how to present interview findings in qualitative research

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Buttoning up research: How to present and visualize qualitative data

15 Minute Read

There is no doubt that data visualization is an important part of the qualitative research process. Whether you're preparing a presentation or writing up a report, effective visualizations can help make your findings clear and understandable for your audience. 

In this blog post, we'll discuss some tips for creating effective visualizations of qualitative data. 

First, let's take a closer look at what exactly qualitative data is.

What is qualitative data?

Qualitative data is information gathered through observation, questionnaires, and interviews. It's often subjective, meaning that the researcher has to interpret it to draw meaningful conclusions from it. 

The difference between qualitative data and quantitative data

When researchers use the terms qualitative and quantitative, they're referring to two different types of data. Qualitative data is subjective and descriptive, while quantitative data is objective and numerical.

Qualitative data is often used in research involving psychology or sociology. This is usually where a researcher may be trying to identify patterns or concepts related to people's behavior or attitudes. It may also be used in research involving economics or finance, where the focus is on numerical values such as price points or profit margins. 

Before we delve into how best to present and visualize qualitative data, it's important that we highlight how to be gathering this data in the first place. ‍

How best to gather qualitative data

In order to create an effective visualization of qualitative data, ensure that the right kind of information has been gathered. 

Here are six ways to gather the most accurate qualitative data:

• Define your research question: What data is being set out to collect? A qualitative research question is a definite or clear statement about a condition to be improved, a project’s area of concern, a troubling question that exists, or a difficulty to be eliminated. It not only defines who the participants will be but guides the data collection methods needed to achieve the most detailed responses.
• ‍ Determine the best data collection method(s): The data collected should be appropriate to answer the research question. Some common qualitative data collection methods include interviews, focus groups, observations, or document analysis. Consider the strengths and weaknesses of each option before deciding which one is best suited to answer the research question.  ‍
• Develop a cohesive interview guide: Creating an interview guide allows researchers to ask more specific questions and encourages thoughtful responses from participants. It’s important to design questions in such a way that they are centered around the topic of discussion and elicit meaningful insight into the issue at hand. Avoid leading or biased questions that could influence participants’ answers, and be aware of cultural nuances that may affect their answers.
• ‍ Stay neutral – let participants share their stories: The goal is to obtain useful information, not to influence the participant’s answer. Allowing participants to express themselves freely will help to gather more honest and detailed responses. It’s important to maintain a neutral tone throughout interviews and avoid judgment or opinions while they are sharing their story. 
• ‍ Work with at least one additional team member when conducting qualitative research: Participants should always feel comfortable while providing feedback on a topic, so it can be helpful to have an extra team member present during the interview process – particularly if this person is familiar with the topic being discussed. This will ensure that the atmosphere of the interview remains respectful and encourages participants to speak openly and honestly.
• ‍ Analyze your findings: Once all of the data has been collected, it’s important to analyze it in order to draw meaningful conclusions. Use tools such as qualitative coding or content analysis to identify patterns or themes in the data, then compare them with prior research or other data sources. This will help to draw more accurate and useful insights from the results. 

By following these steps, you will be well-prepared to collect and analyze qualitative data for your research project. Next, let's focus on how best to present the qualitative data that you have gathered and analyzed.

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How to visually present qualitative data.

When it comes to how to present qualitative data visually, the goal is to make research findings clear and easy to understand. To do this, use visuals that are both attractive and informative. 

Presenting qualitative data visually helps to bring the user’s attention to specific items and draw them into a more in-depth analysis. Visuals provide an efficient way to communicate complex information, making it easier for the audience to comprehend. 

Additionally, visuals can help engage an audience by making a presentation more interesting and interactive.

Here are some tips for creating effective visuals from qualitative data:

• ‍ Choose the right type of visualization: Consider which type of visual would best convey the story that is being told through the research. For example, bar charts or line graphs might be appropriate for tracking changes over time, while pie charts or word clouds could help show patterns in categorical data. 
• ‍ Include contextual information: In addition to showing the actual numbers, it's helpful to include any relevant contextual information in order to provide context for the audience. This can include details such as the sample size, any anomalies that occurred during data collection, or other environmental factors.
• ‍ Make it easy to understand: Always keep visuals simple and avoid adding too much detail or complexity. This will help ensure that viewers can quickly grasp the main points without getting overwhelmed by all of the information. 
• ‍ Use color strategically: Color can be used to draw attention to certain elements in your visual and make it easier for viewers to find the most important parts of it. Just be sure not to use too many different colors, as this could create confusion instead of clarity. 
• ‍ Use charts or whiteboards: Using charts or whiteboards can help to explain the data in more detail and get viewers engaged in a discussion. This type of visual tool can also be used to create storyboards that illustrate the data over time, helping to bring your research to life. 

Visualizing qualitative data in Notably

Notably helps researchers visualize their data on a flexible canvas, charts, and evidence based insights. As an all-in-one research platform, Notably enables researchers to collect, analyze and present qualitative data effectively.

Notably provides an intuitive interface for analyzing data from a variety of sources, including interviews, surveys, desk research, and more. Its powerful analytics engine then helps you to quickly identify insights and trends in your data . Finally, the platform makes it easy to create beautiful visuals that will help to communicate research findings with confidence. 

Research Frameworks in Analysis

The canvas in Analysis is a multi-dimensional workspace to play with your data spatially to find likeness and tension. Here, you may use a grounded theory approach to drag and drop notes into themes or patterns that emerge in your research. Utilizing the canvas tools such as shapes, lines, and images, allows researchers to build out frameworks such as journey maps, empathy maps, 2x2's, etc. to help synthesize their data.

Going one step further, you may begin to apply various lenses to this data driven canvas. For example, recoloring by sentiment shows where pain points may distributed across your customer journey. Or, recoloring by participant may reveal if one of your participants may be creating a bias towards a particular theme.

Exploring Qualitative Data through a Quantitative Lens

Once you have begun your analysis, you may visualize your qualitative data in a quantitative way through charts. You may choose between a pie chart and or a stacked bar chart to visualize your data. From here, you can segment your data to break down the ‘bar’ in your bar chart and slices in your pie chart one step further.

To segment your data, you can choose between ‘Tag group’, ‘Tag’, ‘Theme’, and ‘Participant'. Each group shows up as its own bar in the bar chart or slice in the pie chart. For example, try grouping data as ‘Participant’ to see the volume of notes assigned to each person. Or, group by ‘Tag group’ to see which of your tag groups have the most notes.

Depending on how you’ve grouped or segmented your charts will affect the options available to color your chart. Charts use colors that are a mix of sentiment, tag, theme, and default colors. Consider color as a way of assigning another layer of meaning to your data. For example, choose a red color for tags or themes that are areas of friction or pain points. Use blue for tags that represent opportunities.

AI Powered Insights and Cover Images

One of the most powerful features in Analysis is the ability to generate insights with AI. Insights combine information, inspiration, and intuition to help bridge the gap between knowledge and wisdom. Even before you have any tags or themes, you may generate an AI Insight from your entire data set. You'll be able to choose one of our AI Insight templates that are inspired by trusted design thinking frameworks to stimulate generative, and divergent thinking. With just the click of a button, you'll get an insight that captures the essence and story of your research. You may experiment with a combination of tags, themes, and different templates or, create your own custom AI template. These insights are all evidence-based, and are centered on the needs of real people. You may package these insights up to present your research by embedding videos, quotes and using AI to generate unique cover image.

You can sign up to run an end to end research project for free and receive tips on how to make the most out of your data. Want to chat about how Notably can help your team do better, faster research? Book some time here for a 1:1 demo with your whole team.

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[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!

How To Write The Results/Findings Chapter

For qualitative studies (dissertations & theses).

By: Jenna Crossley (PhD). 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. 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
• Free results chapter template

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 for writing 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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21 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?

For qualitative studies, can the findings be structured according to the Research questions? Thank you.

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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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Qualitative research method-interviewing and observation

Shazia jamshed.

Department of Pharmacy Practice, Kulliyyah of Pharmacy, International Islamic University Malaysia, Kuantan Campus, Pahang, Malaysia

Buckley and Chiang define research methodology as “a strategy or architectural design by which the researcher maps out an approach to problem-finding or problem-solving.”[ 1 ] According to Crotty, research methodology is a comprehensive strategy ‘that silhouettes our choice and use of specific methods relating them to the anticipated outcomes,[ 2 ] but the choice of research methodology is based upon the type and features of the research problem.[ 3 ] According to Johnson et al . mixed method research is “a class of research where the researcher mixes or combines quantitative and qualitative research techniques, methods, approaches, theories and or language into a single study.[ 4 ] In order to have diverse opinions and views, qualitative findings need to be supplemented with quantitative results.[ 5 ] Therefore, these research methodologies are considered to be complementary to each other rather than incompatible to each other.[ 6 ]

Qualitative research methodology is considered to be suitable when the researcher or the investigator either investigates new field of study or intends to ascertain and theorize prominent issues.[ 6 , 7 ] There are many qualitative methods which are developed to have an in depth and extensive understanding of the issues by means of their textual interpretation and the most common types are interviewing and observation.[ 7 ]

Interviewing

This is the most common format of data collection in qualitative research. According to Oakley, qualitative interview is a type of framework in which the practices and standards be not only recorded, but also achieved, challenged and as well as reinforced.[ 8 ] As no research interview lacks structure[ 9 ] most of the qualitative research interviews are either semi-structured, lightly structured or in-depth.[ 9 ] Unstructured interviews are generally suggested in conducting long-term field work and allow respondents to let them express in their own ways and pace, with minimal hold on respondents’ responses.[ 10 ]

Pioneers of ethnography developed the use of unstructured interviews with local key informants that is., by collecting the data through observation and record field notes as well as to involve themselves with study participants. To be precise, unstructured interview resembles a conversation more than an interview and is always thought to be a “controlled conversation,” which is skewed towards the interests of the interviewer.[ 11 ] Non-directive interviews, form of unstructured interviews are aimed to gather in-depth information and usually do not have pre-planned set of questions.[ 11 ] Another type of the unstructured interview is the focused interview in which the interviewer is well aware of the respondent and in times of deviating away from the main issue the interviewer generally refocuses the respondent towards key subject.[ 11 ] Another type of the unstructured interview is an informal, conversational interview, based on unplanned set of questions that are generated instantaneously during the interview.[ 11 ]

In contrast, semi-structured interviews are those in-depth interviews where the respondents have to answer preset open-ended questions and thus are widely employed by different healthcare professionals in their research. Semi-structured, in-depth interviews are utilized extensively as interviewing format possibly with an individual or sometimes even with a group.[ 6 ] These types of interviews are conducted once only, with an individual or with a group and generally cover the duration of 30 min to more than an hour.[ 12 ] Semi-structured interviews are based on semi-structured interview guide, which is a schematic presentation of questions or topics and need to be explored by the interviewer.[ 12 ] To achieve optimum use of interview time, interview guides serve the useful purpose of exploring many respondents more systematically and comprehensively as well as to keep the interview focused on the desired line of action.[ 12 ] The questions in the interview guide comprise of the core question and many associated questions related to the central question, which in turn, improve further through pilot testing of the interview guide.[ 7 ] In order to have the interview data captured more effectively, recording of the interviews is considered an appropriate choice but sometimes a matter of controversy among the researcher and the respondent. Hand written notes during the interview are relatively unreliable, and the researcher might miss some key points. The recording of the interview makes it easier for the researcher to focus on the interview content and the verbal prompts and thus enables the transcriptionist to generate “verbatim transcript” of the interview.

Similarly, in focus groups, invited groups of people are interviewed in a discussion setting in the presence of the session moderator and generally these discussions last for 90 min.[ 7 ] Like every research technique having its own merits and demerits, group discussions have some intrinsic worth of expressing the opinions openly by the participants. On the contrary in these types of discussion settings, limited issues can be focused, and this may lead to the generation of fewer initiatives and suggestions about research topic.

Observation

Observation is a type of qualitative research method which not only included participant's observation, but also covered ethnography and research work in the field. In the observational research design, multiple study sites are involved. Observational data can be integrated as auxiliary or confirmatory research.[ 11 ]

Research can be visualized and perceived as painstaking methodical efforts to examine, investigate as well as restructure the realities, theories and applications. Research methods reflect the approach to tackling the research problem. Depending upon the need, research method could be either an amalgam of both qualitative and quantitative or qualitative or quantitative independently. By adopting qualitative methodology, a prospective researcher is going to fine-tune the pre-conceived notions as well as extrapolate the thought process, analyzing and estimating the issues from an in-depth perspective. This could be carried out by one-to-one interviews or as issue-directed discussions. Observational methods are, sometimes, supplemental means for corroborating research findings.

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4 Writing Up the Research Findings

• Published: May 2013
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This chapter discusses different theoretical and practical tools which are meant to assist researchers in writing up their findings. It first deals with the problem of how to reduce a large amount of data into something that can be communicated in a short journal article or book chapter. It then discusses different ways of organizing the presentation of one's findings in terms of the macrostructure, i.e. the general argumentative or communicative drive of the research text, and the microstructure, i.e. the crafting of concrete sentences and paragraphs, of the text. Finally, the chapter examines the role of theory in writing up the research findings and presents two examples of excellent interview reports that demonstrate diametrically opposed uses of theory. The first example uses theory in articulating the findings by telling an analytic story, while the other is theory-free, but deeply evocative, written in a literary style, crafted rather more like a mystery story.

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• UNC Libraries
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• Qualitative Research Resources
• 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).
• << Previous: Publishing Qualitative Research
• Next: Qualitative & Libraries: a few gems >>
• Last Updated: Jul 28, 2024 4:11 PM
• URL: https://guides.lib.unc.edu/qual

blog @ precision

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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• 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.

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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.

Spencer L, Ritchie J, O'Connor W . Analysis: practices, principles and processes. In Ritchie J, Lewis J (eds) Qualitative research practice . pp 199–218. London: Sage Publications, 2004.

Google Scholar  

Lathlean J . Qualitative analysis. In Gerrish K, Lacy A (eds) The research process in nursing . pp 417–433. Oxford: Blackwell Science, 2006.

Williams C, Bower E J, Newton J T . Research in primary dental care part 6: data analysis. Br Dent J 2004; 197 : 67–73.

Article   Google Scholar  

Pope C, Ziebland S, Mays N . Analysing qualitative data. In Pope C, Mays N (eds) Qualitative research in health care . 2nd ed. pp 75–88. London: BMJ Books, 1999.

Ritchie J, Spencer L, O'Connor W . Carrying out qualitative analysis. In Ritchie J, Lewis J (eds) Qualitative research practice . pp 219–262. London: Sage Publications, 2004.

Glaser B G, Strauss A L . The discovery of grounded theory: strategies for qualitative research . Chicago: Aldine Publishing Company, 1967.

Stewart K, Gill P, Chadwick B, Treasure E . Qualitative research in dentistry. Br Dent J 2008; 204 : 235–239.

Seale C . Analysing your data. In Silverman D (ed) Doing qualitative research . pp 154–174. London: Sage Publications, 2000.

Morse J M, Field P . Nursing research: the application of qualitative approaches . Cheltenham: Stanley Thornes, 1996.

Book   Google Scholar  

Stewart K, Gill P, Treasure E, Chadwick B . Understanding about food among 6-11 year olds in South Wales. Food Cult Soc 2006; 9 : 317–333.

Burnard P . A method of analysing interview transcripts in qualitative research. Nurse Educ Today 1991; 11 : 461–466.

Burnard P . A pragmatic approach to qualitative data analysis. In Newell R, Burnard P (eds). Research for evidence based practice . pp 97–107. Oxford: Blackwell Publishing, 2006.

Mays N, Pope C . Rigour and qualitative research. BMJ 1995; 311 : 109–112.

Barbour R S . Checklists for improving rigour in qualitative research: a case of the tail wagging the dog? BMJ 2001; 322 : 1115–1117.

Long T, Johnson M . Rigour, reliability and validity in qualitative research. Clin Eff Nurs 2000; 4 : 30–37.

Cutcliffe J R, McKenna H P . Establishing the credibility of qualitative research findings: the plot thickens. J Adv Nurs 1999; 30 : 374–380.

Andrews M, Lyne P, Riley E . Validity in qualitative health care research: an exploration of the impact of individual researcher perspectives within collaborative enquiry. J Adv Nurs 1996; 23 : 441–447.

Silverman D . Doing qualitative research . London: Sage Publications, 2000.

Polit D F, Beck C T . Essentials of nursing research: methods, appraisal, and utilization . 6th ed. Philadelphia: Lippincott Williams & Wilkins, 2006.

Burnard P . Writing a qualitative research report. Nurse Educ Today 2004; 24 : 174–179.

Ludvigsen A, Sharma N . Burger boy and sporty girl; children and young people's attitudes towards food in school . Barkingside: Barnardo's, 2004.

Watt R G, Sheiham A . Towards an understanding of young people's conceptualisation of food and eating. Health Educ J 1997; 56 : 340–349.

Bryman A, Burgess R (eds). Analysing qualitative data . London: Routledge, 1993.

Miles M, Huberman A . Qualitative data analysis . 2nd ed. Thousand Oaks: Sage Publications, 1994.

Silverman D . Interpreting qualitative data: methods for analysing talk, text and interaction . 3rd ed. Thousand Oaks: Sage Publications, 2006.

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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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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.

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Description of qualitative data analysis techniques.

Home » Description of qualitative data analysis techniques

Qualitative Analysis Methods play a crucial role in understanding human behavior and experiences. By focusing on the nuances of individuals’ thoughts and feelings, researchers can uncover insights that quantitative data alone may miss. This approach often involves gathering data through interviews, focus groups, and observations, allowing for a rich tapestry of information that highlights context and meaning.

In this section, we will explore various qualitative analysis techniques, each designed to interpret and derive meaningful patterns from qualitative data. Understanding these methods not only enhances research quality but also empowers practitioners to inform decision-making effectively. Emphasizing a people-centered approach, qualitative analysis fosters deeper insight into consumer perspectives and behaviors, proving essential in fields ranging from market research to psychology.

Key Qualitative Analysis Methods

Qualitative Analysis Methods encompass several approaches that help researchers draw meaningful insights from non-numerical data. One popular method is thematic analysis, which involves identifying and analyzing patterns or themes within the data. This approach enables researchers to summarize key findings and understand participants' perspectives in depth.

Another key method is grounded theory, where researchers explore underlying social processes or theories that emerge from the data itself. In this approach, analysis happens concurrently with data collection, allowing the theory to evolve based on the information gathered. Additionally, narrative analysis focuses on the stories participants tell, providing context and richness to their experiences. These techniques collectively enhance the understanding of qualitative data and facilitate a comprehensive interpretation of the human experience. Engaging with these methods not only enriches the analysis but also helps in capturing the nuances that quantitative measures might overlook.

Grounded Theory in Qualitative Analysis Methods

Grounded Theory is a powerful approach within qualitative analysis methods, focusing on generating theories directly from data rather than testing existing theories. This inductive methodology allows researchers to discover patterns and concepts by closely examining qualitative data, such as interviews or observations. By systematically coding the data, researchers can identify key themes and develop new theories that explain social phenomena.

The process involves several steps, including data collection, open coding, axial coding, and selective coding. First, researchers gather data without predefined categories. Next, they break the data into smaller segments to identify initial codes. Then, by connecting related codes, they form categories that highlight the relationships within the data. Finally, through selective coding, the core categories are identified and developed into a cohesive theory. This method enhances the depth and richness of qualitative analysis, making it particularly valuable for understanding complex human behaviors and social contexts.

Thematic Analysis in Qualitative Analysis Methods

Thematic analysis is a widely recognized method within qualitative analysis techniques. It involves identifying, analyzing, and reporting patterns or themes within qualitative data. This approach allows researchers to interpret various aspects of the data, providing a richly detailed understanding of participants’ perspectives and experiences. Through thematic analysis, one can distill extensive data sets into meaningful themes that reflect key insights drawn from the transcripts.

When performing thematic analysis, several essential steps are typically followed. First, researchers must familiarize themselves with the data by reading and re-reading transcripts or notes. Next, initial coding is conducted, where significant features of the data are highlighted. Subsequent phases include searching for themes, reviewing themes for coherence, and defining and naming these themes. Finally, the research findings can be articulated, providing a comprehensive narrative that reflects the qualitative analysis methods employed. This structured approach enables clarity and depth in presenting qualitative insights.

Implementing Qualitative Analysis Techniques

Implementing qualitative analysis techniques involves understanding and applying various qualitative analysis methods effectively. The first step is to collect data through interviews, focus groups, or observations, ensuring rich and detailed responses. After gathering the data, researchers should transcribe interviews and organize notes for analysis.

Next, coding the data is crucial. This involves identifying themes or patterns by tagging segments of text with codes that represent specific ideas. Researchers can then group similar codes together to form categories, which aids in identifying overarching themes. Finally, synthesizing the findings and interpreting the results allows researchers to draw meaningful insights.

These methods provide a structured approach to qualitative data analysis, making it accessible to both novice and experienced researchers. By following these steps, you can ensure your qualitative analysis method yields reliable and actionable insights.

Coding and Categorizing Data

Coding and categorizing data are vital steps in qualitative data analysis. This process enables researchers to systematically organize large amounts of information into manageable segments. Initially, coding involves identifying key concepts, themes, or patterns within the data by assigning labels to meaningful text. This stage allows researchers to highlight essential aspects that may emerge from interviews, focus groups, or open-ended survey responses.

Once coding is complete, researchers can categorize these codes into broader themes. This categorization helps clarify how different pieces of data relate to one another and contributes to a cohesive understanding of the findings. By employing these qualitative analysis methods, one can derive insights and develop interpretations, ultimately leading to actionable recommendations. This structured approach ensures that data analysis remains thorough and comprehensive, paving the way for a deeper understanding of the research subject.

Interpreting and Presenting Findings

Interpreting and presenting findings is a crucial aspect of qualitative analysis methods. This process involves examining collected data to uncover patterns, themes, and insights that inform decisions. The interpretation phase requires a careful assessment of the data's context, making sense of participant responses, and considering the broader implications of the findings.

Once the analysis is complete, presenting the findings effectively becomes essential. Using clear, engaging visual representations can enhance understanding and facilitate communication with stakeholders. Employing graphical elements, concise summaries, and well-organized reports can make the insights more accessible. Furthermore, tailoring the presentation to the audience’s needs ensures that the findings resonate and lead to informed actions. Overall, interpreting and presenting findings requires not only analytical skills but also creativity and clarity to convey valuable insights effectively.

Conclusion on Qualitative Analysis Methods

Qualitative Analysis Methods offer crucial insights into human behavior and perceptions, enriching our understanding of complex issues. These methods, such as thematic analysis and grounded theory, enable researchers to collect and interpret data in more nuanced ways. By focusing on participants' experiences, researchers can unveil patterns and themes that quantitative data might overlook.

The conclusion drawn from qualitative analysis emphasizes the importance of context and subjectivity in research. These methods transform raw data into meaningful narratives, highlighting the significance of human experiences. Ultimately, Qualitative Analysis Methods not only inform decision-making but also foster a deeper connection to the participants’ perspectives, enhancing the overall impact of research findings.

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Qualitative research examples: How to unlock, rich, descriptive insights

Qualitative research uncovers in-depth user insights, but what does it look like? Here are seven methods and examples to help you get the data you need.

Armin Tanovic

Behind every what, there’s a why . Qualitative research is how you uncover that why. It enables you to connect with users and understand their thoughts, feelings, wants, needs, and pain points.

There’s many methods for conducting qualitative research, and many objectives it can help you pursue—you might want to explore ways to improve NPS scores, combat reduced customer retention, or understand (and recreate) the success behind a well-received product. The common thread? All these metrics impact your business, and qualitative research can help investigate and improve that impact.

In this article, we’ll take you through seven methods and examples of qualitative research, including when and how to use them.

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7 Qualitative research methods: An overview

There are various qualitative UX research methods that can help you get in-depth, descriptive insights. Some are suited to specific phases of the design and development process, while others are more task-oriented.

Here’s our overview of the most common qualitative research methods. Keep reading for their use cases, and detailed examples of how to conduct them.

1. User interviews

A user interview is a one-on-one conversation between a UX researcher, designer or Product Manager and a target user to understand their thoughts, perspectives, and feelings on a product or service. User interviews are a great way to get non-numerical data on individual experiences with your product, to gain a deeper understanding of user perspectives.

Interviews can be structured, semi-structured, or unstructured . Structured interviews follow a strict interview script and can help you get answers to your planned questions, while semi and unstructured interviews are less rigid in their approach and typically lead to more spontaneous, user-centered insights.

When to use user interviews

Interviews are ideal when you want to gain an in-depth understanding of your users’ perspectives on your product or service, and why they feel a certain way.

Interviews can be used at any stage in the product design and development process, being particularly helpful during:

• The discovery phase: To better understand user needs, problems, and the context in which they use your product—revealing the best potential solutions
• The design phase: To get contextual feedback on mockups, wireframes, and prototypes, helping you pinpoint issues and the reasons behind them
• Post-launch: To assess if your product continues to meet users’ shifting expectations and understand why or why not

How to conduct user interviews: The basics

• Draft questions based on your research objectives
• Recruit relevant research participants and schedule interviews
• Conduct the interview and transcribe responses
• Analyze the interview responses to extract insights
• Use your findings to inform design, product, and business decisions

💡 A specialized user interview tool makes interviewing easier. With Maze Interview Studies , you can recruit, host, and analyze interviews all on one platform.

User interviews: A qualitative research example

Let’s say you’ve designed a recruitment platform, called Tech2Talent , that connects employers with tech talent. Before starting the design process, you want to clearly understand the pain points employers experience with existing recruitment tools'.

You draft a list of ten questions for a semi-structured interview for 15 different one-on-one interviews. As it’s semi-structured, you don’t expect to ask all the questions—the script serves as more of a guide.

One key question in your script is: “Have tech recruitment platforms helped you find the talent you need in the past?”

Most respondents answer with a resounding and passionate ‘no’ with one of them expanding:

“For our company, it’s been pretty hit or miss honestly. They let just about anyone make a profile and call themselves tech talent. It’s so hard sifting through serious candidates. I can’t see any of their achievements until I invest time setting up an interview.”

You begin to notice a pattern in your responses: recruitment tools often lack easily accessible details on talent profiles.

You’ve gained contextual feedback on why other recruitment platforms fail to solve user needs.

2. Focus groups

A focus group is a research method that involves gathering a small group of people—around five to ten users—to discuss a specific topic, such as their’ experience with your new product feature. Unlike user interviews, focus groups aim to capture the collective opinion of a wider market segment and encourage discussion among the group.

When to use focus groups

You should use focus groups when you need a deeper understanding of your users’ collective opinions. The dynamic discussion among participants can spark in-depth insights that might not emerge from regular interviews.

Focus groups can be used before, during, and after a product launch. They’re ideal:

• Throughout the problem discovery phase: To understand your user segment’s pain points and expectations, and generate product ideas
• Post-launch: To evaluate and understand the collective opinion of your product’s user experience
• When conducting market research: To grasp usage patterns, consumer perceptions, and market opportunities for your product

How to conduct focus group studies: The basics

• Draft prompts to spark conversation, or a series of questions based on your UX research objectives
• Find a group of five to ten users who are representative of your target audience (or a specific user segment) and schedule your focus group session
• Conduct the focus group by talking and listening to users, then transcribe responses
• Analyze focus group responses and extract insights
• Use your findings to inform design decisions

The number of participants can make it difficult to take notes or do manual transcriptions. We recommend using a transcription or a specialized UX research tool , such as Maze, that can automatically create ready-to-share reports and highlight key user insights.

Focus groups: A qualitative research example

You’re a UX researcher at FitMe , a fitness app that creates customized daily workouts for gym-goers. Unlike many other apps, FitMe takes into account the previous day’s workout and aims to create one that allows users to effectively rest different muscles.

However, FitMe has an issue. Users are generating workouts but not completing them. They’re accessing the app, taking the necessary steps to get a workout for the day, but quitting at the last hurdle.

Time to talk to users.

You organize a focus group to get to the root of the drop-off issue. You invite five existing users, all of whom have dropped off at the exact point you’re investigating, and ask them questions to uncover why.

A dialog develops:

Participant 1: “Sometimes I’ll get a workout that I just don’t want to do. Sure, it’s a good workout—but I just don’t want to physically do it. I just do my own thing when that happens.”

Participant 2: “Same here, some of them are so boring. I go to the gym because I love it. It’s an escape.”

Participant 3: “Right?! I get that the app generates the best one for me on that specific day, but I wish I could get a couple of options.”

Participant 4: “I’m the same, there are some exercises I just refuse to do. I’m not coming to the gym to do things I dislike.”

Conducting the focus groups and reviewing the transcripts, you realize that users want options. A workout that works for one gym-goer doesn’t necessarily work for the next.

A possible solution? Adding the option to generate a new workout (that still considers previous workouts)and the ability to blacklist certain exercises, like burpees.

3. Ethnographic research

Ethnographic research is a research method that involves observing and interacting with users in a real-life environment. By studying users in their natural habitat, you can understand how your product fits into their daily lives.

Ethnographic research can be active or passive. Active ethnographic research entails engaging with users in their natural environment and then following up with methods like interviews. Passive ethnographic research involves letting the user interact with the product while you note your observations.

When to use ethnographic research

Ethnographic research is best suited when you want rich insights into the context and environment in which users interact with your product. Keep in mind that you can conduct ethnographic research throughout the entire product design and development process —from problem discovery to post-launch. However, it’s mostly done early in the process:

• Early concept development: To gain an understanding of your user's day-to-day environment. Observe how they complete tasks and the pain points they encounter. The unique demands of their everyday lives will inform how to design your product.
• Initial design phase: Even if you have a firm grasp of the user’s environment, you still need to put your solution to the test. Conducting ethnographic research with your users interacting with your prototype puts theory into practice.

How to conduct ethnographic research:

• Recruit users who are reflective of your audience
• Meet with them in their natural environment, and tell them to behave as they usually would
• Take down field notes as they interact with your product
• Engage with your users, ask questions, or host an in-depth interview if you’re doing an active ethnographic study
• Collect all your data and analyze it for insights

While ethnographic studies provide a comprehensive view of what potential users actually do, they are resource-intensive and logistically difficult. A common alternative is diary studies. Like ethnographic research, diary studies examine how users interact with your product in their day-to-day, but the data is self-reported by participants.

⚙️ Recruiting participants proving tough and time-consuming? Maze Panel makes it easy, with 400+ filters to find your ideal participants from a pool of 3 million participants.

Ethnographic research: A qualitative research example

You're a UX researcher for a project management platform called ProFlow , and you’re conducting an ethnographic study of the project creation process with key users, including a startup’s COO.

The first thing you notice is that the COO is rushing while navigating the platform. You also take note of the 46 tabs and Zoom calls opened on their monitor. Their attention is divided, and they let out an exasperated sigh as they repeatedly hit “refresh” on your website’s onboarding interface.

You conclude the session with an interview and ask, “How easy or difficult did you find using ProFlow to coordinate a project?”

The COO answers: “Look, the whole reason we turn to project platforms is because we need to be quick on our feet. I’m doing a million things so I need the process to be fast and simple. The actual project management is good, but creating projects and setting up tables is way too complicated.”

You realize that ProFlow ’s project creation process takes way too much time for professionals working in fast-paced, dynamic environments. To solve the issue, propose a quick-create option that enables them to move ahead with the basics instead of requiring in-depth project details.

4. Qualitative observation

Qualitative observation is a similar method to ethnographic research, though not as deep. It involves observing your users in a natural or controlled environment and taking notes as they interact with a product. However, be sure not to interrupt them, as this compromises the integrity of the study and turns it into active ethnographic research.

When to qualitative observation

Qualitative observation is best when you want to record how users interact with your product without anyone interfering. Much like ethnographic research, observation is best done during:

• Early concept development: To help you understand your users' daily lives, how they complete tasks, and the problems they deal with. The observations you collect in these instances will help you define a concept for your product.
• Initial design phase: Observing how users deal with your prototype helps you test if they can easily interact with it in their daily environments

How to conduct qualitative observation:

• Recruit users who regularly use your product
• Meet with users in either their natural environment, such as their office, or within a controlled environment, such as a lab
• Observe them and take down field notes based on what you notice

Qualitative observation: An qualitative research example

You’re conducting UX research for Stackbuilder , an app that connects businesses with tools ideal for their needs and budgets. To determine if your app is easy to use for industry professionals, you decide to conduct an observation study.

Sitting in with the participant, you notice they breeze past the onboarding process, quickly creating an account for their company. Yet, after specifying their company’s budget, they suddenly slow down. They open links to each tool’s individual page, confusingly switching from one tab to another. They let out a sigh as they read through each website.

Conducting your observation study, you realize that users find it difficult to extract information from each tool’s website. Based on your field notes, you suggest including a bullet-point summary of each tool directly on your platform.

5. Case study research

Case studies are a UX research method that provides comprehensive and contextual insights into a real-world case over a long period of time. They typically include a range of other qualitative research methods, like interviews, observations, and ethnographic research. A case study allows you to form an in-depth analysis of how people use your product, helping you uncover nuanced differences between your users.

When to use case studies

Case studies are best when your product involves complex interactions that need to be tracked over a longer period or through in-depth analysis. You can also use case studies when your product is innovative, and there’s little existing data on how users interact with it.

As for specific phases in the product design and development process:

• Initial design phase: Case studies can help you rigorously test for product issues and the reasons behind them, giving you in-depth feedback on everything between user motivations, friction points, and usability issues
• Post-launch phase: Continuing with case studies after launch can give you ongoing feedback on how users interact with the product in their day-to-day lives. These insights ensure you can meet shifting user expectations with product updates and future iterations

How to conduct case studies:

• Outline an objective for your case study such as examining specific user tasks or the overall user journey
• Select qualitative research methods such as interviews, ethnographic studies, or observations
• Collect and analyze your data for comprehensive insights
• Include your findings in a report with proposed solutions

Case study research: A qualitative research example

Your team has recently launched Pulse , a platform that analyzes social media posts to identify rising digital marketing trends. Pulse has been on the market for a year, and you want to better understand how it helps small businesses create successful campaigns.

To conduct your case study, you begin with a series of interviews to understand user expectations, ethnographic research sessions, and focus groups. After sorting responses and observations into common themes you notice a main recurring pattern. Users have trouble interpreting the data from their dashboards, making it difficult to identify which trends to follow.

With your synthesized insights, you create a report with detailed narratives of individual user experiences, common themes and issues, and recommendations for addressing user friction points.

Some of your proposed solutions include creating intuitive graphs and summaries for each trend study. This makes it easier for users to understand trends and implement strategic changes in their campaigns.

6. Secondary research

Secondary research is a research method that involves collecting and analyzing documents, records, and reviews that provide you with contextual data on your topic. You’re not connecting with participants directly, but rather accessing pre-existing available data. For example, you can pull out insights from your UX research repository to reexamine how they apply to your new UX research objective.

Strictly speaking, it can be both qualitative and quantitative—but today we focus on its qualitative application.

When to use secondary research

Record keeping is particularly useful when you need supplemental insights to complement, validate, or compare current research findings. It helps you analyze shifting trends amongst your users across a specific period. Some other scenarios where you need record keeping include:

• Initial discovery or exploration phase: Secondary research can help you quickly gather background information and data to understand the broader context of a market
• Design and development phase: See what solutions are working in other contexts for an idea of how to build yours

Secondary research is especially valuable when your team faces budget constraints, tight deadlines, or limited resources. Through review mining and collecting older findings, you can uncover useful insights that drive decision-making throughout the product design and development process.

How to conduct secondary research:

• Outline your UX research objective
• Identify potential data sources for information on your product, market, or target audience. Some of these sources can include: a. Review websites like Capterra and G2 b. Social media channels c. Customer service logs and disputes d. Website reviews e. Reports and insights from previous research studies f. Industry trends g. Information on competitors
• Analyze your data by identifying recurring patterns and themes for insights

Secondary research: A qualitative research example

SafeSurf is a cybersecurity platform that offers threat detection, security audits, and real-time reports. After conducting multiple rounds of testing, you need a quick and easy way to identify remaining usability issues. Instead of conducting another resource-intensive method, you opt for social listening and data mining for your secondary research.

Browsing through your company’s X, you identify a recurring theme: many users without a background in tech find SafeSurf ’s reports too technical and difficult to read. Users struggle with understanding what to do if their networks are breached.

After checking your other social media channels and review sites, the issue pops up again.

With your gathered insights, your team settles on introducing a simplified version of reports, including clear summaries, takeaways, and step-by-step protocols for ensuring security.

By conducting secondary research, you’ve uncovered a major usability issue—all without spending large amounts of time and resources to connect with your users.

7. Open-ended surveys

Open-ended surveys are a type of unmoderated UX research method that involves asking users to answer a list of qualitative research questions designed to uncover their attitudes, expectations, and needs regarding your service or product. Open-ended surveys allow users to give in-depth, nuanced, and contextual responses.

When to use open-ended surveys

User surveys are an effective qualitative research method for reaching a large number of users. You can use them at any stage of the design and product development process, but they’re particularly useful:

• When you’re conducting generative research : Open-ended surveys allow you to reach a wide range of users, making them especially useful during initial research phases when you need broad insights into user experiences
• When you need to understand customer satisfaction: Open-ended customer satisfaction surveys help you uncover why your users might be dissatisfied with your product, helping you find the root cause of their negative experiences
• In combination with close-ended surveys: Get a combination of numerical, statistical insights and rich descriptive feedback. You’ll know what a specific percentage of your users think and why they think it.

How to conduct open-ended surveys:

• Design your survey and draft out a list of survey questions
• Distribute your surveys to respondents
• Analyze survey participant responses for key themes and patterns
• Use your findings to inform your design process

Open-ended surveys: A qualitative research example

You're a UX researcher for RouteReader , a comprehensive logistics platform that allows users to conduct shipment tracking and route planning. Recently, you’ve launched a new predictive analytics feature that allows users to quickly identify and prepare for supply chain disruptions.

To better understand if users find the new feature helpful, you create an open-ended, in-app survey.

The questions you ask your users:

• “What has been your experience with our new predictive analytics feature?"
• “Do you find it easy or difficult to rework your routes based on our predictive suggestions?”
• “Does the predictive analytics feature make planning routes easier? Why or why not?”

Most of the responses are positive. Users report using the predictive analytics feature to make last-minute adjustments to their route plans, and some even rely on it regularly. However, a few users find the feature hard to notice, making it difficult to adjust their routes on time.

To ensure users have supply chain insights on time, you integrate the new feature into each interface so users can easily spot important information and adjust their routes accordingly.

💡 Surveys are a lot easier with a quality survey tool. Maze’s Feedback Surveys solution has all you need to ensure your surveys get the insights you need—including AI-powered follow-up and automated reports.

Qualitative research vs. quantitative research: What’s the difference?

Alongside qualitative research approaches, UX teams also use quantitative research methods. Despite the similar names, the two are very different.

Here are some of the key differences between qualitative research and quantitative research .

Before selecting either qualitative or quantitative methods, first identify what you want to achieve with your UX research project. As a general rule of thumb, think qualitative data collection for in-depth understanding and quantitative studies for measurement and validation.

Conduct qualitative research with Maze

You’ll often find that knowing the what is pointless without understanding the accompanying why . Qualitative research helps you uncover your why.

So, what about how —how do you identify your 'what' and your 'why'?

The answer is with a user research tool like Maze.

Maze is the leading user research platform that lets you organize, conduct, and analyze both qualitative and quantitative research studies—all from one place. Its wide variety of UX research methods and advanced AI capabilities help you get the insights you need to build the right products and experiences faster.

Frequently asked questions about qualitative research examples

What is qualitative research?

Qualitative research is a research method that aims to provide contextual, descriptive, and non-numerical insights on a specific issue. Qualitative research methods like interviews, case studies, and ethnographic studies allow you to uncover the reasoning behind your user’s attitudes and opinions.

Can a study be both qualitative and quantitative?

Absolutely! You can use mixed methods in your research design, which combines qualitative and quantitative approaches to gain both descriptive and statistical insights.

For example, user surveys can have both close-ended and open-ended questions, providing comprehensive data like percentages of user views and descriptive reasoning behind their answers.

Is qualitative or quantitative research better?

The choice between qualitative and quantitative research depends upon your research goals and objectives.

Qualitative research methods are better suited when you want to understand the complexities of your user’s problems and uncover the underlying motives beneath their thoughts, feelings, and behaviors. Quantitative research excels in giving you numerical data, helping you gain a statistical view of your user's attitudes, identifying trends, and making predictions.

What are some approaches to qualitative research?

There are many approaches to qualitative studies. An approach is the underlying theory behind a method, and a method is a way of implementing the approach. Here are some approaches to qualitative research:

• Grounded theory: Researchers study a topic and develop theories inductively
• Phenomenological research: Researchers study a phenomenon through the lived experiences of those involved
• Ethnography: Researchers immerse themselves in organizations to understand how they operate

• Open access
• Published: 20 August 2024

Advice to future family physicians: findings from qualitative interviews with family medicine residents and early-career family physicians

• Sean Wang 1 ,
• Richard Buote 1 ,
• Lauren R. Moritz 1 ,
• M. Ruth Lavergne 1 &
• Emily Gard Marshall 1  

BMC Medical Education volume  24 , Article number:  897 ( 2024 ) Cite this article

Metrics details

Canadians continue to report challenges accessing primary care. Practice choices made by primary care providers shape services available to Canadians. Although there is literature observing family medicine practice trends, there is less clarity on the reasoning underlying primary care providers’ practice intentions. Advice offered by residents and early-career family physicians may reveal challenges they have experienced, how they have adapted to them, and strategies for new residents. In this paper, we examine advice family medicine residents and early-career family physicians would give to new family medicine residents.

Sixty early-career family physicians and thirty residents were interviewed as part of a mixed-methods study of practice patterns of family medicine providers in Canada. During qualitative interviews, participants were asked, “what advice would you give [a new family medicine resident] about planning their career as a family physician?” We inductively analyzed responses to this question.

Advice consisted of understanding the current climate of family medicine (need for specialization, business management burden, physician burnout) and revealed reasons behind said challenges (lack of support for comprehensive clinic care, practical limitations of different practice models, and how payment models influence work-life balance). Subtheme analyses showed early-career family physicians being more vocal on understanding practical aspects of the field including practice logistics and achieving job security.

Most advice mirrored current changes and challenges as well as revealing strategies on how primary care providers are handling the realities of practicing family medicine. Multi-modal systemic interventions may be needed to support family physicians throughout the changing reality of family medicine and ensure family medicine is an appealing specialty.

Peer Review reports

Primary care access is essential to ensure good population health outcomes and reduce health disparities [ 1 ]. Within the Canadian health system, primary care providers, such as family physicians, are the first point of contact, acting as “gatekeepers” to other aspects of the healthcare system, including specialist care [ 2 , 3 , 4 ]. However, Canadians increasingly report challenges accessing primary care, shown by a steady increase in the number of Canadians without a regular primary care provider [ 5 , 6 ]. Strains on primary care appear to have worsened during the COVID-19 pandemic, with higher numbers of family physicians leaving their practice during the pandemic compared to pre-pandemic. [ 7 ] There is a need to understand what is driving challenges in primary care access and influencing the choices made by primary care providers.

Over the past several decades, there have been substantial changes in practice patterns among family physicians. Compared to 1997/1998, today’s practicing family physicians have fewer contacts with patients, and fewer family physicians provide comprehensive primary care [ 8 , 9 , 10 ]. A variety of factors (e.g., health policy, patient population, practice setting, advice received as a trainee) [ 11 , 12 ] may influence these practice patterns. While we have examined current practice trends in family medicine, there is less clarity on how and why primary care providers are adapting to the practice environment in different ways. The experiences of family medicine residents and early-career family physicians and the advice they would offer to people entering residency programs may provide insight into factors shaping practice intentions and choices and, by extension, access to primary care [ 13 ].

Advice given by experienced family physicians to trainees at pivotal decision-making stages may shape practice decisions and trajectories of these learners, including scope of practice and academic involvement [ 12 , 14 ]. Advice can also prepare trainees for the realities of managing a practice, readying them for making logistical, fiscal, and human resource decisions [ 15 ]. In this study, we examine the types of advice early-career family physicians and family practice residents would offer to new family medicine residents. Findings from this study may provide insight into the existing challenges in family medicine and how these challenges may be shaping practice intentions.

Study design and population

We analyzed a subset of qualitative interview data from a larger mixed-methods study ( Practice patterns among early-career primary care physicians [ECPC] ) which explored factors contributing to practice intentions of early-career family physicians and family medicine residents across three Canadian provinces: British Columbia (BC), Ontario (ON), and Nova Scotia (NS). The complete study protocol has been published previously [ 16 ].

Participants were recruited via provincial medical association newsletters, family medicine residency programme email lists, and social media (Twitter and Facebook). To be included in the study, participants had to be a current family medicine resident or a family physician who had completed their family medicine residency between 2008 and 2018 and were currently practicing. Only those practicing in BC, ON, or NS were eligible. Prospective study participants completed a demographic screening questionnaire to ensure they met the inclusion criteria for the study. This questionnaire (Appendix 1 ) also served to facilitate diverse purposeful sampling based upon previously identified characteristics (i.e., gender, rurality, specialization, practice/training location, practice type/model, relationship status, and whether they have dependents) [ 16 ]. During recruitment, 359 residents and family physicians completed the demographic screening questionnaire. To ensure maximum variation, of those who completed the questionnaire, 32 family medicine residents and 69 early-career family physicians were purposively selected to participate in the study based on their responses to the screening questionnaire. Interviews were completed with 31 of 32 family medicine residents and 63 of 69 early-career family physicians invited to participate across the three Canadian provinces. Seven interviews were declined due to scheduling conflicts, lack of response, or an undisclosed reason. Participants were offered an honorarium.

Data collection

Semi-structured, ~ 1-hour, in-depth telephone interviews (Appendix 2 ) were conducted to understand the practice patterns and motivations of early-career family physicians and family medicine residents in BC, ON, and NS. Interviews were conducted by experienced qualitative interviewers (one per province), at a time suitable for participants, thereby engaging more geographically diverse interviewees with lower overall costs. Interviews were audio-recorded and transcribed verbatim, removing personally identifiable information.

Data analysis

Data were coded according to a robust coding framework developed by three experienced qualitative research analysts and supported by the principal investigators for the study. For the purpose of this paper, thematic analysis was performed by two analysts on the code “advice given to residents,” which corresponded to the interview question; “If you were mentoring a new family medicine resident , what advice would you give them about planning their career as a family physician?” Relevant excerpts were reviewed and analyzed independently by two analysts (SW, LRM), who identified initial themes. Refinements were made to the initial themes through discussion among analysts (SW, RB, LRM) and three general themes, with multiple subthemes, were agreed upon. Themes were finalized through discussion and support of all authors (SW, RB, LRM, MRL, EGM). This study was approved by the Simon Fraser University (#H18-03291), University of Ottawa (#S-05-18-776), and Nova Scotia Health Authority research ethics boards (#1023561).

Out of the 94 participants from the ECPC study, 60 early-career family physicians and 30 family medicine residents (90 total; 30 from BC, 30 from NS, 30 from ON) shared advice they could offer to family medicine residents and were included in this analysis. Table  1 shows the demographic and practice characteristics of participants. Participants practiced in a variety of settings and models. Men and women were interviewed, most of whom were partnered, and some cared for dependents (primarily children). Participants of this study did not agree for their individual data to be shared publicly, so supporting data are not available.

Family physicians and residents provided many pieces of advice to potential family medicine residents. We identified three themes in the data: (1) advice on the importance of having diverse practice experiences; (2) advice on the unanticipated aspects of family medicine; and (3) advice on taking care of yourself while practicing family medicine.

Theme 1. Advice on the importance of having diverse practice experiences

Participants who were early-career family physicians and residents emphasized the importance of experiencing a diversity of practice settings and fields. A family physician advised that residents should spend time “test[ing] the waters ” and finding “where you feel that you fit and you’re happy.” (Family Physician, BC). As one participant explained:

“I’d tell them to do as many electives in different places and experience as many different types of clinics and types of practices that they can… I never would have thought that I could be doing what I was doing. I sort of thought buying into a practice was sort of your only option… And I honestly tell people… don’t commit to something right away… there are so many opportunities out there that you’re not exposed to.” (Family Physician, BC).

Several participants recommended that residents should locum first to gain experience across a variety of family medicine models, communities, and specialties. By locuming, new physicians can “get the sense of how you want to schedule your day… You’re working with different types of administrators. You’re not having to work with your own administrators. So , you can figure out who you want to hire in a secretary or if you need more than one secretary… you get to see what it’s like either in a collaborative or a solo practice… see different areas , get different experiences as a working physician.” (Family Physician, NS).

Locum work can provide new family physicians with the opportunity to “try” out potential future practice locations “before putting roots down” (Family Physician, NS). A family physician said that residents should know “… it’s okay to locum and try out different types of models because at the end of the day , I hope that everyone can find the passion to do what they do in a model where they love how they get to practice medicine.” (Family Physician, ON).

Interviewees advised that residents seek variety in areas of practice such as emergency and obstetrics and experience practicing in rural areas, where one can “really see what the breadth of family medicine is” (Resident, ON). Experience in other areas of medicine can offer family physicians “flexibility” in their practice. As a resident said, “…you can work in a diverse number of environments… plus the operating room , palliative , long-term care , geriatrics… it’s so diverse… you just have to find as many opportunities as possible and build sort the practice you want…” (Resident, ON).

Theme 2. Advice on the unanticipated aspects of family medicine

The business of family medicine.

Participants would advise residents on areas of knowledge not necessarily taught in the formal medical school curriculum but represented the realities of working as a family physician. Family physicians and residents noted a dearth of formal education about the “business” of family medicine and described situations where they learned by doing. Advice from early-career family physician participants in our study emphasized that new family physicians need to expose themselves to “lots of learning around billing and management” (Family Physician, NS) to better perform administrative tasks revolving around their future practices (e.g., billing, insurance, contract negotiations, starting financial planning early, get occupational health and safety training, and learn how to hire and fire staff). Billing is a necessary part of family medicine for fee-for-service physicians, but is not formally taught in medical school or postgraduate training. As one participant stated, “No one taught me how to bill. That was a disaster – learning how to do that.” (Family Physician, NS). Advice was given to “… talk to preceptors that you work with and see … how do they handle hiring and firing people … how do they schedule … the logistics of being a family doctor” and “know who are support people are and who can advocate for you.” (Resident, NS).

Realities of working under different models

Interviewees not only detailed that learning the administrative duties of a family physician is critical for effectively running their family medicine practice, but they also emphasized the difficulties and limitations that come with working within the current payment and practice models offered. For instance, interviewees discussed how the business side of family medicine intersected with their well-being. For example, new family physicians might need to create time for vacation when working in solo practice, but “ You need to find somebody to cover for you in that kind of model. So yeah , I don’t know that I can fully endorse that kind of work. But I think it is the most personally and professionally valuable” (Family Physician, BC). Another interviewee suggested that new family physicians should consider how pay might influence work-life balance: “I make twice as much per hour [working in emergency medicine] as working in a clinic. So , I can work half as much and have time for myself and my wife or kids or whatever’s in the future.” (Family Physician, BC).

Not all interviewees were responsible for their own clinic, but many provided advice about the business of family medicine. Early-career family physician and resident participants in our study advised that physicians must be careful about the contracts they sign and the agreements they make. As one participant explained:

“… avoid committing yourself to any contracts … I see so many new grads being taken advantage of all the time … they’re basically taking advantage of new grads who don’t have that knowledge.” (Family Physician, BC).

Because it can be challenging to navigate the business of family medicine, a resident advised that other residents should “… not just jump into the first offer that you’re given … you want to make sure that you’re not being over-worked. You want to make sure that you’re being compensated properly… aware of your call schedule… to know who your support people are, or who can, advocate for you. So , whether that’s [your provincial professional association] , whether it’s other physicians.” (Resident, NS).

Relevancy of and support for family medicine

Family physicians and residents recommended that new residents have an awareness of the relevancy of, and support for, family medicine . Some interviewees voiced their frustration with the lower level of support family physicians receive, describing their profession as “eroding” and that residents should consider whether they want to do family medicine. As one participant explained, “ I could see it becoming less and less relevant. You know , being a generalist… That’s what I’m afraid of… So , I think I would tell them to have a back-up plan… a different skillset in medicine.” (Family Physician, NS). Thus, to prevent the erosion of the family medicine profession and ensure it remains relevant, participants were urged to “keep advocating for fee parity and improvements in family medicine” (Family Physician, BC).

Complexity of family medicine

Furthermore, participants often discussed the high and increasing complexity of family medicine. Interviewees described how family physicians are responsible for caring for increasingly complex patients “ due to the [family physician] shortage… or the long timelines to get people into specialists.” (Family Physician, NS). Because of the perceived growing expectations of family physicians, an interviewee advised that residents should “go easy on yourself” as there is a “tendency of that [frustration] in family medicine because all the problems always come back to us , ” suggesting that once specialists have exhausted all of their options, the onus falls back on the family physician to decide “now what are you going to do about it?” (Family Physician, NS).

Participants also discussed important considerations about working with patients. As one interviewee described, “… don’t… under-estimate… a patient’s knowledge of themselves even if it doesn’t fall into a guideline” (Family Physician, NS), going on to imply the importance of considering the patients’ preferences in treatment.

As one participant described, the medical complexity of family medicine requires a flexible schedule, with consideration of patients with urgent or emergent needs, “… there’s lots of surprises that come in in family medicine… you have to allow a little bit of flexibility in the schedule for urgent people you need to fit in , or people that come in with chest pain , or suicidality , or things like that. So , it’s teaching around… being flexible and giving people the time when they need it. But also teaching residents and learners that sometimes you just have to set down some ground rules with patients for their own benefit sometimes.” (Family Physician, NS).

Importance of lifelong learning

Participants also emphasized the importance of lifelong learning in family medicine, sharing that “… the minute that I think that I know everything about a subject is probably when I do something that I don’t mean to do and potentially harm a patient.” (Family Physician, ON).

One participant advised future residents to “ expect change throughout your career… [w]hether that’s government changes , whether it’s the advent of AI and technology…” (Family Physician, ON).

Perceived need to specialize within family medicine

Finally, not only were family medicine residents advised to be flexible and expect change throughout their careers, but participants also urged residents to specialize within an area of family medicine to stay afloat . As a resident explained, “I think the nature of family medicine is changing , and increasingly so , there are less and less true general practitioners. And so , if you don’t carve something out that you’re interested in , I think you kind of get lost in the shuffle” (Resident, BC). Participants recommended that residents narrow their practice into a subspecialty like “sports medicine or addictions” (Family Physician, BC) and that residents “…could apply for enhanced training skills or a plus one program to help develop those skills and make them more competitive after they’re done their training” (Resident, NS).

Theme 3. Advice on taking care of yourself while practicing family medicine

Participants offered several pieces of advice for residents to understand how to take care of themselves in family medicine . Of particular concern to participants was preventing burnout. Strategies for avoiding burnout included not “jump[ing] right into a practice” (Family Physician, BC), “find[ing] a niche… Something you can do to get a good balance in your career and so you don’t burn out.” (Resident, ON), and “… guarding… personal and private time.” (Family Physician, NS).

Many participants suggested that new family medicine residents need to prioritize work/life balance . Family physician and resident participants discussed how general, full-time family medicine can lead to little personal flexibility and dissatisfaction with work and burnout. As a participant advised, “I would tell them to design their life first and then find an area within family medicine , whether that’s clinic or otherwise , that will let them actually live the life they want. Because if you just sign up to be a doctor first , you can work endlessly and not have any time for yourself” (Family Physician, BC).

Many participants discussed difficulties managing work and personal considerations and how poor balance in these areas can result in physicians leaving the profession. Participants provided advice for residents about planning for the future, with several participants suggesting that new residents should build their practice starting smaller, including core interests and then “build from that. If you find you have room in your life , then add the second or third thing. Because it’s a lot easier to build up than it is to say no.” (Family Physician, NS). Similarly, some participants advised that residents envision their personal goals and “work backwards.” As this participant suggested, “picture where you want to be in 10 to 20 years , and then kind of plant the seeds.” (Family Physician NS). Having a mentor or role model may help with this: “… find people whose work-life balance reflects your own values. And then strive to follow a similar path.” (Family Physician, BC).

Overall, participants advised that residents should find personal satisfaction in their work and “end up with a career that you are truly passionate about and that you love” (Resident NS). As previously mentioned, there was a substantial amount of advice provided on obtaining experience in a variety of areas. One participant advised that residents should “… understand… the aspects of the work that you enjoy the most. And then you can use that to guide where you end up working. So , do you like having longitudinal relationships? Do you like quick diagnostics? Do you… like to do procedures? Do you like the complexity of working in resource-limited spaces?” (Family Physician, BC). As participants described, it is essential that residents spend time finding what they like and dislike about their job because “how am I going to be able to provide the care that I want to be able to provide to my patients without feeling angry or bitter or whatever it is about the system?” (Family Physician, ON) and “no one’s going to give you a medal at the end of 30 years for making yourself miserable.” (Family Physician, BC).

Subtheme 1. Advice comparison between providers, provinces, and genders

Responses from both residents and early-career family physicians were examined showing many similarities in the advice that they would give incoming residents. Common themes include finding work-life balance, being open-minded, becoming a mentor, finding self-fulfillment, being aware of pre-mature commitment, the need for practice specialization, importance of patient advocacy, and preventing burnout. Early-career family physicians were more likely to emphasize the importance of understanding practice logistics and achieving job security.

Between the three provinces, the advice participants would give are similar, with NS and ON emphasizing the importance of practice logistics and job security more than BC. Otherwise, all provinces gave similar advice on finding work-life balance, being open-minded, becoming a mentor, finding self-fulfillment, being aware of pre-mature commitment, the need for practice specialization, importance of patient advocacy, and preventing burnout.

Responses from both genders of participants showed commonality in discussing advice on finding work-life balance, being open-minded, becoming a mentor, finding self-fulfillment, being aware of pre-mature commitment, the need for practice specialization, the importance of understanding practice logistic, and preventing burnout. Male providers emphasized more about the importance of patient advocacy and achieving job security.

The advice early-career family physicians and family medicine residents would offer to new family medicine residents provides insight into not only the present challenges and opportunities in family medicine, but also how these factors influence their decision-making and adaptation processes in clinical practice. We found that the advice of early-career family physicians aligned with previous research, as we identified themes within our interviews such as challenges of staff management, coping with burnout, and the increased responsibility of family physicians to care for an increasingly complex patient population [ 9 , 12 , 14 ]. Importantly, our research provides new insight into the reasoning behind the these themes, including the perceived necessity for specialization within family practice, need for readiness in advancing technologies and health informatics, and advocacy for structural changes such as remuneration parity. Last, we examined differences between residents and early-career physicians. While themes of advice were similar, more emphasis was placed on practice logistics and job security by early-career physicians than residents.

Our first overarching theme of need for seeking diverse experiences in family medicine has previously been identified with fewer family physicians committing to and offering comprehensive primary care [ 13 ], and a greater number of family physicians are working under a specialized scope of practice, partitioning their practice into specific fields of interest, such as obstetrics, surgical assist, small procedures, and emergency medicine [ 11 , 13 , 16 , 26 , 27 ]. Our findings add to the current literature by demonstrating the reasoning behind this trend of specialized rather than generalized family practice; such that, family physicians may be doing this to remain competitive with respect to pay, reduce burnout with regards to schedule flexibility and evade contractual agreements that try to take advantage of new graduates [ 8 , 13 ]. The insight gained from this advice allows health system planners and decision-makers to understand the factors considered by family physicians in how they practice and address the concerns in their policy-making, thereby attracting more family physicians to practice comprehensive clinic care.

We secondly demonstrated that family physicians and residents face a practice environment that poses challenges not only with clinically complex patients [ 23 , 24 , 25 ] but also developing a detailed understanding of practice logistics and business [ 20 ]. Our participants not only identify the gaps in education on financial planning, technological advances, and compensation, but strategies in which they take to mitigate these challenges and optimize clinical care for their patients. For instance, providers can take advantage of variety of scheduling, areas of focus, and practice models [ 17 ]. A novel finding in our study shows an emphasis on seeking preceptors that act as mentors in learning business management. This demonstrates an important wealth of knowledge on the administrative practice of family medicine, as formal curriculum in such topics are not concretely implemented in training [ 15 , 16 , 21 , 22 ]. Finding mentorship from preceptors is especially important as our results demonstrate that residents are less likely to be concerned about practice logistics and job security than staff physicians. In brief, participants demonstrate that challenges endured by family physicians can be explored through taking advantage of practice flexibility and informal mentorship. Formal education may need to be more agile to train new cohorts of family physicians in a changing primary care landscape.

Family physicians and residents’ well-being and burnout prevention is a commonly identified theme in previous literature [ 14 , 18 , 19 ]. Interestingly, our interviewees recommended that in order to prevent burnout, new family physicians ought to focus on both structural and personal strategies such as start their career with a part-time practice and build up from there, designing their practice around the type of lifestyle they wish to have and ultimately practicing the aspects of family medicine they genuinely enjoy and value. However, participants noted that the current capacity of organizational and funding models available for family physicians limits their opportunities. A specific example includes being compensated fairly for their practice, with participants detailing the difficulties of specific family medicine remuneration models, such as the inflexibility of taking vacation time in a solo fee-for-service practice, or how specialized compared to general family practice is compensated relatively higher. This is supported by previous research, which suggests that fee-for-service remuneration models may discourage the practice of comprehensive family medicine [ 13 ]. Parity in pay may help family physicians feel more valued within the health system and encourage them to provide primary care services that are desperately needed within the Canadian health system [ 20 ]. It is evident that strategies to combat physician burnout is limited without policy changes to adequately fund comprehensive family practice.

In all, our study confirms previous research which found that the need for specialization, clinical complexity, burnout, and job logistics amalgamate, forming ongoing concerns for family medicine residents [ 14 ]. Not only does it emphasize these themes, it identifies motives, strategies, and reasoning behind the practice patterns and trends of current family physicians and how they adapt to current challenges and opportunities. While participants shared many positive aspects of family medicine, they focused significantly on the perils and challenges of practicing family medicine. When we are in a time of needing to increase the number of family physicians to meet the primary care needs of patients across the country, it may be important to reflect on how more experienced family physicians influence trainees away from family practice and the need to advocate for improvements in primary care such as revising formal curriculum to include non-clinical aspects of practice, parity in remuneration, and mentorship supports for new family physicians. Individual-level interventions are not enough to counter system-level challenges. Systemic interventions will be needed if system decision-makers wish to encourage greater involvement in comprehensive family medicine [ 26 , 28 , 29 , 30 ].

Advice from early-career family physicians and senior family medicine residents to new family medicine residents emphasized the importance of taking advantage of early-career opportunities, understanding the realities and complexities of modern family medicine, and advocating for personal well-being and satisfaction. Our results also revealed the strategies and decision-making behind the current family medicine curriculum and practice trends. Systemic intervention is needed to support family physicians throughout their entire careers to allow them to practice in a way that is personally and professionally fulfilling while supporting their lifelong learning in an ever-changing field.

Data availability

The datasets supporting the conclusions of this article are included within the article.

Abbreviations

British Columbia

Nova Scotia

Continuing Medical Education

Starfield B, Shi L, Macinko J. Contribution of primary care to health systems and health. Milbank Q. 2005;83(3):457–502. https://doi.org/10.1111/j.1468-0009.2005.00409.x .

Article   Google Scholar  

Starfield B. Primary care: an increasingly important contributor to effectiveness, equity, and efficiency of health services. SESPAS Report 2012. Gac Sanit. 2012;26:20–6. https://doi.org/10.1016/j.gaceta.2011.10.009 .

Scotia DN, Nova Scotia College of Family Physicians. The backbone of primary health care: The role and value of family physicians in Nova Scotia [Internet]. Nova Scotia, Canada; 2019 [cited 2021 Sep 23]. https://doctorsns.com/sites/default/files/2019-01/next-steps/Role-of-Family-Physician-position-paper.pdf

Allin S, Marchildon G, Peckham A. International health care system profiles: Canada [Internet]. The Commonwealth Fund; 2020 [cited 2021 Sep 23]. https://www.commonwealthfund.org/international-health-policy-center/countries/canada

Statistics Canada. Tables 105–0508 - Canadian health characteristics, annual estimates, by age group and sex, Canada (excluding territories) and provinces. [Internet]. 2018 [cited 2020 Jan 16]. https://www150.statcan.gc.ca/t1/tbl1/en/tv.action?pid=1310009601

Canadian Institute for Health Information (CIHI). How Canada compares: Results from the Commonwealth Fund’s 2016 International Health Policy Survey of Adults in 11 Countries [Internet]. Ottawa, ON: CIHI. 2017. https://www.cihi.ca/en/health-system-performance/performance-reporting/international/wait-times-for-primary-and-specialist

Kiran T, Green ME, Wu FC, Kopp A, Latifovic L, Frymire E et al. Did the COVID-19 pandemic result in more family physicians stopping practice? Results from Ontario, Canada [Internet]. medRxiv; 2021 [cited 2022 Aug 8]. p. 2021.09.21.21263891. https://www.medrxiv.org/content/10.1101/2021.09.21.21263891v1

Marshall EG, Horrey K, Moritz LR, Buote R, Grudniewicz A, Goldsmith LJ, et al. Influences on intentions for obstetric practice among family physicians and residents in Canada: an explorative qualitative inquiry. BMC Pregnancy Childbirth. 2022;22(1):857. https://doi.org/10.1186/s12884-022-05165-1 .

Chan BTB. The declining comprehensiveness of primary care. CMAJ. 2002;166(4):429–34. https://www.cmaj.ca/content/166/4/429 .

Google Scholar  

Rudoler D, Peterson S, Stock D, Taylor C, Wilton D, Blackie D, et al. Changes over time in patient visits and continuity of care among graduating cohorts of family physicians in 4 Canadian provinces. CMAJ. 2022;194(48):E1639–46. https://www.cmaj.ca/content/194/48/E1639 .

Reitz R, Horst K, Davenport M, Klemmetsen S, Clark M. Factors influencing family physician scope of practice: a grounded theory study. Fam Med. 2018;50(4):269–74. https://doi.org/10.22454/fammed.2018.602663 .

Russell A, Fromewick J, Macdonald B, Kimmel S, Franke K, Leach K, et al. Drivers of scope of practice in family medicine: a conceptual model. Annals Family Med. 2021;19(3):217–23. https://doi.org/10.1370/afm.2669 .

Kabir M, Randall E, Mitra G, Lavergne MR, Scott I, Snadden D, et al. Resident and early-career family physicians’ focused practice choices in Canada: a qualitative study. Br J Gen Pract. 2022;72(718):e334–41. https://doi.org/10.3399/bjgp.2021.0512 .

Lin S, Nguyen C, Walters E, Gordon P. Residents’ perspectives on careers in academic medicine: obstacles and opportunities. Fam Med. 2018;50(3):204–11. https://doi.org/10.22454/fammed.2018.306625 .

Brown JB, Thorpe C, Paquette-Warren J, Stewart M, Kasperski J. The mentoring needs of trainees in family practice. Educ Prim Care. 2012;23(3):196–203. https://doi.org/10.1080/14739879.2012.11494103 .

Lavergne MR, Goldsmith LJ, Grudniewicz A, Rudoler D, Marshall EG, Ahuja M, et al. Practice patterns among early-career primary care (ECPC) physicians and workforce planning implications: protocol for a mixed methods study. BMJ Open. 2019;9(9):e030477. https://doi.org/10.1136/bmjopen-2019-030477 .

Ward ZD, Morgan ZJ, Peterson LE. Family physician burnout does not differ with rurality. J Rural Health. 2021;37(4):755–61. https://doi.org/10.1111/jrh.12515 .

Rutherford K, Oda J. Family medicine residency training and burnout: a qualitative study. Can Med Educ J. 2014;5(1):e13–23. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4563612/ .

Tawfik DS, Shanafelt TD, Dyrbye LN, Sinsky CA, West CP, Davis AS, et al. Personal and professional factors associated with work-life integration among US physicians. JAMA Netw Open. 2021;4(5):e2111575. https://doi.org/10.1001/jamanetworkopen.2021.11575 .

Canadian Institute for Health Information. A profile of physicians in Canada. 2021. https://www.cihi.ca/en/a-profile-of-physicians-in-canada

Lavergne RM, Peterson S, Mckendry R, Sivananthan S, McGrail K. Full-service family practice in British Columbia: policy interventions and trends in practice, 1991–2010. Healthc Policy. 2014;9(4):32–47. https://pubmed.ncbi.nlm.nih.gov/24973482/ .

Glazer J. Specialization in family medicine education: abandoning our generalist roots. Fam Pract Manag. 2007;14(2):13–5. https://www.aafp.org/pubs/fpm/issues/2007/0200/p13.html .

Katerndahl D, Wood R, Jaén CR. Family medicine outpatient encounters are more complex than those of cardiology and psychiatry. J Am Board Fam Med. 2011;24(1):6–15. https://www.jabfm.org/content/jabfp/24/1/6.full.pdf .

Grant RW, Ashburner JM, Hong CS, Chang Y, Barry MJ, Atlas SJ. Defining patient complexity from the primary care physician’s perspective: A cohort study. Annals of Internal Medicine: Vol 155, No 12 [Internet]. [cited 2023 Mar 10]. https://www.acpjournals.org/doi/full/ https://doi.org/10.7326/0003-4819-155-12-201112200-00001

Stange KC, Ferrer RL. The paradox of primary care. Ann Fam Med. 2009;7(4):293–9. https://doi.org/10.1370/afm.1023 .

Mitra G, Grudniewicz A, Lavergne MR, Fernandez R, Scott I. Alternative payment models: a path forward. Can Fam Physician. 2021;67(11):805–7. https://www.cfp.ca/content/67/11/805 .

Oandasan IF, Archibald D, Authier L, Lawrence K, McEwen LA, Mackay MP, et al. Future practice of comprehensive care: practice intentions of exiting family medicine residents in Canada. Can Fam Physician. 2018;64(7):520–8. http://www.ncbi.nlm.nih.gov/pmc/articles/pmc6042659/ .

Walsh M, Pearson H. Nova Scotia doctor calls family doctor shortage a crisis [Internet]. [cited 2017 Jun 6]. http://globalnews.ca/news/3270444/nova-scotia-doctor-calls-family-doctor-shortage-a-crisis/

Canadian Institute for Health Information. Supply, Distribution and Migration of Physicians in Canada, 2020 - data tables. Ottawa, ON: CIHI; 2021. https://secure.cihi.ca/estore/productSeries.htm?pc=PCC34 .

Somé NH, Devlin RA, Mehta N, Zaric GS, Sarma S. Team-based primary care practice and physician’s services: evidence from Family Health teams in Ontario, Canada. Soc Sci Med. 2020;264:113310. https://doi.org/10.1016/j.socscimed.2020.113310 .

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Qualitative studies involving users of clinical neurotechnology: a scoping review

• Georg Starke 1 , 2 ,
• Tugba Basaran Akmazoglu 3 ,
• Annalisa Colucci 4 ,
• Mareike Vermehren 4 ,
• Amanda van Beinum 5 ,
• Maria Buthut 4 ,
• Surjo R. Soekadar 4 ,
• Christoph Bublitz 7 ,
• Jennifer A. Chandler 6 &
• Marcello Ienca 1 , 2  

BMC Medical Ethics volume  25 , Article number:  89 ( 2024 ) Cite this article

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The rise of a new generation of intelligent neuroprostheses, brain-computer interfaces (BCI) and adaptive closed-loop brain stimulation devices hastens the clinical deployment of neurotechnologies to treat neurological and neuropsychiatric disorders. However, it remains unclear how these nascent technologies may impact the subjective experience of their users. To inform this debate, it is crucial to have a solid understanding how more established current technologies already affect their users. In recent years, researchers have used qualitative research methods to explore the subjective experience of individuals who become users of clinical neurotechnology. Yet, a synthesis of these more recent findings focusing on qualitative methods is still lacking.

To address this gap in the literature, we systematically searched five databases for original research articles that investigated subjective experiences of persons using or receiving neuroprosthetics, BCIs or neuromodulation with qualitative interviews and raised normative questions.

36 research articles were included and analysed using qualitative content analysis. Our findings synthesise the current scientific literature and reveal a pronounced focus on usability and other technical aspects of user experience. In parallel, they highlight a relative neglect of considerations regarding agency, self-perception, personal identity and subjective experience.

Conclusions

Our synthesis of the existing qualitative literature on clinical neurotechnology highlights the need to expand the current methodological focus as to investigate also non-technical aspects of user experience. Given the critical role considerations of agency, self-perception and personal identity play in assessing the ethical and legal significance of these technologies, our findings reveal a critical gap in the existing literature. This review provides a comprehensive synthesis of the current qualitative research landscape on neurotechnology and the limitations thereof. These findings can inform researchers on how to study the subjective experience of neurotechnology users more holistically and build patient-centred neurotechnology.

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Introduction

Due to a rapid expansion in public-private investment, market size and availability of Artificial Intelligence (AI) tools for functional optimization, the clinical advancement of novel neurotechnologies is accelerating its pace [ 1 ]. Bidirectional intelligent Brain-Computer interfaces (BCI) that aim at merging both read-out and write-in devices are in active development and are expanding in functional capabilities and commercial availability. [ 2 , 3 ]. Such BCIs that can decode and modulate neural activity through direct stimulation of brain tissue, promise additional avenues in the treatment of neurological diseases by adapting to the particularities of individual users’ brain. Potential applications are Parkinson’s disease [ 4 ] or epilepsy [ 5 ] as well as psychiatric disorders, such as major depressive disorder [ 6 ] or obsessive compulsive disorder [ 7 ]. Driven by these advances and in conjunction with progress in deep learning and generative AI software as well as higher-bandwidth hardware, clinical neurotechnology is likely to take an increasingly central role in the prevention, diagnosis and treatment of neuropsychiatric disorders.

In line with these scientific trends, the last decade has seen a consequent fast rise in the ethical attention devoted to neurotechnological systems that establish a direct connection with the human central nervous system [ 8 ], including neurostimulation devices. Yet, at times, neuroethical concerns may have outpaced real-life possibilities, particularly with view to the impact of neurotechnology on personality, identity, autonomy, authenticity, agency or self (PIAAAS) [ 9 ]. This points to the need for basing ethical assessments and personal decisions about deploying devices on solid empirical grounds. In particular, it is crucial to gain a comprehensive understanding of the lived experience of using neurotechnologies from the epistemically privileged first-person perspective of users – “what it is like” to use neurotechnologies. Its examination by empirical studies have added a vital contribution to the literature [ 10 ].

Yet, few reviews have attempted to synthesize the growing body of empirical studies on user experience with clinical neurotechnology. Burwell et al. [ 11 ] reviewed literature from biomedical ethics on BCIs up to 2016, identifying key ethical, legal and societal challenges, yet noting a lack of concrete ethical recommendations for implementation. Worries about a lack of attention to ethics in BCI studies have been further corroborated by two reviews by Specker Sullivan and Illes, reviewing BCI research published up until 2015. They critically assessed the rationales of BCI research studies [ 12 ] and found a remarkable absence of ethical language in published BCI research [ 13 ]. Taking a different focus, Kögel et al. [ 14 ] have provided a scoping review summarizing empirical studies investigating ethics of BCIs until 2017, with a strong focus on quantitative methods in the reviewed papers. Most recently, this list of reviews has been complemented by van Velthoven et al. [ 15 ], who review empirical and conceptual ethical literature on the use of visual neuroprostheses.

To the best of our knowledge, a specific review of qualitative research on the ethics of emerging neurotechnologies such as neuroprosthetics, BCIs and neuromodulation systems is outstanding. We believe that qualitative research involving actual or prospective neurotechnology users is particularly significant as it allows researchers to tap into the richness of first-person experiences as compared to standardized questionnaires without the option of free report. In the following, we synthesize published research on the subjective experience of using clinical neurotechnologies to enrich the ethical debate and provide guidance to developers and regulators.

On January 13, 2022 we conducted a search of relevant scientific literature across 5 databases, namely Pubmed (89 results), Scopus (178 results), Web of Science (79 results), PsycInfo (134 results) and IEEE Xplore (4 results). The search was performed for title, abstract and keywords, using a search string to identify articles employing qualitative methods that engaged with users of neurotechnology, and covered normative issues: [“qualitative” OR “interview” OR “focus group” OR “ethnography” OR “grounded theory” OR “discourse analysis” OR “interpretative phenomenological analysis” OR “thematic analysis”] AND [“user” OR “patient” OR “people” OR “person” OR “participant” OR “subject”] AND [“Brain-Computer” OR “BCI” OR “Brain-Machine” OR “neurostimulation” OR “neuromodulation” OR “TMS” OR “transcranial” OR “neuroprosthetic*” OR “neuroprosthesis” OR “DBS”] AND [“ethic*” OR “bioethic*” OR “normative” OR “value” OR “evaluation”].

Across databases, search syntax was adapted to reflect the respective logic of each library. Our search yielded a total of 484 articles. Of these, 133 duplicates were removed. 52 further results were marked as ineligible by automation tools, due to either not being written in English or not representing original research in a peer-reviewed journal. The remaining 299 were screened manually, with screening tasks being shared equally among the authors GS, TBA, AC, MV, CB, JC, and MI. Articles were included if they were written in English, published in a peer-reviewed journal, and reported original research of empirical qualitative findings among human users of a neurotechnological system that establishes a direct connection with the human central nervous system (including neurostimulation devices). Other types of articles such as perspectives, letters to the editor, or review articles were not included. Potential methods included individual interviews, focus groups, stakeholder consultations but excluded studies that did not use any direct verbal input from the users. Each abstract was screened individually by two reviewers. Unclear cases were resolved by discussion among reviewers. This process resulted in the exclusion of 247 articles, leaving 52 publications for inclusion into the final synthesis.

Full texts of these 52 articles were retrieved and assessed for eligibility. Again, this task was shared equally across the 7 authors who made independent recommendations whether an article was included for further analysis, and disagreement was resolved by discussion. 20 articles were excluded at this stage, due to not meeting the inclusion criteria. This resulted in a body of 32 articles plus 4 additional papers identified through citation chaining, as customary in scoping reviews.

In the data analysis phase, we compiled a descriptive summary of the findings and conducted a thematic analysis. When compiling the descriptive summary, we followed the recommendations by Arksey and O’Malley [ 16 ] and included comprehensive information beyond authors, year, and title of the study, extracting also study location, methodology, study population, type of neurotechnology, and more. For the thematic analysis, the full text was read and coded by the authors through annotations in pdf files, with papers evenly distributed among the group. Coding was based on a previously agreed coding structure of four thematic families, covering (1) subjective experience with BCIs, (2) aspects concerning usability and technology, (3) ethical questions, (4) impact on social relations, and a fifth miscellaneous category for future resolution. In accordance with the suggestions by Braun and Clarke [ 17 ], codes that were not clearly covered by the coding tree were grouped into a category “miscellaneous”, and after discussion used to develop new themes or subsumed under the existing thematic families. The results were compiled and unified by the first author and imported into the Atlas.ti software (version 22.2), with adaptations to the coding tree being discussed between first and last author.

In line with the framework suggested by Pham, Rajić [ 18 ], we adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) in conducting and presenting our results [ 19 ]. A flow diagram representing the entire process is depicted in Fig.  1 .

PRISMA flow diagram: search and screening strategy. Based on Page et al [ 19 ]

Descriptive findings

Our study included 36 papers reporting original qualitative research among users of BCIs, neuroprosthetics and neuromodulation. We found a pronounced increase in the number of publications employing qualitative methods in the investigation of such neurotechnology users over time, with the earliest study dating back to 2012. However, contrary to what one may expect as reflection of the growing number of neurotechnology users, we did not find an increase in the average sample size of participants enrolled in qualitative studies nor a correlation between year of publication and number of participants (see Fig.  2 ).

Average number of participants and number of publications over time

The included studies were exclusively conducted in Western countries, with 11 studies from the US, 9 from Australia and the remaining 16 distributed across Europe (UK: 6, Germany: 4, Sweden, Netherlands and Switzerland 2 each). The majority of studies investigated the effects of invasive neurotechnology in the form of Deep Brain Stimulators (DBS) (26/36), especially in patients with Parkinson’s Disease (PD) (19/36). Many papers also investigated users’ experiences with non-invasive EEG-based BCIs (7/36), whereas all other technologies such as TMS, ECT, FES, intracortical microelectrode arrays, or spinal cord stimulation were only covered by one or two papers each. Footnote 1 Due to the large focus on PD patients, other potential fields for clinical neurotechnological applications were much less present in the analysed research, with only 4 papers each investigating the effects of DBS on patients with major depressive disorder (4/36) or obsessive-compulsive disorder (OCD) (4/36). Across all technologies and patient groups, studies most frequently relied on semi-structured interviews with individual participants (28/36), with much fewer studies using focus groups (3/36) or other qualitative methods.

We found that a large number of papers (14/36) incorporated longitudinal aspects in their study design. With view to non-invasive BCIs, this comprised involving users in the development and testing of BCIs for acquired brain injury [ 20 , 21 ], assessing subjective reports across sessions for experimental BCI training [ 22 ], or having a 2-month follow-up interview for users of a BCI for pain management after spinal cord injury [ 23 ]. Studies of invasive devices often included interviews pre- and post-implantation, with a potential third follow-up. In studies with two interviews, the first interview after implantation took place a few weeks after implantation [ 24 , 25 ], after 3 months [ 26 ], after 9 months [ 27 , 28 ] or after a year [ 29 ]. In studies with 3 interviews, post-implantation interviews were either conducted after surgery and again after 3 months in a study on spinal cord stimulation [ 30 ] or, in the case of DBS for PD, after 3 and 6 months [ 31 , 32 ] or after 3–6 and 9–12 months respectively [ 33 ]. Table  1 provides a full overview over the included studies.

Thematic findings

Our findings from the thematic analysis can be grouped into four overlapping thematic families, namely (1) ethical challenges of neurotechnology use, (2) subjective experience with clinical neurotechnologies, (3) impact on social relations, and (4) usability and technological aspects. The raw data of our findings are accessible in the supplementary file.

Ethical concerns

With respect to users’ experiences of neurotechnology that touch on classical ethical topics, we found that autonomy played a central role in slightly more than half of all papers (20/36), yet in four different ways. Many papers noted the positive impact neurotechnology has on users’ autonomy. Users often perceive the technology as enabler of greater control over their own life, allowing them “to become who they wanted to be” [ 2 ], providing them with agency and greater independence, restoring their ability to help others, or allowing them to be more spontaneous in their everyday life [ 2 , 10 , 28 , 31 , 32 , 34 , 35 , 36 , 37 ]. Some studies reported how neurotechnology may impact users’ autonomy negatively, especially by making them more dependent on technological and medical support [ 25 , 28 , 35 , 38 , 39 ]. When balancing these positive and negative impacts, some users seem to prefer such dependency and to leave control over the devices to healthcare professionals, to ensure its safe and appropriate working [ 2 , 32 , 39 , 40 ]. Also related to autonomy were concerns about consent, especially with a view to the level of information patients received before the implantation of an invasive device, which was deemed inadequate by some patients [ 2 , 24 , 31 , 34 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 ]. Several papers called to include patients during the technology design process [ 2 , 31 , 39 ]. In addition, questions of responsibility and accountability in case of malfunctioning were repeatedly named as key concern [ 10 , 25 , 37 , 38 , 45 , 47 ].

Concerns about beneficence and about harming patients also featured prominently in most of the analysed papers (24/36), yet with substantive differences on a more granular level. While symptom improvement and restorative changes were widely reported [ 2 , 10 , 23 , 26 , 29 , 31 , 33 , 34 , 35 , 38 , 39 , 40 , 43 , 44 , 46 ], some users reported experiencing physical or psychological side effects, such as postoperative complications, new worries – for instance about magnetic fields or about changing batteries –, stigma, or becoming more aware of their past suffering [ 23 , 25 , 26 , 28 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 42 , 46 , 48 , 49 ]. Less frequently we found concerns about patient-doctor-relationships [ 2 , 24 , 32 , 40 , 42 , 43 ], which seem to mediate the acceptance of clinical neurotechnologies but are also themselves impacted by technology use. For instance, while some research points to the importance of patients’ trust in healthcare professionals for the acceptance of neurotechnology [ 24 ], a personal narrative described a breakdown of patient-physician relationship following a distressful DBS implantation for treating PD [ 42 ].

Impact on subjective experiences

Since the subjective lived experiences of neurotechnology users commonly constituted the central element of the reviewed qualitative papers, we found a rich field of reports in the vast majority of paper (31/36), describing experiences that were perceived as positive, negative or neutral. Neurotechnology-induced behavioural changes [ 28 , 36 , 37 , 40 , 42 , 46 , 47 , 49 ], as well as changes in feelings [ 27 , 41 , 42 ], (self-) perception [ 10 , 23 , 34 , 36 , 40 , 41 , 42 , 44 , 48 , 50 ], personality [ 27 , 29 , 34 , 35 , 36 , 37 , 42 , 43 , 44 , 47 , 49 ], preferences [ 49 , 50 ] or thinking [ 10 , 41 ] were also reported, particularly in users receiving continuous, non-adaptive deep brain stimulation (DBS).

Behavioural changes often concerned desired outcomes such as fewer obsessive thoughts and compulsive behaviours after successful OCD treatment [ 49 ], acting with less impediment due to seizure predictions [ 36 ], or acting more boldly with more energy and increased confidence due to symptom improvement in PD [ 37 , 47 ]. Nevertheless, it was necessary for patients and for their environment to adapt and get used to new patterns of behaviour. Some patients also reported undesirable behavioural changes after subthalamic DBS implantation, “bordering on mania” [ 42 ], such as being excessively talkative [ 46 ] or shopping compulsions that were later described by the patient as “ridiculous” [ 28 ].

These outwardly observable changes were often related to psychological changes that users reported. Some DBS users experienced mood changes, ranging from elevated to depressed [ 27 , 41 , 42 , 44 ], while others reported changed preferences. Sometimes this affected what users valued as important in life [ 50 ], sometimes it related to very particular preferences, such as taste in music, with one patient attributing a transition from The Rolling Stones and The Beatles to Johnny Cash to their DBS implantation [ 49 ]. In patients treated for OCD or motor disorders, two studies also found positive impact on users’ thinking, whether by freeing them from obsessive thoughts [ 41 ] or improving their concentration skill [ 10 ]. In line with the large neuroethical debate on the subject, changes at times amounted to what neurotechnology users described as personality changes. Such changes included negative impacts such as being more irritable, anxious or less patient [ 34 , 35 ] or overly increased libido [ 49 ], neutral changes, such as (re-)taking an interest in politics or movies [ 49 ], and positive changes linked to improvement of psychiatric symptoms, such as being more easy-going and daring, being more expressive and assertive, or simply being more confident [ 35 , 49 ].

In line with the diversity of these changes, patients reported a vast spectrum of different attitudes towards and relations with the neurotechnology. Some users embraced the BCI explicitly as part of themselves [ 14 , 37 , 39 , 49 ] and described how “DBS becomes a part of who you are rather than changing you” [ 37 ]. Others felt estranged using the BCI [ 28 , 36 , 37 , 42 , 49 ] and even expressed desires to remove the alien device in forceful terms: “I hate it! I wish I could pull it out!” [ 37 ]. Aside from changes brought about by the device, the patients’ state before using neurotechnology and especially their relation to their illness seemed to play a crucial role [ 28 , 51 ]. An overview over the different thematic findings is provided in Fig.  3 .

Impact of clinical neurotechnology on subjective experience. The colours represent the valence of the impact, with orange dots representing negative, green dots representing positive, and blue dots representing ambivalent changes

The overwhelming majority of studies (23/36) reported improvements of the treated symptoms [ 2 , 26 , 28 , 31 , 33 , 34 , 35 , 37 , 40 , 41 , 42 , 43 , 46 , 47 , 48 , 49 , 50 , 52 ], making patients’ lives easier [ 48 , 49 ] or – as some put it – even saving their lives [ 34 , 45 , 48 ]. Patients felt that the neurotechnology allowed them an increase in activity [ 33 , 34 , 40 ] and a return to previous forms of behaviour [ 33 , 40 , 48 , 49 ], strengthening their sense of freedom and independence [ 2 , 10 , 22 , 33 , 34 , 35 , 36 , 40 , 43 , 49 , 50 , 53 ]. Emotionally, users reported feeling more daring [ 29 , 35 ], self-confident [ 28 , 35 , 36 , 37 , 44 ] or more stable [ 34 , 50 ] as well as feelings of hope or joy [ 10 , 22 , 35 , 50 ]. For better or worse, such changes were sometimes perceived as providing a “new start” [ 34 , 48 ] or even a “new identity” [ 34 , 41 , 42 , 49 ], while others perceived their changes as a reversion to their “former” [ 28 , 29 , 47 , 49 , 50 ] or their “real” self [ 36 , 42 , 49 ].

Among the negative subjective impacts of clinical neurotechnology mentioned in the literature (16/36), users commonly reported issues of estrangement, caused by self-perceived changes to behaviour, feelings, personality traits, or patients’ relation to their disease or disorder [ 28 , 36 , 37 , 42 , 49 ]. The negative impact differed largely depending on the type of neurotechnology used as well as on the disorders and symptoms treated with the technology. While ALS patients as users of non-invasive BCIs for spelling interfaces reported increased anxiety in interaction with the devices [ 53 ], PD patients with invasive DBS reported presurgical fears of pain and of the invasive procedure as well as fear of outward manipulation within their brain through the DBS implantation [ 40 , 43 , 54 ]. Frequently, it was not entirely clear whether adverse developments such as further cognitive decline were attributable to the implanted device or to the persisting disease and its natural trajectory [ 31 , 33 , 34 , 40 , 43 , 48 , 50 ]. However, occasionally very severe psychiatric consequences of treatment were reported, notably by one PD patient who experienced mania and depressive symptoms through DBS treatment, resulting in a suicide attempt [ 42 ]. For DBS patients with OCD, negative impacts seem more related to difficulties of adapting to the new situation [ 35 , 49 ], for instance to their suddenly increased libido as a side-effect of DBS use that may be perceived as “too much” [ 49 ], or to a perceived lack of preparation for their new (OCD-free) identity [ 41 ]. In two studies on patients with OCD, the sudden improvement of symptoms also led to moments of existential crisis, given that the symptoms had shaped a great part of their previous daily activities [ 41 , 49 ].

Impact on social relations

Using a neurotechnology not only impacts users but can also affect social relations with others (23/36), particularly primary caregivers. While some neurotechnologies such as non-invasive BCIs for communication may create additional workload for caregivers if the BCI needs to be set up, neurotechnologies can also reduce their burden by rendering patients more independent [ 10 , 34 , 40 , 53 ]. Beyond workload, neurotechnologies were also reported to enrich social relations by facilitating communication [ 10 , 34 , 53 ], though in some cases, they led to potential tension between informal caregivers and patients, e.g. due to personality changes [ 28 , 35 , 37 , 40 , 42 , 47 , 49 , 55 ] or if the device was blamed for a patient’s behaviour or suggested as a solution to interpersonal problems [ 2 ]. Whether positive or negative, family and social support were reportedly playing a vital role in the treatment [ 2 , 28 , 40 , 50 ].

Similarly important was support by clinicians [ 39 , 40 ] and the wish for support groups with fellow neurotechnology users [ 27 , 30 , 40 , 41 ]. Inclusion in research activities was also reported as a positive effect of (experimental) BCIs [ 10 , 38 ]. More importantly though, in a large number of studies, neurotechnology users reported positive effects on their social relations [ 2 , 29 , 35 , 43 , 46 , 48 , 50 ], with some users reporting an increased wish to help others [ 35 , 50 ]. A negative social consequence in public was perceived stigma [ 25 , 35 , 48 ], even though some patients chose to actively show their device in public, “to spread information and knowledge about this treatment” [ 39 ].

Usability concerns

Concerns with technical questions and usability issues comprising efficiency, effectiveness and satisfaction [ 52 ] were also raised by almost half of the research papers (17/36), yet differed greatly between neurotechnologies, owing to large differences in hardware (e.g., between EEG caps and implanted electrodes) and handling (e.g., between passive neurostimulation or training-intensive active BCIs). Across all applications, invasive as much as non-invasive, the most frequent concerns (8/36 each) related to hardware issues [ 2 , 22 , 23 , 38 , 39 , 46 , 52 , 53 ] as well as to the required fine-tuning of devices to find optimal settings, associated with time-burden for their users [ 20 , 23 , 27 , 32 , 39 , 46 , 50 , 56 ]. Similarly, the training of patients required for the successful use of non-invasive, active BCIs was reported as being perceived as cumbersome or complicated, providing a potential obstacle to their implementation in everyday contexts [ 38 , 52 ]. Several studies reported that the use of such active BCIs required considerable concentration, leading to fatigue after prolonged use [ 10 , 38 , 53 ]. Mediating factors to address such obstacles were the availability of technical support [ 33 , 53 ], general attitudes towards technology [ 53 ], ease of integrating the technology into everyday life [ 10 , 38 , 53 ] and realistic expectations regarding the neurotechnology’s effects [ 30 , 38 , 40 , 46 ].

The identified publications highlight that qualitative research through interviews and focus groups offers a useful way to gain access to the subjective experience of users of a diverse range of neurotechnologies. Such investigation of users’ privileged knowledge about novel devices in turn is crucial to improve future neurotechnological developments and align them with ethical considerations already at an early stage [ 57 ]. Here, we discuss our findings by comparing different clinical neurotechnologies, identify gaps in the literature and point to the limitations of our scoping review.

One finding of our scoping review is that qualitative research on neurotechnologies has so far primarily focused on users of DBS treated for PD. In part, this may reflect that DBS is an established, effective treatment for controlling motor symptoms in PD, improving patients’ quality of life, resulting in its wide-spread adoption in many different healthcare systems worldwide [ 58 , 59 , 60 , 61 ]. Still, it would be highly beneficial to extend qualitative research to different patient groups and other clinical neurotechnologies that directly target mental states or processes, where more pronounced effects of subjective experiences may be expected.

A potential obstacle to involving more neurotechnology users beyond PD patients treated with DBS is that, for many other technologies, users are still likely to receive their treatment as part of an experimental trial. Qualitative research with such patients may face the additional practical barrier of convincing the other researchers to facilitate access to their patients. Better communication across disciplines and research fields may facilitate such access, providing much-needed insights into user experiences of experimental neurotechnologies.

Some of the articles reviewed here already offer such perspectives, e.g. the ones investigating DBS used for major depressive disorder or OCD. Such research may also help to further clarify which differences in subjective outcome are owed to technology and which are owed to differences in the treated disorders. As different patient groups are likely to have different needs and views, further research is needed to explore those needs and views and develop implementation strategies designed to address them in a patient-tailored manner. Furthermore, different neurotechnologies (and applications thereof) are likely to impact the mind of their users in a different way. Therefore, future research should investigate whether the type and modality of stimulation exert differential impacts on the subjective experience of the end users.

Our findings reveal differential effects among patients using DBS for the treatment of PD and patients using DBS for the treatment of OCD, respectively. For example, some reported effects of invasive neurotechnology such as the induction of more assertive behaviour may be a reason for concern in PD [ 28 ], while being considered a successful treatment outcome in OCD [ 35 , 49 ]. More comparative research among DBS users treated for OCD or other neuropsychiatric disorders, such as depression, are needed [ 62 ] and may help to better understand which experiences are directly attributable to the stimulation of specific brain areas such as the subthalamic nucleus for PD and the nucleus accumbens for OCD, and which result from other factors, e.g., related to undergoing surgery or to different treatment settings in neurological and psychiatric care [ 63 , 64 ].

Research on such differences may also imply practical consequences. For instance, one may wonder whether different preparation stages and possibly different degrees of information for obtaining consent may be called for between invasive clinical neurotechnologies used in psychiatry and neurology—or whether, on the contrary, similarities in the use of neurotechnologies ultimately point towards ending the distinction between mental and neurological illnesses [ 63 ]. In either case, our findings highlight that psychological impacts of clinical neurotechnologies are complex and multi-faceted phenomena—mediated by many factors—calling for more qualitative research to better grasp the lived experiences of those using novel neurotechnologies.

Our scoping review identified several gaps in the literature related to research methodology, investigated topics and investigated neurotechnologies. First, while a large number of studies embrace a longitudinal approach to investigating users’ experiences, none of the included studies looked at impacts beyond a timeframe of one year. However, as is known from DBS studies in major depressive disorder, it is important to investigate and evaluate long-term effects of neurotechnologies such as DBS [ 6 ]. Future qualitative research should therefore address this gap. Connected to this are, second, research questions that have not yet been investigated in full, such as long-term impacts of clinical neurotechnologies on memory or belief continuity. Third, empirical findings on closed-loop neurotechnologies that integrate artificial intelligence are so far nascent [ 2 , 36 ]. As there are important conceptual and ethical questions that arise specifically from the integration of human and artificial intelligence, e.g. questions of control and responsibility, further qualitative research should be conducted on users of such devices.

Finally, our findings reveal a complex and multifaceted landscape of ethical considerations. While considerations regarding personal autonomy appear largely prevalent among users, the perceived or expected impacts of neurotechnology use on personal autonomy differ significantly. Some studies suggest that neurotechnology use may enhance personal autonomy by allowing users to be more autonomous and independent in their daily lives and even restore part of the autonomous control that was disrupted by their disorders. Other studies suggest that some neurotechnologies, especially neural implants relying on autonomous components, may diminish autonomy as they may override some users’ intentions. Sometimes this ambivalent effect is observed within the same study. This is consistent with previous theoretical reflections on this topic [ 65 ] and urges scientists to develop fine-grained and patient-centred models for assessing the impact of neurotechnology on personal autonomy. These models should distinguish on-target and off-target effects and elucidate which subcomponents of personal autonomy (e.g., volition, behavioural control, authenticity etc.) are impacted by the use of neurotechnology.

Our scoping review has several limitations. Owing to the nature of a scoping review and to our inclusion criteria, there may be relevant literature that we missed to identify and analyse. For instance, since we only included English publications, we may have missed relevant research published in other languages, which may explain why we only found qualitative studies conducted in Western countries. Furthermore, our narrow search strategy excluded other relevant research, for instance qualitative studies conducted with potential users of clinical neurotechnology or with caregivers. Yet, a scoping reviews can provide a useful tool to map existing literature [ 16 , 18 ], and given recent advances in technology and accompanying qualitative research, an update of earlier reviews such as the one by Kögel et al. [ 14 ], provides an important addition to the existing literature. By looking at qualitative studies only we further import general limitations of qualitative studies, such as a lack of generalizability and a dependency on the skills and experience of the involved researchers. More standardized instruments to complement the investigation of subjective experiences of neurotechnology users therefore seem highly desirable. Recent quantitative approaches such as online surveys assessing the subjective preferences of DBS users concerning the timing of implantation [ 66 ] or studies combining qualitative data with quantitative assessments [ 67 ] point in this direction. Additionally, experimental approaches to the monitoring and evaluation of the effects of neurotechnology on the user’s experience are currently absent. Therefore, future research should complement qualitative and quantitative user evaluations based on social science methods (e.g., interviews, focus groups and questionnaires) with experimental models.

The findings of our review emphasize the diversity of individual experiences with neurotechnology across individuals and different technologies. They underscore the need to conduct qualitative research among diverse groups at different time-points to better assess the impact of such technologies on their users, which are important to inform requirements of efficacy and safety for clinical neurotechnologies. In addition, qualitative research offers one way to implement user-centred ethical considerations into product development through user-centred design and to accompany the development of novel neurotechnologies with ethical considerations as they mature and become clinical standard.

Data availability

The availability of the full data supporting the findings of this study is subject to restrictions due to the copyright of the included papers. The quotes analysed during this study are included in this published article and its supplementary information files. Further data are available from the authors upon request.

As many publications included patients with different diagnoses or investigated the effects of different neurotechnologies, the numbers indicated here do not add up.

UNESCO. Unveiling the neurotechnology landscape: scientific advancements innovations and major trends. 2023.

Klein E, et al. Brain-computer interface-based control of closed-loop brain stimulation: attitudes and ethical considerations. Brain-Computer Interfaces. 2016;3(3):140–8.

Article   Google Scholar  

Kellmeyer P, et al. The effects of closed-loop medical devices on the autonomy and accountability of persons and systems. Camb Q Healthc Ethics. 2016;25(4):623–33.

Limousin P, Foltynie T. Long-term outcomes of deep brain stimulation in Parkinson disease. Nat Reviews Neurol. 2019;15(4):234–42.

Alkawadri R. Brain–computer interface (BCI) applications in mapping of epileptic brain networks based on intracranial-EEG: an update. Front NeuroSci. 2019;13:191.

Crowell AL, et al. Long-term outcomes of subcallosal cingulate deep brain stimulation for treatment-resistant depression. Am J Psychiatry. 2019;176(11):949–56.

Mar-Barrutia L, et al. Deep brain stimulation for obsessive-compulsive disorder: a systematic review of worldwide experience after 20 years. World J Psychiatry. 2021;11(9):659.

Clausen J, et al. Help, hope, and hype: ethical dimensions of neuroprosthetics. Science. 2017;356(6345):1338–9.

Gilbert F, Viaña JNM, Ineichen C. Deflating the DBS causes personality changes bubble. Neuroethics. 2021;14(1):1–17.

Kögel J, Jox RJ, Friedrich O. What is it like to use a BCI? - insights from an interview study with brain-computer interface users. BMC Med Ethics. 2020;21(1):2.

Burwell S, Sample M, Racine E. Ethical aspects of brain computer interfaces: a scoping review. BMC Med Ethics. 2017;18(1):1–11.

Sullivan LS, Illes J. Beyond ‘communication and control’: towards ethically complete rationales for brain-computer interface research. Brain-Computer Interfaces. 2016;3(3):156–63.

Specker Sullivan L, Illes J. Ethics in published brain–computer interface research. J Neural Eng. 2018;15(1):013001.

Kögel J, et al. Using brain-computer interfaces: a scoping review of studies employing social research methods. BMC Med Ethics. 2019;20(1):18.

van Velthoven E, et al. Ethical implications of visual neuroprostheses—a systematic review. J Neural Eng. 2022;19(2):026055.

Arksey H, O’Malley L. Scoping studies: towards a methodological framework. Int J Soc Res Methodol. 2005;8(1):19–32.

Braun V, Clarke V. Using thematic analysis in psychology. Qualitative Res Psychol. 2006;3(2):77–101.

Pham MT, et al. A scoping review of scoping reviews: advancing the approach and enhancing the consistency. Res Synthesis Methods. 2014;5(4):371–85.

Page MJ, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. Syst Reviews. 2021;10(1):1–11.

Mulvenna M, et al. Realistic expectations with brain computer interfaces. J Assist Technol. 2012;6(4):233–44.

Martin S, et al. A qualitative study adopting a user-centered approach to design and validate a brain computer interface for cognitive rehabilitation for people with brain injury. Assist Technol. 2018;30(5):233–41.

Kryger M, et al. Flight simulation using a brain-computer interface: a pilot, pilot study. Exp Neurol. 2017;287:473–8.

Al-Taleb M, et al. Home used, patient self-managed, brain-computer interface for the management of central neuropathic pain post spinal cord injury: usability study. J Neuroeng Rehabil. 2019;16(1):1–24.

Wexler A, et al. Ethical issues in intraoperative neuroscience research: assessing subjects’ recall of informed consent and motivations for participation. AJOB Empir Bioeth. 2022;13(1):57–66.

Goering S, Wexler A, Klein E. Trading vulnerabilities: living with Parkinson’s Disease before and after deep brain stimulation. Camb Q Healthc Ethics. 2021;30(4):623–30.

Maier F, et al. Patients’ expectations of deep brain stimulation, and subjective perceived outcome related to clinical measures in Parkinson’s disease: a mixed-method approach. J Neurol Neurosurg Psychiatry. 2013;84(11):1273–81.

Thomson CJ, Segrave RA, Carter A. Changes in Personality Associated with Deep Brain Stimulation: a qualitative evaluation of clinician perspectives. Neuroethics. 2021;14:109–24.

Thomson CJ, et al. He’s back so I’m not alone: the impact of deep brain stimulation on personality, self, and relationships in Parkinson’s disease. Qual Health Res. 2020;30(14):2217–33.

Lewis CJ, et al. Subjectively perceived personality and mood changes associated with subthalamic stimulation in patients with Parkinson’s disease. Psychol Med. 2015;45(1):73–85.

Ryan CG, et al. An exploration of the experiences and Educational needs of patients with failed back surgery syndrome receiving spinal cord stimulation. Neuromodulation. 2019;22(3):295–301.

Kubu CS, et al. Patients’ shifting goals for deep brain stimulation and informed consent. Neurology. 2018;91(5):e472–8.

Merner AR, et al. Changes in patients’ desired control of their deep brain stimulation and subjective Global Control over the Course of Deep Brain Stimulation. Front Hum Neurosci. 2021;15:642195.

Liddle J, et al. Impact of deep brain stimulation on people with Parkinson’s disease: a mixed methods feasibility study exploring lifespace and community outcomes. Hong Kong J Occup Ther. 2019;32(2):97–107.

Chacón Gámez YM, Brugger F, Biller-Andorno N. Parkinson’s Disease and Deep Brain Stimulation Have an Impact on My Life: A Multimodal Study on the Experiences of Patients and Family Caregivers. Int J Environ Res Public Health. 2021;18(18):9516.

de Haan S et al. Effects of deep brain stimulation on the lived experience of obsessive-compulsive disorder patients: in-depth interviews with 18 patients. PLoS One. 2015;10(8):e0135524.

Gilbert F, et al. Embodiment and estrangement: results from a first-in-Human Intelligent BCI Trial. Sci Eng Ethics. 2019;25(1):83–96.

Gilbert F, et al. I miss being me: phenomenological effects of deep brain stimulation. AJOB Neurosci. 2017;8(2):96–109.

Grübler G, et al. Psychosocial and ethical aspects in non-invasive EEG-based BCI research - A survey among BCI users and BCI professionals. Neuroethics. 2014;7(1):29–41.

Hariz G-M, Hamberg K. Perceptions of living with a device-based treatment: an account of patients treated with deep brain stimulation for Parkinson’s disease. Neuromodulation: Technol Neural Interface. 2014;17(3):272–8.

Liddle J, et al. Mapping the experiences and needs of deep brain stimulation for people with Parkinson’s disease and their family members. Brain Impairment. 2019;20(3):211–25.

Bosanac P, et al. Identity challenges and ‘burden of normality’ after DBS for severe OCD: a narrative case study. BMC Psychiatry. 2018;18(1):186.

Gilbert F, Viaña JN. A personal narrative on living and dealing with Psychiatric symptoms after DBS surgery. Narrat Inq Bioeth. 2018;8(1):67–77.

Cabrera LY, Kelly-Blake K, Sidiropoulos C. Perspectives on deep brain stimulation and its earlier use for parkinson’s disease: a qualitative study of US patients. Brain Sci. 2020;10(1).

Bluhm R, et al. They affect the person, but for Better or worse? Perceptions of Electroceutical interventions for Depression among psychiatrists, patients, and the Public. Qual Health Res. 2021;31(13):2542–53.

Sankary LR et al. Exit from Brain Device Research: A Modified Grounded Theory Study of Researcher Obligations and Participant Experiences. AJOB Neurosci. 2021;1–12.

Thomson CJ, et al. Nothing to lose, absolutely everything to Gain: patient and caregiver expectations and subjective outcomes of deep brain stimulation for treatment-resistant depression. Front Hum Neurosci. 2021;15:755276.

Mosley PE, et al. Woe betides anybody who tries to turn me down.’ A qualitative analysis of neuropsychiatric symptoms following subthalamic deep brain stimulation for Parkinson’s Disease. Neuroethics. 2021;14:47–63.

Hariz G-M, Limousin P, Hamberg K. DBS means everything-for some time. Patients’ perspectives on daily life with deep brain stimulation for Parkinson’s disease. J Parkinson’s Disease. 2016;6(2):335–47.

de Haan S, et al. Becoming more oneself? Changes in personality following DBS treatment for psychiatric disorders: experiences of OCD patients and general considerations. PLoS ONE. 2017;12(4):e0175748.

Shahmoon S, Smith JA, Jahanshahi M. The lived experiences of deep brain stimulation in parkinson’s disease: an interpretative phenomenological analysis. Parkinson’s Disease. 2019;2019(1):1937235.

Adamson AS, Welch HG. Machine learning and the Cancer-diagnosis problem - no gold Standard. N Engl J Med. 2019;381(24):2285–7.

Zulauf-Czaja A, et al. On the way home: a BCI-FES hand therapy self-managed by sub-acute SCI participants and their caregivers: a usability study. J Neuroeng Rehabil. 2021;18(1):1–18.

Blain-Moraes S, et al. Barriers to and mediators of brain-computer interface user acceptance: Focus group findings. Ergonomics. 2012;55(5):516–25.

LaHue SC, et al. Parkinson’s disease patient preference and experience with various methods of DBS lead placement. Parkinsonism Relat Disord. 2017;41:25–30.

Lewis CJ, et al. The impact of subthalamic deep brain stimulation on caregivers of Parkinson’s disease patients: an exploratory study. J Neurol. 2015;262(2):337–45.

Cabrera LY, et al. Beyond the cuckoo’s nest: patient and public attitudes about Psychiatric Electroceutical interventions. Psychiatr Q. 2021;92(4):1425–38.

Jongsma KR, Bredenoord AL. Ethics parallel research: an approach for (early) ethical guidance of biomedical innovation. BMC Med Ethics. 2020;21(1):1–9.

Lozano AM, et al. Deep brain stimulation: current challenges and future directions. Nat Reviews Neurol. 2019;15(3):148–60.

Schuepbach W, et al. Neurostimulation for Parkinson’s disease with early motor complications. N Engl J Med. 2013;368(7):610–22.

Follett KA, et al. Pallidal versus subthalamic deep-brain stimulation for Parkinson’s disease. N Engl J Med. 2010;362(22):2077–91.

Mahajan A, et al. Global variability in Deep Brain Stimulation practices for Parkinson’s Disease. Front Hum Neurosci. 2021;15:667035.

Bublitz C, Gilbert F, Soekadar SR. Concerns with the promotion of deep brain stimulation for obsessive-compulsive disorder. Nat Med. 2023.

White P, Rickards H, Zeman A. Time to end the distinction between mental and neurological illnesses. BMJ. 2012;344.

Martin JB. The integration of neurology, psychiatry, and neuroscience in the 21st century. Am J Psychiatry. 2002;159(5):695–704.

Ferretti A, Ienca M. Enhanced cognition, enhanced self? On neuroenhancement and subjectivity. J Cogn Enhancement. 2018;2(4):348–55.

Montemayor J, et al. Deep brain stimulation for Parkinson’s Disease: why earlier use makes Shared decision making important. Neuroethics. 2022;15(2):1–11.

Maier F, et al. Subjective perceived outcome of subthalamic deep brain stimulation in Parkinson’s disease one year after surgery. Parkinsonism Relat Disord. 2016;24:41–7.

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Acknowledgements

GS would like to thank the attendees of the ERA-NET NEURON mid-term seminar (Madrid, January 2023) for kind and constructive feedback on an earlier draft.

This work was supported by the ERA-NET NEURON project HYBRIDMIND (SNSF 32NE30_199436; BMBF, 01GP2121A and -B), and in part by the European Research Council (ERC) under the project NGBMI (759370), the Federal Ministry of Research and Education (BMBF) under the projects SSMART (01DR21025A), NEO (13GW0483C), QHMI (03ZU1110DD), QSHIFT (01UX2211) and NeuroQ (13N16486), as well as the Einstein Foundation Berlin (A-2019-558).

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Tugba Basaran Akmazoglu

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GS, TBA, AC, MV, SS, CB, JC and MI contributed to the design and planning of the review, conducted the literature searches and organized and analyzed collected references. GS and MI wrote different sections of the article. All authors provided review of analysis results and suggested revisions for the write-up. All authors reviewed and approved the manuscript before submission.

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Starke, G., Akmazoglu, T.B., Colucci, A. et al. Qualitative studies involving users of clinical neurotechnology: a scoping review. BMC Med Ethics 25 , 89 (2024). https://doi.org/10.1186/s12910-024-01087-z

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Received : 23 January 2023

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DOI : https://doi.org/10.1186/s12910-024-01087-z

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