reform that used interviews 5 :

The first question was, “Without the accreditation mandate, how much of this curriculum reform would have been attempted?” According to respondents, accreditation played a significant role in prompting the broad-based curricular change, and their comments revealed a nuanced view. Most indicated that the change would likely have occurred even without the mandate from the accreditation process: “It reflects where the profession wants to be … training a professional who wants to take on more responsibility.” However, they also commented that “if it were not mandated, it could have been a very difficult road.” Or it “would have happened, but much later.” The change would more likely have been incremental, “evolutionary,” or far more limited in its scope. “Accreditation tipped the balance” was the way one person phrased it. “Nobody got serious until the accrediting body said it would no longer accredit programs that did not change.”

Data From Observations

The following example is some data taken from observation of pharmacist patient consultations using the Calgary Cambridge guide. 6 , 7 The data are first presented and a discussion follows:

Pharmacist: We will soon be starting a stop smoking clinic. Patient: Is the interview over now? Pharmacist: No this is part of it. (Laughs) You can't tell me to bog off (sic) yet. (pause) We will be starting a stop smoking service here, Patient: Yes. Pharmacist: with one-to-one and we will be able to help you or try to help you. If you want it. In this example, the pharmacist has picked up from the patient's reaction to the stop smoking clinic that she is not receptive to advice about giving up smoking at this time; in fact she would rather end the consultation. The pharmacist draws on his prior relationship with the patient and makes use of a joke to lighten the tone. He feels his message is important enough to persevere but he presents the information in a succinct and non-pressurised way. His final comment of “If you want it” is important as this makes it clear that he is not putting any pressure on the patient to take up this offer. This extract shows that some patient cues were picked up, and appropriately dealt with, but this was not the case in all examples.

Data From Focus Groups

This excerpt from a study involving 11 focus groups illustrates how findings are presented using representative quotes from focus group participants. 8

Those pharmacists who were initially familiar with CPD endorsed the model for their peers, and suggested it had made a meaningful difference in the way they viewed their own practice. In virtually all focus groups sessions, pharmacists familiar with and supportive of the CPD paradigm had worked in collaborative practice environments such as hospital pharmacy practice. For these pharmacists, the major advantage of CPD was the linking of workplace learning with continuous education. One pharmacist stated, “It's amazing how much I have to learn every day, when I work as a pharmacist. With [the learning portfolio] it helps to show how much learning we all do, every day. It's kind of satisfying to look it over and see how much you accomplish.” Within many of the learning portfolio-sharing sessions, debates emerged regarding the true value of traditional continuing education and its outcome in changing an individual's practice. While participants appreciated the opportunity for social and professional networking inherent in some forms of traditional CE, most eventually conceded that the academic value of most CE programming was limited by the lack of a systematic process for following-up and implementing new learning in the workplace. “Well it's nice to go to these [continuing education] events, but really, I don't know how useful they are. You go, you sit, you listen, but then, well I at least forget.”

The following is an extract from a focus group (conducted by the author) with first-year pharmacy students about community placements. It illustrates how focus groups provide a chance for participants to discuss issues on which they might disagree.

Interviewer: So you are saying that you would prefer health related placements? Student 1: Not exactly so long as I could be developing my communication skill. Student 2: Yes but I still think the more health related the placement is the more I'll gain from it. Student 3: I disagree because other people related skills are useful and you may learn those from taking part in a community project like building a garden. Interviewer: So would you prefer a mixture of health and non health related community placements?

GUIDANCE FOR PUBLISHING QUALITATIVE RESEARCH

Qualitative research is becoming increasingly accepted and published in pharmacy and medical journals. Some journals and publishers have guidelines for presenting qualitative research, for example, the British Medical Journal 9 and Biomedcentral . 10 Medical Education published a useful series of articles on qualitative research. 11 Some of the important issues that should be considered by authors, reviewers and editors when publishing qualitative research are discussed below.

Introduction.

A good introduction provides a brief overview of the manuscript, including the research question and a statement justifying the research question and the reasons for using qualitative research methods. This section also should provide background information, including relevant literature from pharmacy, medicine, and other health professions, as well as literature from the field of education that addresses similar issues. Any specific educational or research terminology used in the manuscript should be defined in the introduction.

The methods section should clearly state and justify why the particular method, for example, face to face semistructured interviews, was chosen. The method should be outlined and illustrated with examples such as the interview questions, focusing exercises, observation criteria, etc. The criteria for selecting the study participants should then be explained and justified. The way in which the participants were recruited and by whom also must be stated. A brief explanation/description should be included of those who were invited to participate but chose not to. It is important to consider “fair dealing,” ie, whether the research design explicitly incorporates a wide range of different perspectives so that the viewpoint of 1 group is never presented as if it represents the sole truth about any situation. The process by which ethical and or research/institutional governance approval was obtained should be described and cited.

The study sample and the research setting should be described. Sampling differs between qualitative and quantitative studies. In quantitative survey studies, it is important to select probability samples so that statistics can be used to provide generalizations to the population from which the sample was drawn. Qualitative research necessitates having a small sample because of the detailed and intensive work required for the study. So sample sizes are not calculated using mathematical rules and probability statistics are not applied. Instead qualitative researchers should describe their sample in terms of characteristics and relevance to the wider population. Purposive sampling is common in qualitative research. Particular individuals are chosen with characteristics relevant to the study who are thought will be most informative. Purposive sampling also may be used to produce maximum variation within a sample. Participants being chosen based for example, on year of study, gender, place of work, etc. Representative samples also may be used, for example, 20 students from each of 6 schools of pharmacy. Convenience samples involve the researcher choosing those who are either most accessible or most willing to take part. This may be fine for exploratory studies; however, this form of sampling may be biased and unrepresentative of the population in question. Theoretical sampling uses insights gained from previous research to inform sample selection for a new study. The method for gaining informed consent from the participants should be described, as well as how anonymity and confidentiality of subjects were guaranteed. The method of recording, eg, audio or video recording, should be noted, along with procedures used for transcribing the data.

Data Analysis.

A description of how the data were analyzed also should be included. Was computer-aided qualitative data analysis software such as NVivo (QSR International, Cambridge, MA) used? Arrival at “data saturation” or the end of data collection should then be described and justified. A good rule when considering how much information to include is that readers should have been given enough information to be able to carry out similar research themselves.

One of the strengths of qualitative research is the recognition that data must always be understood in relation to the context of their production. 1 The analytical approach taken should be described in detail and theoretically justified in light of the research question. If the analysis was repeated by more than 1 researcher to ensure reliability or trustworthiness, this should be stated and methods of resolving any disagreements clearly described. Some researchers ask participants to check the data. If this was done, it should be fully discussed in the paper.

An adequate account of how the findings were produced should be included A description of how the themes and concepts were derived from the data also should be included. Was an inductive or deductive process used? The analysis should not be limited to just those issues that the researcher thinks are important, anticipated themes, but also consider issues that participants raised, ie, emergent themes. Qualitative researchers must be open regarding the data analysis and provide evidence of their thinking, for example, were alternative explanations for the data considered and dismissed, and if so, why were they dismissed? It also is important to present outlying or negative/deviant cases that did not fit with the central interpretation.

The interpretation should usually be grounded in interviewees or respondents' contributions and may be semi-quantified, if this is possible or appropriate, for example, “Half of the respondents said …” “The majority said …” “Three said…” Readers should be presented with data that enable them to “see what the researcher is talking about.” 1 Sufficient data should be presented to allow the reader to clearly see the relationship between the data and the interpretation of the data. Qualitative data conventionally are presented by using illustrative quotes. Quotes are “raw data” and should be compiled and analyzed, not just listed. There should be an explanation of how the quotes were chosen and how they are labeled. For example, have pseudonyms been given to each respondent or are the respondents identified using codes, and if so, how? It is important for the reader to be able to see that a range of participants have contributed to the data and that not all the quotes are drawn from 1 or 2 individuals. There is a tendency for authors to overuse quotes and for papers to be dominated by a series of long quotes with little analysis or discussion. This should be avoided.

Participants do not always state the truth and may say what they think the interviewer wishes to hear. A good qualitative researcher should not only examine what people say but also consider how they structured their responses and how they talked about the subject being discussed, for example, the person's emotions, tone, nonverbal communication, etc. If the research was triangulated with other qualitative or quantitative data, this should be discussed.

Discussion.

The findings should be presented in the context of any similar previous research and or theories. A discussion of the existing literature and how this present research contributes to the area should be included. A consideration must also be made about how transferrable the research would be to other settings. Any particular strengths and limitations of the research also should be discussed. It is common practice to include some discussion within the results section of qualitative research and follow with a concluding discussion.

The author also should reflect on their own influence on the data, including a consideration of how the researcher(s) may have introduced bias to the results. The researcher should critically examine their own influence on the design and development of the research, as well as on data collection and interpretation of the data, eg, were they an experienced teacher who researched teaching methods? If so, they should discuss how this might have influenced their interpretation of the results.

Conclusion.

The conclusion should summarize the main findings from the study and emphasize what the study adds to knowledge in the area being studied. Mays and Pope suggest the researcher ask the following 3 questions to determine whether the conclusions of a qualitative study are valid 12 : How well does this analysis explain why people behave in the way they do? How comprehensible would this explanation be to a thoughtful participant in the setting? How well does the explanation cohere with what we already know?

CHECKLIST FOR QUALITATIVE PAPERS

This paper establishes criteria for judging the quality of qualitative research. It provides guidance for authors and reviewers to prepare and review qualitative research papers for the American Journal of Pharmaceutical Education . A checklist is provided in Appendix 1 to assist both authors and reviewers of qualitative data.

ACKNOWLEDGEMENTS

Thank you to the 3 reviewers whose ideas helped me to shape this paper.

Appendix 1. Checklist for authors and reviewers of qualitative research.

Introduction

• □ Research question is clearly stated.
• □ Research question is justified and related to the existing knowledge base (empirical research, theory, policy).
• □ Any specific research or educational terminology used later in manuscript is defined.
• □ The process by which ethical and or research/institutional governance approval was obtained is described and cited.
• □ Reason for choosing particular research method is stated.
• □ Criteria for selecting study participants are explained and justified.
• □ Recruitment methods are explicitly stated.
• □ Details of who chose not to participate and why are given.
• □ Study sample and research setting used are described.
• □ Method for gaining informed consent from the participants is described.
• □ Maintenance/Preservation of subject anonymity and confidentiality is described.
• □ Method of recording data (eg, audio or video recording) and procedures for transcribing data are described.
• □ Methods are outlined and examples given (eg, interview guide).
• □ Decision to stop data collection is described and justified.
• □ Data analysis and verification are described, including by whom they were performed.
• □ Methods for identifying/extrapolating themes and concepts from the data are discussed.
• □ Sufficient data are presented to allow a reader to assess whether or not the interpretation is supported by the data.
• □ Outlying or negative/deviant cases that do not fit with the central interpretation are presented.
• □ Transferability of research findings to other settings is discussed.
• □ Findings are presented in the context of any similar previous research and social theories.
• □ Discussion often is incorporated into the results in qualitative papers.
• □ A discussion of the existing literature and how this present research contributes to the area is included.
• □ Any particular strengths and limitations of the research are discussed.
• □ Reflection of the influence of the researcher(s) on the data, including a consideration of how the researcher(s) may have introduced bias to the results is included.

Conclusions

• □ The conclusion states the main finings of the study and emphasizes what the study adds to knowledge in the subject area.

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Presenting your qualitative analysis findings: tables to include in chapter 4.

The earliest stages of developing a doctoral dissertation—most specifically the topic development  and literature review  stages—require that you immerse yourself in a ton of existing research related to your potential topic. If you have begun writing your dissertation proposal, you have undoubtedly reviewed countless results and findings sections of studies in order to help gain an understanding of what is currently known about your topic. 

In this process, we’re guessing that you observed a distinct pattern: Results sections are full of tables. Indeed, the results chapter for your own dissertation will need to be similarly packed with tables. So, if you’re preparing to write up the results of your statistical analysis or qualitative analysis, it will probably help to review your APA editing  manual to brush up on your table formatting skills. But, aside from formatting, how should you develop the tables in your results chapter?

In quantitative studies, tables are a handy way of presenting the variety of statistical analysis results in a form that readers can easily process. You’ve probably noticed that quantitative studies present descriptive results like mean, mode, range, standard deviation, etc., as well the inferential results that indicate whether significant relationships or differences were found through the statistical analysis . These are pretty standard tables that you probably learned about in your pre-dissertation statistics courses.

But, what if you are conducting qualitative analysis? What tables are appropriate for this type of study? This is a question we hear often from our dissertation assistance  clients, and with good reason. University guidelines for results chapters often contain vague instructions that guide you to include “appropriate tables” without specifying what exactly those are. To help clarify on this point, we asked our qualitative analysis experts to share their recommendations for tables to include in your Chapter 4.

Demographics Tables

As with studies using quantitative methods , presenting an overview of your sample demographics is useful in studies that use qualitative research methods. The standard demographics table in a quantitative study provides aggregate information for what are often large samples. In other words, such tables present totals and percentages for demographic categories within the sample that are relevant to the study (e.g., age, gender, job title). 

If conducting qualitative research  for your dissertation, however, you will use a smaller sample and obtain richer data from each participant than in quantitative studies. To enhance thick description—a dimension of trustworthiness—it will help to present sample demographics in a table that includes information on each participant. Remember that ethical standards of research require that all participant information be deidentified, so use participant identification numbers or pseudonyms for each participant, and do not present any personal information that would allow others to identify the participant (Blignault & Ritchie, 2009). Table 1 provides participant demographics for a hypothetical qualitative research study exploring the perspectives of persons who were formerly homeless regarding their experiences of transitioning into stable housing and obtaining employment.

Participant Demographics

Tables to Illustrate Initial Codes

Most of our dissertation consulting clients who are conducting qualitative research choose a form of thematic analysis . Qualitative analysis to identify themes in the data typically involves a progression from (a) identifying surface-level codes to (b) developing themes by combining codes based on shared similarities. As this process is inherently subjective, it is important that readers be able to evaluate the correspondence between the data and your findings (Anfara et al., 2002). This supports confirmability, another dimension of trustworthiness .

A great way to illustrate the trustworthiness of your qualitative analysis is to create a table that displays quotes from the data that exemplify each of your initial codes. Providing a sample quote for each of your codes can help the reader to assess whether your coding was faithful to the meanings in the data, and it can also help to create clarity about each code’s meaning and bring the voices of your participants into your work (Blignault & Ritchie, 2009).

Table 2 is an example of how you might present information regarding initial codes. Depending on your preference or your dissertation committee’s preference, you might also present percentages of the sample that expressed each code. Another common piece of information to include is which actual participants expressed each code. Note that if your qualitative analysis yields a high volume of codes, it may be appropriate to present the table as an appendix.

Initial Codes

Tables to Present the Groups of Codes That Form Each Theme

As noted previously, most of our dissertation assistance clients use a thematic analysis approach, which involves multiple phases of qualitative analysis  that eventually result in themes that answer the dissertation’s research questions. After initial coding is completed, the analysis process involves (a) examining what different codes have in common and then (b) grouping similar codes together in ways that are meaningful given your research questions. In other words, the common threads that you identify across multiple codes become the theme that holds them all together—and that theme answers one of your research questions.

As with initial coding, grouping codes together into themes involves your own subjective interpretations, even when aided by qualitative analysis software such as NVivo  or MAXQDA. In fact, our dissertation assistance clients are often surprised to learn that qualitative analysis software does not complete the analysis in the same ways that statistical analysis software such as SPSS does. While statistical analysis software completes the computations for you, qualitative analysis software does not have such analysis capabilities. Software such as NVivo provides a set of organizational tools that make the qualitative analysis far more convenient, but the analysis itself is still a very human process (Burnard et al., 2008).

Because of the subjective nature of qualitative analysis, it is important to show the underlying logic behind your thematic analysis in tables—such tables help readers to assess the trustworthiness of your analysis. Table 3 provides an example of how to present the codes that were grouped together to create themes, and you can modify the specifics of the table based on your preferences or your dissertation committee’s requirements. For example, this type of table might be presented to illustrate the codes associated with themes that answer each research question. 

Grouping of Initial Codes to Form Themes

Tables to Illustrate the Themes That Answer Each Research Question

Creating alignment throughout your dissertation is an important objective, and to maintain alignment in your results chapter, the themes you present must clearly answer your research questions. Conducting qualitative analysis is an in-depth process of immersion in the data, and many of our dissertation consulting  clients have shared that it’s easy to lose your direction during the process. So, it is important to stay focused on your research questions during the qualitative analysis and also to show the reader exactly which themes—and subthemes, as applicable—answered each of the research questions.

Below, Table 4 provides an example of how to display the thematic findings of your study in table form. Depending on your dissertation committee’s preference or your own, you might present all research questions and all themes and subthemes in a single table. Or, you might provide separate tables to introduce the themes for each research question as you progress through your presentation of the findings in the chapter.

Emergent Themes and Research Questions

Bonus Tip! Figures to Spice Up Your Results

Although dissertation committees most often wish to see tables such as the above in qualitative results chapters, some also like to see figures that illustrate the data. Qualitative software packages such as NVivo offer many options for visualizing your data, such as mind maps, concept maps, charts, and cluster diagrams. A common choice for this type of figure among our dissertation assistance clients is a tree diagram, which shows the connections between specified words and the words or phrases that participants shared most often in the same context. Another common choice of figure is the word cloud, as depicted in Figure 1. The word cloud simply reflects frequencies of words in the data, which may provide an indication of the importance of related concepts for the participants.

As you move forward with your qualitative analysis and development of your results chapter, we hope that this brief overview of useful tables and figures helps you to decide on an ideal presentation to showcase the trustworthiness your findings. Completing a rigorous qualitative analysis for your dissertation requires many hours of careful interpretation of your data, and your end product should be a rich and detailed results presentation that you can be proud of. Reach out if we can help  in any way, as our dissertation coaches would be thrilled to assist as you move through this exciting stage of your dissertation journey!

Anfara Jr., V. A., Brown, K. M., & Mangione, T. L. (2002). Qualitative analysis on stage: Making the research process more public.  Educational Researcher ,  31 (7), 28-38. https://doi.org/10.3102/0013189X031007028

Blignault, I., & Ritchie, J. (2009). Revealing the wood and the trees: Reporting qualitative research.  Health Promotion Journal of Australia ,  20 (2), 140-145. https://doi.org/10.1071/HE09140

Burnard, P., Gill, P., Stewart, K., Treasure, E., & Chadwick, B. (2008). Analysing and presenting qualitative data.  British Dental Journal ,  204 (8), 429-432. https://doi.org/10.1038/sj.bdj.2008.292

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Dissertation findings and discussion sections

(Last updated: 2 March 2020)

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We have helped 10,000s of undergraduate, Masters and PhD students to maximise their grades in essays, dissertations, model-exam answers, applications and other materials. If you would like a free chat about your project with one of our UK staff, then please just reach out on one of the methods below.

Granted that at some point in the discussion you are going to have to link back to this previous research. But you still have the opportunity to demonstrate how you have met that coveted gap in the research and generally made a useful contribution to knowledge.

There are many ways to write up both your findings and discussion. In shorter dissertations, it might make sense to have both of these comprise one section. In longer pieces of work, these chapters are usually separate.

Preparing to write

We also assume that you have used some sort of software program to help you with the organisation of your findings. If you have not completed this process, you must do so before beginning to write. If not, your findings chapter may end up a confusing and unorganised mess of random information. If you need help in this area, make sure to seek it out before beginning to put your findings down on paper.

One of the main issues that students tend to encounter when writing up their findings is the amount of data to include. By the end of the research process, you've probably collected very large amounts of data . Not all of this can possibly appear in your dissertation without completely overwhelming the reader. As a result, you need to be able to make smart decisions about what to include and what to leave out.

One of the easiest ways to approach this task is to create an outline. In approaching the outline, it is in your best interest to focus on two key points. Firstly, you need to focus on answering your research questions. Secondly, you must include any particularly interesting findings that have cropped up as you completed your research.

An outline will give you the structure you need, and should make the whole process of presenting your findings easier. We realise that it is going to be a difficult process to pick and choose pieces of data to include. But you must be diligent in the work that you cut out. A findings chapter that is long and confusing is going to put the reader off reading the rest of your work.

Introducing your findings

It can be up to 40% of the total word count within your dissertation writing . This is a huge chunk of information, so it's essential that it is clearly organised and that the reader knows what is supposed to be happening. One of the ways you can achieve this is through a logical and organised introduction.

There are four main components that your introduction should include:

Reminding the reader of what you set out to do

A brief description of how you intend approaching the write up of the results

Placing the research in context

Letting the reader know where they can find the research instruments (i.e. the Appendix)

With a findings chapter, there should be no suspense for the reader. You need to tell them what they need to know right from the beginning. This way, they'll have a clear idea about what is still to come. A good introduction will start by telling the reader where you have come from in the research process and what the outcome was (in a couple of paragraphs or less).

You need to highlight the structure of the chapter (as you generally will do with all chapters) and where the reader might find any further information (e.g. in the appendices).

Organisation of data

This is really going to depend on the type of project you have created .

For example, if you have completed a qualitative research project, you might have identified some key themes within the software program you used to organise your data. In this case, highlighting these themes in your findings chapter may be the most appropriate way to proceed. Not only are you using information that you have already documented, you are telling a story in each of your sections (which can be useful in qualitative research).

But what if you undertook a more quantitative type study? You might be better off structuring your findings chapter in relation to your research questions or your hypotheses. This assumes, of course, that you have more than one research question or hypothesis. Otherwise you would end up just having one really long section.

This brings us to our next student mistake – trying to do too much within one section.

Subheadings are ultimately going to be your friend throughout your dissertation writing . Not only do they organise your information into logical pieces, they give the reader guidelines for where your research might be going. This is also a break for the reader. Looking at pages and pages of text without any breaks can be daunting and overwhelming for a reader. You don't want to overwhelm someone who is going to mark your work and who is responsible for your success (or failure).

When writing your introduction, be clear, organised and methodical. Tell the reader what they need to know and try to organise the information in a way that makes the most sense to you and your project. If in doubt, discuss this with your supervisor before you start writing.

Presentation of qualitative data

If you have conducted things like interviews or observations, you are likely to have transcripts that encompass pages and pages of work.

Putting this all together cohesively within one chapter can be particularly challenging. This is true for two reasons. First, it is always difficult to determine what you are going to cut and/or include. Secondly, unlike quantitative data, it can often be difficult to represent qualitative data through figures and tables, so condensing the information into a visual representation is simply not possible. As a writer, it is important to address both these challenges.

When considering how to present your qualitative data, it may be helpful to begin with the initial outline you have created (and the one described above). Within each of your subsections, you are going to have themes or headings that represent impactful talking points that you want to focus on.

Once you have these headings, it might be helpful to go back to your data and highlight specific lines that can/might be used as examples in your writing. If you have used multiple different instruments to collect data (e.g. interviews and observations), you are going to want to ensure that you are using both examples within each section (if possible). This is so that you can demonstrate to more well-rounded perspective of the points you are trying to make. Once you have identified some key examples for each section, you might still have to do some further cutting/editing.

Once you have your examples firmly selected for each subsection, you want to ensure that you are including enough information. This way, the reader will understand the context and circumstances around what you are trying to ‘prove’. You must set up the examples you have chosen in a clear and coherent way.

Students often make the mistake of including quotations without any other information. It is important that you embed your quotes/examples within your own thoughts. Usually this means writing about the example both before and after. So you might say something like, “One of the main topics that my participants highlighted was the need for more teachers in elementary schools. This was a focal point for 7 of my 12 participants, and examples of their responses included: [insert example] by participant 3 and [insert example] by participant 9. The reoccurring focus by participants on the need for more teachers demonstrates [insert critical thought here]. By embedding your examples in the context, you are essentially highlighting to the reader what you want them to remember.

Aside from determining what to include, the presentation of such data is also essential. Participants, when speaking in an interview might not do so in a linear way. Instead they might jump from one thought to another and might go off topic here and there.

It is your job to present the reader with information on your theme/heading without including all the extra information. So the quotes need to be paired down to incorporate enough information for the reader to be able to understand, while removing the excess.

Finding this balance can be challenging. You have likely worked with the data for a long time and so it might make sense to you. Try to see your writing through the eyes of someone else, which should help you write more clearly.

Presentation of quantitative data

Something to consider first with numeric data is that presentation style depends what department you are submitting to. In the hard sciences, there is likely an expectation of heavy numeric input and corresponding statistics to accompany the findings. In the arts and humanities, however, such a detailed analysis might not be as common. Therefore as you write out your quantitative findings, take your audience into consideration.

Just like with the qualitative data, you must ensure that your data is appropriately organised. Again, you've likely used a software program to run your statistical analysis, and you have an outline and subheadings where you can focus your findings. There are many software programs available and it is important that you have used one that is most relevant to your field of study.

For some, Microsoft Excel may be sufficient for basic analysis. Others may rely on SPSS, Stata, R, or any of the other programs available through your institution or online. Whatever program you have used, make sure that you document what you have done and the variables that have affected your analysis.

One common mistake found in student writing is the presentation of the statistical analysis. During your analysis of the data, you are likely to have run multiple different analyses from regressions to correlations. Often, we see students presenting multiple different statistical analyses without any real understanding of what the tests mean.

Presentation of quantitative data is more than just about numbers and tables. You must explain your findings and justify why you have run/presented the tests that you have. You could also explain how they relate to the research question. However, depending on how you have organised your work, this might end up in the discussion section.

Students who are not confident with statistical analysis often have a tendency to revert back to their secondary school mathematics skills. They commonly document the mean, median, and mode for all of their results. Now, these three outcomes can be important. But having a good understanding of why you are proceeding with this strategy of analysis is going to be essential in a primarily quantitative study.

That noted, there are different expectations for an undergraduate dissertation and a PhD thesis, so knowing what these expectations are can be really helpful before you begin.

Presentation of graphs, tables, and figures

The first is the use of colour and/or variables. Depending on the presentation of your dissertation, you may be required to print out a final copy for the marker(s). In many cases, this final copy must be printed in black and white. This means that any figures or graphs that you create must be readable in a black and white (or greyscale) format.

This can be challenging because there are only so many distinct shades of grey. In a pie chart, you might show one section as purple and the other as green. Yet when printed, both the purple and the green translate to approximately the same shade of grey, making your graph suddenly unreadable.

Another common error is overwhelming the reader with graphs and tables. Let's think about your outline and subheadings. If you're including a table under each subheadings, it needs to be relevant to the information that is being discussed in that chapter. There is no correct or incorrect number of graphs that should exist within the section, but you should use your judgement about what looks appropriate.

The final mistake we see is the duplication of writing (or absence of writing) when presenting a graph. Some students will present their findings in a graph or table and then write out this information again below the graph. This defeats the entire purpose of using the graph in the first place. So avoid this at all times.

Conversely, other students sometimes include a graph or figure but nothing else. Doing this denies the reader of context or purpose of said graph or figure. At some point, a balance needs to be struck where the reader has the information they require to really understand the point being made within the section.

Analysis and synthesis in a discussion

The purpose of a discussion chapter.

The structure of your discussion chapter is really going to depend on what you are trying to do and how you have structured your findings. If you chose to structure your findings by theme, it might make sense to continue this into the analysis chapter.

Other people might structure it according to the research questions. This clearly indicates to the reader how you have addressed your study. Marking a dissertation usually requires the marker to comment on the extent to which the research questions have been addressed. So by structuring a dissertation that lays out each research question for the marker, you are making their job easier. Needless to say, this a great thing.

Like any other chapter in your thesis, an introduction is an essential component of your discussion. By this point, the reader has gone through your findings and is now looking for your interpretation. Therefore, at the end of your discussion introduction you should highlight the content that each of the subsections will cover.

A conclusion to your discussion section (or a chapter summary) is also going to be beneficial. The length of the analysis chapter is usually quite long, so a wrap up of the key points at the end can help the reader digest your work. It can also help ensure that the reader actually understands the points you are trying to highlight within your project.

Critical thinking

Without any critical thinking, you are really doing yourself a disservice. It will affect the mark that you obtain on your overall dissertation. This is why the analysis chapter is usually weighted quite heavily on the marking rubric.

We tell students about critical thinking and the importance of it on a daily basis. And yet, there does seem to be a general confusion about what critical thinking entails, i.e. what constitutes critical thinking versus what is a simple description.

Critical thinking asks you to provide your own opinion on your topic, which can be daunting at first. For much of your academic career, you've likely been asked to use research to justify a position that has already been set. Unlike critical thinking, this requires you to use other people’s ideas. But even if you're new to it, try and get to grips with what critical thinking entails and use it in your work.

Creating sub-sections

Subheadings need to be informative but not too long. It is possible to layer your subheadings, so you might have a Chapter 2, a Section 2.1 and then a 2.1.1 and 2.2.2. Usually anything after 3 numerical points does not get a number and would not appear in your table of contents.

When creating titles for your subheadings, consider how they are going to look in the table of contents. They need to fit on one line, ideally, so putting your research question as the subheading might end up being too long. Conversely, one- or two-word subheadings usually doesn't give enough information about the purpose of the section.

Finding this balance is important. But remember you can always edit your subheadings retrospectively.

Linking to previous chapters

Ideally, you will be able to concisely and effectively link your research to what has been researched previously. But this can be a challenge. You don't want to repeat what has been said in your literature review or the findings . But you need to pull examples from both of these sections in order to make the points that you need to.

So, how do you tackle this?

One way is by referring the reader back to previous chapters, sections, or subsections. This process can generally be done at the end. You can put in a place holder until you know how your sections will be numbered. For example you might write: “In Section XYZ, the theme of … was discussed. Findings from this study indicate…. (see Section XYZ for details)”. While ‘XYZ’ is obviously not going to be the same section, by using the same abbreviation, you can then search ‘XYZ’ after you have completed writing and replace each term with the appropriate number. This also makes the proofreading process easier.

If you are submitting an electronic version of this document, you may also consider hyperlinks to take the reader to the different sections. But be aware that this can be considerably more work, so you should allow for this in your timescale if it's something you wish to implement.

Let's outline the main takeaway points:

It is essential that you keep in mind the ‘describe, analyse, synthesise’ model.

The findings chapter is essentially the describe part. You need to ensure that you have clearly identified data that relates to your research questions, hypotheses, or themes of your study.

For the ‘describe’ component, you are not looking to support your work with other research, but rather to present your contribution. It is also important to consider your data in the ‘describe’ section. If you have qualitative data, ensure that you have edited the quotes and examples to a reasonable length. Pick quotes that accurately represent your theme. Try not to focus solely on one or two participants (if possible). Ensure that you are demonstrating links between multiple instruments, if you used them.

If you are using quantitative data, be careful about how many statistical tests you run. Make sure you can justify why you chose one particular test over another. When presenting graphs, use a colour scheme that's appropriate for the reader when printing in black and white. Ensure that graphs and tables are appropriately explained, but that the information provided is not duplicated.

From the ‘describe’ element, you move into the 'analysis' and 'synthesis'. These parts usually appear in the discussion and ask you to employ your critical thinking skills to demonstrate how your research fits into the bigger picture. It is often the case that your analysis holds the most weight in the marking scheme. So you should spend considerable time ensuring this section is appropriate. It needs to demonstrate how you have attempted to answer your research questions.

Finally, create an outline before you begin. While this might seem tedious at first, filling in the sections with the appropriate information will mean that you are not writing things over and over again. It'll also make sure you do not go wildly off topic. It is always beneficial to have a second set of eyes assess your work for any errors or omissions. Many students choose to contact professional editors to help with this as they hold the relevant expertise to guide you on the correct path to creating a perfect discussion section that is ready for submission.

In terms of presentation, both the findings and discussion chapters will benefit from a clear and logical introduction and chapter summary. Remember that both of these chapters are meant to inform. You are leading the reader on a journey, so make sure they stay on the path and arrive at the final destination with you!

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Qualitative Results and Discussion

• First Online: 20 August 2020

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• Peijian Paul Sun 2  

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This chapter presents the results and discussion in line with the five research questions of the present study based on the qualitative data collected from the focus groups and semi-structured interviews. A total of 7 focus groups and 10 semi-structured interviews were conducted to explore the research questions from a more in-depth qualitative perspective. Two types of interviews were utilized in order to bring different lines of insights together to ensure that more profound and appropriate understandings of the research questions could be facilitated. This chapter starts with an introduction to the background information of the participants and the coding system. The qualitative findings in relation to each research question are presented sequentially followed by a summary and discussion.

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Alrabai, Fakieh. 2015. The Influence of Teachers’ Anxiety-Reducing Strategies on Learners’ Foreign Language Anxiety. Innovation in Language Learning and Teaching 9 (2): 128–163. https://doi.org/10.1080/17501229.2014.890203 .

Article   Google Scholar  

Amiryousefi, Mohammad. 2018. Willingness to Communicate, Interest, Motives to Communicate with the Instructor, and L2 Speaking: A Focus on the Role of Age and Gender. Innovation in Language Learning and Teaching 12 (3): 221–234. https://doi.org/10.1080/17501229.2016.1170838 .

Armon-Lotem, Sharon, Susan Joffe, Hadar Abutbul-Oz, Carmit Altman, and Joel Walters. 2014. Language Exposure, Ethnolinguistic Identity and Attitudes in the Acquisition of Hebrew as a Second Language among Bilingual Preschool Children from Russian- and English-Speaking Backgrounds. In Input and Experience in Bilingual Development , edited by Theres Grüter and Johanne Paradis, 77–98. Amsterdam, Netherlands: John Benjamins.

Google Scholar  

Bright, Peter, Julia Ouzia, and Roberto Filippi. 2019. Multilingualism and Metacognitive Processing. In The Handbook of the Neuroscience of Multilingualism , ed. John W. Schwieter, 355–371. Chichester, UK: Wiley. https://doi.org/10.1002/9781119387725.ch17 .

Caprara, Gian Vittorio, Michele Vecchione, Guido Alessandri, Maria Gerbino, and Claudio Barbaranelli. 2011. The Contribution of Personality Traits and Self-Efficacy Beliefs to Academic Achievement: A Longitudinal Study. British Journal of Educational Psychology 81 (1): 78–96. https://doi.org/10.1348/2044-8279.002004 .

Cenoz, Jasone, and Durk Gorter. 2019. Multilingualism, Translanguaging, and Minority Languages in SLA. The Modern Language Journal 103: 130–135. https://doi.org/10.1111/modl.12529 .

Clément, Richard, Susuan C. Baker, and Peter D. MacIntyre. 2003. Willingness to Communicate in a Second Language: The Effect of Context, Norms, and Vitality. Journal of Language and Social Psychology 22: 190–209.

Dörnyei, Zoltán. 2005. The Psychology of the Language Learner: Individual Differences in Second Language Acquisition . Mahwah, NJ: Lawrence Erlbaum.

Dörnyei, Zoltán. 2009. The L2 Motivational Self System. In Motivation, Language Identity and the L2 Self , edited by Zoltán Dörnyei and Ema Ushioda, 9–42. Bristol, UK: Multilingual Matters.

Effiong, Okon. 2016. Getting Them Speaking: Classroom Social Factors and Foreign Language Anxiety. TESOL Journal 7 (1): 132–161. https://doi.org/10.1002/tesj.194 .

Florack, Arnd, Anette Rohmann, Johanna Palcu, and Agostino Mazziotta. 2014. How Initial Cross-Group Friendships Prepare for Intercultural Communication: The Importance of Anxiety Reduction and Self-Confidence in Communication. International Journal of Intercultural Relations 43, Part B (0): 278–288. https://doi.org///dx.doi.org/10.1016/j.ijintrel.2014.09.004 .

Ghorbani, Mohammad Reza, and Seyyed Ehsan Golparvar. 2019. Modeling the Relationship between Socioeconomic Status, Self-Initiated, Technology-Enhanced Language Learning, and Language Outcome. Computer Assisted Language Learning 1–21. https://doi.org/10.1080/09588221.2019.1585374 .

Hernández, Todd A. 2006. Integrative Motivation as a Predictor of Success in the Intermediate Foreign Language Classroom. Foreign Language Annals 22: 30–37.

Hu, Hsueh-chao Marcella, and Hossein Nassaji. 2014. Lexical Inferencing Strategies: The Case of Successful versus Less Successful Inferencers. System 45 (1): 27–38. https://doi.org/10.1016/j.system.2014.04.004 .

Huang, Becky, Yung-Hsiang Shawn Chang, Luping Niu, and Mingxia Zhi. 2018. Examining the Effects of Socio-Economic Status and Language Input on Adolescent English Learners’ Speech Production Outcomes. System 73: 27–36. https://doi.org/10.1016/j.system.2017.07.004 .

Hyland, Ken. 1993. Culture and Learning: A Study of the Learning Style Preferences of Japanese Students. RELC Journal 24 (2): 69–87. https://doi.org/10.1177/003368829302400204 .

Kang, Su-Ja. 2005. Dynamic Emergence of Situational Willingness to Communicate in a Second Language. System 33 (2): 277–292. https://doi.org/10.1016/j.system.2004.10.004 .

Khajavy, Gholam Hassan, Peter D. MacIntyre, and Elyas Barabadi. 2018. Role of the Emotions and Classroom Environment in Willingness to Communicate: Applying Doubly Latent Multilevel Analysis in Second Language Acquisition Research. Studies in Second Language Acquisition 40 (3): 605–624. https://doi.org/10.1017/S0272263117000304 .

Kim, Tae-Young, and Yoon-Kyoung Kim. 2014. A Structural Model for Perceptual Learning Styles, the Ideal L2 Self, Motivated Behavior, and English Proficiency. System 46 (0): 14–27. https://doi.org///dx.doi.org/10.1016/j.system.2014.07.007 .

Kırkgöz, Yasemin. 2018. Fostering Young Learners’ Listening and Speaking Skills. In The Routledge Handbook of Teaching English to Young Learners , ed. Sue Carton and Fiona Copland, 171–187. Routledge.

Krashen, Stephen D. 1982. Principles and Practice in Second Language Acquisition . Oxford, UK: Pergamon.

Liu, Meihua, and Wenhong Huang. 2011. An Exploration of Foreign Language Anxiety and English Learning Motivation. Education Research International 12: 1–8.

MacIntyre, Peter D. 2007. Willingness to Communicate in the Second Language: Understanding the Decision to Speak as a Volitional Process. The Modern Language Journal 91 (4): 564–576. https://doi.org/10.1111/j.1540-4781.2007.00623.x .

MacIntyre, Peter D., Zoltán Dörnyei, Richard Clément, and Kimberly A. Noels. 1998. Conceptualizing Willingness to Communicate in a L2: A Situational Model of L2 Confidence and Affiliation. The Modern Language Journal 82 (4): 545–62. https://doi.org/10.1111/j.1540-4781.1998.tb05543.x .

Magogwe, Joel Mokuedi, and Rhonda Oliver. 2007. The Relationship Between Language Learning Strategies, Proficiency, Age and Self-Efficacy Beliefs: A Study of Language Learners in Botswana. System 35 (3): 338–352. https://doi.org/10.1016/j.system.2007.01.003 .

Mahmoodzadeh, Masoud. 2012. Investigating Foreign Language Speaking Anxiety within the EFL Learner’s Interlanguage System: The Case of Iranian Learners. Journal of Language Teaching and Research 3 (3): 466–476. https://doi.org/10.4304/jltr.3.3.466-476 .

Minagawa, Harumi, Dallas Nesbitt, Masayoshi Ogino, Junji Kawai, and Ryoko de Burgh-Hirabe. 2019. Why I Am Studying Japanese: A National Survey Revealing the Voices of New Zealand Tertiary Students. Japanese Studies. https://doi.org/10.1080/10371397.2019.1678365 .

Nakatani, Yasuo. 2006. Developing an Oral Communication Strategy Inventory. The Modern Language Journal 90 (2): 151–168. https://doi.org/10.1111/j.1540-4781.2006.00390.x .

Nakatani, Yasuo, and Christine Goh. 2007. A Review of Oral Communication Strategies: Focus on Interactionist and Psycholinguistic Perspectives. In Language Learner Strategies: Thirty Years of Research and Practice , ed. Andrew D. Cohen and Ernesto Macaro, 207–227. Oxford, UK: Oxford University Press.

Naserieh, Farid, and Mohammad Reza Anani Sarab. 2013. Perceptual Learning Style Preferences among Iranian Graduate Students. System 41 (1): 122–133. https://doi.org/10.1016/j.system.2013.01.018 .

Nicolson, Margaret, and Helga Adams. 2008. Travelling in Space and Encounters of the Third Kind: Distance Language Learner Negotiation of Speaking Activities. Innovation in Language Learning and Teaching 2 (2): 105–116. https://doi.org/10.1080/17501220802158859 .

Nomura, Kazuyuki, and Rui Yuan. 2019. Long-Term Motivations for L2 Learning: A Biographical Study from a Situated Learning Perspective. Journal of Multilingual and Multicultural Development 40 (2): 164–178. https://doi.org/10.1080/01434632.2018.1497041 .

Oxford, Rebecca L. 1990. Language Learning Strategies: What Every Teacher Should Know . Boston, MA: Heinle and Heinle.

Peacock, Matthew. 2001. Match or Mismatch? Learning Styles and Teaching Styles in EFL. International Journal of Applied Linguistics 11 (1): 1–20. https://doi.org/10.1111/1473-4192.00001 .

Peng, Jian-E. 2019. The Roles of Multimodal Pedagogic Effects and Classroom Environment in Willingness to Communicate in English. System 82: 161–173. https://doi.org/10.1016/j.system.2019.04.006 .

Phongsa, Manivone, Shaik Abdul Malik Mohamed Ismail, and Hui Min Low. 2018. Multilingual Effects on EFL Learning: A Comparison of Foreign Language Anxiety Experienced by Monolingual and Bilingual Tertiary Students in the Lao PDR. Journal of Multilingual and Multicultural Development 39 (3): 271–282. https://doi.org/10.1080/01434632.2017.1371723 .

Psaltou-Joycey, Angeliki, and Zoe Gavriilidou. 2018. Language Learning Strategies of Greek EFL Primary and Secondary School Learners: How Individual Characteristics Affect Strategy Use. In Language Learning Strategies and Individual Learner Characteristics: Situating Strategy Use in Diverse Contexts , ed. Rebecca L. Oxford and Carmen M. Amerstorfer, 167–187. London, UK: Bloomsbury.

Ryan, Richard M., and Edward L. Deci. 2000. Self-Determination Theory and the Facilitation of Intrinsic Motivation, Social Development, and Well-Being. American Psychologist 55 (1): 68–78. https://doi.org/10.1037/0003-066X.55.1.68 .

Saito, Kazuya, Masatoshi Sato, and Roy Lyster. 2013. Oral Corrective Feedback in Second Language Classrooms. Language Teaching 46 (2): 1–40.

Sauer, Luzia, and Rod Ellis. 2019. The Social Lives of Adolescent Study Abroad Learners and Their L2 Development. The Modern Language Journal 103 (4): 739–762. https://doi.org/10.1111/modl.12589 .

Schauer, Gila A. 2006. The Development of ESL Learners’ Pragmatic Competence: A Longitudinal Investigation of Awareness and Production. In Pragmatics and Language Learning Volume 11 , edited by Kathleen Bardovi-Harlig, César Félix-Brasdefer, and Alwiya S. Omar, 135–64. Mānoa, HI: University of Hawaii Press.

Scovel, Thomas. 1978. The Effect of Affect on Foreign Language Learning: A Review of the Anxiety Research. Language Learning 28 (1): 129–142. https://doi.org/10.1111/j.1467-1770.1978.tb00309.x .

Segalowitz, Norman. 2010. Cognitive Bases of Second Language Fluency . New York, NY: Routledge.

Shaikholeslami, Razieh, and Mohammad Khayyer. 2006. Intrinsic Motivation, Extrinsic Motivation, and Learning English as a Foreign Language. Psychological Reports 99 (3): 813–818.

Stewart, David W, and Prem N Shamdasani. 2015. Focus Groups: Theory and Practice . 3rd ed. Thousand Oaks, CA: Sage.

Taguchi, Naoko, Feng Xiao, and Shuai Li. 2016. Effects of Intercultural Competence and Social Contact on Speech Act Production in a Chinese Study Abroad Context. Modern Language Journal 100 (4): 775–796. https://doi.org/10.1111/modl.12349 .

Tarone, Elaine. 1981. Some Thoughts on the Notion of Communication Strategy. TESOL Quarterly 15 (3): 285–95. https://doi.org/10.2307/3586754 .

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Sun, P.P. (2020). Qualitative Results and Discussion. In: Chinese as a Second Language Multilinguals’ Speech Competence and Speech Performance. Springer, Singapore. https://doi.org/10.1007/978-981-15-6941-8_7

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Home » Qualitative Research – Methods, Analysis Types and Guide

Qualitative Research – Methods, Analysis Types and Guide

Table of Contents

Qualitative Research

Qualitative research is a type of research methodology that focuses on exploring and understanding people’s beliefs, attitudes, behaviors, and experiences through the collection and analysis of non-numerical data. It seeks to answer research questions through the examination of subjective data, such as interviews, focus groups, observations, and textual analysis.

Qualitative research aims to uncover the meaning and significance of social phenomena, and it typically involves a more flexible and iterative approach to data collection and analysis compared to quantitative research. Qualitative research is often used in fields such as sociology, anthropology, psychology, and education.

Qualitative Research Methods

Qualitative Research Methods are as follows:

One-to-One Interview

This method involves conducting an interview with a single participant to gain a detailed understanding of their experiences, attitudes, and beliefs. One-to-one interviews can be conducted in-person, over the phone, or through video conferencing. The interviewer typically uses open-ended questions to encourage the participant to share their thoughts and feelings. One-to-one interviews are useful for gaining detailed insights into individual experiences.

Focus Groups

This method involves bringing together a group of people to discuss a specific topic in a structured setting. The focus group is led by a moderator who guides the discussion and encourages participants to share their thoughts and opinions. Focus groups are useful for generating ideas and insights, exploring social norms and attitudes, and understanding group dynamics.

Ethnographic Studies

This method involves immersing oneself in a culture or community to gain a deep understanding of its norms, beliefs, and practices. Ethnographic studies typically involve long-term fieldwork and observation, as well as interviews and document analysis. Ethnographic studies are useful for understanding the cultural context of social phenomena and for gaining a holistic understanding of complex social processes.

Text Analysis

This method involves analyzing written or spoken language to identify patterns and themes. Text analysis can be quantitative or qualitative. Qualitative text analysis involves close reading and interpretation of texts to identify recurring themes, concepts, and patterns. Text analysis is useful for understanding media messages, public discourse, and cultural trends.

This method involves an in-depth examination of a single person, group, or event to gain an understanding of complex phenomena. Case studies typically involve a combination of data collection methods, such as interviews, observations, and document analysis, to provide a comprehensive understanding of the case. Case studies are useful for exploring unique or rare cases, and for generating hypotheses for further research.

Process of Observation

This method involves systematically observing and recording behaviors and interactions in natural settings. The observer may take notes, use audio or video recordings, or use other methods to document what they see. Process of observation is useful for understanding social interactions, cultural practices, and the context in which behaviors occur.

Record Keeping

This method involves keeping detailed records of observations, interviews, and other data collected during the research process. Record keeping is essential for ensuring the accuracy and reliability of the data, and for providing a basis for analysis and interpretation.

This method involves collecting data from a large sample of participants through a structured questionnaire. Surveys can be conducted in person, over the phone, through mail, or online. Surveys are useful for collecting data on attitudes, beliefs, and behaviors, and for identifying patterns and trends in a population.

Qualitative data analysis is a process of turning unstructured data into meaningful insights. It involves extracting and organizing information from sources like interviews, focus groups, and surveys. The goal is to understand people’s attitudes, behaviors, and motivations

Qualitative Research Analysis Methods

Qualitative Research analysis methods involve a systematic approach to interpreting and making sense of the data collected in qualitative research. Here are some common qualitative data analysis methods:

Thematic Analysis

This method involves identifying patterns or themes in the data that are relevant to the research question. The researcher reviews the data, identifies keywords or phrases, and groups them into categories or themes. Thematic analysis is useful for identifying patterns across multiple data sources and for generating new insights into the research topic.

Content Analysis

This method involves analyzing the content of written or spoken language to identify key themes or concepts. Content analysis can be quantitative or qualitative. Qualitative content analysis involves close reading and interpretation of texts to identify recurring themes, concepts, and patterns. Content analysis is useful for identifying patterns in media messages, public discourse, and cultural trends.

Discourse Analysis

This method involves analyzing language to understand how it constructs meaning and shapes social interactions. Discourse analysis can involve a variety of methods, such as conversation analysis, critical discourse analysis, and narrative analysis. Discourse analysis is useful for understanding how language shapes social interactions, cultural norms, and power relationships.

Grounded Theory Analysis

This method involves developing a theory or explanation based on the data collected. Grounded theory analysis starts with the data and uses an iterative process of coding and analysis to identify patterns and themes in the data. The theory or explanation that emerges is grounded in the data, rather than preconceived hypotheses. Grounded theory analysis is useful for understanding complex social phenomena and for generating new theoretical insights.

Narrative Analysis

This method involves analyzing the stories or narratives that participants share to gain insights into their experiences, attitudes, and beliefs. Narrative analysis can involve a variety of methods, such as structural analysis, thematic analysis, and discourse analysis. Narrative analysis is useful for understanding how individuals construct their identities, make sense of their experiences, and communicate their values and beliefs.

Phenomenological Analysis

This method involves analyzing how individuals make sense of their experiences and the meanings they attach to them. Phenomenological analysis typically involves in-depth interviews with participants to explore their experiences in detail. Phenomenological analysis is useful for understanding subjective experiences and for developing a rich understanding of human consciousness.

Comparative Analysis

This method involves comparing and contrasting data across different cases or groups to identify similarities and differences. Comparative analysis can be used to identify patterns or themes that are common across multiple cases, as well as to identify unique or distinctive features of individual cases. Comparative analysis is useful for understanding how social phenomena vary across different contexts and groups.

Applications of Qualitative Research

Qualitative research has many applications across different fields and industries. Here are some examples of how qualitative research is used:

• Market Research: Qualitative research is often used in market research to understand consumer attitudes, behaviors, and preferences. Researchers conduct focus groups and one-on-one interviews with consumers to gather insights into their experiences and perceptions of products and services.
• Health Care: Qualitative research is used in health care to explore patient experiences and perspectives on health and illness. Researchers conduct in-depth interviews with patients and their families to gather information on their experiences with different health care providers and treatments.
• Education: Qualitative research is used in education to understand student experiences and to develop effective teaching strategies. Researchers conduct classroom observations and interviews with students and teachers to gather insights into classroom dynamics and instructional practices.
• Social Work : Qualitative research is used in social work to explore social problems and to develop interventions to address them. Researchers conduct in-depth interviews with individuals and families to understand their experiences with poverty, discrimination, and other social problems.
• Anthropology : Qualitative research is used in anthropology to understand different cultures and societies. Researchers conduct ethnographic studies and observe and interview members of different cultural groups to gain insights into their beliefs, practices, and social structures.
• Psychology : Qualitative research is used in psychology to understand human behavior and mental processes. Researchers conduct in-depth interviews with individuals to explore their thoughts, feelings, and experiences.
• Public Policy : Qualitative research is used in public policy to explore public attitudes and to inform policy decisions. Researchers conduct focus groups and one-on-one interviews with members of the public to gather insights into their perspectives on different policy issues.

How to Conduct Qualitative Research

Here are some general steps for conducting qualitative research:

• Identify your research question: Qualitative research starts with a research question or set of questions that you want to explore. This question should be focused and specific, but also broad enough to allow for exploration and discovery.
• Select your research design: There are different types of qualitative research designs, including ethnography, case study, grounded theory, and phenomenology. You should select a design that aligns with your research question and that will allow you to gather the data you need to answer your research question.
• Recruit participants: Once you have your research question and design, you need to recruit participants. The number of participants you need will depend on your research design and the scope of your research. You can recruit participants through advertisements, social media, or through personal networks.
• Collect data: There are different methods for collecting qualitative data, including interviews, focus groups, observation, and document analysis. You should select the method or methods that align with your research design and that will allow you to gather the data you need to answer your research question.
• Analyze data: Once you have collected your data, you need to analyze it. This involves reviewing your data, identifying patterns and themes, and developing codes to organize your data. You can use different software programs to help you analyze your data, or you can do it manually.
• Interpret data: Once you have analyzed your data, you need to interpret it. This involves making sense of the patterns and themes you have identified, and developing insights and conclusions that answer your research question. You should be guided by your research question and use your data to support your conclusions.
• Communicate results: Once you have interpreted your data, you need to communicate your results. This can be done through academic papers, presentations, or reports. You should be clear and concise in your communication, and use examples and quotes from your data to support your findings.

Examples of Qualitative Research

Here are some real-time examples of qualitative research:

• Customer Feedback: A company may conduct qualitative research to understand the feedback and experiences of its customers. This may involve conducting focus groups or one-on-one interviews with customers to gather insights into their attitudes, behaviors, and preferences.
• Healthcare : A healthcare provider may conduct qualitative research to explore patient experiences and perspectives on health and illness. This may involve conducting in-depth interviews with patients and their families to gather information on their experiences with different health care providers and treatments.
• Education : An educational institution may conduct qualitative research to understand student experiences and to develop effective teaching strategies. This may involve conducting classroom observations and interviews with students and teachers to gather insights into classroom dynamics and instructional practices.
• Social Work: A social worker may conduct qualitative research to explore social problems and to develop interventions to address them. This may involve conducting in-depth interviews with individuals and families to understand their experiences with poverty, discrimination, and other social problems.
• Anthropology : An anthropologist may conduct qualitative research to understand different cultures and societies. This may involve conducting ethnographic studies and observing and interviewing members of different cultural groups to gain insights into their beliefs, practices, and social structures.
• Psychology : A psychologist may conduct qualitative research to understand human behavior and mental processes. This may involve conducting in-depth interviews with individuals to explore their thoughts, feelings, and experiences.
• Public Policy: A government agency or non-profit organization may conduct qualitative research to explore public attitudes and to inform policy decisions. This may involve conducting focus groups and one-on-one interviews with members of the public to gather insights into their perspectives on different policy issues.

Purpose of Qualitative Research

The purpose of qualitative research is to explore and understand the subjective experiences, behaviors, and perspectives of individuals or groups in a particular context. Unlike quantitative research, which focuses on numerical data and statistical analysis, qualitative research aims to provide in-depth, descriptive information that can help researchers develop insights and theories about complex social phenomena.

Qualitative research can serve multiple purposes, including:

• Exploring new or emerging phenomena : Qualitative research can be useful for exploring new or emerging phenomena, such as new technologies or social trends. This type of research can help researchers develop a deeper understanding of these phenomena and identify potential areas for further study.
• Understanding complex social phenomena : Qualitative research can be useful for exploring complex social phenomena, such as cultural beliefs, social norms, or political processes. This type of research can help researchers develop a more nuanced understanding of these phenomena and identify factors that may influence them.
• Generating new theories or hypotheses: Qualitative research can be useful for generating new theories or hypotheses about social phenomena. By gathering rich, detailed data about individuals’ experiences and perspectives, researchers can develop insights that may challenge existing theories or lead to new lines of inquiry.
• Providing context for quantitative data: Qualitative research can be useful for providing context for quantitative data. By gathering qualitative data alongside quantitative data, researchers can develop a more complete understanding of complex social phenomena and identify potential explanations for quantitative findings.

When to use Qualitative Research

Here are some situations where qualitative research may be appropriate:

• Exploring a new area: If little is known about a particular topic, qualitative research can help to identify key issues, generate hypotheses, and develop new theories.
• Understanding complex phenomena: Qualitative research can be used to investigate complex social, cultural, or organizational phenomena that are difficult to measure quantitatively.
• Investigating subjective experiences: Qualitative research is particularly useful for investigating the subjective experiences of individuals or groups, such as their attitudes, beliefs, values, or emotions.
• Conducting formative research: Qualitative research can be used in the early stages of a research project to develop research questions, identify potential research participants, and refine research methods.
• Evaluating interventions or programs: Qualitative research can be used to evaluate the effectiveness of interventions or programs by collecting data on participants’ experiences, attitudes, and behaviors.

Characteristics of Qualitative Research

Qualitative research is characterized by several key features, including:

• Focus on subjective experience: Qualitative research is concerned with understanding the subjective experiences, beliefs, and perspectives of individuals or groups in a particular context. Researchers aim to explore the meanings that people attach to their experiences and to understand the social and cultural factors that shape these meanings.
• Use of open-ended questions: Qualitative research relies on open-ended questions that allow participants to provide detailed, in-depth responses. Researchers seek to elicit rich, descriptive data that can provide insights into participants’ experiences and perspectives.
• Sampling-based on purpose and diversity: Qualitative research often involves purposive sampling, in which participants are selected based on specific criteria related to the research question. Researchers may also seek to include participants with diverse experiences and perspectives to capture a range of viewpoints.
• Data collection through multiple methods: Qualitative research typically involves the use of multiple data collection methods, such as in-depth interviews, focus groups, and observation. This allows researchers to gather rich, detailed data from multiple sources, which can provide a more complete picture of participants’ experiences and perspectives.
• Inductive data analysis: Qualitative research relies on inductive data analysis, in which researchers develop theories and insights based on the data rather than testing pre-existing hypotheses. Researchers use coding and thematic analysis to identify patterns and themes in the data and to develop theories and explanations based on these patterns.
• Emphasis on researcher reflexivity: Qualitative research recognizes the importance of the researcher’s role in shaping the research process and outcomes. Researchers are encouraged to reflect on their own biases and assumptions and to be transparent about their role in the research process.

Advantages of Qualitative Research

Qualitative research offers several advantages over other research methods, including:

• Depth and detail: Qualitative research allows researchers to gather rich, detailed data that provides a deeper understanding of complex social phenomena. Through in-depth interviews, focus groups, and observation, researchers can gather detailed information about participants’ experiences and perspectives that may be missed by other research methods.
• Flexibility : Qualitative research is a flexible approach that allows researchers to adapt their methods to the research question and context. Researchers can adjust their research methods in real-time to gather more information or explore unexpected findings.
• Contextual understanding: Qualitative research is well-suited to exploring the social and cultural context in which individuals or groups are situated. Researchers can gather information about cultural norms, social structures, and historical events that may influence participants’ experiences and perspectives.
• Participant perspective : Qualitative research prioritizes the perspective of participants, allowing researchers to explore subjective experiences and understand the meanings that participants attach to their experiences.
• Theory development: Qualitative research can contribute to the development of new theories and insights about complex social phenomena. By gathering rich, detailed data and using inductive data analysis, researchers can develop new theories and explanations that may challenge existing understandings.
• Validity : Qualitative research can offer high validity by using multiple data collection methods, purposive and diverse sampling, and researcher reflexivity. This can help ensure that findings are credible and trustworthy.

Limitations of Qualitative Research

Qualitative research also has some limitations, including:

• Subjectivity : Qualitative research relies on the subjective interpretation of researchers, which can introduce bias into the research process. The researcher’s perspective, beliefs, and experiences can influence the way data is collected, analyzed, and interpreted.
• Limited generalizability: Qualitative research typically involves small, purposive samples that may not be representative of larger populations. This limits the generalizability of findings to other contexts or populations.
• Time-consuming: Qualitative research can be a time-consuming process, requiring significant resources for data collection, analysis, and interpretation.
• Resource-intensive: Qualitative research may require more resources than other research methods, including specialized training for researchers, specialized software for data analysis, and transcription services.
• Limited reliability: Qualitative research may be less reliable than quantitative research, as it relies on the subjective interpretation of researchers. This can make it difficult to replicate findings or compare results across different studies.
• Ethics and confidentiality: Qualitative research involves collecting sensitive information from participants, which raises ethical concerns about confidentiality and informed consent. Researchers must take care to protect the privacy and confidentiality of participants and obtain informed consent.

Also see Research Methods

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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Open Access

Study Protocol

The effectiveness of group interpersonal synchrony in young autistic adults’ work environment: A mixed methods RCT study protocol

Roles Conceptualization, Data curation, Investigation, Methodology, Project administration, Resources, Software, Supervision, Visualization, Writing – original draft, Writing – review & editing

* E-mail: [email protected]

Affiliation University of Haifa, Faculty of Social Welfare & Health Sciences, School of Creative Arts Therapies, Haifa, Israel

Roles Conceptualization, Methodology, Supervision, Writing – review & editing

• Tamar Dvir, 
• Tal-Chen Rabinowitch, 
• Cochavit Elefant

• Published: July 31, 2024
• https://doi.org/10.1371/journal.pone.0307956
• Peer Review
• Reader Comments

Introduction

Few autistic adults are able to integrate successfully into the world of work given their difficulties adapting to the social and stressful aspects of work environments. Interpersonal synchrony, when two or more individuals share body movements or sensations, is a powerful force that consolidates human groups while promoting the ability to self-regulate and cooperate with others. The abilities to self-regulate and cooperate are crucial for maintaining a calm and productive work environment. This study protocol outlines research that aims to assess the effects of group interpersonal synchrony on prosociality and work-related stress of young autistic adults in their work environment.

Methods and analysis

This mixed-methods randomized controlled trial will investigate two movement-based group synchronous and non-synchronous intervention conditions. The sample will be composed of young adults enrolled in an innovative Israeli program designed to integrate cognitively-abled 18- to 25-year-old autistic adults into the Israeli army work force. The movement-based intervention sessions will take place in groups of 10–14 participants, once a week for 10 weeks. Questionnaires, behavioral collaborative tasks and semi-structured interviews will be conducted. Quantitative data will be collected for each participant at three points of time: before and after the intervention period, and 17 weeks after the end of the intervention. Qualitative data will be collected after the intervention period in interviews with the participants.

Little is known about interventions that promote successful integration into social and stressful work environments. The findings are likely to shed new light on the use of group interpersonal synchrony in autistic individuals at work.

Trial registration

NCT05846308 .

Citation: Dvir T, Rabinowitch T-C, Elefant C (2024) The effectiveness of group interpersonal synchrony in young autistic adults’ work environment: A mixed methods RCT study protocol. PLoS ONE 19(7): e0307956. https://doi.org/10.1371/journal.pone.0307956

Editor: Stergios Makris, Edge Hill University, UNITED KINGDOM OF GREAT BRITAIN AND NORTHERN IRELAND

Received: May 9, 2023; Accepted: July 12, 2024; Published: July 31, 2024

Copyright: © 2024 Dvir et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: Deidentified research data will be made publicly available when the study is completed and published.

Funding: The author(s) received no specific funding for this work.

Competing interests: The authors have declared that no competing interests exist.

Individuals diagnosed with Autism Spectrum Disorder (ASD) have difficulties related to social interaction and communication, as well as repetitive and stereotyped interests [ 1 ]. According to the DSM-V [ 1 ] cognitively-abled autistic people are characterized by a high intellectual level and the least requirements for support. There are few cognitively-abled autistic adults who can successfully integrate into the world of work since they often manifest atypical behavior in social situations, find it hard to initiate social interactions, have limited interest in forming social relationships, find it challenging to cooperate with co-workers and often fail to regulate work-related stress [ 2 – 4 ]. The ability to work, according to the International Classification of Functioning, Disability and Health (World Health Organization, 2001) is considered to be a significant factor affecting individuals’ health, quality of life, and wellbeing. This accounts for the growing interest in developing tailored interventions to promote the long-term integration of challenged populations into social and stressful work environments [ 5 , 6 ].

A new wave of research in autism suggests that in addition to difficulties with social interactions and stressful environments, ASD is also characterized by fundamental differences in sensorimotor functioning including the delayed development of motor skills [ 7 ], abnormal gait [ 8 ], difficulty with balance [ 9 ], difficulties in coordinating movements that involve both sides of the body, and in controlling force and direction when throwing a ball [ 10 ]. These altered modes of perceiving and moving in the world (alone, as well as with other people) may help explain some of the key fundamental social impairments in autism and asynchronous social behavior in particular [ 11 – 15 ]. Asynchronous social behavior in autism (e.g., reduced eye contact, absence of well-timed co-regulation, no coherent engagement of mutual attention, no anticipation and no emotional build up in shared interactions) was first identified in a micro-analytic study of videos of an 11-month old infant who was diagnosed with ASD during her second year of life [ 16 ]. Stronger evidence for the association between atypical interpersonal synchrony and autism was recently described [ 13 ] in a study which also suggested that there may be a disruption in intrapersonal mechanisms such as atypical motor timing, and in interpersonal mechanisms such as atypical inter-individual coupling.

The aim of this trial is to assess the effects of group interpersonal synchrony on the prosociality and work-related stress of young autistic adults in their work environment. The trial is designed as a randomized controlled trial with two parallel groups (experimental group and treated control group), primary and secondary endpoints and a follow-up of intervention effectiveness after 17 weeks as described in Fig 1 . Randomization will be performed as block randomization with a 1:1 allocation. In the following sections we review research on interpersonal synchrony in autism and on the associations between interpersonal synchrony, prosociality and work-related stress.

• PPT PowerPoint slide
• PNG larger image
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Note: EHQ, Edinburgh Handedness Questionnaire; NTB, Need to Belong Scale; IOS, Inclusion of Other in Self Scale; FCI, Friendship Closeness Inventory; GSB, General Sense of Belonging Scale; IS, Irritation Scale; CT, Collection Task; PGG, Public Goods Game.

https://doi.org/10.1371/journal.pone.0307956.g001

Interpersonal synchrony in autism

Interpersonal synchrony is said to occur when two or more individuals are engaged in body movements or sensations (such as gaze, affect, voice and touch) at the same time (precise synchrony) or as a responsive behavior (lagged synchrony) [ 17 , 18 ]. This form of interpersonal relationship has at times been called “togetherness”, especially when there is no leader or follower in this form of non-verbal behavioral sharing [ 19 ]. Body movements may be connected spatially (spatial synchrony), temporally (rhythmic synchrony) or qualitatively (effort synchrony) [ 20 , 21 ]. Interpersonal synchrony can emerge intentionally as a result of an explicit shared goal, such as running at same pace, or spontaneously without being aware of it as part of a social interaction, such as when dancing, singing or playing an instrument [ 22 ]. Studies over the last ten years have shown that autistic children and adults demonstrate poor ability to synchronize their body with a partner during rhythmic interaction activities and games [ 11 , 12 , 23 – 26 ]. For example, an innovative study focusing on motion synchronization during an open-ended joint improvisation paradigm dubbed the Mirror Game found that cognitively-abled autistic adults exhibited much less interpersonal synchronization than neurotypical individuals [ 23 ]. Autistic adolescents also presented less interpersonal synchrony, and fewer intentional and spontaneous motor interactions on a pendulum coordination paradigm [ 12 ].

The effects of interpersonal synchrony on prosociality

Prosociality refers to behaviors that are intended to benefit others, such as helping, cooperating, sharing and donating [ 27 ]. Recently, there has been increased interest in studying the causal influences of interpersonal synchrony on prosociality in general [ 28 , 29 ] and specifically in work environments [ 30 , 31 ]. A meta-analysis of 60 studies that compared an interpersonal synchrony condition to at least one control condition found a medium-sized effect of interpersonal synchrony on the prosociality of neurotypical adults with regard to both attitudes and behavior towards individuals or groups involved in the same intervention [ 28 ]. Another meta-analysis of 42 studies suggested that synchrony in larger groups increases prosociality [ 29 ]. Other studies that have assessed the effects of interventions based on mirroring movement in autistic adults suggest that interpersonal synchrony may be an effective intervention tool for enhancing social skills [ 32 ] and specifically emotional inference [ 33 ], which is a fundamental skill underlying prosociality. Manders et al. [ 34 ] argued that the structured mirroring task, which encourages interpersonal synchrony such as in the case of the Mirror Game, may not be sufficient to effectively support social engagement in autistic individuals, since they tend to simply follow the instructions to synchronize their movements. These findings emphasize the need to include synchronized sensory-motor interactions in tailored interventions to foster prosociality, while proposing both structured intentional synchrony and less structured spontaneous synchrony [ 35 ]. To the best of our knowledge, no study has examined the effectiveness of group interpersonal synchrony on the prosociality of autistic individuals in the context of a social work environment. Since working teams’ cognitive performance declines in stressful environments [ 36 ], in the following section we review research on the associations between interpersonal synchrony and work-related stress.

The effects of interpersonal synchrony on work-related stress

Work-related stress is defined as individuals’ responses when presented with work demands and pressures that are misaligned with their knowledge or abilities and which challenge their ability to cope [ 37 ]. A recent longitudinal field experiment in a neurotypical work environment found that a 9-week synchronous movement intervention reduced work-related stress and diminished sick days immediately following the intervention, but not after three months [ 30 ]. A qualitative evaluation of workplace choir singing in Health Service staff reported greater enjoyment at work and an improvement in work engagement [ 31 ]. One possible explanation is that participating in synchronous activities may release endogenous opioids such as endorphin, which are involved in the regulation of emotional pain [ 38 ]. While these studies support the widespread belief that togetherness and harmony only have beneficial effects on personal wellbeing, a study by Galbusera et al.’s [ 39 ] suggested that interpersonal synchrony when implemented in the form of a dyadic moving task designed to encourage spontaneous social interaction, could decrease people’s ability to self-regulate due to their extra reliance on the dyadic interaction. This may imply that an effective intervention to support autistic individuals in stressful work environments should include co-regulation with others in a group setting rather than in an intimate dyadic framework that might be less efficient in terms of stress regulation. To the best of our knowledge, no studies have examined the effectiveness of interpersonal synchrony on the work-related stress of autistic individuals in the context of a group.

The effects of interpersonal synchrony on social closeness and a sense of belonging

According to McNeill’s [ 40 ] Muscular Bonding hypothesis, group interpersonal synchrony, which involves coordinated rhythmic movement, is a powerful force uniting human groups and enhancing social closeness and a sense of belonging. Social closeness is defined as the way individuals engage in friendships, interact and relate to significant others [ 41 ]. Social closeness in a workplace setting was enhanced using an intervention in which participants shared synchronous movement [ 30 ]. Sense of belonging is the experience of personal involvement in a system or environment, which makes individuals feel that they are an integral part [ 42 ]. Interpersonal synchrony has been found to enhance people’s sense of belonging in an experimental setting using a finger tapping task [ 43 ]. Furthermore, these feelings of social closeness and belongingness among individuals are known to promote prosocial behavior [ 44 ] as well as the ability to cope with various stressors [ 45 ].

Moderating factor underlying the effects of interpersonal synchrony

The need to belong is characterized by the drive to be noticed, valued and accepted by others [ 46 ]. It is a fundamental need that exerts a strong influence in virtually every domain of social behavior starting early in development [ 47 ]. While all individuals differ in the strength of their desire to belong to social groups, the social motivation hypothesis argues that autistic individuals’ need to belong is diminished because they find social stimuli less rewarding as compared to neurotypicals [ 4 ]. For example, Brezis et al. [ 23 ] found that autistic adults who played the Mirror Game with an expert improvisor were less likely to want to continue playing, but their ratings of how they felt during the game did not differ. Hence, group interpersonal synchrony may be more effective when the need to belong is higher, since the intrinsic motivation is likely to have a positive effect on the sense of belonging to the group. The suggested moderating model is depicted in Fig 2 .

https://doi.org/10.1371/journal.pone.0307956.g002

The aim of this study is to assess the effects of group interpersonal synchrony on the prosociality and work-related stress of young autistic adults in their work environment. The primary objective is to determine whether a synchronized group intervention will have an immediate and/or long-term positive effect on participants’ prosociality and work-related stress. The secondary objectives are to determine: (1) Whether a synchronized group intervention will have an immediate and/or long-term positive effect on participants’ social closeness and sense of belonging, (2) Whether this effect will be influenced by participants’ need to belong as reported before the intervention, (3) How participants perceive the intervention as affecting their prosociality and work-related stress, and (4) In what ways the participants’ perception will contribute to a better understanding of the intervention effect.

Materials and methods

A convergent mixed methods design will be applied, where quantitative and qualitative data are collected and analyzed in parallel. The use of mixed methods may provide a better understanding of the study objectives. Specifically, a convergent design will be used [ 48 ] to gain a more in-depth understanding of the quantitative results by incorporating the participants’ qualitative perspectives. The two sets of results will be compared to obtain a more complete understanding of the study objectives by validating one set of findings with the other and ensuring that the participants’ perspectives are consistent and not dependent on the research method.

Participants

This study will be conducted in collaboration with Roim Rachok Program (RRP) an innovative Israeli civilian program designed to integrate cognitively-abled young autistic adults first into the Israeli army work force, and later into the labor market [ 6 ]. As part of the program, before joining the army, the trainees take part in a professional 13 weeks course delivered by an interdisciplinary team that includes army officers and instructors, an occupational therapist, a speech therapist and an art therapist. The course content is composed of two main fields: (a) army related professional instruction (e.g., software programming, data analysis and image interpretation), and (b) integration into the army working environment. Trainees who successfully complete the course are inducted into the army as civilian volunteers for a four-month trial period. The trial period is designed to allow trainees to experience their future working environment before committing to long-term army service. Trainees who successfully complete the trial period can sign up for one more year of service with an annual option of extension, for up to three years. The RRP participants are integrated into the army corps with other soldiers who do not have developmental disabilities.

The sample for this study will be comprised of young adults enrolled in an RRP who fulfill the following criteria: Inclusion criteria: (a) Aged 18 to 25 when accepted to the program, since these age limits are defined as part of the admission requirements for the RRP. (b) Diagnosis of autism spectrum disorder: Participants must have an official diagnosis of an autism spectrum disorder as assessed by a child psychiatrist or clinical psychologist according to the DSM-V [ 1 ] before acceptance to the RRP. Exclusion criteria: Trainees with severe sensory impairments such as blindness or deafness and/or severe physical disability.

Ethical considerations

This study has been approved by the ethics committee for human experiments of the Faculty of Social Welfare and Health Sciences at the University of Haifa (Approval # 017/21). Participation in the study will be voluntary without preconditions. All participants will receive a letter explaining the study and how it will be conducted, and will sign an informed consent form to participate in the study. Participants who have custodian will be required to present a written custodian approval as well. No risks or discomfort are expected as a result of participation in this study. However, if any physical or emotional discomfort is experienced, the participants will receive appropriate support from the RRP professional staff. The data will be coded to protect the participants’ confidentiality. All data, including the questionnaires, the behavioral task outcomes and audio recordings will be stored in a secure cloud and will not be available to anyone other than the research team. The audio recordings will be deleted immediately after being transcribed.

Sample size

A meta-analysis on prosocial consequences of interpersonal synchrony among neurotypical adults found a medium-sized effect of interpersonal synchrony on prosociality with regard to both attitudes and behavior towards individuals or groups involved in the same intervention [ 28 ]. Therefore, an effect defined as d = 0.25 may be expected [ 49 ]. An a-priori power analysis using the G*Power computer program [ 50 ] indicated that a total sample size of 40 participants would be needed to detect medium-sized effects defined as f = 0.25, with 80% power and alpha at .05, using a repeated measure, within-between interaction ANOVA with four groups and three measurements. We will recruit at least N = 60 participants (30 in each intervention group) to plan for possible dropouts.

Participant recruitment

A total of 60 participants will be recruited at the beginning of a program cycle from approximately four consecutive program cycles, each of which is composed of 20 to 30 trainees. A new program cycle starts every four months. The first author will be responsible for the study approval procedure at the beginning of the course while providing information about the study to all trainees and inviting them to participate. The trainees’ decision to participate or not in the study will not affect their participation in the course in any way. The trainees who agree to take part in the study will sign an informed consent form that clarifies that participation in the study is on a voluntary basis and that anonymity and confidentiality are guaranteed as well as the right to withdraw at any time without this affecting their participation in the program. Participants who have a custodian will be required to present the custodian’s approval as well. This form will also include information about the data collection procedures, including data from the RRP personal file.

Study design

This study will implement a randomized controlled trial (RCT) design to investigate a synchronous or non-synchronous movement-based group intervention, so that each participant will only engage in one intervention condition, alongside a phenomenological study with the participants of both groups. The RCT will compare the experimental group (synchronous movement) with a treated control group (non-synchronous movement) and will follow the recommendations of the Consolidate Standards of Reporting Trials (CONSORT) [ 51 ] and the recommendations of the Standards for Reporting Qualitative Research [ 52 ]. In addition, the SPIRIT guidelines [ 53 ] have been followed. Fig 1 outlines when each study component occurs. This design does not include a nontreated control group to meet the program’s requirement that all trainees should participate in all course activities including the movement-based group intervention. The study was registered with ClinicalTrials.gov (registration number: NCT05846308) afterthe enrolment of participants started due to the uncertainty about the clinical character of the target population and intervention. The authors confirm that all ongoing and related trials for this intervention are registered.

The condition groups will be matched according to the following control variables: (a) gender (male/female); since there is diagnostic gender bias with respect to ASD [ 54 ] (b) army related profession (image interpretation/GIS/data analytics/software programming/electro-optics/data annotation) (c) handedness (right-handed/left-handed); since there is a larger distribution of left-handedness in the ASD population compared to the general population [ 55 ] (d) need to belong level (NTBL) (high/low). To control for handedness and NTBL during the randomization process, the following questionnaires will be administered to the participants: (a) The Hebrew adaptation of the Edinburgh Handedness questionnaire [ 56 ], the most common method for measuring handedness in individuals with Autism [ 57 ]. (b) The Hebrew adaptation of the Need to Belong (NTB) Scale [ 59 ] which comprises ten items rated on a 5-point Likert scale ranging from “Strongly Disagree” (1) to “Strongly Agree” (5). This scale has acceptable interitem reliability (the Cronbach’s alpha generally exceeds .80) and has been positively correlated with extraversion, agreeableness, and neuroticism and with having an identity that is defined in terms of social attributes [ 58 ]. NTBL(high/low) will be calculated using a cut-off of the NTB measure, so that participants with the 50% highest NTB score will be assigned a high NTBL and the rest will be assigned a low NTBL. After inclusion in the study and assessment of the control variables, participants will be assigned by the first author to one of the intervention conditions on an individual basis according to a computer-generated randomization procedure. The allocation ratio of the intended numbers of participants in the comparison groups will be 1:1 so that the number of participants assigned to the synchronous intervention will be similar to the number of participants assigned to the non-synchronous intervention. To this end, we will first create subgroups containing participants with same gender, army-related profession, handedness and NTBL. For each subgroup, alternate assignments will be made in random order. The order of subgroup assignments will also be determined randomly. For the first subgroup, we will use a simple coin flip randomization procedure to determine the intervention type to start assigning to. An overview of the study design is shown in Fig 3 .

https://doi.org/10.1371/journal.pone.0307956.g003

The interventions will be conducted by the first author, who is a professional Dance Movement therapist, as part of the RRP course, once a week for the duration of the 10 weeks of each program cycle. A graduate student of the RRP will take part as a co-instructor for modelling and assistance. Each intervention group will have between 10 and 14 participants. Since autistic participants may feel anxious without a predictable structure, a structured physical training protocol will be used for each condition. The protocols were designed by the first author with the help of a professional physical trainer and after consulting with dance movement therapists who have research experience in the area of synchrony interventions in ASD. Each protocol is composed of 10 physical training sessions, each lasting 60 minutes. The protocols differ in terms of using synchronous activity vs. non-synchronous activity. They do not differ in terms of physical exercise type or duration to control for the effect of exercise type and duration on the dependent variables. Some exercises include the use of a training mattress, an elastic band or a sponge ball. To allow for some flexibility in terms of spontaneous synchrony, each session includes a social engagement segment either as a warm-up or as a social game. A Tabata Timer [ 59 ] will be used to break the workout into clearly defined intervals during the main training segment. A metronome beat (every second) will be used to help the participants do the exercises at the right pace.

Synchronous condition

The instructors and the participants will form a circle facing each other while doing the physical exercises as shown in Fig 4 . To facilitate interpersonal synchrony, the participants will be instructed to do the same physical exercises (spatial synchrony) together at the same pace (rhythmic synchrony). The participants will not be instructed to use the same amount of effort, to accommodate a range of strengths and intensities.

https://doi.org/10.1371/journal.pone.0307956.g004

Non-synchronous condition

The participants will do the same physical exercises as the participants in the synchronous group but in the form of circuit training with seven stations. The circuit training will require the participants to do a different physical exercise at a different pace at each station. A detailed description of the exercises will be provided for each station. The instructors will demonstrate all the exercises before the beginning of training. The participants will be instructed to do the exercise for a set period of time, the same duration used in the synchronous group. The circuit training stations will be in the form of a circle, as shown in Fig 5 , but will be set up so that the participants do not to face each other when doing the exercises to prevent spontaneous synchronization. Depending on group size, the participants will work either as dyads or as single trainees in each station. In the dyad form one participant will do the exercise while the partner is resting and vice-versa. In the single form each participant will exercise as though a partner were present. The participants will be instructed to change partners each week so that each participant will have the opportunity to experience both the single and dyadic forms, with different partners.

https://doi.org/10.1371/journal.pone.0307956.g005

Intervention protocol

Each session will consist of four parts as listed in Table 1 .

https://doi.org/10.1371/journal.pone.0307956.t001

Quantitative data collection: Background and control variables

Background and control data will be collected for each participant from the RRP personal file which contains demographic and medical information obtained by the program staff using dedicated questionnaires. The questionnaires are handed out routinely to all RRP trainees during the program selection process, a few months before admission to the program. These cover information such as demographic data (e.g. age, gender, country of birth, residential area, number of siblings and birth order), medical data (e.g. diagnosis, age at diagnosis, comorbidities, use of psychiatric medication and HMO disability bracket) and physiological data (e.g. body weight and height).

Quantitative data collection: Outcome variables

Quantitative data on the following outcome variables (as listed in Table 2 ) will be collected for each participant using validated questionnaires and behavioral tasks at three points of time: before the first intervention session, after the last intervention session (pre-post) and 17 weeks after the end of the intervention period (follow-up). The data collection procedure will be administered by the first author in a group session, corresponding to the same group as the intervention group, in a classroom at RRP facilities. This procedure will be composed of two parts: (a) A group behavioral task which will be recorded using one video camera. (b) Questionnaire administration via online software (Qualtrics).

https://doi.org/10.1371/journal.pone.0307956.t002

Social closeness.

Social closeness will be measured using the Inclusion of Other in Self Scale (IOS) [ 60 , 61 ]. This scale is made up of seven Venn diagram-like pictures where one circle represents the participant and the other circle represents the entire intervention group. The diagrams, ranging from no overlap to near complete overlap, measure close relationships between self and the group by capturing aspects of both feeling close and behaving close. The scale has high reliability for the friendship subgroup sample (Cronbach’s alpha .92) and a high test-retest correlation (r = .86 (n = 31)). Significant correlations between the IOS and measures of closeness that are primarily verbal and multi-item were found (60).

Friendship closeness.

Friendship closeness will be measured using the Hebrew adaptation of the Friendship Closeness Inventory [ 41 ]. The FCI is composed of 49 items that measure closeness in same-sex friendships and is divided into three distinguishable yet related subscales: Emotional Closeness (EC), Behavioral Closeness (BC), and Cognitive Closeness (CC). For the purposes of the present study the first item will be adjusted to include a reference to participants in the intervention group alone: “ Do you have friends among the participants in the physical training group whom you consider to be ’close friends’ ?”. The scale has high reliability for both the total score (Cronbach’s alpha .94) and for the subscales scores (Cronbach’s alpha .91 for EC, Cronbach’s alpha .93 for BC and Cronbach’s alpha .87 for CC) [ 41 ].

Sense of belonging.

Sense of belonging will be measured using the Hebrew adaptation of the General Sense of Belonging Scale [ 62 ]. This scale is composed of 12 items that measure sense of belonging (achieved belongingness) which are rated on a 7-point Likert scale ranging from “Strongly Disagree” (1) to “Strongly Agree” (7). Six items measure sense of acceptance and inclusion; for example: I have a sense of belonging . The other six items measure sense of rejection and exclusion; for example: I feel like an outsider . For the purposes of the present study, the scale will be adjusted so that the words “other people” or “others” will be replaced by the words “participants in the physical training group”; for example: “ When I am with participants in the physical training group , I feel included ”. The scale has high reliability (Coefficient alpha = .94 and an average inter-item correlation (AIC) = .57 (M = 66.3, SD = 13.5) and strong patterns of validity estimates have been established (62). The original version of the General Sense of Belonging Scale [ 62 ] will also be used to validate the adapted one.

Work-related stress.

Work-related stress will be measured using the Hebrew adaptation of the Irritation Scale [ 63 ]. This scale comprises eight items, three of which assess cognitive irritation and five of which assess emotional irritation. Items are rated on a 7-point Likert scale ranging from “Strongly Disagree” (1) to “Strongly Agree” (7). For the purposes of the present study, the scale will be slightly adjusted in that the words “at work” will be replaced by the words “in the course”, for example: “ Even at home I often think of my problems in the course ”. The scale has high reliability (Cronbach’s alpha .89) and for the German version, a large number of studies report correlations between this scale and stressors at work, further impairments such as psychosomatic complaints or depression, and missing resources such as social support [ 63 ].

Prosociality.

Prosociality will be measured using the following behavioral group cooperation tasks, both of which resemble the classic N-person cooperation dilemma as a “collective action problem of a common good” as described by [ 64 ].

1 . Collection task . Participants will have to work together to pick up 100 small washers (a flat plastic coin with a diameter of 4 cm), as described in [ 65 ]. The participants will be asked to remain quietly in their seats for 5 minutes while the washers are being randomly scattered in a rectangular structure on one side of the classroom. Then the participants will be asked to pick up one washer at a time and put it in a small basket located on the other side of the classroom in the shortest time, until all washers are collected by the group. Only then will they be able to return to their seats and remain quietly for another 5 minutes. Participant will be asked to abstain from running to avoid collisions and maintain group safety. In this specific task, the act of gathering washers embodies the concept of the common good. Participants must collect all washers and place them in a small basket before returning to their seats. However, the temptation to free ride, relying on others’ efforts, illustrates the collective action problem. While it benefits both individuals and the group to gather the washers, the impact of any single person’s contribution is minimal and difficult to discern. This dynamic creates an incentive to conserve energy by abstaining from action and allowing others to undertake the task. Participants must work together toward a common goal (collecting all washers in the shortest time), therefore there is likely no incentive to compete. As in previous social loafing paradigms [ 66 ], cooperation on this task will be operationalized by participants’ effort to overcome the incentive to conserve energy, represented by their step rate (number of steps per second). The number of steps will be measured using a wearable fitness tracker (Fitbit Inspire 2) that will be attached to the participants’ wrists using a special band. Fitbit fitness trackers are commonly used in clinical trials [ 67 ]. Each tracker will be customized with participants’ personal height and weight to ensure step rate accuracy. The collection procedure will be recorded using one video camera to control task execution. Since cooperation on this task will depend on the participants’ physical fitness and might be influenced by group pressure, we will also use a non-physical confidential task to measure pure voluntary cooperation.

2 . Public goods game . Participants will be told they will be given 30 NIS and that they can donate some or all of it to a group investment, as described in [ 68 ]. The money in the group investment will then be doubled and divided equally among all members of the group. The money earned in this game will be compensation for participating in the study. In contrast to the collection task, participants’ contribution will be confidential to avoid group pressure. Cooperation on this task will be operationalized by the amount of money each participant decides to donate to the group investment.

Qualitative data collection

Qualitative data will be collected from the participants till data saturation is achieved, using semi-structured interviews. After each intervention cycle, all participants will be asked to volunteer to be interviewed. The interviewees will be chosen out of the pool of volunteers based on the following criteria: (a) At least one participant from each intervention group. (b) At least one participant from each army related profession. (c) High verbal self-expression—the participant must have been appraised by army officers as being able to verbally express thoughts, emotions and views. The interviews will be carried out one to two weeks after the end of the intervention cycle. The interview guide for the semi-structured interviews will be composed of 11 questions ranging from the most general (e.g., “ How did you experience the course in general ?”) to the most specific (e.g., “ How did the group physical training sessions affect your experience during the course : (a) with respect to your sense of belonging (b) with respect to friendship closeness (c) with respect to your sense of involvement and cooperation (d) with respect to your work-related stress ”). In order to merge the qualitative and quantitative data, the qualitative questions in the interview guide will be congruent with the quantitative objectives of this study. To motivate the participants to discuss their perspective and express their emotions, two questions out of the 11 will be administered using a set of projective cards. This set of cards contains 13 words and 17 pictures reflecting associations with the word “group”. On the first question the participants will be asked to choose a word that best describes their relationship with other members of the intervention group (e.g. “coherence”, “loneliness” and “opportunity”) and to explain why they chose this specific word. On the second question the participants will be asked to choose the picture that best depicts their experience during the group intervention process and to explain why they chose this specific picture. The use of semi‐ambiguous words and pictures is less challenging for individuals on the autistic spectrum than the presentation of more ambiguous stimuli. The interviews will be conducted by the first author and will be audio recorded and fully transcribed before analysis.

Data analyses

To answer the five study objectives (see above in Introduction) the following data analysis will be conducted:

Quantitative data analysis.

The data obtained as study variables will be coded, processed and analyzed at the end of the collection process. IBM SPSS Statistics Version 27 will be used for statistical analysis. To control the family-wise error rate when performing multiple hypothesis tests, Bonferroni Step-Down (Holm) procedure will be applied. Participants must attend at least 4 sessions to be included in the analyses. To describe the sample, descriptive statistics will be calculated followed by univariate and bivariate statistical analyses. The first step will be to assess whether the data follows a normal distribution for each of the variables which will guide the choice of parametric or non-parametric tests. To answer the primary study objective and the first secondary study objective, the effects of the intervention over time (at the end of the intervention and after 17 weeks) will be examined using a two-way mixed model ANOVA. To explore the second secondary study objective, the influence of the need to belong on the effect of the intervention over time (at the end of the intervention and after 17 weeks) will be examined using a three-way mixed model ANOVA.

Qualitative data analysis.

To investigate the participants’ experiences as related to the third secondary study objective, the semi-structured interviews will be analyzed using a thematic analysis approach [ 69 , 70 ] in which the data are systematically parsed to identify patterns of meanings (themes). The analysis will be performed using MAXQDA 2022.

Mixed methods analysis.

For data integration related to the fourth secondary study objective, a merged data analysis will be conducted based on side-by-side comparison of the quantitative findings with the interview data [ 48 ].

Study status

This study is currently ongoing. A feasibility assessment [ 71 ] of the intervention protocol was conducted to fine-tune the intervention protocol by documenting the experiences of the participants in terms of the goals of each of the intervention conditions (see above in Procedure). Participants’ allocation to intervention conditions during the feasibility assessment was not randomized or controlled and no data was collected. Full RCT implementation during three program cycles (starting in August 2021) have been completed successfully. The RCT implementation of the fourth program cycle is in process.

Serving in the army in Israel is mandatory at the age of 18 and represents the first step towards independent life outside of the home. Until recently, cognitively-abled autistic adults were automatically exempt from military service. The Roim Rachok civilian program aims to develop professional skills and tools to enable the successful integration of this population into an army work environment [ 6 ]. Recently, a new army program was developed to enable a full mandatory service for cognitively-abled autistic adults on a larger scale, and is currently being pilot tested. Clearly more needs to be known about interventions that promote successful integration in social and stressful work environments.

This study constitutes an innovative effort to empirically examine the use of group interpersonal synchrony as an effective intervention for young autistic adults who would like to successfully integrate into the Israeli army work force. It can contribute to the enhancement of the state of the art in the area of interpersonal synchrony as an effective intervention for autistic individuals specifically, and for individuals with difficulties in adapting to social and stressful work environments in general. The findings are also expected to contribute to the evidence base on intervention options for young autistic adults. The results are likely to provide information on the relevance of synchronized intervention as compared to non-synchronized interventions for individual wellbeing by incorporating the participants’ experiences. The findings can also contribute to further specify treatment guidelines for this population and to enrich future training and education of dance movement therapists, music therapists and other health care professionals working in the field of ASD.

The strength of this study lies in its ability to conduct an RCT in a field setting where the interventions are embedded in a plausible context: a program that aims to improve participants’ work-related soft skills. The trainees’ motivation to participate in this study is expected to be high, since both the intervention and data collection processes are embedded within the program schedule with no need for extra time-consuming activities (except for the individual interviews). The strength of this study is also linked to its potential limitations in terms of quantitative data generalizability due to the relatively medium sample size and the heterogeneity of the population. We expect that merging the quantitative results with in-depth qualitative outcomes will facilitate the transferability of the findings to other contexts.

Supporting information

S1 checklist. spirit 2013 checklist: recommended items to address in a clinical trial protocol and related documents*..

https://doi.org/10.1371/journal.pone.0307956.s001

https://doi.org/10.1371/journal.pone.0307956.s002

Acknowledgments

We thank the following individuals for their voluntary collaboration and support of this study: Tal Vardi (RRP Manager), Dr. Efrat Selanikyo (RRP Professional manager), Eyal Ron (RRP Course manager), Ori Dvir (computer science student) for helping develop the fitness tracker data retrieval software, Tomer Wasserman (certified physical trainer) for helping in the design of the intervention protocol, and Elad Shtayinmatz (RRP graduate) for helping administer the intervention protocol.

• 1. DSM-V. Diagnostic and Statistical Manual of Mental Disorders. VA: American Psychiatric Association; 2013.
• 2. Hendrickx S. Asperger Syndrome & Employment: What People with Asperger Syndrome Really Really Want. First. London and Philadelphia: Jessica Kingsley; 2009.
• View Article
• PubMed/NCBI
• Google Scholar
• 17. Bernieri FJ, Rosenthal R. Interpersonal coordination: Behavior matching and interactional synchrony. In: S F R., Rime B, editors. Fundamentals of nonverbal behavior. Cambridge University Press; 1991. p. 401–432.
• 20. Kestenberg Amighi Janet Loman Susan, Mark Sossin K. The Meaning of Movement Embodied Developmental, Clinical, and Cultural Perspectives of the Kestenberg Movement Profile. [Internet]. 2nd editio. NY: Routledge; 2018 [cited 2018 Aug 1]. Available from: https://www.routledge.com/The-Meaning-of-Movement-Embodied-Developmental-Clinical-and-Cultural/Kestenberg-Amighi-Loman-Sossin/p/book/9781138484634 .
• 40. McNeill WH. Keeping Together in Time. Cambridge, MA: Harvard University Press; 1995.
• 46. Dunning D. Social Motivation. Dunning D, editor. Psychology Press, Taylor & Francis Group; 2011.
• 48. Creswell JW, Clark VLP. Designing and Conducting Mixed Methods Research. SAGE Publications Ltd; 2017. 520 p.

• Open access
• Published: 23 July 2024

The “what, why, and how?” of story completion in health services research: a scoping review

• Candelyn Yu Pong 1 ,
• Nicola J. Roberts 4 &
• Elaine Lum 1 , 2 , 3  

BMC Medical Research Methodology volume  24 , Article number:  159 ( 2024 ) Cite this article

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The story completion method provides a different way of doing qualitative research. We note the emergent popularity of this method in health-related research, while much remains to be negotiated in terms of best practices for such studies. This scoping review aims to provide a synthesis on how researchers have used the story completion method in health services research. We offer implications for research and practice for further discussion by the scholarly community.

We used the JBI methodology for scoping reviews. Six databases were searched for published literature till March 1, 2023: Medline, Embase, CINAHL, PsycINFO, SAGE Journals Online databases, and SAGE Research Methods. We included primary studies of any study design using the story completion method in health services research.

A total of 17 studies were included. Findings suggest that the story completion method is useful for research on sensitive topics, and affords the use of comparative study designs and large sample sizes which may be difficult with conventional qualitative research methods. More than 80% of included studies used story completion as the sole method. However, the data collected from this method were limited in terms of the inferences that can be drawn; and richness of participant responses may vary widely. Less than 30% of included studies reported piloting of the story stems. Most studies were conducted online and analyzed qualitatively, though the story stem design and sample size varied widely.

The story completion method, with its attendant affordances for larger sample sizes, comparative study designs, and streamlined data collection is an innovative and useful stand-alone or adjunct qualitative method for health services research.

Peer Review reports

Qualitative methods increasingly underpin robust population health research, health services research, and implementation research [ 1 , 2 , 3 ]. The insights provided by qualitative methods allow us to appropriately design, execute, and evaluate a plethora of healthcare programs and innovations, including digital health and AI-augmented healthcare [ 4 , 5 , 6 ].

Qualitative methods used in these fields include interviews and focus groups. These methods are often time and resource intensive [ 7 ], and arguably less efficacious in eliciting uncensored views especially for topics that are socio-culturally sensitive [ 8 ]. In that, participants may adjust their positions on an issue to align with what they perceive as accepted social or cultural discourses, perhaps to avoid potential repercussions [ 9 ].

Story completion is a method not often used in population health, health services, and implementation research. Given its attributes, apart from being used on its own to explore socio-culturally sensitive topics, story completion promises to be a useful adjunct to semi-structured interviews and focus groups. The story completion method has already garnered much interest in the scholarly community, with several published discussions regarding its utility and issues [ 10 , 11 ], flexibility as a method across disciplines [ 12 ], and potential for decolonizing research methodologies [ 13 ].

What is story completion?

Story completion, first used in quantitative developmental psychology research and in psychoanalysis as a projective technique for clinical assessment, was subsequently re-developed as a qualitative method by Kitzinger for feminist research [ 8 ]. Importantly, Kitzinger re-conceptualized story completion in the mid-1990s as a way “to access not just psychological meanings but also social discourses” [ 8 ]. More recently, Clarke and colleagues re-ignited interest in this method with the publication of a special issue “Using Story Completion Methods in Qualitative Research” in the Qualitative Research in Psychology journal [ 8 ]. Although story completion originated as a pen-and-paper task, this method has been increasingly administered online. Hence, the moniker, digital story completion.

In typical story completion studies, participants are presented with one or several hypothetical scenarios that act as writing prompts (story stems) and asked to complete the story however they like (Table 1 ). In example 1, researchers used story completion as a stand-alone qualitative method to collect narratives from Australian adults regarding their views on the COVID-19 restrictions implemented, and how it affected their health and well-being [ 14 ]. The story completion method was chosen due to its ability to examine social discourses, meanings, norms, and assumptions; and researchers were interested to understand how individuals would react to constantly changing situations, such as COVID-19 restrictions [ 14 ]. In example 2, researchers also used story completion as a stand-alone method to explore how evangelical Christians perceive depression [ 15 ]. Story completion method was chosen in this case due to the stigma associated with depression or mental health in general; and as this method does not explicitly obtain respondents’ personal experiences or views, it reduces the risk of social desirability bias [ 15 ].

A key advantage of the story completion method is its ability to side-step solely direct personal experiences to include socio-cultural discourse and representations, which enables researchers to understand meaning-making frameworks of a particular social group [ 10 ]. Other notable advantages of the method include the ability to accommodate larger samples of participants relative to traditional qualitative methods, and the contentious use of comparative study designs, uncommon in qualitative research [ 10 ].

A perceived weakness of this method has to do with the invitation to participants to be imaginative when responding to the story stem, triggering some researchers (and users of research) to be concerned that “anything goes.” To alleviate this concern, we recognize the bi-directional connection between imagination and experience, where imagination is influenced by an individual’s experiences [ 16 ] and “experiences are partly constituted through the stories within [one’s] socio-cultural landscapes [ 17 ]. So, despite its apparent playfulness, story completion holds merit as a sole method and as a useful adjunct to traditional qualitative methods in multiple- or mixed-methods studies.

Rationale for this review

We observed a steady increase via PubMed in the number of studies using story completion for health-related research in the last five years. While each study justifies and explains its use, it is our opinion that much needs to be clarified and negotiated about best practices for this method. For example, how should story stems be derived? How and when to use comparator groups? How large should the sample be to yield adequate data for meaningful analysis? These questions pertain to future discussions about best practices or ‘shoulds’. However, we first need to understand the current landscape. In this scoping review we elicited how the story completion method has been used in health-related research. Specifically, we were interested in: (a) the target populations and/or health conditions, (b) the study designs used, (c) how story stems were derived, (d) how data were analyzed, (e) other research methods used to triangulate data from the story completion method, and (f) strengths and weaknesses of the method stated by study authors. Our findings serve as a useful resource or starting point for health services researchers interested in using the story completion method, when planning or designing their study.

Search strategy

This study was carried out in accordance with the JBI methodology for scoping review [ 18 ]. The protocol was published on Open Science Framework (available here: https://osf.io/rk2e6/ ) [ 19 ]. We developed a search strategy using the PRESS guidelines [ 20 ] and consulted university librarians for refinement around the following key terms: story completion and health services research (Additional File 1 ). We searched six databases: Medline, Embase, CINAHL, PsycINFO, SAGE Journals Online databases, and SAGE Research Methods for published literature till March 1, 2023.

Eligibility criteria

Inclusion criteria: a primary study of any study design using the story completion method in health services research. For the purposes of this review, we defined story completion as a type of qualitative research method where study participants are asked to complete a story based on an assigned story “stem” or opening [ 8 ], and health services research as an interdisciplinary study of scientific investigation that explores how social determinants, financial policies, organizational systems and structures, medical technology, and individual actions influence cost, access, quality of healthcare, and also our well-being and health [ 21 ]. This definition of health services research does not confine it to the provision of health services or health structures, but also includes the exploration of how social determinants and individual behaviors affect health and well-being. The World Health Organization recognizes social determinants such as social exclusion and discrimination as important factors that can affect access to healthcare and health equity in negative ways [ 22 ]. Hence, studies investigating perceptions of potentially stigmatizing conditions or sexual orientations which are likely to influence how/whether those individuals seek help/healthcare have been included. Studies were excluded if they were editorials, commentaries, discussion papers, methodological papers (non-empirical), conference papers, systematic reviews, meta-analyses, or study protocols.

Selection of studies

Three researchers (CP, NJR, EL) independently conducted title/abstract and full text screening of studies captured by the search strategy. Conflicts at both screening stages were resolved through discussion by two lead researchers (NJR, EL). Covidence ® , a web-based software for conducting reviews (Veritas Health Innovation, Melbourne, Australia) and Endnote 20 (Clarivate Analytics, PA, USA) were used for screening and managing citations respectively. Studies in languages other than English were translated using ChatGPT (OpenAI, CA, USA) and screened by two researchers (CP, EL), to determine eligibility.

Data extraction and data analysis

A standardized form was developed for data extraction using Google Forms. The following data were extracted: publication year, author, country of study, characteristics of the study population, study aim(s), study design, description of the story completion study, sample size, how story stems were derived, how data was captured and analyzed including type of analysis (e.g. Braun & Clarke’s reflexive thematic analysis, etc.), other research methods used to triangulate data (e.g. semi-structured interviews, surveys, focus groups, etc.), reported strengths and weaknesses of the story completion method, assumptions and underlying theories.

The form was piloted by three researchers (CP, NJR, EL) using three included studies, and refined accordingly. How we operationalized data extraction is shown in Additional File 2 . Two researchers (CP, EL) independently completed data extraction for the remaining studies. Publication year and sample size were extracted as numerical values. Other data points expressed as textual data were summarized rather than extracted verbatim from included studies, apart from author, country of study, and study aims. For example, data point “characteristics of the study population” were summarized as “Australia-based adults aged 18 and above during the COVID-19 pandemic”, “adolescents aged 14–25 years old with complex regional pain syndrome” and so forth. Descriptive statistics, where appropriate, were used to summarize extracted data in Excel ® (Version 1808 (Microsoft)). For example, to provide a numerical count of how many included studies were single country versus multi-country, and so forth.

The search yielded 278 studies. After removing 75 duplicates, 203 studies remained for screening. At full text screening stage there were nine studies reported in languages other than English which were translated using ChatGPT; these did not meet eligibility criteria and were excluded. A total of 17 studies were included in this review (Fig.  1 ). The list of included studies is provided as Additional File 3 .

PRISMA-scoping review flow diagram [ 18 ]

Study characteristics

The main characteristics of included studies are summarized in Table  2 . The majority were single country studies (15/17, 88·2%), originating from the European region (9/17, 52·9%) and Western Pacific region (4/17, 23·5%). Most of the studies were published between 2021 and 2023 (9/17, 52·9%). In terms of the study design used, of the 17 studies, 13 (76·5%) were qualitative, three (3/17, 17·6%) used a mixed-method design, and one (1/17, 5·9%) used a multi-method design (Table  2 ). We used the following definitions for mixed-method and multi-method studies, respectively. Mixed-method studies use two or more methods in a single research project comprising both qualitative and quantitative approaches, that involves the connection, integration, or linking of these two approaches [ 23 ]. Multi-method studies use two or more solely qualitative or solely quantitative methods in a single research project [ 24 ]. In addition, although the story completion method allows for comparative study designs, this was adopted by only three studies (3/17, 17·6%) [ 25 , 26 , 27 ].

Description of the story completion study

Most studies asked participants to complete one story stem each, with the exception of five studies (5/17, 29·4%) which asked each participant to complete either two [ 30 , 31 , 32 ] or three story stems [ 33 , 34 ]. Of these five studies, four provided multiple story stems to allow a diversity of illnesses, genders, socio-economic groups, or occupations to be included in the stem [ 30 , 32 , 33 , 34 ]; while one did not provide a rationale for having multiple stems. Story stems provided were fairly brief, consisting of two to five short sentences. Examples of story stems can be found in Table 1 .

For single story stem studies ( n  = 12), most provided the same story opening to every participant, except three (3/12, 25.0%) which adopted a comparative design where study authors developed two story stems of the same narrative but with different protagonists in terms of gender [ 25 , 26 ] or occupation [ 27 ]. Participants were allocated [ 25 ] or randomly allocated to either stem [ 26 , 27 ]. Another study (1/12, 8.3%) randomized each participant to one of three story stems pertaining to the research, with results from each stem analyzed separately [ 35 ]. Of the five multi-story stems studies, three (3/5, 60.0%) provided the story openings in the same order for participants [ 31 , 33 , 34 ]. Two studies (2/5, 40.0%) counterbalanced the order of the story openings with half the participants presented with the first story stem followed by the second story stem while the other half were presented with the second story stem followed by the first [ 30 , 32 ].

Most studies provided participant guidelines for either time (minutes) and/or length (number of words/ characters/ sentences) for story responses (10/17, 58·8%), though these varied widely among studies (Table  3 ). Sample size varied widely among studies as well; ranging from 17 to as large as 227 (Table  3 ).

Populations studied and health conditions

Study aims, populations studied, and health conditions are shown in Table  3 . Study participants were recruited from general populations or subgroups of general populations (e.g. adolescents, gay men), or were working adults in the healthcare industry and/or students in a health-related course. Most studies targeted a particular health condition (13/17, 76·5%). Of those that did, six studies focused on mental health conditions (6/17, 35·3%), three on chronic diseases (3/17, 17·6%), and one on cancer (1/17, 5·9%).

Study aims of some included studies are socio-culturally sensitive. For example, in the study by Lloyd et al 2022 one of the aims was to “explore how self-harm is perceived” [ 36 ], while Walsh et al 2010 aimed to “explore the ways in which ‘anorexic’ and ‘bulimic’ young women are discursively constructed by those who neither self-identify as ‘eating disordered’ nor are involved in ‘eating disorder’ interventions” [ 32 ].

How story stems were derived

Story stems were constructed by study authors in most studies, except for four studies (4/17, 23.5%) where study authors reported using either published literature or a theoretical framework to inform the development of story stems [ 27 , 33 , 36 , 37 ], and one study (1/17, 5.9%) which derived and modified the story stems based on the Wallace (1956) measure [ 31 , 38 ]. The Wallace measure estimates how far into the future a person typically plans (future time perspective) and consists of two types of questions concerning timeframes about future actions or outcomes [ 38 ]. For example, the first type of question may ask participants to list 10 events that will occur in their lives and the age they would expect to be for each event. The second type of question asks participants to write endings to story stems (i.e. story completion) and to indicate the duration in which the story occurred (e.g. “x” minutes, days, years).

The majority of studies did not pre-test the story stems (12/17, 70·6%); of those that did, they were either piloted to ensure clarity [ 15 , 30 , 35 , 36 ] or to prevent potential narrowing of responses [ 9 ]. Most studies adopted third-person story stem(s), except two studies (2/17, 11.8%) that used a first-person story stem to allow participants to reflect on their perceived future [ 39 , 40 ].

How data was captured and analyzed

Twelve out of 17 studies (70·6%) administered the story completion task online. The remaining five studies (5/17, 29.4%) were administered either in-person [ 31 , 34 ], a combination of both in-person and online [ 9 ], or did not report the mode of data collection [ 30 , 32 ]. Most studies analyzed the data qualitatively (14/17, 82·4%), with Braun & Clarke’s reflexive thematic analysis [ 41 ] as the most commonly used approach (12/17, 70·6%) (Table  2 ). However, three studies (3/17, 17.6%) applied a quantitative approach to the analysis of story completion data, as follows. The study by Nimbley et al. 2021 analyzed the stories collected using the Linguistic Inquiry and Word Count (LIWC) program which identified and coded words against pre-selected categories pertaining to positive or negative emotions, social, and cognitive dimensions determined by study authors [ 39 ]. The LIWC program subsequently generated quantitative data in the form of frequencies (counts) and proportions of words against these categories, which were further analyzed using statistical programs such as SPSS [ 39 ]. In the study by Jones et al. 2009, participants were asked to complete two story stems and to also indicate the duration in which the story occurred (e.g. minutes, days, years). The duration was quantitatively analyzed (salient to their research question), while the stories collected were not subjected to further analysis [ 31 ]. The study by Tichenor et al. 1977 analyzed the stories collected via deductive coding using a schema of 12 categories pre-developed by study authors, then assigning a frequency score [ 34 ]. The rates of expression for each of these categories were standardized through dividing the frequency scores by the number of words written by participants and multiplying this number by a constant of 1000 [ 34 ].

Research methods used to triangulate data

The majority of studies did not use other research methods to triangulate the data from the story completion method, with the exception of two (2/17, 11.8%) that used surveys [ 30 , 34 ] and one that used semi-structured interviews (1/17, 5·9%) [ 40 ]. Of the two studies that used surveys to triangulate data, one conducted the survey prior to the story completion task [ 30 ] whilst the other did not specify the order in which the tasks were carried out [ 34 ]. The sole study that used semi-structured interviews conducted them after the story completion task to explore the stories crafted by participants in greater detail [ 40 ].

Reported strengths and weaknesses of the story completion method

The story completion method is reported to be useful for exploring sensitive topics and vulnerable populations [ 9 , 15 , 25 , 32 , 36 , 37 , 42 ] as it does not require participants to reveal their personal experiences [ 14 , 27 , 33 ]. Instead of actual behaviors, story completion method uncovers participants’ unconscious and subconscious patterns and ways of sense-making as well as perceptions towards a given scenario, beyond their lived experiences [ 9 , 14 , 15 , 27 , 35 , 42 ], thereby reducing the risk of social desirability bias [ 15 , 36 ].

Hence, this method reportedly allows study authors the potential to obtain rich data pertaining to both individual and collective experiences of major social events and problems [ 14 , 30 ] that may not be elicited through more conventional data collection methods [ 26 , 27 ]. Additionally, data from a larger group of participants can be collected more efficiently, relative to other forms of qualitative methods [ 26 , 40 ].

However, the story completion method is not without weaknesses. Study authors discerned that as the story completion method does not explicitly obtain participants’ personal experiences [ 15 , 27 , 36 ], it limits the inferences that can be derived from the findings [ 14 , 37 ]. When crafting responses, participants may exaggerate the protagonist’s life to produce a “good” story that they would otherwise not have done in a more conventional data collection method [ 32 ] or orientate their responses to include more social elements than what they would have otherwise given due to the type of story stem provided [ 40 ].

Additionally, study authors reported that participants’ engagement with the story stem varied widely. Some would provide complex and detailed responses while others produced superficial and short stories [ 25 ], and some may misinterpret the task and provide a theoretical account of the assigned story opening instead of completing the story [ 25 , 26 ]. Study authors also noted that in common with other qualitative research, it is hard to recruit male participants [ 26 ].

Underpinning philosophy

Most studies specified the ontology, epistemology, or theoretical lens used (10/17, 58·8%). The top three were social constructionism (4/17, 23·5%), critical realism (2/17, 11·8%), and epistemic contextualism (2/17, 11·8%) (Table  2 ). Study authors deemed the story completion method to be compatible with their selected underpinning philosophy, which was in turn used to inform interpretation of the narratives collected.

This scoping review provides a synthesis of how the story completion method has been used in health services research thus far. Our findings serve as a useful resource for health services researchers interested in exploring and using the story completion method, when planning or designing their study. We found several distinct advantages of the story completion method, suggesting its usefulness as either a sole or adjunct approach to undertaking qualitative research, provided its shortcomings are mitigated.

First, the story completion method enables large sample sizes as the collection of data can be done in a relatively efficient way, compared to traditional qualitative methods such as semi-structured interviews. Several studies included in this scoping review reported sample sizes of over 100 [ 9 , 15 , 26 , 31 , 36 , 37 ], the largest being 227 [ 31 ]. In contrast, the average sample size was between 18 and 45 in a recent systematic analysis of sample sizes for interview-based studies published over a 15-year period in health research journals [ 43 ]. Second, the story completion method can accommodate comparative study designs, which is unusual in qualitative methods, and useful for systematically eliciting differences in variables salient to the research question (e.g. male/female, novice/expert, and so forth). An overview of the story completion method by Clarke et al. 2019 underscores that this advantage allows a more “nuanced understanding of how a particular phenomenon is socially constructed” [ 8 ]. Third, story completion is especially appropriate for research on sensitive topics as it minimizes the risk of social desirability bias, a common problem reported in qualitative health research literature [ 44 ]. This is because in contrast to qualitative methods such as semi-structured interviews, the story completion method allows participants to respond to socio-culturally sensitive topics as a third party and to participate anonymously (assuming the story stem references a third party e.g. “Tom”, “Ali”, and data collection was conducted via an online platform). In our review, conditions that carry social stigma such as mental health issues and eating disorders, were target health conditions among included studies.

The shortcomings of the story completion method reported by study authors are acknowledged in methodological discussions about this innovative approach [ 10 , 11 ]. The non-intrusive data collection afforded by the story completion method might limit the inferences study authors can draw from the findings as responses might not reflect participants’ lived experiences [ 14 , 15 , 27 , 36 , 37 ]. However, Clarke et al. 2019 cautions that whether this constitutes a problem depends on the ontological stance taken: “Essentialist/realist/(post)positivist researchers may be concerned that data may not reflect or predict “real-life” behaviour. By contrast, for social constructionist or critical realist researchers interested in the sociocultural meanings or discourses people draw on when writing their stories, this critique holds no water” [ 8 ].

Additionally, story completion is a fixed self-administered task unlike other qualitative research methods such as semi-structured interviews or focus groups where researchers and participants interact to co-shape the research-in-progress. Hence, some participants may misinterpret the task [ 25 , 26 ] or provide responses that fall short of the study authors’ requirements or expectations. When confronted with such data, researchers need to judge whether these responses are sufficiently meaningful to warrant inclusion in the dataset for analysis [ 11 ]. Misinterpretation of the story completion task can be mitigated by piloting to ensure clarity [ 15 , 30 , 35 , 36 ] or to prevent potential narrowing of responses [ 9 ]. Yet, piloting of story stems was conducted by less than a third of included studies.

We note that most studies used story completion as the sole method rather than as an adjunct method. For example, other quantitative or qualitative research methods were not used to triangulate data from the story completion method. Admittedly, some research questions may not require more than a single method. However, the wider literature recognizes the potentially complementary pairing of the story completion method with another method such as semi-structured interviews [ 11 , 12 ].

Most studies adopted a qualitative approach to data analysis, with Braun & Clarke’s reflexive thematic analysis [ 41 ] being the most prominently used. Story stems were brief to allow participants the freedom to construct their own stories; and story stem design varied widely, with the most common being participants completing a single third-person story stem, with the same story opening provided to all.

Since the COVID-19 pandemic, the pace of research has sped up significantly [ 45 ]. Researchers engaged in population health, health services, or implementation research have worked on ways to accelerate actionable outputs without compromising scientific rigor; for example, rapid qualitative analysis to reduce the time taken to analyze qualitative data [ 46 , 47 ] and methods to hasten on-the-ground implementation [ 48 ]. The story completion method, with its attendant affordances for larger sample sizes, comparative study designs, and streamlined data collection adds to these innovative methods.

Limitations and strengths

There are some limitations to this review. First, we may have missed capturing some studies as the search was restricted to peer-reviewed articles and we did not manually search the reference lists of included papers to identify potential studies for inclusion. Second, we did not include an assessment of the reporting quality of included studies. We attempted to assess the reporting quality of 14 out of 17 included studies which conducted qualitative analysis on collected data, using an established checklist for reporting qualitative research — the Consolidated Criteria for Reporting Qualitative Research, COREQ [ 49 ]. However, many items on the COREQ checklist were neither appropriate nor relevant to the reporting of story completion studies; for example, interview guide, repeat interviews, field notes, participant checking, and so forth. We are mindful of salient scholarly critique regarding COREQ’s trustworthiness and reliability in reflecting the quality of reporting [ 50 ]. Therefore, we could not justifiably adapt COREQ for the purposes of this study.

Strengths of this review include having an extensive search strategy and broad inclusion criteria, allowing us to retrieve as many relevant studies as possible. University librarians were consulted for refinement of search strategy and included studies were not limited to a particular search period or geographical area. We piloted our data extraction form to evaluate its ability to capture relevant study information. Issues were flagged and the form was revised accordingly prior to actual extraction by two researchers.

Implications for research and practice

Currently, there are no universally agreed best practice nor reporting standard for the story completion method in health services research. Given the various ways in which the story completion method has been used in this scoping review, we offer several suggestions for research and practice for further discussions by the scholarly community.

First, piloting is crucial and recommended by key proponents of the story completion method [ 8 , 11 ]. Story completion is a fixed task unlike other qualitative methods such as semi-structured interviews or focus groups where it is possible to iteratively modify the questions as participants co-shape the research-in-progress. Piloting is a smart way to ensure that both the instructions and story stem(s) provided to participants are clear, to prevent misinterpretations.

Second, consider using other quantitative or qualitative research methods to triangulate or corroborate the data from the story completion method if thorough investigation of the research question(s) requires more than one method. While a methodological strength of the story completion method is that it uncovers participants’ patterns and ways of sense-making beyond their lived experiences [ 9 , 14 , 15 , 27 , 35 , 42 ], this also means that there may be limited inferences that can be drawn from the findings since responses may not reflect participants’ realities. Hence, pairing story completion with a story-mediated interview, for example, may lend further insights [ 12 ].

Third, as story completion studies are markedly different from traditional qualitative research methods, having an agreed set of reporting criteria for such studies will be useful for health services researchers. For example, a minimalist set of reporting criteria could comprise the 10-item JBI critical appraisal checklist for qualitative research [ 51 ] plus a description of the study design, development of the story stems, number of participants/sample size, and how participants completed the task in terms of modality, the number of story stems per participant, and sequence of story stem presentation.

The story completion method is an exciting and innovative way of doing qualitative research, and has the potential to be used more widely. This scoping review generated a comprehensive summary of how the story completion method has been used in health-related research. Findings and suggestions for research and practice serve as useful resources for researchers interested in experimenting with and adopting the story completion method in their work.

Data availability

The dataset supporting the conclusions of this article are available in the Open Science Framework repository, https://osf.io/rk2e6/.

Stickley T, O’Caithain A, Homer C. The value of qualitative methods to public health research, policy and practice. Perspect Public Health. 2022;142(4):237–40.

Article   PubMed   PubMed Central   CAS   Google Scholar  

Renjith V, Yesodharan R, Noronha JA, Ladd E, George A. Qualitative methods in Health Care Research. Int J Prev Med. 2021;12:20.

Article   PubMed   PubMed Central   Google Scholar  

Hamilton AB, Finley EP. Qualitative methods in implementation research: an introduction. Psychiatry Res. 2019;280:112516.

Noyes J. Never mind the qualitative feel the depth! The evolving role of qualitative research in Cochrane intervention reviews. J Res Nurs. 2010;15(6):525–34.

Article   Google Scholar  

Yarker J, Lewis R, Sinclair A, Michlig G, Munir F. Meta-synthesis of qualitative research on the barriers and facilitators to implementing workplace mental health interventions. SSM - Mental Health. 2022;2:100148.

Rolfe DE, Ramsden VR, Banner D, Graham ID. Using qualitative Health Research methods to improve patient and public involvement and engagement in research. Res Involv Engagem. 2018;4(1):49.

Sofaer S. Qualitative research methods. Int J Qual Health Care. 2002;14(4):329–36.

Article   PubMed   Google Scholar  

Clarke V, Braun V, Frith H, Moller N. Editorial introduction to the Special Issue: using Story Completion methods in qualitative research. Qualitative Res Psychol. 2019;16(1):1–20.

Moller N, Tischner I. Young people’s perceptions of fat counsellors: how can THAT help me? Qualitative Res Psychol. 2019;16(1):34–53.

Braun V, Clarke V, Hayfield N, Frith H, Malson H, Moller N, et al. Qualitative story completion: possibilities and potential pitfalls. Qualitative Res Psychol. 2019;16(1):136–55.

Urry K, Hunter S, Feo R, Scholz B. Qualitative story completion: opportunities and considerations for Health Research. Qual Health Res. 2023;33(4):345–55.

Gravett K. Story Completion: Storying as a method of meaning-making and Discursive Discovery. Int J Qualitative Methods. 2019;18:1609406919893155.

Lenette C, Vaughan P, Boydell K. How can Story Completion be used in culturally safe ways? Int J Qualitative Methods. 2022;21:16094069221077764.

Vaughan P, Lenette C, Boydell K. ‘This bloody rona!’: using the digital story completion method and thematic analysis to explore the mental health impacts of COVID-19 in Australia. BMJ Open. 2022;12(1):e057393.

Lloyd CEM, Mengistu BS, Reid G. “His main problem was not being in a relationship with God”: perceptions of depression, help-seeking, and treatment in evangelical Christianity. Front Psychol. 2022;13:831534.

Andrews M. Narrative, imagination and extending visions of the possible. Sociétés. 2016;133(3):15–20.

Smith B. Some modest thoughts on Story Completion methods in qualitative research. Qualitative Res Psychol. 2019;16(1):156–9.

Peters MD, Godfrey C, McInerney P, Munn Z, Tricco AC, Khalil H. Chapter 11: Scoping Reviews (2020 version). In: Aromataris, E., Munn, Z., editors. JBI Manual for Evidence Synthesis [Internet]. JBI; 2020 [cited 2021 Oct 14]. https://synthesismanual.jbi.global .

Open Science Framework. There’s a better way to manage your research [Internet]. 2023 [cited 2023 Jan 18]. https://osf.io/ .

McGowan J, Sampson M, Salzwedel DM, Cogo E, Foerster V, Lefebvre C. PRESS peer review of electronic search strategies: 2015 Guideline Statement. J Clin Epidemiol. 2016;75:40–6.

Lohr KN, Steinwachs DM. Health Services Research: an evolving definition of the field. Health Serv Res. 2002;37(1):15–7.

Article   PubMed Central   Google Scholar  

World Health Organization. Social determinants of health [Internet]. World Health Organization; 2024 [cited 2024 May 6]. https://www.who.int/health-topics/social-determinants-of-health#tab=tab_1 .

Creswell JW. Mapping the Developing Landscape of Mixed Methods Research. In: Tashakkori A, Teddlie C, editors. SAGE Handbook of Mixed Methods in Social & Behavioral Research (2nd edition). Thousand Oaks, California: SAGE Publications, Inc; 2010. p. 51.

Schoonenboom J, Johnson RB. How to construct a mixed methods Research Design. Kolner Z Soz Sozpsychol. 2017;69(Suppl 2):107–31.

Shah-Beckley I, Clarke V. Exploring therapists’ and psychology students’ constructions of sexual refusal in heterosexual relationships: a qualitative story completion study. Counselling Psychother Res. 2021;21(4):946–56.

Tischner I. Tomorrow is the start of the rest of their life-So who cares about health? Exploring constructions of weight-loss motivations and health using story completion. Qualitative Res Psychol. 2019;16(1):54–73.

Scholz B, Bocking J, Hedt P, Lu VN, Happell B. ‘Not in the room, but the doctors were’: an Australian story-completion study about consumer representation. Health Promot Int. 2020;35(4):752–61.

World Health Organization. Countries [Internet]. World Health Organization; 2023 [cited 2023 Oct 16]. https://www.who.int/countries .

LIWC, Introducing. LIWC-22: Pennebaker Conglomerates; [cited 2023 Oct 16]. https://www.liwc.app/ .

Diniz E, Castro P, Bousfield A, Figueira Bernardes S. Classism and dehumanization in chronic pain: a qualitative study of nurses’ inferences about women of different socio-economic status. Br J Health Psychol. 2020;25(1):152–70.

Jones BA, Landes RD, Yi R, Bickel WK. Temporal horizon: modulation by smoking status and gender. Drug Alcohol Depend. 2009;104(Suppl1):S87–93.

Walsh E, Malson H. Discursive constructions of eating disorders: a story completion task. Feminism Psychol. 2010;20(4):529–37.

Lupton D. ‘The internet both reassures and terrifies’: exploring the more-than-human worlds of health information using the story completion method. Med Humanit. 2021;47(1):68–77.

Tichenor CC, Rundall TG. Attitudes of physical therapists toward cancer: a pilot study. Phys Ther. 1977;57(2):160–5.

Article   PubMed   CAS   Google Scholar  

Scott AG, Hunter SC, Johnson BJ. Exploring the social norms regarding parents’ food provision in Australia using story completion methodology. Appetite. 2022;178:106165.

Lloyd CEM, Panagopoulos MC. ‘Mad, bad, or possessed’? Perceptions of self-harm and mental illness in evangelical Christian communities. Pastoral Psychol. 2022;71:291–311.

Hayfield N, Campbell C. Students’ representations of menopause and perimenopause: out of control bodies and empathetic expert doctors. Sex Roles. 2022;87:365–78.

Wallace M. Future time perspective in schizophrenia. J Abnorm Psychol. 1956;52(2):240–5.

PubMed   CAS   Google Scholar  

Nimbley E, Caes L, Jones A, Fisher E, Noel M, Jordan A. A linguistic analysis of future narratives in adolescents with complex regional pain syndrome and their pain-free peers. Eur J Pain. 2021;25(3):693–703.

Jones A, Caes L, Eccleston C, Noel M, Rugg T, Jordan A. Loss-adjusting: Young people’s constructions of a future living with Complex Regional Pain Syndrome. Clin J Pain. 2020;36(12):932–9.

Braun V, Clarke V. Thematic analysis: a practical guide. London, England: SAGE Publications; 2021.

Google Scholar  

Olstein J, Finn MD. Daring to speak its name: perceptions of suicidal ideation among Australian gay men. J Community Psychol. 2021;50(3):1756–67.

Vasileiou K, Barnett J, Thorpe S, Young T. Characterising and justifying sample size sufficiency in interview-based studies: systematic analysis of qualitative health research over a 15-year period. BMC Med Res Methodol. 2018;18(1):148.

Bispo Júnior JP. Social desirability bias in qualitative health research. Rev Saude Publica. 2022;56:101.

Aviv-Reuven S, Rosenfeld A. Publication patterns’ changes due to the COVID-19 pandemic: a longitudinal and short-term scientometric analysis. Scientometrics. 2021;126(8):6761–84.

Nevedal AL, Reardon CM, Opra Widerquist MA, Jackson GL, Cutrona SL, White BS, et al. Rapid versus traditional qualitative analysis using the Consolidated Framework for Implementation Research (CFIR). Implement Sci. 2021;16(1):67.

Lewinski AA, Crowley MJ, Miller C, Bosworth HB, Jackson GL, Steinhauser K, et al. Applied rapid qualitative analysis to develop a contextually appropriate intervention and increase the likelihood of uptake. Med Care. 2021;59(Suppl 3):S242–51.

Proctor E, Ramsey AT, Saldana L, Maddox TM, Chambers DA, Brownson RC. FAST: a framework to assess speed of translation of health innovations to practice and policy. Glob Implement Res Appl. 2022;2(2):107–19.

Tong A, Sainsbury P, Craig J. Consolidated criteria for reporting qualitative research (COREQ): a 32-item checklist for interviews and focus groups. Int J Qual Health Care. 2007;19(6):349–57.

Buus N, Perron A. The quality of quality criteria: replicating the development of the Consolidated Criteria for Reporting Qualitative Research (COREQ). Int J Nurs Stud. 2020;102:103452.

Lockwood C, Munn Z, Porritt K. Qualitative research synthesis: methodological guidance for systematic reviewers utilizing meta-aggregation. Int J Evid Based Healthc. 2015;13(3):179–87.

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Acknowledgements

We thank university librarians from these institutions for consultations on the search strategy: Queensland University of Technology, Australia and Edinburgh Napier University, United Kingdom.

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Author contributions described according to the CRediT taxonomy as follows. Conceptualized the study: EL. Drafted, revised, and finalized the study protocol including search strategy: CYP, EL, and NJR. Conducted the study: CYP and EL. Curated and analyzed the data: CYP and EL. Interpreted the data: EL, CYP, and NJR. Supervised the study: EL. Wrote the first draft of the manuscript including data visualizations: CYP and EL. Revised the manuscript following peer review: EL. Provided critical input to the first draft of the manuscript: NJR. Provided critical input to the revised manuscript: NJR and CYP. All authors approved the final manuscript for submission.

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Pong, C.Y., Roberts, N.J. & Lum, E. The “what, why, and how?” of story completion in health services research: a scoping review. BMC Med Res Methodol 24 , 159 (2024). https://doi.org/10.1186/s12874-024-02274-7

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