presenting findings in qualitative research examples

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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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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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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.

How To Write The Results/Findings Chapter

For qualitative studies (dissertations & theses).

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

So, you’ve collected and analysed your qualitative data, and it’s time to write up your results chapter – exciting! But where do you start? In this post, we’ll guide you through the qualitative results chapter (also called the findings chapter), step by step.  

Overview: Qualitative Results Chapter

• What (exactly) the qualitative results chapter is
• What to include in your results chapter
• How to write up your results chapter
• A few tips and tricks to help you along the way

What exactly is the results chapter?

The results chapter in a dissertation or thesis (or any formal academic research piece) is where you objectively and neutrally present the findings of your qualitative analysis (or analyses if you used multiple qualitative analysis methods ). This chapter can sometimes be combined with the discussion chapter (where you interpret the data and discuss its meaning), depending on your university’s preference.  We’ll treat the two chapters as separate, as that’s the most common approach.

In contrast to a quantitative results chapter that presents numbers and statistics, a qualitative results chapter presents data primarily in the form of words . But this doesn’t mean that a qualitative study can’t have quantitative elements – you could, for example, present the number of times a theme or topic pops up in your data, depending on the analysis method(s) you adopt.

Adding a quantitative element to your study can add some rigour, which strengthens your results by providing more evidence for your claims. This is particularly common when using qualitative content analysis. Keep in mind though that qualitative research aims to achieve depth, richness and identify nuances , so don’t get tunnel vision by focusing on the numbers. They’re just cream on top in a qualitative analysis.

So, to recap, the results chapter is where you objectively present the findings of your analysis, without interpreting them (you’ll save that for the discussion chapter). With that out the way, let’s take a look at what you should include in your results chapter.

What should you include in the results chapter?

As we’ve mentioned, your qualitative results chapter should purely present and describe your results , not interpret them in relation to the existing literature or your research questions . Any speculations or discussion about the implications of your findings should be reserved for your discussion chapter.

In your results chapter, you’ll want to talk about your analysis findings and whether or not they support your hypotheses (if you have any). Naturally, the exact contents of your results chapter will depend on which qualitative analysis method (or methods) you use. For example, if you were to use thematic analysis, you’d detail the themes identified in your analysis, using extracts from the transcripts or text to support your claims.

While you do need to present your analysis findings in some detail, you should avoid dumping large amounts of raw data in this chapter. Instead, focus on presenting the key findings and using a handful of select quotes or text extracts to support each finding . The reams of data and analysis can be relegated to your appendices.

While it’s tempting to include every last detail you found in your qualitative analysis, it is important to make sure that you report only that which is relevant to your research aims, objectives and research questions .  Always keep these three components, as well as your hypotheses (if you have any) front of mind when writing the chapter and use them as a filter to decide what’s relevant and what’s not.

Need a helping hand?

How do I write the results chapter?

Now that we’ve covered the basics, it’s time to look at how to structure your chapter. Broadly speaking, the results chapter needs to contain three core components – the introduction, the body and the concluding summary. Let’s take a look at each of these.

Section 1: Introduction

The first step is to craft a brief introduction to the chapter. This intro is vital as it provides some context for your findings. In your introduction, you should begin by reiterating your problem statement and research questions and highlight the purpose of your research . Make sure that you spell this out for the reader so that the rest of your chapter is well contextualised.

The next step is to briefly outline the structure of your results chapter. In other words, explain what’s included in the chapter and what the reader can expect. In the results chapter, you want to tell a story that is coherent, flows logically, and is easy to follow , so make sure that you plan your structure out well and convey that structure (at a high level), so that your reader is well oriented.

The introduction section shouldn’t be lengthy. Two or three short paragraphs should be more than adequate. It is merely an introduction and overview, not a summary of the chapter.

Pro Tip – To help you structure your chapter, it can be useful to set up an initial draft with (sub)section headings so that you’re able to easily (re)arrange parts of your chapter. This will also help your reader to follow your results and give your chapter some coherence.  Be sure to use level-based heading styles (e.g. Heading 1, 2, 3 styles) to help the reader differentiate between levels visually. You can find these options in Word (example below).

Section 2: Body

Before we get started on what to include in the body of your chapter, it’s vital to remember that a results section should be completely objective and descriptive, not interpretive . So, be careful not to use words such as, “suggests” or “implies”, as these usually accompany some form of interpretation – that’s reserved for your discussion chapter.

The structure of your body section is very important , so make sure that you plan it out well. When planning out your qualitative results chapter, create sections and subsections so that you can maintain the flow of the story you’re trying to tell. Be sure to systematically and consistently describe each portion of results. Try to adopt a standardised structure for each portion so that you achieve a high level of consistency throughout the chapter.

For qualitative studies, results chapters tend to be structured according to themes , which makes it easier for readers to follow. However, keep in mind that not all results chapters have to be structured in this manner. For example, if you’re conducting a longitudinal study, you may want to structure your chapter chronologically. Similarly, you might structure this chapter based on your theoretical framework . The exact structure of your chapter will depend on the nature of your study , especially your research questions.

As you work through the body of your chapter, make sure that you use quotes to substantiate every one of your claims . You can present these quotes in italics to differentiate them from your own words. A general rule of thumb is to use at least two pieces of evidence per claim, and these should be linked directly to your data. Also, remember that you need to include all relevant results , not just the ones that support your assumptions or initial leanings.

In addition to including quotes, you can also link your claims to the data by using appendices , which you should reference throughout your text. When you reference, make sure that you include both the name/number of the appendix , as well as the line(s) from which you drew your data.

As referencing styles can vary greatly, be sure to look up the appendix referencing conventions of your university’s prescribed style (e.g. APA , Harvard, etc) and keep this consistent throughout your chapter.

Section 3: Concluding summary

The concluding summary is very important because it summarises your key findings and lays the foundation for the discussion chapter . Keep in mind that some readers may skip directly to this section (from the introduction section), so make sure that it can be read and understood well in isolation.

In this section, you need to remind the reader of the key findings. That is, the results that directly relate to your research questions and that you will build upon in your discussion chapter. Remember, your reader has digested a lot of information in this chapter, so you need to use this section to remind them of the most important takeaways.

Importantly, the concluding summary should not present any new information and should only describe what you’ve already presented in your chapter. Keep it concise – you’re not summarising the whole chapter, just the essentials.

Tips and tricks for an A-grade results chapter

Now that you’ve got a clear picture of what the qualitative results chapter is all about, here are some quick tips and reminders to help you craft a high-quality chapter:

• Your results chapter should be written in the past tense . You’ve done the work already, so you want to tell the reader what you found , not what you are currently finding .
• Make sure that you review your work multiple times and check that every claim is adequately backed up by evidence . Aim for at least two examples per claim, and make use of an appendix to reference these.
• When writing up your results, make sure that you stick to only what is relevant . Don’t waste time on data that are not relevant to your research objectives and research questions.
• Use headings and subheadings to create an intuitive, easy to follow piece of writing. Make use of Microsoft Word’s “heading styles” and be sure to use them consistently.
• When referring to numerical data, tables and figures can provide a useful visual aid. When using these, make sure that they can be read and understood independent of your body text (i.e. that they can stand-alone). To this end, use clear, concise labels for each of your tables or figures and make use of colours to code indicate differences or hierarchy.
• Similarly, when you’re writing up your chapter, it can be useful to highlight topics and themes in different colours . This can help you to differentiate between your data if you get a bit overwhelmed and will also help you to ensure that your results flow logically and coherently.

If you have any questions, leave a comment below and we’ll do our best to help. If you’d like 1-on-1 help with your results chapter (or any chapter of your dissertation or thesis), check out our private dissertation coaching service here or book a free initial consultation to discuss how we can help you.

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20 Comments

This was extremely helpful. Thanks a lot guys

Hi, thanks for the great research support platform created by the gradcoach team!

I wanted to ask- While “suggests” or “implies” are interpretive terms, what terms could we use for the results chapter? Could you share some examples of descriptive terms?

I think that instead of saying, ‘The data suggested, or The data implied,’ you can say, ‘The Data showed or revealed, or illustrated or outlined’…If interview data, you may say Jane Doe illuminated or elaborated, or Jane Doe described… or Jane Doe expressed or stated.

I found this article very useful. Thank you very much for the outstanding work you are doing.

What if i have 3 different interviewees answering the same interview questions? Should i then present the results in form of the table with the division on the 3 perspectives or rather give a results in form of the text and highlight who said what?

I think this tabular representation of results is a great idea. I am doing it too along with the text. Thanks

That was helpful was struggling to separate the discussion from the findings

this was very useful, Thank you.

Very helpful, I am confident to write my results chapter now.

It is so helpful! It is a good job. Thank you very much!

Very useful, well explained. Many thanks.

Hello, I appreciate the way you provided a supportive comments about qualitative results presenting tips

I loved this! It explains everything needed, and it has helped me better organize my thoughts. What words should I not use while writing my results section, other than subjective ones.

Thanks a lot, it is really helpful

Thank you so much dear, i really appropriate your nice explanations about this.

Thank you so much for this! I was wondering if anyone could help with how to prproperly integrate quotations (Excerpts) from interviews in the finding chapter in a qualitative research. Please GradCoach, address this issue and provide examples.

what if I’m not doing any interviews myself and all the information is coming from case studies that have already done the research.

Very helpful thank you.

This was very helpful as I was wondering how to structure this part of my dissertation, to include the quotes… Thanks for this explanation

This is very helpful, thanks! I am required to write up my results chapters with the discussion in each of them – any tips and tricks for this strategy?

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Preparing the presentation of qualitative findings: considering your roles and goals

Dr. Philip Adu is a Methodology Expert at The Chicago School of Professional Psychology (TCSPP). In this post he explains the things to consider when presenting your research findings.

This post follows on from his previous blog post “Perfecting the art of qualitative coding” in which he took us through the stages of qualitative coding and, along the way, outlined the features he found most useful.

In my previous blog post, I presented on making good use of the innovative features of NVivo across the three main stages of qualitative analysis. Expounding on the third stage which is the ‘ Post-Coding stage (Presenting your findings) ’, I want to throw light on things to consider when drafting and refining your presentation. The moment you reach a milestone of successfully using NVivo 12 (Version 12.1.249; QSR International Pty Ltd, 2018) to complete the data analysis process, the reality of preparing all of this data so you can present your findings sets in (Adu, 2016). Your methodical review of the qualitative data and development of codes, categories and themes has yielded massive and interesting NVivo outputs. The outcomes include but are not limited to; codes/nodes, categories/themes, Word Clouds, Word Tree, Framework Matrices, Cluster Tree, code-case matrices, and code-attribute matrices (see Figure 1). These findings need to be carefully examined – selecting the ones that will be useful in drafting a meaningful presentation. You can watch the presentation I developed below:

Source: https://www.youtube.com/watch?v=xEyGGFtVQFw

Note, not all of this information (i.e. the outcomes) needs to be presented to your audience (see Adu, 2019 ). Other questions that may arise as you develop your presentation include; what kind of results should you present? How do you engage with your audience when presenting your findings? How would you help your audience to understand and believe your findings?

In this post, I will discuss the three pertinent components a good presentation of qualitative findings should have. They are; background information, data analysis process and main findings.

Figure 1. Presentation of findings

Presenting background information

Participants’ past and current situations influence the information they provide to you. Due to this, there is the need to provide readers a summary of who participants are and any background information which may help them to put the findings into the proper context. Also, as a researcher analyzing qualitative data, there is the likelihood of your own background impacting the data analysis process. In the same way, you need to let readers know who you are, what your background is and how you ‘bracketed’ them from not having an effect on the findings ( Adu, 2019 ).

Presenting the data analysis process

Qualitative analysis doesn’t only involve engaging in subjective development of codes and categories, but also promoting transparency in the coding and categorization process (Greckhamer & Cilesiz, 2014). Due to this, you are expected to describe the main and detailed steps you took to analyze your data to arrive at your findings and their respective outcomes. Addressing the following questions would be great:

• What coding strategy did you use?
• What kinds of codes did you assign to relevant excerpts of the data?
• What are the examples of codes you generated?
• What categorization technique did you use?
• How did you develop categories/themes out of the codes?

Your audience’s aim is not only consuming what you found but also learning more about how you came up with the results.

Presenting main findings

When it comes to the presentation of findings, there are two main structures you could choose from. You could present them based on the themes generated or based on the cases (participants or groups of participants) you have. The decision to either structure depends on the kind of research question(s) or the research purpose you have. For a detailed explanation of the types of presentation formats and how to select an appropriate structure, see Chapter 13 of the book, “ A Step-by-Step Guide to Qualitative Data Coding ”.

Considering your roles and goals

As you plan on how to communicate the above components, make sure you accomplish your goals and carry out your role as a communicator of qualitative data analysis outcomes (See Figure 1). Your roles are; to thoughtfully arrange the data analysis outcomes and to adequately address your research questions.

Liken the presentation of your findings to sharing a puzzle which has been solved. Your goal is to prevent a situation where the burden is put on the audience to piece together the puzzle of findings. In other words, you are expected to present the findings in a meaningful way that would enhance the audience’s understanding of the data analysis outcomes (Adu, 2016 & 2019). By so doing, they are more likely to trust what you found.

Let’s summarize the action items:

• Out of a pool of qualitative analysis outcomes, select the ones that would allow you to address your research questions and meaningfully communicate your findings.
• Decide on how you want to structure the presentation of the findings.
• Irrespective of the presentation format you choose, make sure you include background information, the data analysis process and main findings in your presentation.
• Make sure you are ‘narrating’ participants’ stories or what you found – making the numeric outputs include the tables and charts generated play a supporting role when presenting the main findings.

Adu, P. (2016). Presenting Qualitative Findings Using NVivo Output to Tell the Story. [PowerPoint slides]. SlideShare. Retrieved from https://www.slideshare.net/kontorphilip/presenting-qualitative-findings-using-nvivo-output-to-tell-the-story

QSR International Pty Ltd. (2018). NVivo 12. Version 12.1.249 [Computer software]. Retrieved from https://qsrinternational.com/nvivo-qualitative-data-analysis-software

Adu, P. (2019). A Step-by-Step Guide to Qualitative Data Coding . Oxford: Routledge

Greckhamer, T., & Cilesiz, S. (2014). Rigor, Transparency, Evidence, and Representation in Discourse Analysis: Challenges and Recommendations. International Journal of Qualitative Methods, 13(1), 422-443. doi:10.1177/160940691401300123

ABOUT THE AUTHOR

Dr. Philip Adu is a Methodology Expert at The Chicago School of Professional Psychology (TCSPP). His role is to provide support to dissertating students in TCSPP addressing their methodology related concerns. You could access some of his webinars at the ‘Methodology Related Presentations – TCSPP’ YouTube Channel. He completed his Doctoral degree in Education with a concentration in Learning, Instructional Design and Technology from West Virginia University (WVU). Dr. Adu recently authored a book titled, “A Step-by-Step Guide to Qualitative Data Coding” (available on routledge.com or amazon.com ). You could reach Dr. Adu at [email protected] and @drphilipadu on twitter.

Recent Articles

[Guide] How to Present Qualitative Research Findings in PowerPoint?

By: Author Shrot Katewa

As a researcher, it is quite pointless to do the research if we are unable to share the findings with our audience appropriately! Using PowerPoint is one of the best ways to present research outcomes. But, how does one present qualitative research findings using PowerPoint?

In order to present the qualitative research findings using PowerPoint, you need to create a robust structure for your presentation, make it engaging and visually appealing, present the patterns with explanations for it and highlight the conclusion of your research findings.

In this article, we will help you understand the structure of your presentation. Plus, we’ll share some handy tips that will make your qualitative research presentation really effective!

How to Create a Structure for your Qualitative Research Presentation?

Creating the right structure for your presentation is key to ensuring that it is correctly understood by your audience.

The structure of your Research Presentation not only makes it easier for you to create the document, it also makes it simple for the audience to understand what all will be covered in the presentation at the time of presenting it to your audience.

Furthermore, having a robust structure is a great way to ensure that you don’t miss out on any of the points while working on creating the presentation.

But, what structure should one follow?

Creating a good structure can be tricky for some. Thus, I’m sharing what has worked well for me during my previous research projects.

NOTE – It is important to note that although the following structure is highly effective for most research findings presentation, it has been generalized in order to serve a wide range of research projects. You may want to take a look at points that are very specific to the nature of your research project and include them at your discretion.

Here’s my recommended structure to create your Research Findings presentation –

1. Objective of the Research

A great way to start your presentation is to highlight the objective of your research project.

It is important to remember that merely sharing the objective may sometimes not be enough. A short backstory along with the purpose of your research project can pack a powerful punch ! It not only validates the reasoning for your project but also subtly establishes trust with your audience.

However, do make sure that you’re not reading the backstory from the slide. Let it flow naturally when you are delivering the presentation. Keep the presentation as minimalistic as possible.

2. Key Parameters Considered for Measurement

Once you’ve established the objective, the next thing that you may want to do is perhaps share the key parameters considered for the success of your project.

Every research project, including qualitative research, needs to have a few key parameters to measure against the objective of the research.

For example – If the goal of your project is to gather the sentiments of a certain group of people for a particular product, you may need to measure their feelings. Are they happy or unhappy using the product? How do they perceive the branding of the product? Is it affordable?

Make sure that you list down all such key parameters that were considered while conducting the qualitative research.

In general, laying these out before sharing the outcome can help your audience think from your perspective and look at the findings from the correct lens.

3. Research Methodology Adopted

The next thing that you may want to include in your presentation is the methodology that you adopted for conducting the research.

By knowing your approach, the audience can be better prepared for the outcome of your project. Ensure that you provide sound reasoning for the chosen methodology.

This section of your presentation can also showcase some pictures of the research being conducted. If you have captured a video, include that. Doing this provides further validation of your project.

4. Research Outcomes (Presenting Descriptive Analysis)

This is the section that will constitute the bulk of the your presentation.

Use the slides in this section to describe the observations, and the resulting outcomes on each of the key parameters that were considered for the research project.

It is usually a good idea to dedicate at least 1 or more slides for each parameter . Make sure that you present data wherever possible. However, ensure that the data presented can be easily comprehended.

Provide key learnings from the data, highlight any outliers, and possible reasoning for it. Try not to go too in-depth with the stats as this can overwhelm the audience. Remember, a presentation is most helpful when it is used to provide key highlights of the research !

Apart from using the data, make sure that you also include a few quotes from the participants.

5. Summary and Learnings from the Research

Once you’ve taken the audience through the core part of your research findings, it is a good practice to summarize the key learnings from each of the section of your project.

Make sure your touch upon some of the key learnings covered in the research outcome of your presentation.

Furthermore, include any additional observations and key points that you may have had which were previously not covered.

The summary slide also often acts as “Key Takeaways” from the research for your audience. Thus, make sure that you maintain brevity and highlight only the points that you want your audience to remember even after the presentation.

6. Inclusions and Exclusions (if any)

While this can be an optional section for some of the researchers.

However, dedicating a section on inclusions and exclusions in your presentation can be a great value add! This section helps your audience understand the key factors that were excluded (or included) on purpose!

Moreover, it creates a sense of thoroughness in the minds of your audience.

7. Conclusion of the Research

The purpose of the conclusion slide of your research findings presentation is to revisit the objective, and present a conclusion.

A conclusion may simply validate or nullify the objective. It may sometimes do neither. Nevertheless, having a conclusion slide makes your presentation come a full circle. It creates this sense of completion in the minds of your audience.

8. Questions

Finally, since your audience did not spend as much time as you did on the research project, people are bound to have a few questions.

Thus, the last part of your presentation structure should be dedicated to allowing your audience to ask questions.

Tips for Effectively Presenting Qualitative Research Findings using PowerPoint

For a presentation to be effective, it is important that the presentation is not only well structured but also that it is well created and nicely delivered!

While we have already covered the structure, let me share with you some tips that you can help you create and deliver the presentation effectively.

Tip 1 – Use Visuals

Using visuals in your presentation is a great way to keep the presentations engaging!

Visual aids not only help make the presentation less boring, but it also helps your audience in retaining the information better!

So, use images and videos of the actual research wherever possible. If these do not suffice or do not give a professional feel, there are a number of resources online from where you can source royalty-free images.

My recommendation for high-quality royalty-free images would be either Unsplash or Pexels . Both are really good. The only downside is that they often do not provide the perfect image that can be used. That said, it can get the job done for at least half the time.

If you are unable to find the perfect free image, I recommend checking out Dreamstime . They have a huge library of images and are much cheaper than most of the other image banks. I personally use Dreamstime for my presentation projects!

Tip 2 – Tell a Story (Don’t Show Just Data!)

I cannot stress enough on how important it is to give your presentation a human touch. Delivering a presentation in the form of a story does just that! Furthermore, storytelling is also a great tool for visualization .

Data can be hard-hitting, whereas a touching story can tickle the emotions of your audience on various levels!

One of the best ways to present a story with your research project is to start with the backstory of the objective. We’ve already talked about this in the earlier part of this article.

Start with why is this research project is so important. Follow a story arc that provides an exciting experience of the beginning, the middle, and a progression towards a climax; much like a plot of a soap opera.

Tip 3 – Include Quotes of the Participants

Including quotes of the participants in your research findings presentation not only provides evidence but also demonstrates authenticity!

Quotes function as a platform to include the voice of the target group and provide a peek into the mindset of the target audience.

When using quotes, keep these things in mind –

1. Use Quotes in their Unedited Form

When using quotes in your presentation, make sure that you use them in their raw unedited form.

The need to edit quotes should be only restricted to aid comprehension and sometimes coherence.

Furthermore, when editing the quotes, make sure that you use brackets to insert clarifying words. The standard format for using the brackets is to use square brackets for clarifying words and normal brackets for adding a missing explanation.

2. How to Decide which Quotes to Consider?

It is important to know which quotes to include in your presentation. I use the following 3 criteria when selecting the quote –

• Relevance – Consider the quotes that are relevant, and trying to convey the point that you want to establish.
• Length – an ideal quote should be not more than 1-2 sentences long.
• Choose quotes that are well-expressed and striking in nature.

3. Preserve Identity of the Participant

It is important to preserve and protect the identity of the participant. This can be done by maintaining confidentiality and anonymity.

Thus, refrain from using the name of the participant. An alternative could be using codes, using pseudonyms (made up names) or simply using other general non-identifiable parameters.

Do note, when using pseudonyms, remember to highlight it in the presentation.

If, however, you do need to use the name of the respondent, make sure that the participant is okay with it and you have adequate permissions to use their name.

Tip 4 – Make your Presentation Visually Appealing and Engaging

It is quite obvious for most of us that we need to create a visually appealing presentation. But, making it pleasing to the eye can be a bit challenging.

Fortunately, we wrote a detailed blog post with tips on how to make your presentation attractive. It provides you with easy and effective tips that you can use even as a beginner! Make sure you check that article.

7 EASY tips that ALWAYS make your PPT presentation attractive (even for beginners)

In addition to the tips mentioned in the article, let me share a few things that you can do which are specific to research outcome presentations.

4.1 Use a Simple Color Scheme

Using the right colors are key to make a presentation look good.

One of the most common mistakes that people make is use too many colors in their presentation!

My recommendation would be to go with a monochromatic color scheme in PowerPoint .

4.2 Make the Data Tables Simple and Visually Appealing

When making a presentation on research outcomes, you are bound to present some data.

But, when data is not presented in a proper manner, it can easily and quickly make your presentation look displeasing! The video below can be a good starting point.

Using neat looking tables can simply transform the way your presentation looks. So don’t just dump the data from excel on your PowerPoint presentation. Spend a few minutes on fixing it!

4.3 Use Graphs and Charts (wherever necessary)

When presenting data, my recommendation would be that graphs and charts should be your first preference.

Using graphs or charts make it easier to read the data, takes less time for the audience to comprehend, and it also helps to identify a trend.

However, make sure that the correct chart type is used when representing the data. The last thing that you want is to poorly represent a key piece of information.

4.4 Use Icons instead of Bullet Points

Consider the following example –

This slide could have been created just as easily using bullet points. However, using icons and representing the information in a different format makes the slide pleasing on the eye.

Thus, always try to use icons wherever possible instead of bullet points.

Tip 5 – Include the Outliers

Many times, as a research project manager, we tend to focus on the trends extracted from a data set.

While it is important to identify patterns in the data and provide an adequate explanation for the pattern, it is equally important sometimes to highlight the outliers prominently.

It is easy to forget that there may be hidden learnings even in the outliers. At times, the data trend may be re-iterating the common wisdom. However, upon analyzing the outlier data points, you may get insight into how a few participants are doing things successfully despite not following the common knowledge.

That said, not every outlier will reveal hidden information. So, do verify what to include and what to exclude.

Tip 6 – Take Inspiration from other Presentations

I admit, making any presentation can be a tough ask let alone making a presentation for showcasing qualitative research findings. This is especially hard when we don’t have the necessary skills for creating a presentation.

One quick way to overcome this challenge could be take inspiration from other similar presentations that we may have liked.

There is no shame in being inspired from others. If you don’t have any handy references, you can surely Google it to find a few examples.

One trick that almost always works for me is using Pinterest .

But, don’t just directly search for a research presentation. You will have little to no success with it. The key is to look for specific examples for inspiration. For eg. search for Title Slide examples, or Image Layout Examples in Presentation.

Tip 7 – Ask Others to Critic your Presentation

The last tip that I would want to provide is to make sure that you share the presentation with supportive colleagues or mentors to attain feedback.

This step can be critical to iron out the chinks in the armor. As research project manager, it is common for you to get a bit too involved with the project. This can lead to possibilities wherein you miss out on things.

A good way to overcome this challenge is to get a fresh perspective on your project and the presentation once it has been prepared.

Taking critical feedback before your final presentation can also prepare you to handle tough questions in an adept manner.

Final Thoughts

It is quite important to ensure that we get it right when working on a presentation that showcases the findings of our research project. After all, we don’t want to be in a situation wherein we put in all the hard-work in the project, but we fail to deliver the outcome appropriately.

I hope you will find the aforementioned tips and structure useful, and if you do, make sure that you bookmark this page and spread the word. Wishing you all the very best for your project!

• UNC Libraries
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• Presenting Qualitative Research

Qualitative Research Resources: Presenting Qualitative Research

Created by health science librarians.

• What is Qualitative Research?
• Qualitative Research Basics
• Special Topics
• Training Opportunities: UNC & Beyond
• Help at UNC
• Qualitative Software for Coding/Analysis
• Software for Audio, Video, Online Surveys
• Finding Qualitative Studies
• Assessing Qualitative Research
• Writing Up Your Research
• Integrating Qualitative Research into Systematic Reviews
• Publishing Qualitative Research

Presenting Qualitative Research, with a focus on posters

• Qualitative & Libraries: a few gems
• Data Repositories

Example posters

• The Meaning of Work for People with MS: a Qualitative Study A good example with quotes
• Fostering Empathy through Design Thinking Among Fourth Graders in Trinidad and Tobago Includes quotes, photos, diagrams, and other artifacts from qualitative study
• Examining the Use and Perception of Harm of JUULs by College Students: A Qualitative Study Another interesting example to consider
• NLM Informationist Supplement Grant: Daring to Dive into Documentation to Determine Impact An example from the Carolina Digital Repository discussed in a class more... less... Allegri, F., Hayes, B., & Renner, B. (2017). NLM Informationist Supplement Grant: Daring to Dive into Documentation to Determine Impact. https://doi.org/10.17615/bk34-p037
• Qualitative Posters in F1000 Research Archive (filtered on "qualitative" in title) Sample qualitative posters
• Qualitative Posters in F1000 Research Archive (filtered on "qualitative" in keywords) Sample qualitative posters

Michelle A. Krieger Blog (example, posts follow an APA convention poster experience with qualitative posters):

• Qualitative Data and Research Posters I
• Qualitative Data and Research Posters II

"Oldies but goodies":

• How to Visualize Qualitative Data: Ann K. Emery, September 25, 2014 Data Visualization / Chart Choosing, Color-Coding by Category, Diagrams, Icons, Photographs, Qualitative, Text, Timelines, Word Clouds more... less... Getting a little older, and a commercial site, but with some good ideas to get you think.
• Russell, C. K., Gregory, D. M., & Gates, M. F. (1996). Aesthetics and Substance in Qualitative Research Posters. Qualitative Health Research, 6(4), 542–552. Older article with much good information. Poster materials section less applicable.Link is for UNC-Chapel Hill affiliated users.

Additional resources

• CDC Coffee Break: Considerations for Presenting Qualitative Data (Mark D. Rivera, March 13, 2018) PDF download of slide presentation. Display formats section begins on slide 10.
• Print Book (Davis Library): Miles, M. B., Huberman, A. M., & Saldaña, J. (2014). Qualitative data analysis: A methods sourcebook, 3rd edition From Paul Mihas, Assistant Director of Education and Qualitative Research at the Odum Institute for Research in Social Science at UNC: Qualitative Data Analysis: A Methods Sourcebook (4th ed.) by Miles, Huberman, and Saldana has a section on Displaying the Data (and a chapter on Designing Matrix, Network, and Graphic Displays) that can help students consider numerous options for visually synthesizing data and findings. Many of the suggestions can be applied to designing posters (April 15, 2021).
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• Next: Qualitative & Libraries: a few gems >>
• Last Updated: Apr 2, 2024 10:42 AM
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Chapter 20. Presentations

Introduction.

If a tree falls in a forest, and no one is around to hear it, does it make a sound? If a qualitative study is conducted, but it is not presented (in words or text), did it really happen? Perhaps not. Findings from qualitative research are inextricably tied up with the way those findings are presented. These presentations do not always need to be in writing, but they need to happen. Think of ethnographies, for example, and their thick descriptions of a particular culture. Witnessing a culture, taking fieldnotes, talking to people—none of those things in and of themselves convey the culture. Or think about an interview-based phenomenological study. Boxes of interview transcripts might be interesting to read through, but they are not a completed study without the intervention of hours of analysis and careful selection of exemplary quotes to illustrate key themes and final arguments and theories. And unlike much quantitative research in the social sciences, where the final write-up neatly reports the results of analyses, the way the “write-up” happens is an integral part of the analysis in qualitative research. Once again, we come back to the messiness and stubborn unlinearity of qualitative research. From the very beginning, when designing the study, imagining the form of its ultimate presentation is helpful.

Because qualitative researchers are motivated by understanding and conveying meaning, effective communication is not only an essential skill but a fundamental facet of the entire research project. Ethnographers must be able to convey a certain sense of verisimilitude, the appearance of true reality. Those employing interviews must faithfully depict the key meanings of the people they interviewed in a way that rings true to those people, even if the end result surprises them. And all researchers must strive for clarity in their publications so that various audiences can understand what was found and why it is important. This chapter will address how to organize various kinds of presentations for different audiences so that your results can be appreciated and understood.

In the world of academic science, social or otherwise, the primary audience for a study’s results is usually the academic community, and the primary venue for communicating to this audience is the academic journal. Journal articles are typically fifteen to thirty pages in length (8,000 to 12,000 words). Although qualitative researchers often write and publish journal articles—indeed, there are several journals dedicated entirely to qualitative research [1] —the best writing by qualitative researchers often shows up in books. This is because books, running from 80,000 to 150,000 words in length, allow the researcher to develop the material fully. You have probably read some of these in various courses you have taken, not realizing what they are. I have used examples of such books throughout this text, beginning with the three profiles in the introductory chapter. In some instances, the chapters in these books began as articles in academic journals (another indication that the journal article format somewhat limits what can be said about the study overall).

While the article and the book are “final” products of qualitative research, there are actually a few other presentation formats that are used along the way. At the very beginning of a research study, it is often important to have a written research proposal not just to clarify to yourself what you will be doing and when but also to justify your research to an outside agency, such as an institutional review board (IRB; see chapter 12), or to a potential funder, which might be your home institution, a government funder (such as the National Science Foundation, or NSF), or a private foundation (such as the Gates Foundation). As you get your research underway, opportunities will arise to present preliminary findings to audiences, usually through presentations at academic conferences. These presentations can provide important feedback as you complete your analyses. Finally, if you are completing a degree and looking to find an academic job, you will be asked to provide a “job talk,” usually about your research. These job talks are similar to conference presentations but can run significantly longer.

All the presentations mentioned so far are (mostly) for academic audiences. But qualitative research is also unique in that many of its practitioners don’t want to confine their presentation only to other academics. Qualitative researchers who study particular contexts or cultures might want to report back to the people and places they observed. Those working in the critical tradition might want to raise awareness of a particular issue to as large an audience as possible. Many others simply want everyday, nonacademic people to read their work, because they think it is interesting and important. To reach a wide audience, the final product can look like almost anything—it can be a poem, a blog, a podcast, even a science fiction short story. And if you are very lucky, it can even be a national or international bestseller.

In this chapter, we are going to stick with the more basic quotidian presentations—the academic paper / research proposal, the conference slideshow presentation / job talk, and the conference poster. We’ll also spend a bit of time on incorporating universal design into your presentations and how to create some especially attractive and impactful visual displays.

Researcher Note

What is the best piece of advice you’ve ever been given about conducting qualitative research?

The best advice I’ve received came from my adviser, Alford Young Jr. He told me to find the “Jessi Streib” answer to my research question, not the “Pierre Bourdieu” answer to my research question. In other words, don’t just say how a famous theorist would answer your question; say something original, something coming from you.

—Jessi Streib, author of The Power of the Past and Privilege Lost 

Writing about Your Research

The journal article and the research proposal.

Although the research proposal is written before you have actually done your research and the article is written after all data collection and analysis is complete, there are actually many similarities between the two in terms of organization and purpose. The final article will (probably—depends on how much the research question and focus have shifted during the research itself) incorporate a great deal of what was included in a preliminary research proposal. The average lengths of both a proposal and an article are quite similar, with the “front sections” of the article abbreviated to make space for the findings, discussion of findings, and conclusion.

Figure 20.1 shows one model for what to include in an article or research proposal, comparing the elements of each with a default word count for each section. Please note that you will want to follow whatever specific guidelines you have been provided by the venue you are submitting the article/proposal to: the IRB, the NSF, the Journal of Qualitative Research . In fact, I encourage you to adapt the default model as needed by swapping out expected word counts for each section and adding or varying the sections to match expectations for your particular publication venue. [2]

You will notice a few things about the default model guidelines. First, while half of the proposal is spent discussing the research design, this section is shortened (but still included) for the article. There are a few elements that only show up in the proposal (e.g., the limitations section is in the introductory section here—it will be more fully developed in the conclusory section in the article). Obviously, you don’t have findings in the proposal, so this is an entirely new section for the article. Note that the article does not include a data management plan or a timeline—two aspects that most proposals require.

It might be helpful to find and maintain examples of successfully written sections that you can use as models for your own writing. I have included a few of these throughout the textbook and have included a few more at the end of this chapter.

Make an Argument

Some qualitative researchers, particularly those engaged in deep ethnographic research, focus their attention primarily if not exclusively on describing the data. They might even eschew the notion that they should make an “argument” about the data, preferring instead to use thick descriptions to convey interpretations. Bracketing the contrast between interpretation and argument for the moment, most readers will expect you to provide an argument about your data, and this argument will be in answer to whatever research question you eventually articulate (remember, research questions are allowed to shift as you get further into data collection and analysis). It can be frustrating to read a well-developed study with clear and elegant descriptions and no argument. The argument is the point of the research, and if you do not have one, 99 percent of the time, you are not finished with your analysis. Calarco ( 2020 ) suggests you imagine a pyramid, with all of your data forming the basis and all of your findings forming the middle section; the top/point of the pyramid is your argument, “what the patterns in your data tell us about how the world works or ought to work” ( 181 ).

The academic community to which you belong will be looking for an argument that relates to or develops theory. This is the theoretical generalizability promise of qualitative research. An academic audience will want to know how your findings relate to previous findings, theories, and concepts (the literature review; see chapter 9). It is thus vitally important that you go back to your literature review (or develop a new one) and draw those connections in your discussion and/or conclusion. When writing to other audiences, you will still want an argument, although it may not be written as a theoretical one. What do I mean by that? Even if you are not referring to previous literature or developing new theories or adapting older ones, a simple description of your findings is like dumping a lot of leaves in the lap of your audience. They still deserve to know about the shape of the forest. Maybe provide them a road map through it. Do this by telling a clear and cogent story about the data. What is the primary theme, and why is it important? What is the point of your research? [3]

A beautifully written piece of research based on participant observation [and/or] interviews brings people to life, and helps the reader understand the challenges people face. You are trying to use vivid, detailed and compelling words to help the reader really understand the lives of the people you studied. And you are trying to connect the lived experiences of these people to a broader conceptual point—so that the reader can understand why it matters. ( Lareau 2021:259 )

Do not hide your argument. Make it the focal point of your introductory section, and repeat it as often as needed to ensure the reader remembers it. I am always impressed when I see researchers do this well (see, e.g., Zelizer 1996 ).

Here are a few other suggestions for writing your article: Be brief. Do not overwhelm the reader with too many words; make every word count. Academics are particularly prone to “overwriting” as a way of demonstrating proficiency. Don’t. When writing your methods section, think about it as a “recipe for your work” that allows other researchers to replicate if they so wish ( Calarco 2020:186 ). Convey all the necessary information clearly, succinctly, and accurately. No more, no less. [4] Do not try to write from “beginning to end” in that order. Certain sections, like the introductory section, may be the last ones you write. I find the methods section the easiest, so I often begin there. Calarco ( 2020 ) begins with an outline of the analysis and results section and then works backward from there to outline the contribution she is making, then the full introduction that serves as a road map for the writing of all sections. She leaves the abstract for the very end. Find what order best works for you.

Presenting at Conferences and Job Talks

Students and faculty are primarily called upon to publicly present their research in two distinct contexts—the academic conference and the “job talk.” By convention, conference presentations usually run about fifteen minutes and, at least in sociology and other social sciences, rely primarily on the use of a slideshow (PowerPoint Presentation or PPT) presentation. You are usually one of three or four presenters scheduled on the same “panel,” so it is an important point of etiquette to ensure that your presentation falls within the allotted time and does not crowd into that of the other presenters. Job talks, on the other hand, conventionally require a forty- to forty-five-minute presentation with a fifteen- to twenty-minute question and answer (Q&A) session following it. You are the only person presenting, so if you run over your allotted time, it means less time for the Q&A, which can disturb some audience members who have been waiting for a chance to ask you something. It is sometimes possible to incorporate questions during your presentation, which allows you to take the entire hour, but you might end up shorting your presentation this way if the questions are numerous. It’s best for beginners to stick to the “ask me at the end” format (unless there is a simple clarifying question that can easily be addressed and makes the presentation run more smoothly, as in the case where you simply forgot to include information on the number of interviews you conducted).

For slideshows, you should allot two or even three minutes for each slide, never less than one minute. And those slides should be clear, concise, and limited. Most of what you say should not be on those slides at all. The slides are simply the main points or a clear image of what you are speaking about. Include bulleted points (words, short phrases), not full sentences. The exception is illustrative quotations from transcripts or fieldnotes. In those cases, keep to one illustrative quote per slide, and if it is long, bold or otherwise, highlight the words or passages that are most important for the audience to notice. [5]

Figure 20.2 provides a possible model for sections to include in either a conference presentation or a job talk, with approximate times and approximate numbers of slides. Note the importance (in amount of time spent) of both the research design and the findings/results sections, both of which have been helpfully starred for you. Although you don’t want to short any of the sections, these two sections are the heart of your presentation.

Fig 20.2. Suggested Slideshow Times and Number of Slides

Should you write out your script to read along with your presentation? I have seen this work well, as it prevents presenters from straying off topic and keeps them to the time allotted. On the other hand, these presentations can seem stiff and wooden. Personally, although I have a general script in advance, I like to speak a little more informally and engagingly with each slide, sometimes making connections with previous panelists if I am at a conference. This means I have to pay attention to the time, and I sometimes end up breezing through one section more quickly than I would like. Whatever approach you take, practice in advance. Many times. With an audience. Ask for feedback, and pay attention to any presentation issues that arise (e.g., Do you speak too fast? Are you hard to hear? Do you stumble over a particular word or name?).

Even though there are rules and guidelines for what to include, you will still want to make your presentation as engaging as possible in the little amount of time you have. Calarco ( 2020:274 ) recommends trying one of three story structures to frame your presentation: (1) the uncertain explanation , where you introduce a phenomenon that has not yet been fully explained and then describe how your research is tackling this; (2) the uncertain outcome , where you introduce a phenomenon where the consequences have been unclear and then you reveal those consequences with your research; and (3) the evocative example , where you start with some interesting example from your research (a quote from the interview transcripts, for example) or the real world and then explain how that example illustrates the larger patterns you found in your research. Notice that each of these is a framing story. Framing stories are essential regardless of format!

A Word on Universal Design

Please consider accessibility issues during your presentation, and incorporate elements of universal design into your slideshow. The basic idea behind universal design in presentations is that to the greatest extent possible, all people should be able to view, hear, or otherwise take in your presentation without needing special individual adaptations. If you can make your presentation accessible to people with visual impairment or hearing loss, why not do so? For example, one in twelve men is color-blind, unable to differentiate between certain colors, red/green being the most common problem. So if you design a graphic that relies on red and green bars, some of your audience members may not be able to properly identify which bar means what. Simple contrasts of black and white are much more likely to be visible to all members of your audience. There are many other elements of good universal design, but the basic foundation of all of them is that you consider how to make your presentation as accessible as possible at the outset. For example, include captions whenever possible, both as descriptions on slides and as images on slides and for any audio or video clips you are including; keep font sizes large enough to read from the back of the room; and face the audience when you are.

Poster Design

Undergraduate students who present at conferences are often encouraged to present at “poster sessions.” This usually means setting up a poster version of your research in a large hall or convention space at a set period of time—ninety minutes is common. Your poster will be one of dozens, and conference-goers will wander through the space, stopping intermittently at posters that attract them. Those who stop by might ask you questions about your research, and you are expected to be able to talk intelligently for two or three minutes. It’s a fairly easy way to practice presenting at conferences, which is why so many organizations hold these special poster sessions.

A good poster design will be immediately attractive to passersby and clearly and succinctly describe your research methods, findings, and conclusions. Some students have simply shrunk down their research papers to manageable sizes and then pasted them on a poster, all twelve to fifteen pages of them. Don’t do that! Here are some better suggestions: State the main conclusion of your research in large bold print at the top of your poster, on brightly colored (contrasting) paper, and paste in a QR code that links to your full paper online ( Calarco 2020:280 ). Use the rest of the poster board to provide a couple of highlights and details of the study. For an interview-based study, for example, you will want to put in some details about your sample (including number of interviews) and setting and then perhaps one or two key quotes, also distinguished by contrasting color background.

Incorporating Visual Design in Your Presentations

In addition to ensuring that your presentation is accessible to as large an audience as possible, you also want to think about how to display your data in general, particularly how to use charts and graphs and figures. [6] The first piece of advice is, use them! As the saying goes, a picture is worth a thousand words. If you can cut to the chase with a visually stunning display, do so. But there are visual displays that are stunning, and then there are the tired, hard-to-see visual displays that predominate at conferences. You can do better than most presenters by simply paying attention here and committing yourself to a good design. As with model section passages, keep a file of visual displays that work as models for your own presentations. Find a good guidebook to presenting data effectively (Evergreen 2018 , 2019 ; Schwabisch 2021) , and refer to it often.

Let me make a few suggestions here to get you started. First, test every visual display on a friend or colleague to find out how quickly they can understand the point you are trying to convey. As with reading passages aloud to ensure that your writing works, showing someone your display is the quickest way to find out if it works. Second, put the point in the title of the display! When writing for an academic journal, there will be specific conventions of what to include in the title (full description including methods of analysis, sample, dates), but in a public presentation, there are no limiting rules. So you are free to write as your title “Working-Class College Students Are Three Times as Likely as Their Peers to Drop Out of College,” if that is the point of the graphic display. It certainly helps the communicative aspect. Third, use the themes available to you in Excel for creating graphic displays, but alter them to better fit your needs . Consider adding dark borders to bars and columns, for example, so that they appear crisper for your audience. Include data callouts and labels, and enlarge them so they are clearly visible. When duplicative or otherwise unnecessary, drop distracting gridlines and labels on the y-axis (the vertical one). Don’t go crazy adding different fonts, however—keep things simple and clear. Sans serif fonts (those without the little hooks on the ends of letters) read better from a distance. Try to use the same color scheme throughout, even if this means manually changing the colors of bars and columns. For example, when reporting on working-class college students, I use blue bars, while I reserve green bars for wealthy students and yellow bars for students in the middle. I repeat these colors throughout my presentations and incorporate different colors when talking about other items or factors. You can also try using simple grayscale throughout, with pops of color to indicate a bar or column or line that is of the most interest. These are just some suggestions. The point is to take presentation seriously and to pay attention to visual displays you are using to ensure they effectively communicate what you want them to communicate. I’ve included a data visualization checklist from Evergreen ( 2018 ) here.

Ethics of Presentation and Reliability

Until now, all the data you have collected have been yours alone. Once you present the data, however, you are sharing sometimes very intimate information about people with a broader public. You will find yourself balancing between protecting the privacy of those you’ve interviewed and observed and needing to demonstrate the reliability of the study. The more information you provide to your audience, the more they can understand and appreciate what you have found, but this also may pose risks to your participants. There is no one correct way to go about finding the right balance. As always, you have a duty to consider what you are doing and must make some hard decisions.

The most obvious place we see this paradox emerge is when you mask your data to protect the privacy of your participants. It is standard practice to provide pseudonyms, for example. It is such standard practice that you should always assume you are being given a pseudonym when reading a book or article based on qualitative research. When I was a graduate student, I tried to find information on how best to construct pseudonyms but found little guidance. There are some ethical issues here, I think. [7] Do you create a name that has the same kind of resonance as the original name? If the person goes by a nickname, should you use a nickname as a pseudonym? What about names that are ethnically marked (as in, almost all of them)? Is there something unethical about reracializing a person? (Yes!) In her study of adolescent subcultures, Wilkins ( 2008 ) noted, “Because many of the goths used creative, alternative names rather than their given names, I did my best to reproduce the spirit of their chosen names” ( 24 ).

Your reader or audience will want to know all the details about your participants so that they can gauge both your credibility and the reliability of your findings. But how many details are too many? What if you change the name but otherwise retain all the personal pieces of information about where they grew up, and how old they were when they got married, and how many children they have, and whether they made a splash in the news cycle that time they were stalked by their ex-boyfriend? At some point, those details are going to tip over into the zone of potential unmasking. When you are doing research at one particular field site that may be easily ascertained (as when you interview college students, probably at the institution at which you are a student yourself), it is even more important to be wary of providing too many details. You also need to think that your participants might read what you have written, know things about the site or the population from which you drew your interviews, and figure out whom you are talking about. This can all get very messy if you don’t do more than simply pseudonymize the people you interviewed or observed.

There are some ways to do this. One, you can design a study with all of these risks in mind. That might mean choosing to conduct interviews or observations at multiple sites so that no one person can be easily identified. Another is to alter some basic details about your participants to protect their identity or to refuse to provide all the information when selecting quotes . Let’s say you have an interviewee named “Anna” (a pseudonym), and she is a twenty-four-year-old Latina studying to be an engineer. You want to use a quote from Anna about racial discrimination in her graduate program. Instead of attributing the quote to Anna (whom your reader knows, because you’ve already told them, is a twenty-four-year-old Latina studying engineering), you might simply attribute the quote to “Latina student in STEM.” Taking this a step further, you might leave the quote unattributed, providing a list of quotes about racial discrimination by “various students.”

The problem with masking all the identifiers, of course, is that you lose some of the analytical heft of those attributes. If it mattered that Anna was twenty-four (not thirty-four) and that she was a Latina and that she was studying engineering, taking out any of those aspects of her identity might weaken your analysis. This is one of those “hard choices” you will be called on to make! A rather radical and controversial solution to this dilemma is to create composite characters , characters based on the reality of the interviews but fully masked because they are not identifiable with any one person. My students are often very queasy about this when I explain it to them. The more positivistic your approach and the more you see individuals rather than social relationships/structure as the “object” of your study, the more employing composites will seem like a really bad idea. But composites “allow researchers to present complex, situated accounts from individuals” without disclosing personal identities ( Willis 2019 ), and they can be effective ways of presenting theory narratively ( Hurst 2019 ). Ironically, composites permit you more latitude when including “dirty laundry” or stories that could harm individuals if their identities became known. Rather than squeezing out details that could identify a participant, the identities are permanently removed from the details. Great difficulty remains, however, in clearly explaining the theoretical use of composites to your audience and providing sufficient information on the reliability of the underlying data.

There are a host of other ethical issues that emerge as you write and present your data. This is where being reflective throughout the process will help. How and what you share of what you have learned will depend on the social relationships you have built, the audiences you are writing or speaking to, and the underlying animating goals of your study. Be conscious about all of your decisions, and then be able to explain them fully, both to yourself and to those who ask.

Our research is often close to us. As a Black woman who is a first-generation college student and a professional with a poverty/working-class origin, each of these pieces of my identity creates nuances in how I engage in my research, including how I share it out. Because of this, it’s important for us to have people in our lives who we trust who can help us, particularly, when we are trying to share our findings. As researchers, we have been steeped in our work, so we know all the details and nuances. Sometimes we take this for granted, and we might not have shared those nuances in conversation or writing or taken some of this information for granted. As I share my research with trusted friends and colleagues, I pay attention to the questions they ask me or the feedback they give when we talk or when they read drafts.

—Kim McAloney, PhD, College Student Services Administration Ecampus coordinator and instructor

Final Comments: Preparing for Being Challenged

Once you put your work out there, you must be ready to be challenged. Science is a collective enterprise and depends on a healthy give and take among researchers. This can be both novel and difficult as you get started, but the more you understand the importance of these challenges, the easier it will be to develop the kind of thick skin necessary for success in academia. Scientists’ authority rests on both the inherent strength of their findings and their ability to convince other scientists of the reliability and validity and value of those findings. So be prepared to be challenged, and recognize this as simply another important aspect of conducting research!

Considering what challenges might be made as you design and conduct your study will help you when you get to the writing and presentation stage. Address probable challenges in your final article, and have a planned response to probable questions in a conference presentation or job talk. The following is a list of common challenges of qualitative research and how you might best address them:

• Questions about generalizability . Although qualitative research is not statistically generalizable (and be prepared to explain why), qualitative research is theoretically generalizable. Discuss why your findings here might tell us something about related phenomena or contexts.
• Questions about reliability . You probably took steps to ensure the reliability of your findings. Discuss them! This includes explaining the use and value of multiple data sources and defending your sampling and case selections. It also means being transparent about your own position as researcher and explaining steps you took to ensure that what you were seeing was really there.
• Questions about replicability. Although qualitative research cannot strictly be replicated because the circumstances and contexts will necessarily be different (if only because the point in time is different), you should be able to provide as much detail as possible about how the study was conducted so that another researcher could attempt to confirm or disconfirm your findings. Also, be very clear about the limitations of your study, as this allows other researchers insight into what future research might be warranted.

None of this is easy, of course. Writing beautifully and presenting clearly and cogently require skill and practice. If you take anything from this chapter, it is to remember that presentation is an important and essential part of the research process and to allocate time for this as you plan your research.

Data Visualization Checklist for Slideshow (PPT) Presentations

Adapted from Evergreen ( 2018 )

Text checklist

• Short catchy, descriptive titles (e.g., “Working-class students are three times as likely to drop out of college”) summarize the point of the visual display
• Subtitled and annotations provide additional information (e.g., “note: male students also more likely to drop out”)
• Text size is hierarchical and readable (titles are largest; axes labels smallest, which should be at least 20points)
• Text is horizontal. Audience members cannot read vertical text!
• All data labeled directly and clearly: get rid of those “legends” and embed the data in your graphic display
• Labels are used sparingly; avoid redundancy (e.g., do not include both a number axis and a number label)

Arrangement checklist

• Proportions are accurate; bar charts should always start at zero; don’t mislead the audience!
• Data are intentionally ordered (e.g., by frequency counts). Do not leave ragged alphabetized bar graphs!
• Axis intervals are equidistant: spaces between axis intervals should be the same unit
• Graph is two-dimensional. Three-dimensional and “bevelled” displays are confusing
• There is no unwanted decoration (especially the kind that comes automatically through the PPT “theme”). This wastes your space and confuses.

Color checklist

• There is an intentional color scheme (do not use default theme)
• Color is used to identify key patterns (e.g., highlight one bar in red against six others in greyscale if this is the bar you want the audience to notice)
• Color is still legible when printed in black and white
• Color is legible for people with color blindness (do not use red/green or yellow/blue combinations)
• There is sufficient contrast between text and background (black text on white background works best; be careful of white on dark!)

Lines checklist

• Be wary of using gridlines; if you do, mute them (grey, not black)
• Allow graph to bleed into surroundings (don’t use border lines)
• Remove axis lines unless absolutely necessary (better to label directly)

Overall design checklist

• The display highlights a significant finding or conclusion that your audience can ‘”see” relatively quickly
• The type of graph (e.g., bar chart, pie chart, line graph) is appropriate for the data. Avoid pie charts with more than three slices!
• Graph has appropriate level of precision; if you don’t need decimal places
• All the chart elements work together to reinforce the main message

Universal Design Checklist for Slideshow (PPT) Presentations

• Include both verbal and written descriptions (e.g., captions on slides); consider providing a hand-out to accompany the presentation
• Microphone available (ask audience in back if they can clearly hear)
• Face audience; allow people to read your lips
• Turn on captions when presenting audio or video clips
• Adjust light settings for visibility
• Speak slowly and clearly; practice articulation; don’t mutter or speak under your breath (even if you have something humorous to say – say it loud!)
• Use Black/White contrasts for easy visibility; or use color contrasts that are real contrasts (do not rely on people being able to differentiate red from green, for example)
• Use easy to read font styles and avoid too small font sizes: think about what an audience member in the back row will be able to see and read.
• Keep your slides simple: do not overclutter them; if you are including quotes from your interviews, take short evocative snippets only, and bold key words and passages. You should also read aloud each passage, preferably with feeling!

Supplement: Models of Written Sections for Future Reference

Data collection section example.

Interviews were semi structured, lasted between one and three hours, and took place at a location chosen by the interviewee. Discussions centered on four general topics: (1) knowledge of their parent’s immigration experiences; (2) relationship with their parents; (3) understanding of family labor, including language-brokering experiences; and (4) experiences with school and peers, including any future life plans. While conducting interviews, I paid close attention to respondents’ nonverbal cues, as well as their use of metaphors and jokes. I conducted interviews until I reached a point of saturation, as indicated by encountering repeated themes in new interviews (Glaser and Strauss 1967). Interviews were audio recorded, transcribed with each interviewee’s permission, and conducted in accordance with IRB protocols. Minors received permission from their parents before participation in the interview. ( Kwon 2022:1832 )

Justification of Case Selection / Sample Description Section Example

Looking at one profession within one organization and in one geographic area does impose limitations on the generalizability of our findings. However, it also has advantages. We eliminate the problem of interorganizational heterogeneity. If multiple organizations are studied simultaneously, it can make it difficult to discern the mechanisms that contribute to racial inequalities. Even with a single occupation there is considerable heterogeneity, which may make understanding how organizational structure impacts worker outcomes difficult. By using the case of one group of professionals in one religious denomination in one geographic region of the United States, we clarify how individuals’ perceptions and experiences of occupational inequality unfold in relation to a variety of observed and unobserved occupational and contextual factors that might be obscured in a larger-scale study. Focusing on a specific group of professionals allows us to explore and identify ways that formal organizational rules combine with informal processes to contribute to the persistence of racial inequality. ( Eagle and Mueller 2022:1510–1511 )

Ethics Section Example

I asked everyone who was willing to sit for a formal interview to speak only for themselves and offered each of them a prepaid Visa Card worth $25–40. I also offered everyone the opportunity to keep the card and erase the tape completely at any time they were dissatisfied with the interview in any way. No one asked for the tape to be erased; rather, people remarked on the interview being a really good experience because they felt heard. Each interview was professionally transcribed and for the most part the excerpts are literal transcriptions. In a few places, the excerpts have been edited to reduce colloquial features of speech (e.g., you know, like, um) and some recursive elements common to spoken language. A few excerpts were placed into standard English for clarity. I made this choice for the benefit of readers who might otherwise find the insights and ideas harder to parse in the original. However, I have to acknowledge this as an act of class-based violence. I tried to keep the original phrasing whenever possible. ( Pascale 2021:235 )

Further Readings

Calarco, Jessica McCrory. 2020. A Field Guide to Grad School: Uncovering the Hidden Curriculum . Princeton, NJ: Princeton University Press. Don’t let the unassuming title mislead you—there is a wealth of helpful information on writing and presenting data included here in a highly accessible manner. Every graduate student should have a copy of this book.

Edwards, Mark. 2012. Writing in Sociology . Thousand Oaks, CA: SAGE. An excellent guide to writing and presenting sociological research by an Oregon State University professor. Geared toward undergraduates and useful for writing about either quantitative or qualitative research or both.

Evergreen, Stephanie D. H. 2018. Presenting Data Effectively: Communicating Your Findings for Maximum Impact . Thousand Oaks, CA: SAGE. This is one of my very favorite books, and I recommend it highly for everyone who wants their presentations and publications to communicate more effectively than the boring black-and-white, ragged-edge tables and figures academics are used to seeing.

Evergreen, Stephanie D. H. 2019. Effective Data Visualization 2 . Thousand Oaks, CA: SAGE. This is an advanced primer for presenting clean and clear data using graphs, tables, color, font, and so on. Start with Evergreen (2018), and if you graduate from that text, move on to this one.

Schwabisch, Jonathan. 2021. Better Data Visualizations: A Guide for Scholars, Researchers, and Wonks . New York: Columbia University Press. Where Evergreen’s (2018, 2019) focus is on how to make the best visual displays possible for effective communication, this book is specifically geared toward visual displays of academic data, both quantitative and qualitative. If you want to know when it is appropriate to use a pie chart instead of a stacked bar chart, this is the reference to use.

• Some examples: Qualitative Inquiry , Qualitative Research , American Journal of Qualitative Research , Ethnography , Journal of Ethnographic and Qualitative Research , Qualitative Report , Qualitative Sociology , and Qualitative Studies . ↵
• This is something I do with every article I write: using Excel, I write each element of the expected article in a separate row, with one column for “expected word count” and another column for “actual word count.” I fill in the actual word count as I write. I add a third column for “comments to myself”—how things are progressing, what I still need to do, and so on. I then use the “sum” function below each of the first two columns to keep a running count of my progress relative to the final word count. ↵
• And this is true, I would argue, even when your primary goal is to leave space for the voices of those who don’t usually get a chance to be part of the conversation. You will still want to put those voices in some kind of choir, with a clear direction (song) to be sung. The worst thing you can do is overwhelm your audience with random quotes or long passages with no key to understanding them. Yes, a lot of metaphors—qualitative researchers love metaphors! ↵
• To take Calarco’s recipe analogy further, do not write like those food bloggers who spend more time discussing the color of their kitchen or the experiences they had at the market than they do the actual cooking; similarly, do not write recipes that omit crucial details like the amount of flour or the size of the baking pan used or the temperature of the oven. ↵
• The exception is the “compare and contrast” of two or more quotes, but use caution here. None of the quotes should be very long at all (a sentence or two each). ↵
• Although this section is geared toward presentations, many of the suggestions could also be useful when writing about your data. Don’t be afraid to use charts and graphs and figures when writing your proposal, article, thesis, or dissertation. At the very least, you should incorporate a tabular display of the participants, sites, or documents used. ↵
• I was so puzzled by these kinds of questions that I wrote one of my very first articles on it ( Hurst 2008 ). ↵

The visual presentation of data or information through graphics such as charts, graphs, plots, infographics, maps, and animation.  Recall the best documentary you ever viewed, and there were probably excellent examples of good data visualization there (for me, this was An Inconvenient Truth , Al Gore’s film about climate change).  Good data visualization allows more effective communication of findings of research, particularly in public presentations (e.g., slideshows).

Introduction to Qualitative Research Methods Copyright © 2023 by Allison Hurst is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License , except where otherwise noted.

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Research Findings – Types Examples and Writing Guide

Table of Contents

Research Findings

Definition:

Research findings refer to the results obtained from a study or investigation conducted through a systematic and scientific approach. These findings are the outcomes of the data analysis, interpretation, and evaluation carried out during the research process.

Types of Research Findings

There are two main types of research findings:

Qualitative Findings

Qualitative research is an exploratory research method used to understand the complexities of human behavior and experiences. Qualitative findings are non-numerical and descriptive data that describe the meaning and interpretation of the data collected. Examples of qualitative findings include quotes from participants, themes that emerge from the data, and descriptions of experiences and phenomena.

Quantitative Findings

Quantitative research is a research method that uses numerical data and statistical analysis to measure and quantify a phenomenon or behavior. Quantitative findings include numerical data such as mean, median, and mode, as well as statistical analyses such as t-tests, ANOVA, and regression analysis. These findings are often presented in tables, graphs, or charts.

Both qualitative and quantitative findings are important in research and can provide different insights into a research question or problem. Combining both types of findings can provide a more comprehensive understanding of a phenomenon and improve the validity and reliability of research results.

Parts of Research Findings

Research findings typically consist of several parts, including:

• Introduction: This section provides an overview of the research topic and the purpose of the study.
• Literature Review: This section summarizes previous research studies and findings that are relevant to the current study.
• Methodology : This section describes the research design, methods, and procedures used in the study, including details on the sample, data collection, and data analysis.
• Results : This section presents the findings of the study, including statistical analyses and data visualizations.
• Discussion : This section interprets the results and explains what they mean in relation to the research question(s) and hypotheses. It may also compare and contrast the current findings with previous research studies and explore any implications or limitations of the study.
• Conclusion : This section provides a summary of the key findings and the main conclusions of the study.
• Recommendations: This section suggests areas for further research and potential applications or implications of the study’s findings.

How to Write Research Findings

Writing research findings requires careful planning and attention to detail. Here are some general steps to follow when writing research findings:

• Organize your findings: Before you begin writing, it’s essential to organize your findings logically. Consider creating an outline or a flowchart that outlines the main points you want to make and how they relate to one another.
• Use clear and concise language : When presenting your findings, be sure to use clear and concise language that is easy to understand. Avoid using jargon or technical terms unless they are necessary to convey your meaning.
• Use visual aids : Visual aids such as tables, charts, and graphs can be helpful in presenting your findings. Be sure to label and title your visual aids clearly, and make sure they are easy to read.
• Use headings and subheadings: Using headings and subheadings can help organize your findings and make them easier to read. Make sure your headings and subheadings are clear and descriptive.
• Interpret your findings : When presenting your findings, it’s important to provide some interpretation of what the results mean. This can include discussing how your findings relate to the existing literature, identifying any limitations of your study, and suggesting areas for future research.
• Be precise and accurate : When presenting your findings, be sure to use precise and accurate language. Avoid making generalizations or overstatements and be careful not to misrepresent your data.
• Edit and revise: Once you have written your research findings, be sure to edit and revise them carefully. Check for grammar and spelling errors, make sure your formatting is consistent, and ensure that your writing is clear and concise.

Research Findings Example

Following is a Research Findings Example sample for students:

Title: The Effects of Exercise on Mental Health

Sample : 500 participants, both men and women, between the ages of 18-45.

Methodology : Participants were divided into two groups. The first group engaged in 30 minutes of moderate intensity exercise five times a week for eight weeks. The second group did not exercise during the study period. Participants in both groups completed a questionnaire that assessed their mental health before and after the study period.

Findings : The group that engaged in regular exercise reported a significant improvement in mental health compared to the control group. Specifically, they reported lower levels of anxiety and depression, improved mood, and increased self-esteem.

Conclusion : Regular exercise can have a positive impact on mental health and may be an effective intervention for individuals experiencing symptoms of anxiety or depression.

Applications of Research Findings

Research findings can be applied in various fields to improve processes, products, services, and outcomes. Here are some examples:

• Healthcare : Research findings in medicine and healthcare can be applied to improve patient outcomes, reduce morbidity and mortality rates, and develop new treatments for various diseases.
• Education : Research findings in education can be used to develop effective teaching methods, improve learning outcomes, and design new educational programs.
• Technology : Research findings in technology can be applied to develop new products, improve existing products, and enhance user experiences.
• Business : Research findings in business can be applied to develop new strategies, improve operations, and increase profitability.
• Public Policy: Research findings can be used to inform public policy decisions on issues such as environmental protection, social welfare, and economic development.
• Social Sciences: Research findings in social sciences can be used to improve understanding of human behavior and social phenomena, inform public policy decisions, and develop interventions to address social issues.
• Agriculture: Research findings in agriculture can be applied to improve crop yields, develop new farming techniques, and enhance food security.
• Sports : Research findings in sports can be applied to improve athlete performance, reduce injuries, and develop new training programs.

When to use Research Findings

Research findings can be used in a variety of situations, depending on the context and the purpose. Here are some examples of when research findings may be useful:

• Decision-making : Research findings can be used to inform decisions in various fields, such as business, education, healthcare, and public policy. For example, a business may use market research findings to make decisions about new product development or marketing strategies.
• Problem-solving : Research findings can be used to solve problems or challenges in various fields, such as healthcare, engineering, and social sciences. For example, medical researchers may use findings from clinical trials to develop new treatments for diseases.
• Policy development : Research findings can be used to inform the development of policies in various fields, such as environmental protection, social welfare, and economic development. For example, policymakers may use research findings to develop policies aimed at reducing greenhouse gas emissions.
• Program evaluation: Research findings can be used to evaluate the effectiveness of programs or interventions in various fields, such as education, healthcare, and social services. For example, educational researchers may use findings from evaluations of educational programs to improve teaching and learning outcomes.
• Innovation: Research findings can be used to inspire or guide innovation in various fields, such as technology and engineering. For example, engineers may use research findings on materials science to develop new and innovative products.

Purpose of Research Findings

The purpose of research findings is to contribute to the knowledge and understanding of a particular topic or issue. Research findings are the result of a systematic and rigorous investigation of a research question or hypothesis, using appropriate research methods and techniques.

The main purposes of research findings are:

• To generate new knowledge : Research findings contribute to the body of knowledge on a particular topic, by adding new information, insights, and understanding to the existing knowledge base.
• To test hypotheses or theories : Research findings can be used to test hypotheses or theories that have been proposed in a particular field or discipline. This helps to determine the validity and reliability of the hypotheses or theories, and to refine or develop new ones.
• To inform practice: Research findings can be used to inform practice in various fields, such as healthcare, education, and business. By identifying best practices and evidence-based interventions, research findings can help practitioners to make informed decisions and improve outcomes.
• To identify gaps in knowledge: Research findings can help to identify gaps in knowledge and understanding of a particular topic, which can then be addressed by further research.
• To contribute to policy development: Research findings can be used to inform policy development in various fields, such as environmental protection, social welfare, and economic development. By providing evidence-based recommendations, research findings can help policymakers to develop effective policies that address societal challenges.

Characteristics of Research Findings

Research findings have several key characteristics that distinguish them from other types of information or knowledge. Here are some of the main characteristics of research findings:

• Objective : Research findings are based on a systematic and rigorous investigation of a research question or hypothesis, using appropriate research methods and techniques. As such, they are generally considered to be more objective and reliable than other types of information.
• Empirical : Research findings are based on empirical evidence, which means that they are derived from observations or measurements of the real world. This gives them a high degree of credibility and validity.
• Generalizable : Research findings are often intended to be generalizable to a larger population or context beyond the specific study. This means that the findings can be applied to other situations or populations with similar characteristics.
• Transparent : Research findings are typically reported in a transparent manner, with a clear description of the research methods and data analysis techniques used. This allows others to assess the credibility and reliability of the findings.
• Peer-reviewed: Research findings are often subject to a rigorous peer-review process, in which experts in the field review the research methods, data analysis, and conclusions of the study. This helps to ensure the validity and reliability of the findings.
• Reproducible : Research findings are often designed to be reproducible, meaning that other researchers can replicate the study using the same methods and obtain similar results. This helps to ensure the validity and reliability of the findings.

Advantages of Research Findings

Research findings have many advantages, which make them valuable sources of knowledge and information. Here are some of the main advantages of research findings:

• Evidence-based: Research findings are based on empirical evidence, which means that they are grounded in data and observations from the real world. This makes them a reliable and credible source of information.
• Inform decision-making: Research findings can be used to inform decision-making in various fields, such as healthcare, education, and business. By identifying best practices and evidence-based interventions, research findings can help practitioners and policymakers to make informed decisions and improve outcomes.
• Identify gaps in knowledge: Research findings can help to identify gaps in knowledge and understanding of a particular topic, which can then be addressed by further research. This contributes to the ongoing development of knowledge in various fields.
• Improve outcomes : Research findings can be used to develop and implement evidence-based practices and interventions, which have been shown to improve outcomes in various fields, such as healthcare, education, and social services.
• Foster innovation: Research findings can inspire or guide innovation in various fields, such as technology and engineering. By providing new information and understanding of a particular topic, research findings can stimulate new ideas and approaches to problem-solving.
• Enhance credibility: Research findings are generally considered to be more credible and reliable than other types of information, as they are based on rigorous research methods and are subject to peer-review processes.

Limitations of Research Findings

While research findings have many advantages, they also have some limitations. Here are some of the main limitations of research findings:

• Limited scope: Research findings are typically based on a particular study or set of studies, which may have a limited scope or focus. This means that they may not be applicable to other contexts or populations.
• Potential for bias : Research findings can be influenced by various sources of bias, such as researcher bias, selection bias, or measurement bias. This can affect the validity and reliability of the findings.
• Ethical considerations: Research findings can raise ethical considerations, particularly in studies involving human subjects. Researchers must ensure that their studies are conducted in an ethical and responsible manner, with appropriate measures to protect the welfare and privacy of participants.
• Time and resource constraints : Research studies can be time-consuming and require significant resources, which can limit the number and scope of studies that are conducted. This can lead to gaps in knowledge or a lack of research on certain topics.
• Complexity: Some research findings can be complex and difficult to interpret, particularly in fields such as science or medicine. This can make it challenging for practitioners and policymakers to apply the findings to their work.
• Lack of generalizability : While research findings are intended to be generalizable to larger populations or contexts, there may be factors that limit their generalizability. For example, cultural or environmental factors may influence how a particular intervention or treatment works in different populations or contexts.

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• 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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Presenting and Evaluating Qualitative Research

• Claire Anderson, PhD, BPharm Claire Anderson Correspondence Corresponding Author: Claire Anderson, University of Nottingham, Nottingham, United Kingdom, Phone: +44 115-951-5389. Contact Affiliations Univeristy of Nottingham, Nottingham United Kingdom Search for articles by this author
• qualitative research
• research papers
• American Journal of Pharmaceutical Education

INTRODUCTION

Murphy E, Dingwall R, Greatbatch D, Parker S, Watson P. Qualitative research methods in health technology assessment: a review of the literature. Health Technology Assessment 1998; Vol. 2: No. 16. http://www.ncchta.org/fullmono/mon216.pdf Accessed August 31, 2010.

• Google Scholar
• Scopus (55)
• Creswell J.W.
• Plano Clark V.L.
• Scopus (4489)
• Farris K.B.
• Scopus (16)
• • 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

Strengths and limitations of qualitative research, 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

Data from an interview., data from observations.

• Silverman J.
• Scopus (321)

Greenhill N. An Exploration of Pharmacist-Patient Communication in Clinic-Style Consultations [doctoral thesis]. University of Nottingham, England; October 2010.

Data From Focus Groups

• Glover N.M.

GUIDANCE FOR PUBLISHING QUALITATIVE RESEARCH

Qualitative research. British Medical Journal Web site. http://resources.bmj.com/bmj/authors/checklists-forms/qualitative-research . Accessed August 31, 2010.

Qualitative research review guidelines – RATS. BioMed Central. http://www.biomedcentral.com/info/ifora/rats Accessed August 31, 2010.

• Scopus (27)

Introduction.

Data analysis., discussion., conclusion., checklist for qualitative papers, acknowledgements, appendix 1. checklist for authors and reviewers of qualitative research..

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Identification.

DOI: https://doi.org/10.5688/aj7408141

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• Published: 26 April 2008

Analysing and presenting qualitative data

• P. Burnard 1 ,
• P. Gill 2 ,
• K. Stewart 3 ,
• E. Treasure 4 &
• B. Chadwick 5  

British Dental Journal volume  204 ,  pages 429–432 ( 2008 ) Cite this article

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Analysing and presenting qualitative data is one of the most confusing aspects of qualitative research.

This paper provides a pragmatic approach using a form of thematic content analysis. Approaches to presenting qualitative data are also discussed.

The process of qualitative data analysis is labour intensive and time consuming. Those who are unsure about this approach should seek appropriate advice.

This paper provides a pragmatic approach to analysing qualitative data, using actual data from a qualitative dental public health study for demonstration purposes. The paper also critically explores how computers can be used to facilitate this process, the debate about the verification (validation) of qualitative analyses and how to write up and present qualitative research studies.

You have full access to this article via your institution.

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Introduction

Previous papers in this series have introduced readers to qualitative research and identified approaches to collecting qualitative data. However, for those new to this approach, one of the most bewildering aspects of qualitative research is, perhaps, how to analyse and present the data once it has been collected. This final paper therefore considers a method of analysing and presenting textual data gathered during qualitative work. boxed-text

Box 1: Qualitative research in dentistry

Qualitative research in dentistry

Methods of data collection in qualitative research: interviews and focus groups

Conducting qualitative interviews with school children in dental research

Approaches to analysing qualitative data

There are two fundamental approaches to analysing qualitative data (although each can be handled in a variety of different ways): the deductive approach and the inductive approach. 1 , 2 Deductive approaches involve using a structure or predetermined framework to analyse data. Essentially, the researcher imposes their own structure or theories on the data and then uses these to analyse the interview transcripts. 3

This approach is useful in studies where researchers are already aware of probable participant responses. For example, if a study explored patients' reasons for complaining about their dentist, the interview may explore common reasons for patients' complaints, such as trauma following treatment and communication problems. The data analysis would then consist of examining each interview to determine how many patients had complaints of each type and the extent to which complaints of each type co-occur. 3 However, while this approach is relatively quick and easy, it is inflexible and can potentially bias the whole analysis process as the coding framework has been decided in advance, which can severely limit theme and theory development.

Conversely, the inductive approach involves analysing data with little or no predetermined theory, structure or framework and uses the actual data itself to derive the structure of analysis. This approach is comprehensive and therefore time-consuming and is most suitable where little or nothing is known about the study phenomenon. Inductive analysis is the most common approach used to analyse qualitative data 2 and is, therefore, the focus of this paper.

Whilst a variety of inductive approaches to analysing qualitative data are available, the method of analysis described in this paper is that of thematic content analysis , and is, perhaps, the most common method of data analysis used in qualitative work. 4 , 5 This method arose out of the approach known as grounded theory, 6 although the method can be used in a range of other types of qualitative work, including ethnography and phenomenology (see the first paper in this series 7 for definitions). Indeed, the process of thematic content analysis is often very similar in all types of qualitative research, in that the process involves analysing transcripts, identifying themes within those data and gathering together examples of those themes from the text.

Data collection and data analysis

Interview transcripts, field notes and observations provide a descriptive account of the study, but they do not provide explanations. 4 It is the researcher who has to make sense of the data that have been collected by exploring and interpreting them.

Quantitative and qualitative research differ somewhat in their approach to data analysis. In quantitative research, data analysis often only occurs after all or much of data have been collected. However, in qualitative research, data analysis often begins during, or immediately after, the first data are collected, although this process continues and is modified throughout the study. Initial analysis of the data may also further inform subsequent data collection. For example, interview schedules may be slightly modified in light of emerging findings, where additional clarification may be required.

Computer software for data analysis

The method of analysis described in this paper involves managing the data 'by hand'. However, there are several computer-assisted qualitative data analysis software (CAQDAS) packages available that can be used to manage and help in the analysis of qualitative data. Common programmes include ATLAS. ti and NVivo. It should be noted, however, that such programs do not 'analyse' the data – that is the task of the researcher – they simply manage the data and make handling of them easier.

For example, computer packages can help to manage, sort and organise large volumes of qualitative data, store, annotate and retrieve text, locate words, phrases and segments of data, prepare diagrams and extract quotes. 8 However, whilst computer programmes can facilitate data analysis, making the process easier and, arguably, more flexible, accurate and comprehensive, they do not confirm or deny the scientific value or quality of qualitative research, as they are merely instruments, as good or as bad as the researcher using them.

Stages in the process

Regardless of whether data are analysed by hand or using computer software, the process of thematic content analysis is essentially the same, in that it involves identifying themes and categories that 'emerge from the data'. This involves discovering themes in the interview transcripts and attempting to verify, confirm and qualify them by searching through the data and repeating the process to identify further themes and categories. 4

In order to do this, once the interviews have been transcribed verbatim, the researcher reads each transcript and makes notes in the margins of words, theories or short phrases that sum up what is being said in the text. This is usually known as open coding. The aim, however, is to offer a summary statement or word for each element that is discussed in the transcript. The exception to this is when the respondent has clearly gone off track and begun to move away from the topic under discussion. Such deviations (as long as they really are deviations) can simply be uncoded. Such 'off the topic' material is sometimes known as 'dross'. 9

Table 1 is an example of the initial coding framework used in the data generated from an actual interview with a child in a qualitative dental public health study, exploring primary school children's understanding of food. 10

In the second stage, the researcher collects together all of the words and phrases from all of the interviews onto a clean set of pages. These can then be worked through and all duplications crossed out. This will have the effect of reducing the numbers of 'categories' quite considerably. 11 , 12 Using a section of the initial coding framework from the above study, 10 such a list of categories might read as follows:

Children's perception of food

Positive notions of food and their consequences

Negative notions of food and their consequences

Peer influence

Healthy/unhealthy foods

Effects of sweets and chocolates

Effects of 'junk food'

Food choices in school

Diet in childhood

Food preferences

Expected diet as a 'grown up'

Food choices and preferences of friendship groups

Effects of fizzy drinks

Perceptions of adult/child diets

The need to be 'healthy' as an adult.

Once this second, shorter list of categories has been compiled, the researcher goes a stage further and looks for overlapping or similar categories. Informed by the analytical and theoretical ideas developed during the research, these categories are further refined and reduced in number by grouping them together. 4 A list of several categories (perhaps up to a maximum of twelve) can then be compiled. If we consider the above example, we might eventually come up with the reduced list shown in Table 2 .

This reduced list forms the final category system that can be used to divide up all of the interviews. 12 The next stage is to allocate each of the categories its own coloured marking pen and then each transcript is worked through and data that fit under a particular category are marked with the according colour. Finally, all of the sections of data, under each of the categories (and thus assigned a particular colour) are cut out and pasted onto the A4 sheets. Subject dividers can then be labelled with each category label and the corresponding coloured snippets, on each of the pages, are filed in a lever arch file. What the researcher has achieved is an organised dataset, filed in one folder. It is from this folder that the report of the findings can be written.

As discussed earlier, computer programmes can be used to manage this process and may be particularly useful in qualitative studies with larger datasets. However, researchers wishing to use such software should first undertake appropriate training and should be aware that most programmes often do not abide by normal MS Windows conventions (eg, most interview transcripts have to be converted from MS Word into rich text format before they can be imported into the programme for analysis).

Verification

The analysis of qualitative data does, of course, involve interpreting the study findings. However, this process is arguably more subjective than the process normally associated with quantitative data analysis, since a common belief amongst social scientists is that a definitive, objective view of social reality does not exist. For example, some quantitative researchers claim that qualitative accounts cannot be held straightforwardly to represent the social world, thus different researchers may interpret the same data somewhat differently. 4 Consequently, this leads to the issue of the verifiability of qualitative data analysis.

There is, therefore, a debate as to whether qualitative researchers should have their analyses verified or validated by a third party. 13 , 14 It has been argued that this process can make the analysis more rigorous and reduce the element bias. There are two key ways of having data analyses validated by others: respondent validation (or member check) – returning to the study participants and asking them to validate analyses – and peer review (or peer debrief, also referred to as inter-rater reliability) – whereby another qualitative researcher analyses the data independently. 13 , 14 , 15

Participant validation involves returning to respondents and asking them to carefully read through their interview transcripts and/or data analysis for them to validate, or refute, the researcher's interpretation of the data. Whilst this can arguably help to refine theme and theory development, the process is hugely time consuming and, if it does not occur relatively soon after data collection and analysis, participants may have also changed their perceptions and views because of temporal effects and potential changes in their situation, health, and perhaps even as a result of participation in the study. 15

Some respondents may also want to modify their opinions on re-presentation of the data if they now feel that, on reflection, their original comments are not 'socially desirable'. There is also the problem of how to present such information to people who are likely to be non-academics. Furthermore, it is possible that some participants will not recognise some of the emerging theories, as each of them will probably have contributed only a portion of the data. 16

The process of peer review involves at least one other suitably experienced researcher independently reviewing and exploring interview transcripts, data analysis and emerging themes. It has been argued that this process may help to guard against the potential for lone researcher bias and help to provide additional insights into theme and theory development. 14 , 16 , 17 However, many researchers also feel that the value of this approach is questionable, since it is possible that each researcher may interpret the data, or parts of it, differently. 8 Also, if both perspectives are grounded in and supported by the data, is one interpretation necessarily stronger or more valid than the other?

Unfortunately, despite perpetual debate, there is no definitive answer to the issue of validity in qualitative analysis. However, to ensure that the analysis process is systematic and rigorous, the whole corpus of collected data must be thoroughly analysed. Therefore, where appropriate, this should also include the search for and identification of relevant 'deviant or contrary cases' – ie, findings that are different or contrary to the main findings, or are simply unique to some or even just one respondent. Qualitative researchers should also utilise a process of 'constant comparison' when analysing data. This essentially involves reading and re-reading data to search for and identify emerging themes in the constant search for understanding and the meaning of the data. 18 , 19 Where appropriate, researchers should also provide a detailed explication in published reports of how data was collected and analysed, as this helps the reader to critically assess the value of the study.

It should also be noted that qualitative data cannot be usefully quantified given the nature, composition and size of the sample group, and ultimately the epistemological aim of the methodology.

Writing and presenting qualitative research

There are two main approaches to writing up the findings of qualitative research. 20 The first is to simply report key findings under each main theme or category, using appropriate verbatim quotes to illustrate those findings. This is then accompanied by a linking, separate discussion chapter in which the findings are discussed in relation to existing research (as in quantitative studies). The second is to do the same but to incorporate the discussion into the findings chapter. Below are brief examples of the two approaches, using actual data from a qualitative dental public health study that explored primary school children's understanding of food. 10

Example a (the traditional approach):

Contrasts and contradictions

The interviews demonstrated that children are able to operate contrasts and contradictions about food effortlessly. These contradictions are both sophisticated and complex, incorporating positive and negative notions relating to food and its health and social consequences, which they are able to fluently adopt when talking about food:

'My mother says drink juice because it's healthy and she says if you don't drink it you won't get healthy and you won't have any sweets and you'll end up having to go to hospital if you don't eat anything like vegetables because you'll get weak' . (Girl, school 3, age 11 years).

If this approach was used, the findings chapter would subsequently be followed by a separate supporting discussion and conclusion section in which the findings would be critically discussed and compared to the appropriate existing research. As in quantitative research, these supporting chapters would also be used to develop theories or hypothesise about the data and, if appropriate, to make realistic conclusions and recommendations for practice and further research.

Example b (combined findings and discussion chapter):

Copying friends

In this study, as with others (eg Ludvigsen & Sharma 21 and Watt & Sheiham 22 ), peer influence is a strong factor, with children copying each other's food choices at school meal times:

Girl: 'They say “copy me and what I have.”'

Interviewer: 'And do you copy them if they say that?'

Girl: 'Yes.'

Interviewer: 'Why do you copy them if they say that?'

Girl: 'Because they are my friends.'

(Girl, school 1, age 7).

Children also identified friendship groups according to the school meal type they have. Children have been known to have school dinners, or packed lunches if their friends also have the same. 21

If this approach was used, the combined findings and discussion section would simply be followed by a concluding chapter. Further guidance on writing up qualitative reports can be found in the literature. 20

This paper has described a pragmatic process of thematic content analysis as a method of analysing qualitative data generated by interviews or focus groups. Other approaches to analysis are available and are discussed in the literature. 23 , 24 , 25 The method described here offers a method of generating categories under which similar themes or categories can be collated. The paper also briefly illustrates two different ways of presenting qualitative reports, having analysed the data.

This analysis process, when done properly, is systematic and rigorous and therefore labour-intensive and time consuming. 4 Consequently, for those undertaking this process for the first time, we recommend seeking advice from experienced qualitative researchers.

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Burnard, P., Gill, P., Stewart, K. et al. Analysing and presenting qualitative data. Br Dent J 204 , 429–432 (2008). https://doi.org/10.1038/sj.bdj.2008.292

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• Published: 28 March 2024

Using the consolidated Framework for Implementation Research to integrate innovation recipients’ perspectives into the implementation of a digital version of the spinal cord injury health maintenance tool: a qualitative analysis

• John A Bourke 1 , 2 , 3 ,
• K. Anne Sinnott Jerram 1 , 2 ,
• Mohit Arora 1 , 2 ,
• Ashley Craig 1 , 2 &
• James W Middleton 1 , 2 , 4 , 5  

BMC Health Services Research volume  24 , Article number:  390 ( 2024 ) Cite this article

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Despite advances in managing secondary health complications after spinal cord injury (SCI), challenges remain in developing targeted community health strategies. In response, the SCI Health Maintenance Tool (SCI-HMT) was developed between 2018 and 2023 in NSW, Australia to support people with SCI and their general practitioners (GPs) to promote better community self-management. Successful implementation of innovations such as the SCI-HMT are determined by a range of contextual factors, including the perspectives of the innovation recipients for whom the innovation is intended to benefit, who are rarely included in the implementation process. During the digitizing of the booklet version of the SCI-HMT into a website and App, we used the Consolidated Framework for Implementation Research (CFIR) as a tool to guide collection and analysis of qualitative data from a range of innovation recipients to promote equity and to inform actionable findings designed to improve the implementation of the SCI-HMT.

Data from twenty-three innovation recipients in the development phase of the SCI-HMT were coded to the five CFIR domains to inform a semi-structured interview guide. This interview guide was used to prospectively explore the barriers and facilitators to planned implementation of the digital SCI-HMT with six health professionals and four people with SCI. A team including researchers and innovation recipients then interpreted these data to produce a reflective statement matched to each domain. Each reflective statement prefaced an actionable finding, defined as alterations that can be made to a program to improve its adoption into practice.

Five reflective statements synthesizing all participant data and linked to an actionable finding to improve the implementation plan were created. Using the CFIR to guide our research emphasized how partnership is the key theme connecting all implementation facilitators, for example ensuring that the tone, scope, content and presentation of the SCI-HMT balanced the needs of innovation recipients alongside the provision of evidence-based clinical information.

Conclusions

Understanding recipient perspectives is an essential contextual factor to consider when developing implementation strategies for healthcare innovations. The revised CFIR provided an effective, systematic method to understand, integrate and value recipient perspectives in the development of an implementation strategy for the SCI-HMT.

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Injury to the spinal cord can occur through traumatic causes (e.g., falls or motor vehicle accidents) or from non-traumatic disease or disorder (e.g., tumours or infections) [ 1 ]. The onset of a spinal cord injury (SCI) is often sudden, yet the consequences are lifelong. The impact of a SCI is devastating, with effects on sensory and motor function, bladder and bowel function, sexual function, level of independence, community participation and quality of life [ 2 ]. In order to maintain good health, wellbeing and productivity in society, people with SCI must develop self-management skills and behaviours to manage their newly acquired chronic health condition [ 3 ]. Given the increasing emphasis on primary health care and community management of chronic health conditions, like SCI, there is a growing responsibility on all parties to promote good health practices and minimize the risks of common health complications in their communities.

To address this need, the Spinal Cord Injury Health Maintenance Tool (SCI-HMT) was co-designed between 2018 and 2023 with people living with SCI and their General Practitioners (GPs) in NSW, Australia [ 4 ] The aim of the SCI-HMT is to support self-management of the most common and arguably avoidable potentially life-threatening complications associated with SCI, such as mental health crises, autonomic dysreflexia, kidney infections and pressure injuries. The SCI-HMT provides comprehensible information with resources about the six highest priority health areas related to SCI (as indicated by people with SCI and GPs) and was developed over two phases. Phase 1 focused on developing a booklet version and Phase 2 focused on digitizing this content into a website and smartphone app [ 4 , 5 ].

Enabling the successful implementation of evidence-based innovations such as the SCI-HMT is inevitably influenced by contextual factors: those dynamic and diverse array of forces within real-world settings working for or against implementation efforts [ 6 ]. Contextual factors often include background environmental elements in which an intervention is situated, for example (but not limited to) demographics, clinical environments, organisational culture, legislation, and cultural norms [ 7 ]. Understanding the wider context is necessary to identify and potentially mitigate various challenges to the successful implementation of those innovations. Such work is the focus of determinant frameworks, which focus on categorising or classing groups of contextual determinants that are thought to predict or demonstrate an effect on implementation effectiveness to better understand factors that might influence implementation outcomes [ 8 ].

One of the most highly cited determinant frameworks is the Consolidated Framework for Implementation Research (CFIR) [ 9 ], which is often posited as an ideal framework for pre-implementation preparation. Originally published in 2009, the CFIR has recently been subject to an update by its original authors, which included a literature review, survey of users, and the creation of an outcome addendum [ 10 , 11 ]. A key contribution from this revision was the need for a greater focus on the place of innovation recipients, defined as the constituency for whom the innovation is being designed to benefit; for example, patients receiving treatment, students receiving a learning activity. Traditionally, innovation recipients are rarely positioned as key decision-makers or innovation implementers [ 8 ], and as a consequence, have not often been included in the application of research using frameworks, such as the CFIR [ 11 ].

Such power imbalances within the intersection of healthcare and research, particularly between those receiving and delivering such services and those designing such services, have been widely reported [ 12 , 13 ]. There are concerted efforts within health service development, health research and health research funding, to rectify this power imbalance [ 14 , 15 ]. Importantly, such efforts to promote increased equitable population impact are now being explicitly discussed within the implementation science literature. For example, Damschroder et al. [ 11 ] has recently argued for researchers to use the CFIR to collect data from innovation recipients, and that, ultimately, “equitable population impact is only possible when recipients are integrally involved in implementation and all key constituencies share power and make decisions together” (p. 7). Indeed, increased equity between key constituencies and partnering with innovation recipients promotes the likelihood of sustainable adoption of an innovation [ 4 , 12 , 14 ].

There is a paucity of work using the updated CFIR to include and understand innovation recipients’ perspectives. To address this gap, this paper reports on a process of using the CFIR to guide the collection of qualitative data from a range of innovation recipients within a wider co-design mixed methods study examining the development and implementation of SCI-HMT. The innovation recipients in our research are people living with SCI and GPs. Guided by the CFIR domains (shown in the supplementary material), we used reflexive thematic analysis [ 16 ]to summarize data into reflective summaries, which served to inform actionable findings designed to improve implementation of the SCI-HMT.

The procedure for this research is multi-stepped and is summarized in Fig.  1 . First, we mapped retrospective qualitative data collected during the development of the SCI-HMT [ 4 ] against the five domains of the CFIR in order to create a semi-structured interview guide (Step 1). Then, we used this interview guide to collect prospective data from health professionals and people with SCI during the development of the digital version of the SCI-HMT (Step 2) to identify implementation barriers and facilitators. This enabled us to interpret a reflective summary statement for each CFIR domain. Lastly, we developed an actionable finding for each domain summary. The first (RESP/18/212) and second phase (2019/ETH13961) of the project received ethical approval from The Northern Sydney Local Health District Human Research Ethics Committee. The reporting of this study was conducted in line with the consolidated Criteria for Reporting Qualitative Research (COREQ) guidelines [ 17 ]. All methods were performed in accordance with the relevant guidelines and regulations.

Procedure of synthesising datasets to inform reflective statements and actionable findings. a Two health professionals had a SCI (one being JAB); b Two co-design researchers had a SCI (one being JAB)

Step one: retrospective data collection and analysis

We began by retrospectively analyzing the data set (interview and focus group transcripts) from the previously reported qualitative study from the development phase of the SCI-HMT [ 4 ]. This analysis was undertaken by two team members (KASJ and MA). KASJ has a background in co-design research. Transcript data were uploaded into NVivo software (Version 12: QSR International Pty Ltd) and a directed content analysis approach [ 18 ] was applied to analyze categorized data a priori according to the original 2009 CFIR domains (intervention characteristics, outer setting, inner setting, characteristics of individuals, and process of implementation) described by Damschroder et al. [ 9 ]. This categorized data were summarized and informed the specific questions of a semi-structured interview guide. The final output of step one was an interview guide with context-specific questions arranged according to the CFIR domains (see supplementary file 1). The interview was tested with two people with SCI and one health professional.

Step two: prospective data collection and analysis

In the second step, semi-structured interviews were conducted by KASJ (with MA as observer) with consenting healthcare professionals who had previously contributed to the development of the SCI-HMT. Healthcare professionals included GPs, Nurse Consultants, Specialist Physiotherapists, along with Health Researchers (one being JAB). In addition, a focus group was conducted with consenting individuals with SCI who had contributed to the SCI-HMT design and development phase. The interview schedule designed in step one above guided data collection in all interviews and the focus group.

The focus group and interviews were conducted online, audio recorded, transcribed verbatim and uploaded to NVivo software (Version 12: QSR International Pty Ltd). All data were subject to reflexive, inductive and deductive thematic analysis [ 16 , 19 ] to better understand participants’ perspectives regarding the potential implementation of the SCI-HMT. First, one team member (KASJ) read transcripts and began a deductive analysis whereby data were organized into CFIR domains-specific dataset. Second, KASJ and JAB analyzed this domain-specific dataset to inductively interpret a reflective statement which served to summarise all participant responses to each domain. The final output of step two was a reflective summary statement for each CFIR domain.

Step three: data synthesis

In the third step we aimed to co-create an actionable finding (defined as tangible alteration that can be made to a program, in this case the SCI-HMT [ 20 ]) based on each domain-specific reflective statement. To achieve this, three codesign researchers (KAS and JAB with one person with SCI from Step 2 (deidentified)) focused on operationalising each reflective statement into a recommended modification for the digital version of the SCI-HMT. This was an iterative process guided by the specific CFIR domain and construct definitions, which we deemed salient and relevant to each reflective statement (see Table  2 for example). Data synthesis involved line by line analysis, group discussion, and repeated refinement of actionable findings. A draft synthesis was shared with SCI-HMT developers (JWM and MA) and refinement continued until consensus was agreed on. The final outputs of step three were an actionable finding related to each reflective statement for each CFIR domain.

The characteristics of both the retrospective and prospective study participants are shown in Table  1 . The retrospective data included data from a total of 23 people: 19 people with SCI and four GPs. Of the 19 people with SCI, 12 participated in semi-structured interviews, seven participated in the first focus group, and four returned to the second focus group. In step 2, four people with SCI participated in a focus group and six healthcare professionals participated in one-on-one semi-structured interviews. Two of the healthcare professionals (a GP and a registrar) had lived experience of SCI, as did one researcher (JAB). All interviews and focus groups were conducted either online or in-person and ranged in length between 60 and 120 min.

In our overall synthesis, we actively interpreted five reflective statements based on the updated CFIR domain and construct definitions by Damschroder et al. [ 11 ]. Table  2 provides a summary of how we linked the updated CFIR domain and construct definitions to the reflective statements. We demonstrate this process of co-creation below, including illustrative quotes from participants. Importantly, we guide readers to the actionable findings related to each reflective statement in Table  2 . Each actionable statement represents an alteration that can be made to a program to improve its adoption into practice.

Participants acknowledged that self-management is a major undertaking and very demanding, as one person with SCI said, “ we need to be informed without being terrified and overwhelmed”. Participants felt the HMT could indeed be adapted, tailored, refined, or reinvented to meet local needs. For example, another person with SCI remarked:

“Education needs to be from the get-go but in bite sized pieces from all quarters when readiness is most apparent… at all time points , [not just as a] a newbie tool or for people with [long-term impairment] ” (person with SCI_02).

Therefore, the SCI-HMT had to balance complexity of content while still being accessible and engaging, and required input from both experts in the field and those with lived experience of SCI, for example, a clinical nurse specialist suggested:

“it’s essential [the SCI-HMT] is written by experts in the field as well as with collaboration with people who have had a, you know, the lived experience of SCI” (healthcare professional_03).

Furthermore, the points of contact with healthcare for a person with SCI can be challenging to navigate and the SCI-HMT has the potential to facilitate a smoother engagement process and improve communication between people with SCI and healthcare services. As a GP suggested:

“we need a tool like this to link to that pathway model in primary health care , [the SCI-HMT] it’s a great tool, something that everyone can read and everyone’s reading the same thing” (healthcare professional_05).

Participants highlighted that the ability of the SCI-HMT to facilitate effective communication was very much dependent on the delivery format. The idea of digitizing the SCI-HMT garnered equal support from people with SCI and health care professionals, with one participant with SCI deeming it to be “ essential” ( person with SCI_01) and a health professional suggesting a “digitalized version will be an advantage for most people” (healthcare professional_02).

Outer setting

There was strong interest expressed by both people with SCI and healthcare professionals in using the SCI-HMT. The fundamental premise was that knowledge is power and the SCI-HMT would have strong utility in post-acute rehabilitation services, as well as primary care. As a person with SCI said,

“ we need to leave the [spinal unit] to return to the community with sufficient knowledge, and to know the value of that knowledge and then need to ensure primary healthcare provider [s] are best informed” (person with SCI_04).

The value of the SCI-HMT in facilitating clear and effective communication and shared decision-making between healthcare professionals and people with SCI was also highlighted, as shown by the remarks of an acute nurse specialist:

“I think this tool is really helpful for the consumer and the GP to work together to prioritize particular tests that a patient might need and what the regularity of that is” (healthcare professional_03).

Engaging with SCI peer support networks to promote the SCI-HMT was considered crucial, as one person with SCI emphasized when asked how the SCI-HMT might be best executed in the community, “…peers, peers and peers” (person with SCI_01). Furthermore, the layering of content made possible in the digitalized version will allow for the issue of approachability in terms of readiness for change, as another person with SCI said:

“[putting content into a digital format] is essential and required and there is a need to put summarized content in an App with links to further web-based information… it’s not likely to be accessed otherwise” (person with SCI_02).

Inner setting

Participants acknowledged that self-management of health and well-being is substantial and demanding. It was suggested that the scope, tone, and complexity of the SCI-HMT, while necessary, could potentially be resisted by people with SCI if they felt overwhelmed, as one person with SCI described:

“a manual that is really long and wordy, like, it’s [a] health metric… they maybe lack the health literacy to, to consume the content then yes, it would impede their readiness for [self-management]” (person with SCI_02).

Having support from their GPs was considered essential, and the HMT could enable GP’s, who are under time pressure, to provide more effective health and advice to their patients, as one GP said:

“We GP’s are time poor, if you realize then when you’re time poor you look quickly to say oh this is a patient tool - how can I best use this?” (healthcare professional_05).

Furthermore, health professional skills may be best used with the synthesis of self-reported symptoms, behaviors, or observations. A particular strength of a digitized version would be its ability to facilitate more streamlined communication between a person with SCI and their primary healthcare providers developing healthcare plans, as an acute nurse specialist reflected, “ I think that a digitalized version is essential with links to primary healthcare plans” (healthcare professional_03).

Efficient communication with thorough assessment is essential to ensure serious health issues are not missed, as findings reinforce that the SCI-HMT is an educational tool, not a replacement for healthcare services, as a clinical nurse specialist commented, “ remember, things will go wrong– people end up very sick and in acute care “ (healthcare professional_02).

The SCI-HMT has the potential to provide a pathway to a ‘hope for better than now’ , a hope to ‘remain well’ and a hope to ‘be happy’ , as the informant with SCI (04) declared, “self-management is a long game, if you’re keeping well, you’ve got that possibility of a good life… of happiness”. Participants with SCI felt the tool needed to be genuine and

“acknowledge the huge amount of adjustment required, recognizing that dealing with SCI issues is required to survive and live a good life” (person with SCI_04).

However, there is a risk that an individual is completely overwhelmed by the scale of the SCI-HMT content and the requirement for lifelong vigilance. Careful attention and planning were paid to layering the information accordingly to support self-management as a ‘long game’, which one person with SCI reflected in following:

“the first 2–3 year [period] is probably the toughest to get your head around the learning stuff, because you’ve got to a stage where you’re levelling out, and you’ve kind of made these promises to yourself and then you realize that there’s no quick fix” (person with SCI_01).

It was decided that this could be achieved by providing concrete examples and anecdotes from people with SCI illustrating that a meaningful, healthy life is possible, and that good health is the bedrock of a good life with SCI.

There was universal agreement that the SCI-HMT is aspirational and that it has the potential to improve knowledge and understanding for people with SCI, their families, community workers/carers and primary healthcare professionals, as a GP remarked:

“[different groups] could just read it and realize, ‘Ahh, OK that’s what that means… when you’re doing catheters. That’s what you mean when you’re talking about bladder and bowel function or skin care” (healthcare professional_04).

Despite the SCI-HMT providing an abundance of information and resources to support self-management, participants identified four gaps: (i) the priority issue of sexuality, including pleasure and identity, as one person with SCI remarked:

“ sexuality is one of the biggest issues that people with SCI often might not speak about that often cause you know it’s awkward for them. So yeah, I think that’s a that’s a serious issue” (person with SCI_03).

(ii) consideration of the taboo nature of bladder and bowel topics for indigenous people, (iii) urgent need to ensure links for SCI-HMT care plans are compatible with patient management systems, and (iv) exercise and leisure as a standalone topic taking account of effects of physical activity, including impact on mental health and wellbeing but more especially for fun.

To ensure longevity of the SCI-HMT, maintaining a partnership between people with SCI, SCI community groups and both primary and tertiary health services is required for liaison with the relevant professional bodies, care agencies, funders, policy makers and tertiary care settings to ensure ongoing education and promotion of SCI-HMT is maintained. For example, delivery of ongoing training of healthcare professionals to both increase the knowledge base of primary healthcare providers in relation to SCI, and to promote use of the tools and resources through health communities. As a community nurse specialist suggested:

“ improving knowledge in the health community… would require digital links to clinical/health management platforms” (healthcare professional_02).

In a similar vein, a GP suggested:

“ our common GP body would have continuing education requirements… especially if it’s online, in particular for the rural, rural doctors who you know, might find it hard to get into the city” (healthcare professional_04).

The successful implementation of evidence-based innovations into practice is dependent on a wide array of dynamic and active contextual factors, including the perspectives of the recipients who are destined to use such innovations. Indeed, the recently updated CFIR has called for innovation recipient perspectives to be a priority when considering contextual factors [ 10 , 11 ]. Understanding and including the perspectives of those the innovation is being designed to benefit can promote increased equity and validation of recipient populations, and potentially increase the adoption and sustainability of innovations.

In this paper, we have presented research using the recently updated CFIR to guide the collection of innovation recipients’ perspectives (including people with SCI and GPs working in the community) regarding the potential implementation barriers and facilitators of the digital version of the SCI-HMT. Collected data were synthesized to inform actionable findings– tangible ways in which the SCI-HMT could be modified according of the domains of the CFIR (e.g., see Keith et al. [ 20 ]). It is important to note that we conducted this research using the original domains of the CFIR [ 9 ] prior to Damschroder et al. publishing the updated CFIR [ 11 ]. However, in our analysis we were able to align our findings to the revised CFIR domains and constructs, as Damschroder [ 11 ] suggests, constructs can “be mapped back to the original CFIR to ensure longitudinal consistency” (p. 13).

One of the most poignant findings from our analyses was the need to ensure the content of the SCI-HMT balanced scientific evidence and clinical expertise with lived experience knowledge. This balance of clinical and experiential knowledge demonstrated genuine regard for lived experience knowledge, and created a more accessible, engaging, useable platform. For example, in the innovation and individual domains, the need to include lived experience quotes was immediately apparent once the perspective of people with SCI was included. It was highlighted that while the SCI-HMT will prove useful to many parties at various stages along the continuum of care following onset of SCI, there will be those individuals that are overwhelmed by the scale of the content. That said, the layering of information facilitated by the digitalized version is intended to provide an ease of navigation through the SCI-HMT and enable a far greater sense of control over personal health and wellbeing. Further, despite concerns regarding e-literacy the digitalized version of the SCI-HMT is seen as imperative for accessibility given the wide geographic diversity and recent COVID pandemic [ 21 ]. While there will be people who are challenged by the technology, the universally acceptable use of the internet is seen as less of a barrier than printed material.

The concept of partnership was also apparent within the data analysis focusing on the outer and inner setting domains. In the outer setting domain, our findings emphasized the importance of engaging with SCI community groups, as well as primary and tertiary care providers to maximize uptake at all points in time from the phase of subacute rehabilitation onwards. While the SCI-HMT is intended for use across the continuum of care from post-acute rehabilitation onwards, it may be that certain modules are more relevant at different times, and could serve as key resources during the hand over between acute care, inpatient rehabilitation and community reintegration.

Likewise, findings regarding the inner setting highlighted the necessity of a productive partnership between GPs and individuals with SCI to address the substantial demands of long-term self-management of health and well-being following SCI. Indeed, support is crucial, especially when self-management is the focus. This is particularly so in individuals living with complex disability following survival after illness or injury [ 22 ], where health literacy has been found to be a primary determinant of successful health and wellbeing outcomes [ 23 ]. For people with SCI, this tool potentially holds the most appeal when an individual is ready and has strong partnerships and supportive communication. This can enable potential red flags to be recognized earlier allowing timely intervention to avert health crises, promoting individual well-being, and reducing unnecessary demands on health services.

While the SCI-HMT is an educational tool and not meant to replace health services, findings suggest the current structure would lead nicely to having the conversation with a range of likely support people, including SCI peers, friends and family, GP, community nurses, carers or via on-line support services. The findings within the process domain underscored the importance of ongoing partnership between innovation implementers and a broad array of innovation recipients (e.g., individuals with SCI, healthcare professionals, family, funding agencies and policy-makers). This emphasis on partnership also addresses recent discussions regarding equity and the CFIR. For example, Damschroder et al. [ 11 ] suggests that innovation recipients are too often not included in the CFIR process, as the CFIR is primarily seen as a tool intended “to collect data from individuals who have power and/or influence over implementation outcomes” (p. 5).

Finally, we feel that our inclusion of innovation recipients’ perspectives presented in this article begins to address the notion of equity in implementation, whereby the inclusion of recipient perspectives in research using the CFIR both validates, and increases, the likelihood of sustainable adoption of evidence-based innovations, such as the SCI-HMT. We have used the CFIR in a pragmatic way with an emphasis on meaningful engagement between the innovation recipients and the research team, heeding the call from Damschroder et al. [ 11 ], who recently argued for researchers to use the CFIR to collect data from innovation recipients. Adopting this approach enabled us to give voice to innovation recipient perspectives and subsequently ensure that the tone, scope, content and presentation of the SCI-HMT balanced the needs of innovation recipients alongside the provision of evidence-based clinical information.

Our research is not without limitations. While our study was successful in identifying a number of potential barriers and facilitators to the implementation of the SCI-HMT, we did not test any implementation strategies to impact determinants, mechanisms, or outcomes. This will be the focus of future research on this project, which will investigate the impact of implementation strategies on outcomes. Focus will be given to the context-mechanism configurations which give rise to particular outcomes for different groups in certain circumstances [ 7 , 24 ]. A second potential concern is the relatively small sample size of participants that may not allow for saturation and generalizability of the findings. However, both the significant impact of secondary health complications for people with SCI and the desire for a health maintenance tool have been established in Australia [ 2 , 4 ]. The aim our study reported in this article was to achieve context-specific knowledge of a small sample that shares a particular mutual experience and represents a perspective, rather than a population [ 25 , 26 ]. We feel our findings can stimulate discussion and debate regarding participant-informed approaches to implementation of the SCI-HMT, which can then be subject to larger-sample studies to determine their generalisability, that is, their external validity. Notably, future research could examine the interaction between certain demographic differences (e.g., gender) of people with SCI and potential barriers and facilitators to the implementation of the SCI-HMT. Future research could also include the perspectives of other allied health professionals working in the community, such as occupational therapists. Lastly, while our research gave significant priority to recipient viewpoints, research in this space would benefit for ensuring innovation recipients are engaged as genuine partners throughout the entire research process from conceptualization to implementation.

Employing the CFIR provided an effective, systematic method for identifying recipient perspectives regarding the implementation of a digital health maintenance tool for people living with SCI. Findings emphasized the need to balance clinical and lived experience perspectives when designing an implementation strategy and facilitating strong partnerships with necessary stakeholders to maximise the uptake of SCI-HMT into practice. Ongoing testing will monitor the uptake and implementation of this innovation, specifically focusing on how the SCI-HMT works for different users, in different contexts, at different stages and times of the rehabilitation journey.

Data availability

The datasets supporting the conclusions of this article are available available upon request and with permission gained from the project Steering Committee.

Abbreviations

spinal cord injury

HMT-Spinal Cord Injury Health Maintenance Tool

Consolidated Framework for Implementation Research

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Acknowledgements

Authors of this study would like to thank all the consumers with SCI and healthcare professionals for their invaluable contribution to this project. Their participation and insights have been instrumental in shaping the development of the SCI-HMT. The team also acknowledges the support and guidance provided by the members of the Project Steering Committee, as well as the partner organisations, including NSW Agency for Clinical Innovation, and icare NSW. Author would also like to acknowledge the informant group with lived experience, whose perspectives have enriched our understanding and informed the development of SCI-HMT.

The SCI Wellness project was a collaborative project between John Walsh Centre for Rehabilitation Research at The University of Sydney and Royal Rehab. Both organizations provided in-kind support to the project. Additionally, the University of Sydney and Royal Rehab received research funding from Insurance and Care NSW (icare NSW) to undertake the SCI Wellness Project. icare NSW do not take direct responsibility for any of the following: study design, data collection, drafting of the manuscript, or decision to publish.

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John A Bourke, K. Anne Sinnott Jerram, Mohit Arora, Ashley Craig & James W Middleton

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Project conceptualization: KASJ, MA, JWM; project methodology: JWM, MA, KASJ, JAB; data collection: KASJ and MA; data analysis: KASJ, JAB, MA, JWM; writing—original draft preparation: JAB; writing—review and editing: JAB, KASJ, JWM, MA, AC; funding acquisition: JWM, MA. All authors contributed to the revision of the paper and approved the final submitted version.

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The first (RESP/18/212) and second phase (2019/ETH13961) of the project received ethical approval from The Northern Sydney Local Health District Human Research Ethics Committee. All participants provided informed, written consent. All data were to be retained for 7 years (23rd May 2030).

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MA part salary (from Dec 2018 to Dec 2023), KASJ part salary (July 2021 to Dec 2023) and JAB part salary (Jan 2022 to Aug 2022) was paid from the grant monies. Other authors declare no conflicts of interest.

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Bourke, J.A., Jerram, K.A.S., Arora, M. et al. Using the consolidated Framework for Implementation Research to integrate innovation recipients’ perspectives into the implementation of a digital version of the spinal cord injury health maintenance tool: a qualitative analysis. BMC Health Serv Res 24 , 390 (2024). https://doi.org/10.1186/s12913-024-10847-x

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Received : 14 August 2023

Accepted : 11 March 2024

Published : 28 March 2024

DOI : https://doi.org/10.1186/s12913-024-10847-x

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