writing a qualitative research findings sample

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.

Psst... there’s more!

This post was based on one of our popular Research Bootcamps . If you're working on a research project, you'll definitely want to check this out ...

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20 Comments

This was extremely helpful. Thanks a lot guys

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

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

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

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

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

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

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

this was very useful, Thank you.

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

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

Very useful, well explained. Many thanks.

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

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

Thanks a lot, it is really helpful

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

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

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

Very helpful thank you.

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

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

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Home » Research Findings – Types Examples and Writing Guide

Research Findings – Types Examples and Writing Guide

Table of Contents

Research Findings

Definition:

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

Types of Research Findings

There are two main types of research findings:

Qualitative Findings

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

Quantitative Findings

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

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

Parts of Research Findings

Research findings typically consist of several parts, including:

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

How to Write Research Findings

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

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

Research Findings Example

Following is a Research Findings Example sample for students:

Title: The Effects of Exercise on Mental Health

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

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

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

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

Applications of Research Findings

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

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

When to use Research Findings

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

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

Purpose of Research Findings

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

The main purposes of research findings are:

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

Characteristics of Research Findings

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

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

Advantages of Research Findings

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

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

Limitations of Research Findings

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

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

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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• UNC Libraries
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Qualitative Research Resources: Writing Up Your 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

About this Page

Writing conventions for qualitative research, sample size/sampling:.

• Integrating Qualitative Research into Systematic Reviews
• Publishing Qualitative Research
• Presenting Qualitative Research
• Qualitative & Libraries: a few gems
• Data Repositories

Why is this information important?

• The conventions of good writing and research reporting are different for qualitative and quantitative research.
• Your article will be more likely to be published if you make sure you follow appropriate conventions in your writing.

On this page you will find the following helpful resources:

• Articles with information on what journal editors look for in qualitative research articles.
• Articles and books on the craft of collating qualitative data into a research article.

These articles provide tips on what journal editors look for when they read qualitative research papers for potential publication.  Also see Assessing Qualitative Research tab in this guide for additional information that may be helpful to authors.

Belgrave, L., D. Zablotsky and M.A. Guadagno.(2002). How do we talk to each other? Writing qualitative research for quantitative readers . Qualitative Health Research , 12(10),1427-1439.

Hunt, Brandon. (2011) Publishing Qualitative Research in Counseling Journals . Journal of Counseling and Development 89(3):296-300.

Fetters, Michael and Dawn Freshwater. (2015). Publishing a Methodological Mixed Methods Research Article. Journal of Mixed Methods Research 9(3): 203-213.

Koch, Lynn C., Tricia Niesz, and Henry McCarthy. (2014). Understanding and Reporting Qualitative Research: An Analytic Review and Recommendations for Submitting Authors. Rehabilitation Counseling Bulletin 57(3):131-143.

Morrow, Susan L. (2005) Quality and Trustworthiness in Qualitative Research in Counseling Psychology ; Journal of Counseling Psychology 52(2):250-260.

Oliver, Deborah P. (2011) "Rigor in Qualitative Research." Research on Aging 33(4): 359-360.

Sandelowski, M., & Leeman, J. (2012). Writing usable qualitative health research findings . Qual Health Res, 22(10), 1404-1413.

Schoenberg, Nancy E., Miller, Edward A., and Pruchno, Rachel. (2011) The qualitative portfolio at The Gerontologist : strong and getting stronger. Gerontologist 51(3): 281-284.

Weaver-Hightower, M. B. (2019). How to write qualitative research . [e-book]

Sidhu, Kalwant, Roger Jones, and Fiona Stevenson (2017). Publishing qualitative research in medical journals. Br J Gen Pract ; 67 (658): 229-230. DOI: 10.3399/bjgp17X690821 PMID: 28450340

• This article is based on a workshop on publishing qualitative studies held at the Society for Academic Primary Care Annual Conference, Dublin, July 2016.

Smith, Mary Lee.(1987) Publishing Qualitative Research. American Educational Research Journal 24(2): 173-183.

Tong, Allison, Sainsbury, Peter, Craig, Jonathan ; Consolidated criteria for reporting qualitative research (COREQ): a 32-item checklist for interviews and focus groups , International Journal for Quality in Health Care , Volume 19, Issue 6, 1 December 2007, Pages 349–357, https://doi.org/10.1093/intqhc/mzm042 .

Tracy, Sarah. (2010) Qualitative Quality: Eight 'Big-Tent' Criteria for Excellent Qualitative Research. Qualitative Inquiry 16(10):837-51.

Because reviewers are not always familiar with qualitative methods, they may ask for explanation or justification of your methods when you submit an article. Because different disciplines,different qualitative methods, and different contexts may dictate different approaches to this issue, you may want to consult articles in your field and in target journals for publication.  Additionally, here are some articles that may be helpful in thinking about this issue. 

Bonde, Donna. (2013). Qualitative Interviews: When Enough is Enough . Research by Design.

Guest, Greg, Arwen Bunce, and Laura Johnson. (2006) How Many Interviews are Enough?: An Experiment with Data Saturation and Variability. Field Methods 18(1): 59-82.

Morse, Janice M. (2015) "Data Were Saturated..." Qualitative Health Research 25(5): 587-88 . doi:10.1177/1049732315576699.

Nelson, J. (2016) "Using Conceptual Depth Criteria: Addressing the Challenge of Reaching Saturation in Qualitative Research." Qualitative Research, December. doi:10.1177/1468794116679873.

Patton, Michael Quinn. (2015) "Chapter 5: Designing Qualitative Studies, Module 30 Purposeful Sampling and Case Selection. In Qualitative Research & Evaluation Methods: Integrating Theory and Practice, Fourth edition, pp. 264-72. Thousand Oaks, California: SAGE Publications, Inc. ISBN: 978-1-4129-7212-3

Small, Mario Luis. (2009) 'How Many Cases Do I Need?': On Science and the Logic of Case-Based Selection in Field-Based Research. Ethnography 10(1): 538.

Search the UNC-CH catalog for books about qualitative writing . Selected general books from the catalog are listed below. If you are a researcher at another institution, ask your librarian for assistance locating similar books in your institution's catalog or ordering them via InterLibrary Loan.  

Oft quoted and food for thought

• Morse, J. M. (1997). " Perfectly healthy, but dead": the myth of inter-rater reliability. DOI:10.1177/104973239700700401 Editorial
• Silberzahn, R., Uhlmann, E. L., Martin, D. P., Anselmi, P., Aust, F., Awtrey, E., ... & Carlsson, R. (2018). Many analysts, one data set: Making transparent how variations in analytic choices affect results. Advances in Methods and Practices in Psychologi
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• Last Updated: May 14, 2024 12:50 PM
• URL: https://guides.lib.unc.edu/qual

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Qualitative Data Analysis

23 Presenting the Results of Qualitative Analysis

Mikaila Mariel Lemonik Arthur

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

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

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

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

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

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

Audience and Voice

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

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

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

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

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

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

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

Making Data Come Alive

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

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

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

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

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

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

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

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

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

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

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

The Genre of Research Writing

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

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

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

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

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

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

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

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

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

Concluding Your Work

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

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

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

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

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

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

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

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

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

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

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• What Is Qualitative Research? | Methods & Examples

What Is Qualitative Research? | Methods & Examples

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

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

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

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

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

Table of contents

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

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

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

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

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

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

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

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

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

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

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

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

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

• Flexibility

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

• Natural settings

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

• Meaningful insights

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

• Generation of new ideas

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

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

• Unreliability

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

• Subjectivity

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

• Limited generalizability

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

• Labor-intensive

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

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

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

Research bias

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

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

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

There are five common approaches to qualitative research :

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

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

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

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

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

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Presenting and Evaluating Qualitative Research

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

INTRODUCTION

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

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

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

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

Types of qualitative data include:

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

RIGOUR IN QUALITATIVE RESEARCH

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

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

STRENGTHS AND LIMITATIONS OF QUALITATIVE RESEARCH

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

Strengths of Qualitative Research

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

Limitations of Qualitative Research

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

PRESENTATION OF QUALITATIVE RESEARCH FINDINGS

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

Data From an Interview.

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

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

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

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

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

Data From Observations

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

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

Data From Focus Groups

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

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

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

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

GUIDANCE FOR PUBLISHING QUALITATIVE RESEARCH

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

Introduction.

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

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

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

Data Analysis.

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

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

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

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

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

Discussion.

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

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

Conclusion.

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

CHECKLIST FOR QUALITATIVE PAPERS

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

ACKNOWLEDGEMENTS

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

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

Introduction

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

Conclusions

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

Writing up qualitative research

There are specific challenges to writing up research based on qualitative data: there is a lot of data to present, complex stories to tell and conclusions that took a long time to develop. But some simple guidelines can help structuring any kind of research output

Daniel Turner

There are specific challenges to writing up research based on qualitative data: there is a lot of data to present, complex stories to tell and conclusions that took a long time to develop. But some simple guidelines can help structuring any kind of research output based on qualitative methods, and help communicate the rich results that come from qualitative data.

There’s a very general statement whenever you are writing or speaking – consider your audience. Who is likely to read your research output? Usually, you would have several from a project, such as a summary for the participants or special interest groups, a research paper for the scientific community (and the journal reviewers) and a thesis which is written to demonstrate knowledge and research skills for an examining panel. Understanding who you are writing for should dictate much of the specifics below, especially how much you need to write to explain certain aspects. Will your readers understand qualitative methodologies? A challenge is often writing for reviewers (or supervisors) who don’t have a qualitative background and don’t understand the methods and small sampling approaches in qualitative research.

This guide is designed to be general enough to apply to a research article or thesis chapter, but note that each will have it’s own specific guidelines for structure and content that should be applied. Some research journals have very specific structures and formatting guidelines to follow, where others allow for more flexibility. Regardless, the key points below should give a general overview of ‘best practice’ in writing up qualitative research.

Theory and Methodology

If you are coming from quantitative disciplines, this is the first section that seems unusual when writing up a research project. Although not explicit, all research has a epistemological and theoretical background and set of assumptions that guide the collection methods and interpretation. However, qualitative research has a strong tradition of making those explicit and justified. The researcher(s) should state their philosophical beliefs on knowledge that have shaped the project.

Describing the epistemology in detail would entail writing about how the researchers see the notion of ‘truth’, positivity, and how much can be understood in the world. Usually this need go no further than adopt one an existing critique or interpretation, such as feminist research methods, or post-positivism. But it should also explain why the qualitative approach was appropriate for this research question, and thus what the appropriate methodology was.

While often connected most clearly to method, the methodology should also touch on the approach selected for analysis and interpretation, noting that adopting something common like grounded theory actually implies a whole series of theoretical and epistemological underpinnings. In a journal article, this will be short: typically only a few sentences, unless the paper is adopting or proposing a new or unusual take on some theoretical stance. But in a qualitative-based thesis, this could well be a chapter in it’s own right.

Finally, researchers should consider some sort of engagement with ‘reflexivity’ and explaining the role and influence of the researcher on the research project. I’ve got a whole article on this , but being open and explicit about the fact that research is not ‘value-free’ and that the background and positionality of the researcher influences the project is usually a key principle in qualitative research.

Methods and analysis

Qualitative methodologies have great variety in the type of methods that can be used, and subtleties as to how they are applied. Therefore it is probably more important to describe the method in detail than in quantitative based research projects, which often have very standard formula for applying tools and measurements. It’s rarely enough to say ‘We interviewed’ or ‘We ran focus groups ’ as these common methods can be applied in many different ways. So specify not just whether you used semi-structured or unstructured interviews, but consider describing the settings, interview guides, and any underlining theoretical or methodological stances.

As a reviewer, I also like to see details of both the sampling and recruitment categories – and as I’ve written before, I think these are distinct and important things. When using the small sample sizes that are hallmarks of most qualitative research, it is especially important to know who these people are, where they are from and how they were selected. Although we might get details about individual respondents lives and backgrounds later, its still important to give an overview of the people who make up the data – just remember it’s not always necessary to reduce these to statistical averages, such as the percentage of people in each age range.

It’s also very important to give a good level of detail about the analytical approach. I’ve written a LOT about this, but suffice it to say that just saying ‘We used grounded theory ’ or ‘We applied thematic analysis ’ is rarely specific enough – again due to the many different ways these terms are interpreted and enacted. Usually the qualitative analysis process is exploratory, non-linear and fraught with missteps and overlapping approaches, so is worthy of more detail. As qualitative research relies so much on the interpretation of the researcher, authors deserve some insight into the analytic process. If using coding, a list of codes, or illustration of some of the main ones can be insightful, even in an appendix.

Another pet hate or mine is papers that just refer to any qualitative analysis software as ‘We analysed the results in Quirkos/Nvivo’. Again, this tells the reader no more useful information than saying ‘We wrote the results using a blue pen’ – it’s not the tool, but how is is applied that affects and defines the analytic approach!

Quoting Data

In the results, findings and discussion sections, a lot of outputs based on qualitative research include extracts from the qualitative data: often from the transcripts from interviews, focus groups , diaries etc. Including quotes like this is a key feature in qualitative research outputs, they give the reader a chance to hear the participants in their own words, giving some validation of the researcher’s own interpretations. They also are effective at illustrating key points in the data and moving on the flow, and providing a framing device for discussing findings. Qualitative software like Quirkos can also help greatly at this stage, helping you keep track of quotes on particular topics, or organised by key quotes so you can quickly find them. However, there is the challenge of the ‘wall of text’.

There is a risk of the paper or chapter becoming over-run with quotations, which coming from different participants with different perspectives can become overwhelming for the reader. In general quotes should be used sparingly, for illustrative snapshots, or colourful instances where the quote says something better than the researcher can. In general, quotes from transcripts won’t be as short and generalisable as a sentence from the writer.

There’s also a temptation to use a quote to prove every conclusion or statement that the author wants to make, in the same way you would have a reference to back up each statement made in a literature review or introduction. But this is rarely necessary, as it will also break the flow of the writing and lead to issues with space and length. The writer should use just enough quotes to establish trust from the reader of their interpretations, saving quotes for when the author is making an important or surprising finding.

There is also the possibility of using two different types of quotes: short in-text quips, and longer multiple-sentence extractions. Shorter quotes are best for using just a few words, or a sentence at most that fits within the discussion. For example, one person may comment, ‘Time is always precious when you have children’. Here it’s not always necessary to attribute the quote to a particular individual (unless what they say is particular to their identity or case).

Longer quotes break the flow of the text, and should usually be formatted as an indented paragraph. These should almost always have a separate line after the quote giving the participant’s number, pseudonym and any relevant information about them, for example age, location or gender if it is relevant to understanding the context of the quote. Usually these should be kept as short as necessary, using … to truncate any sections of the quote that are not relevant. They also need to make sense alone, so any references to ‘it’ or ‘them’ or ‘that’ which are not obvious in the extract should be replaced with a definition in square brackets, for example [my feelings], [my husband] or [my car].

This is even true of other data types, especially pictures. Although most research products like journal articles and theses unfortunately make it very difficult to include audio and video extracts, pictures are possible. Yet these also break the flow of text, and take up a lot of space. They should also be used sparingly, and be well integrated and illustrative of the argument being made.

There can also be additional confidentiality considerations including any multimedia extracts. Text quotations automatically remove the audible voice and face of participants, but this might have to be done manually for participants. Permission to share photos, especially those showing faces and other sensitive or personal situations should also be explicitly sought, ideally for each type of output that might be produced.

Finally, quotes can’t do everything, many important aspects of subtext, and the unspoken (whether non-verbal, or not willing to share) are important context to give the reader. It’s up to the writer to connect the dots, be the expert that was part of the whole process and summarise a huge amount of rich qualitative data into a coherent story.

Discussion and other considerations

Latterly, any output needs to summarise the data and process, and refer back to the research questions and the wider literature. There will often be new questions posed by the data, as well as any conclusions from the data. Finally, consider being honest about what went wrong in the project – either in the data collection stage, or the analysis when theories and assumptions were challenged and changed.

Remember, just as good qualitative research has a story at it’s centre, the same should be true of communicating the findings. Partly it’s a story of the research project (and the role of the researchers in it), but also the story of the respondents – their own journey, experiences and lives. That is why creating a single story that encapsulates a common and differing tales across many participants can be a challenge.

Quirkos is a unique tool for qualitative analysis that helps you explore, manage and discover stories in your qualitative data. We designed it to help us write up our own qualitative data easier and better, and you can try yourself for free right here ! There’s no registration needed for the offline version, and the cloud subscription service lets researchers, work, collaborate and share project data with ease.

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Writing a qualitative research report

Affiliation.

• 1 School of Nursing and Midwifery Studies, University of Wales College of Medicine, Heath Park, Cardiff, UK. [email protected]
• PMID: 15234716
• DOI: 10.1016/j.aaen.2003.11.006

A research project in nursing or nursing education is probably only complete once the findings have been published. This paper offers a format for writing a qualitative research report for publication. It suggests, at least, the following sections: introduction, aims of the study, review of the literature, sample, data collection methods, data analysis methods, findings, discussion, conclusion, abstract. Each of these sections is addressed along with many written-out examples. In some sections, alternative approaches are suggested. The aim of the paper is to help the neophyte researcher to structure his or her report and for the experienced researcher to reflect on his or her current practice. References to other source material on qualitative research are given.

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Food insecurity and sleep-related problems in adolescents: findings from the ehdla study.

1. Introduction

2. materials and methods, 2.1. study design and population, 2.2. procedures, 2.2.1. food insecurity, 2.2.2. sleep-related problems, 2.2.3. covariates, 2.3. statistical analysis, 4. discussion, 5. conclusions, author contributions, institutional review board statement, informed consent statement, data availability statement, acknowledgments, conflicts of interest.

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de Camargo, E.M.; Gutiérrez-Espinoza, H.; López-Gil, J.F. Food Insecurity and Sleep-Related Problems in Adolescents: Findings from the EHDLA Study. Nutrients 2024 , 16 , 1960. https://doi.org/10.3390/nu16121960

de Camargo EM, Gutiérrez-Espinoza H, López-Gil JF. Food Insecurity and Sleep-Related Problems in Adolescents: Findings from the EHDLA Study. Nutrients . 2024; 16(12):1960. https://doi.org/10.3390/nu16121960

de Camargo, Edina Maria, Héctor Gutiérrez-Espinoza, and José Francisco López-Gil. 2024. "Food Insecurity and Sleep-Related Problems in Adolescents: Findings from the EHDLA Study" Nutrients 16, no. 12: 1960. https://doi.org/10.3390/nu16121960

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• Published: 19 June 2024

Detection of microplastics in the human penis

• Jason Codrington   ORCID: orcid.org/0009-0003-1490-4211 1 ,
• Alexandra Aponte Varnum 1 ,
• Lars Hildebrandt 2 ,
• Daniel Pröfrock 2 ,
• Joginder Bidhan 1 ,
• Kajal Khodamoradi   ORCID: orcid.org/0000-0003-2951-4382 1 ,
• Anke-Lisa Höhme 3 ,
• Martin Held   ORCID: orcid.org/0000-0003-1869-463X 3 ,
• Aymara Evans 1 ,
• David Velasquez   ORCID: orcid.org/0009-0003-0475-4918 1 ,
• Christina C. Yarborough 1 ,
• Bahareh Ghane-Motlagh 4 ,
• Ashutosh Agarwal 1 , 5 ,
• Justin Achua   ORCID: orcid.org/0000-0002-4159-439X 6 ,
• Edoardo Pozzi   ORCID: orcid.org/0000-0002-0228-7039 1 , 7 , 8 ,
• Francesco Mesquita 1 ,
• Francis Petrella 1 ,
• David Miller 1 &
• Ranjith Ramasamy 1  

International Journal of Impotence Research ( 2024 ) Cite this article

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• Medical research
• Sexual dysfunction

The proliferation of microplastics (MPs) represents a burgeoning environmental and health crisis. Measuring less than 5 mm in diameter, MPs have infiltrated atmospheric, freshwater, and terrestrial ecosystems, penetrating commonplace consumables like seafood, sea salt, and bottled beverages. Their size and surface area render them susceptible to chemical interactions with physiological fluids and tissues, raising bioaccumulation and toxicity concerns. Human exposure to MPs occurs through ingestion, inhalation, and dermal contact. To date, there is no direct evidence identifying MPs in penile tissue. The objective of this study was to assess for potential aggregation of MPs in penile tissue. Tissue samples were extracted from six individuals who underwent surgery for a multi-component inflatable penile prosthesis (IPP). Samples were obtained from the corpora using Adson forceps before corporotomy dilation and device implantation and placed into cleaned glassware. A control sample was collected and stored in a McKesson specimen plastic container. The tissue fractions were analyzed using the Agilent 8700 Laser Direct Infrared (LDIR) Chemical Imaging System (Agilent Technologies. Moreover, the morphology of the particles was investigated by a Zeiss Merlin Scanning Electron Microscope (SEM), complementing the detection range of LDIR to below 20 µm. MPs via LDIR were identified in 80% of the samples, ranging in size from 20–500 µm. Smaller particles down to 2 µm were detected via SEM. Seven types of MPs were found in the penile tissue, with polyethylene terephthalate (47.8%) and polypropylene (34.7%) being the most prevalent. The detection of MPs in penile tissue raises inquiries on the ramifications of environmental pollutants on sexual health. Our research adds a key dimension to the discussion on man-made pollutants, focusing on MPs in the male reproductive system.

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Desai Sethi Urology Institute, Miller School of Medicine, University of Miami, Miami, FL, USA

Jason Codrington, Alexandra Aponte Varnum, Joginder Bidhan, Kajal Khodamoradi, Aymara Evans, David Velasquez, Christina C. Yarborough, Ashutosh Agarwal, Edoardo Pozzi, Francesco Mesquita, Francis Petrella, David Miller & Ranjith Ramasamy

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Jason Codrington—conceptualization, methodology, investigation, project administration, data curation, visualization, writing—original draft, editing. Alexandra Aponte Varnum—investigation, writing—original draft, editing, data curation, visualization. Lars Hildebrandt—investigation, writing—original draft, validation, resources. Daniel Pröfrock—investigation, editing, validation, resources. Joginder Bidhan—resources, writing—original draft. Kajal Khodamoradi—project administration, resources. Anke-Lisa Höhme—investigation, visualization. Martin Held—writing—original draft, editing. Aymara Evans—writing—original draft. David Velasquez—writing—original draft. Christina C. Yarborough—writing—original draft. Bahareh Ghane-Motlagh—investigation. Ashutosh Agarwal—investigation. Justin Achua—writing—original draft. Edoardo Pozzi—editing. Francesco Mesquita—editing. Francis Petrella—writing—review. David Miller—writing—review. Ranjith Ramasamy—conceptualization, methodology, project administration, resources, supervision, editing, funding acquisition

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Codrington, J., Varnum, A.A., Hildebrandt, L. et al. Detection of microplastics in the human penis. Int J Impot Res (2024). https://doi.org/10.1038/s41443-024-00930-6

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Overview and key findings of the 2024 Digital News Report

This year’s report comes at a time when around half the world’s population have been going to the polls in national and regional elections, and as wars continue to rage in Ukraine and Gaza. In these troubled times, a supply of accurate, independent journalism remains more important than ever, and yet in many of the countries covered in our survey we find the news media increasingly challenged by rising mis- and disinformation, low trust, attacks by politicians, and an uncertain business environment.

Our country pages this year are filled with examples of layoffs, closures, and other cuts due to a combination of rising costs, falling advertising revenues, and sharp declines in traffic from social media. In some parts of the world these economic challenges have made it even harder for news media to resist pressures from powerful businesspeople or governments looking to influence coverage and control narratives.

There is no single cause for this crisis; it has been building for some time, but many of the immediate challenges are compounded by the power and changing strategies of rival big tech companies, including social media, search engines, and video platforms. Some are now explicitly deprioritising news and political content, while others have switched focus from publishers to ‘creators’, and pushing more fun and engaging formats – including video – to keep more attention within their own platforms. These private companies do not have any obligations to the news, but with many people now getting much of their information via these competing platforms, these shifts have consequences not only for the news industry, but also our societies. As if this were not enough, rapid advances in artificial intelligence (AI) are about to set in motion a further series of changes including AI-driven search interfaces and chatbots that could further reduce traffic flows to news websites and apps, adding further uncertainty to how information environments might look in a few years.

Our report this year documents the scale and impact of these ‘platform resets’. With TikTok, Instagram Reels, and YouTube on the rise, we look at why consumers are embracing more video consumption and investigate which mainstream and alternative accounts – including creators and influencers – are getting most attention when it comes to news. We also explore the very different levels of confidence people have in their ability to distinguish between trustworthy and untrustworthy content on a range of popular third-party platforms around the world. For the first time in our survey, we also take a detailed look at consumer attitudes towards the use of AI in the news, supported by qualitative research in three countries (the UK, US, and Mexico). As publishers rapidly adopt AI, to make their businesses more efficient and to personalise content, our research suggests they need to proceed with caution, as the public generally wants humans in the driving seat at all times.

With publishers struggling to connect with much of the public, and growing numbers of people selectively (and in some cases continuously) avoiding the news, we have also explored different user needs to understand where the biggest gaps lie between what audiences want and what publishers currently provide. And we look at the price that some consumers are currently paying for online news and what might entice more people to join them. 

An episode on the findings

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This 13th edition of our Digital News Report , which is based on data from six continents and 47 markets, reminds us that these changes are not always evenly distributed. While journalism is struggling overall, in some parts of the world news media remain profitable, independent, and widely trusted. But even in these countries, we find challenges around the pace of change, the role of platforms, and how to adapt to a digital environment that seems to become more complex and fragmented every year. The overall story is captured in this Executive Summary, followed by Section 1 with chapters containing additional analysis, and then individual country and market pages in Section 2.

Here is a summary of some of the key findings from our 2024 research.

In many countries, especially outside Europe and the United States, we find a significant further decline in the use of Facebook for news and a growing reliance on a range of alternatives including private messaging apps and video networks. Facebook news consumption is down 4 percentage points, across all countries, in the last year.

News use across online platforms is fragmenting, with six networks now reaching at least 10% of our respondents, compared with just two a decade ago. YouTube is used for news by almost a third (31%) of our global sample each week, WhatsApp by around a fifth (21%), while TikTok (13%) has overtaken Twitter (10%), now rebranded X, for the first time.

Linked to these shifts, video is becoming a more important source of online news, especially with younger groups. Short news videos are accessed by two-thirds (66%) of our sample each week, with longer formats attracting around half (51%). The main locus of news video consumption is online platforms (72%) rather than publisher websites (22%), increasing the challenges around monetisation and connection.

Although the platform mix is shifting, the majority continue to identify platforms including social media, search, or aggregators as their main gateway to online news. Across markets, only around a fifth of respondents (22%) identify news websites or apps as their main source of online news – that’s down 10 percentage points on 2018. Publishers in a few Northern European markets have managed to buck this trend, but younger groups everywhere are showing a weaker connection with news brands than they did in the past.

Turning to the sources that people pay most attention to when it comes to news on various platforms, we find an increasing focus on partisan commentators, influencers, and young news creators, especially on YouTube and TikTok. But in social networks such as Facebook and X, traditional news brands and journalists still tend to play a prominent role.

Concern about what is real and what is fake on the internet when it comes to online news has risen by 3 percentage points in the last year with around six in ten (59%) saying they are concerned. The figure is considerably higher in South Africa (81%) and the United States (72%), both countries that have been holding elections this year.

Worries about how to distinguish between trustworthy and untrustworthy content in online platforms is highest for TikTok and X when compared with other online networks. Both platforms have hosted misinformation or conspiracies around stories such as the war in Gaza, and the Princess of Wales’s health, as well as so-called ‘deep fake’ pictures and videos.

As publishers embrace the use of AI we find widespread suspicion about how it might be used, especially for ‘hard’ news stories such as politics or war. There is more comfort with the use of AI in behind-the-scenes tasks such as transcription and translation; in supporting rather than replacing journalists. 

Trust in the news (40%) has remained stable over the last year, but is still four points lower overall than it was at the height of the Coronavirus pandemic. Finland remains the country with the highest levels of overall trust (69%), while Greece (23%) and Hungary (23%) have the lowest levels, amid concerns about undue political and business influence over the media.

Elections have increased interest in the news in a few countries, including the United States (+3), but the overall trend remains downward. Interest in news in Argentina, for example, has fallen from 77% in 2017 to 45% today. In the United Kingdom interest in news has almost halved since 2015. In both countries the change is mirrored by a similar decline in interest in politics.

At the same time, we find a rise in selective news avoidance. Around four in ten (39%) now say they sometimes or often avoid the news – up 3 percentage points on last year’s average – with more significant increases in Brazil, Spain, Germany, and Finland. Open comments suggest that the intractable conflicts in Ukraine and the Middle East may have had some impact. In a separate question, we find that the proportion that say they feel ‘overloaded’ by the amount of news these days has grown substantially (+11pp) since 2019 when we last asked this question.

In exploring user needs around news, our data suggest that publishers may be focusing too much on updating people on top news stories and not spending enough time providing different perspectives on issues or reporting stories that can provide a basis for occasional optimism. In terms of topics, we find that audiences feel mostly well served by political and sports news but there are gaps around local news in some countries, as well as health and education news.

Our data show little growth in news subscription, with just 17% saying they paid for any online news in the last year, across a basket of 20 richer countries. North European countries such as Norway (40%) and Sweden (31%) have the highest proportion of those paying, with Japan (9%) and the United Kingdom (8%) amongst the lowest. As in previous years, we find that a large proportion of digital subscriptions go to just a few upmarket national brands – reinforcing the winner-takes-most dynamics that are often linked with digital media.

In some countries we find evidence of heavy discounting, with around four in ten (41%) saying they currently pay less than the full price. Prospects of attracting new subscribers remain limited by a continued reluctance to pay for news, linked to low interest and an abundance of free sources. Well over half (55%) of those that are not currently subscribing say that they would pay nothing for online news, with most of the rest prepared to offer the equivalent of just a few dollars per month, when pressed. Across markets, just 2% of non-payers say that they would pay the equivalent of an average full price subscription.

News podcasting remains a bright spot for publishers, attracting younger, well-educated audiences but is a minority activity overall. Across a basket of 20 countries, just over a third (35%) access a podcast monthly, with 13% accessing a show relating to news and current affairs. Many of the most popular podcasts are now filmed and distributed via video platforms such as YouTube and TikTok.

The great platform reset is underway

Online platforms have shaped many aspects of our lives over the last few decades, from how we find and distribute information, how we are advertised to, how we spend our money, how we share experiences, and most recently, how we consume entertainment. But even as online platforms have brought great convenience for consumers – and advertisers have flocked to them – they have also disrupted traditional publishing business models in very profound ways. Our data suggest we are now at the beginning of a technology shift which is bringing a new wave of innovation to the platform environment, presenting challenges for incumbent technology companies, the news industry, and for society.

Platforms have been adjusting strategies in the light of generative AI, and are also navigating changing consumer behaviour, as well as increased regulatory concerns about misinformation and other issues. Meta in particular has been trying to reduce the role of news across Facebook, Instagram, and Threads, and has restricted the algorithmic promotion of political content. The company has also been reducing support for the news industry, not renewing deals worth millions of dollars, and removing its news tab in a number of countries. 1

The impact of these changes, some which have been going on for a while, is illustrated by our first chart which uses aggregated data from 12, mostly developed, markets we have been following since 2014. It shows declining, though still substantial, reach for Facebook over time – down 16pp since 2016 – as well as increased fragmentation of attention across multiple networks. A decade ago, only Facebook and YouTube had a reach of more than 10% for news in these countries, now there are many more networks, often being used in combination (several of them are owned by Meta). Taken together, platforms remain as important as ever – but the role and strategy of individual platforms is changing as they compete and evolve, with Facebook becoming less important, and many others becoming relatively more so.

The previous chart also highlights the strong shift towards video-based networks such as YouTube, TikTok (and Instagram), all of which have grown in importance for news since the COVID-19 pandemic drove new habits. Faced with new competition, both Facebook and X have been refocusing their strategies, looking to keep users within the platform rather than link out to publishers as they might have done in the past. This has involved a prioritisation of video and other proprietary formats. Industry data show that the combined effect of these changes was to reduce traffic referrals from Facebook to publishers by 48% last year and from X by 27%. 2  Looking at survey data across our 47 markets we find much regional and country-based variation in the use of different networks, with the fastest changes in the Global South, perhaps because they tend to be more dependent on social media for news.

TikTok remains most popular with younger groups and, although its use for any purpose is similar to last year, the proportion using it for news has grown to 13% (+2) across all markets and 23% for 18–24s. These averages hide rapid growth in Africa, Latin America, and parts of Asia. More than a third now use the network for news every week in Thailand (39%) and Kenya (36%), with a quarter or more accessing it in Indonesia (29%) and Peru (27%). This compares with just 4% in the UK, 3% in Denmark, and 9% in the United States. The future of TikTok remains uncertain in the US following concerns about Chinese influence and it is already banned in India, though similar apps, such as Moj, Chingari, and Josh, are emerging there.

The growing reach of TikTok and other youth-orientated networks has not escaped the attention of politicians who have incorporated it into their media campaigns. Argentina’s new populist president, Javier Milei, runs a successful TikTok account with 2.2m followers while the new Indonesian president, Prabowo Subianto, swept to victory in February using a social media campaign featuring AI-generated images, rebranding the former hard-line general as a cute and charming dancing grandpa. We explore the implications for trust and reliability of information later in this report.

Shift to video networks brings different dynamics

Traditional social networks such as Facebook and Twitter were originally built around the social graph – effectively this means content posted directly by friends and contacts (connected content). But video networks such as YouTube and TikTok are focused more on content that can be posted by anybody – recommended content that does not necessarily come from accounts users have chosen to follow. 

In previous research ( Digital News Report 2021 , 2023 ) we have shown that when it comes to online news, most audiences still prefer text because of its flexibility and control, but that doesn’t mean that video – and especially short-form video – is not becoming a much bigger part of media diets. Across countries, two-thirds (66%) say they access a short news video, which we defined as a few minutes or less, at least once a week, again with higher levels outside the US and Western Europe. Almost nine in ten of the online population in Thailand (87%), access short-form videos weekly, with half (50%) saying they do this every day. Americans access a little less often (60% weekly and 20% daily), while the British consume the least short-form news (39% weekly and just 9% daily).

Live news streams and long-form recordings are also widely consumed. Taking the United States as an example, we can see how under 35s consume the most of each format, with older people being relatively less likely to consume live or long-form video.

One of the reasons why news video consumption is higher in the United States than in most European countries is the abundant supply of political content from both traditional and non-traditional sources. Some are creators native to online media. Others have come from broadcast backgrounds. In the last few years, a number of high-profile TV anchors, including Megyn Kelly, Tucker Carlson, and Don Lemon, have switched their focus to online platforms as they look to take advantage of changing consumer behaviour. 

Carlson’s interview with Russian president Vladimir Putin received more than 200m plays on X and 34m on his YouTube channel. In the UK, another controversial figure, Piers Morgan, recently left his daily broadcast show on Talk TV in favour of the flexibility and control offered as an independent operator working across multiple streaming platforms. (It is worth noting that many of these platform moves came only after the person in question walked out on or were ditched by their former employers on mainstream TV.)

The jury is currently out on whether these big personalities can build robust traffic or sustainable businesses within platform environments. There is a similar challenge for mainstream publishers who find platform-based videos harder to monetise than those consumed via owned and operated websites and apps. 

YouTube and Facebook remain the most important platforms for online news video overall (see next chart), but we see significant market differences, with Facebook the most popular for video news in the Philippines, YouTube in South Korea, and X and TikTok playing a key role in Nigeria and Indonesia respectively. YouTube is also the top destination for under 25s, though TikTok and Instagram are not far behind.

Older viewers still like to consume much of their video through news websites, though the majority say they mostly access video via third-party platforms. Only in countries such as Norway do we find that getting on for half of users (45%) say their main video consumption is via websites, a reflection of the strength of brands in that market, a commitment to a good user experience, and a strategy that restricts the number of publisher videos that are posted to platforms like Facebook and YouTube. 

Where do people pay attention when using online platforms?

One of the big challenges of the shift to video networks with a younger age profile is that journalists and news organisations are often eclipsed by news creators and other influencers, even when it comes to news.

This year we repeated a question we asked first in 2021 about where audiences pay most attention when it comes to news on various platforms. As in previous years, we find that across markets, while mainstream media and journalists often lead conversations in X and Facebook, they struggle to get as much attention in Instagram, Snapchat, and TikTok where alternative sources and personalities, including online influencers and celebrities, are often more prominent.

It is a similar story across many markets, though differences emerge when we look at specific online networks and at a country level. In the following chart we compare attention around news content on YouTube, the second largest network overall. We find that alternative sources and online influencers play a bigger role in both the United States and Brazil than is the case in the United Kingdom.

But who are these personalities and celebrities and what kind of alternative sources are attracting attention? To answer these questions, we asked respondents that had selected each option to list up to three mainstream accounts they followed most closely and then three alternative ones (e.g. alternative accounts, influencers, etc). We then counted and coded these responses.

In the United States, in particular, we find a wide range of politically partisan voices including Tucker Carlson, Alex Jones (recently reinstated on X), Ben Shapiro, Glenn Beck, and many more. These voices come mostly from the right, with a narrative around a ‘trusted’ alternative to what they see as the biassed liberal mainstream media, but there is also significant representation on the progressive left (David Pakman and commentators from Meidas Touch). The top 10 named individuals in the US list are all men who tend to express strong opinions about politics.

Partisan voices (from both left and right) are an important part of the picture elsewhere, but we also find diverse perspectives and new approaches to storytelling. In France, Hugo Travers, 27, known online as Hugo Décrypte, has become a leading news source for young French people for his explanatory videos about politics (2.6m subscribers on YouTube and 5.8m on TikTok). Our data show that across all networks he gets more mentions than traditional news brands such as Le Monde or BFMTV. According to our data, the average audience age of his followers is just 27, compared to between 40 and 45 for large traditional brands such as Le Monde or BFM TV.

Youth-focused brands Brut and Konbini were also widely cited in France, while in the UK, Politics Joe and TLDR News, set up by Jack Kelly, attract attention for videos that try to make serious topics accessible for young people. The most mentioned TikTok news creator in the UK is Dylan Page, who has more than 10m followers on the platform. In the United States, Vitus Spehar presents a fun daily news round-up, often from a prone position on the floor, @underthedesknews (a satirical dig at the classic TV format).

Youth-based news influencers around the world

Coverage of war and conflict

We also found a number of accounts sharing videos about the wars in Gaza and Ukraine. With mainstream news access restricted, young social media influencers in Gaza, Yemen, and elsewhere have been filling in the gaps – documenting the often-brutal realities of life on the ground. Because these videos are posted by many different accounts and ordinary people, it is hard to quantify the impact, but our methodology does pick up a few individual influencer accounts as well as campaigning groups that pull together footage from across social media. As one example, the Instagram account Eye on Palestine appears in our data across a number of countries. The account says it brings ‘the sounds and images that official media does not show’. WarMonitor, one of a number of influential accounts that have been recommended by prominent figures such as Elon Musk, has added hundreds of thousands of followers during the Israel–Palestine conflict.

Finally, celebrities such as Taylor Swift, the Kardashians, and Lionel Messi were widely mentioned by younger people, mostly in reference to Instagram, despite the fact that they rarely talk about politics. This suggests that younger people take a wide view of news, potentially including updates on a singer’s tour dates, on fashion, or on football.

Motivations for using social video

In analysing open comments, we found three core reasons why audiences are attracted to video and other content in social and video platforms.

First, respondents, including many younger ones, say the comparatively unfiltered nature of much of the coverage makes it come across as more trustworthy and authentic than traditional media. ‘I like the videos that were taken by an innocent bystander. These videos are unedited and there is no bias or political spin,’ says one. 3  There is an enduring belief that videos are harder to falsify, while enabling people to make up their own mind, even as the development of AI may lead more people to question it.

Secondly, people talk about the convenience of having news served to you on a platform where you already spend time, which knows your interests, and where ‘the algorithm feeds suggestions based on previous viewing’.

Thirdly, social video platforms are valued for the different perspectives they bring. For some people that meant a partisan perspective that aligns with their interests, but for others it related to the greater depth around a personal passion or a wider range of topics to explore.

It is important to note that very few people only use online video for news each week – around 4% across countries according to our data. The majority use a mix of text, video, and audio – and a combination of mainstream brands that may or may not be supplemented by alternative voices. But as audiences consume more content in these networks, they sometimes worry less about where the content comes from, and more about the convenience and choice delivered within their feed. Though there are examples of successful video consumption within news websites and apps, for most publishers the shift towards video presents a difficult balancing act. How can they take advantage of a format that can engage audiences in powerful ways, including younger ones, while developing meaningful relationships – and businesses – on someone else’s platform? 

To what extent do people feel confident about identifying trustworthy news in different online platforms?

In this critical year of elections, many worry about the reliability of content, about the scope for manipulation of online platforms by ‘bad actors’, over how some domestic politicians and media personalities express themselves, and about the opaque ways in which platforms themselves select and promote content. 

Across markets the proportion of our respondents that say they are worried about what is real and what is fake on the internet overall is up 3pp from 56% to 59%. It is highest in some of the countries holding polls this year, including South Africa (81%), the United States (72%), and the UK (70%). Taking a regional view, we find the highest levels of concern in Africa (75%) and lower levels in much of Northern and Western Europe (e.g., Norway 45% and Germany 42%).

Previous research shows that these audience concerns about misinformation are often driven less by news that is completely ‘made up’ and more about seeing opinions and agendas that they may disagree with – as well as journalism they regard as superficial and unsubstantiated. In this context it is perhaps not surprising that politics remains the topic that engenders the most concern about ‘fake or misleading’ content, along with health information and news about the wars in Ukraine and Gaza.

Against this backdrop of widespread concern, we have, for the first time, asked users of specific online platforms, how easy or difficult they find it to distinguish between trustworthy and untrustworthy content. Given its increasing use for news – and its much younger age profile – it is worrying to find that more than a quarter of TikTok users (27%) say they struggle to detect trustworthy news, the highest score out of all the networks covered. A further quarter have no strong opinion and around four in ten (44%) say they find it easy. Fact-checkers and others have been paying much more attention to the network recently, with Newsguard reporting in 2022 that a fifth (20%) of a sample of searches on prominent news topics such as Ukraine and COVID vaccines contained misinformation. 4 Most recently it was at the centre of a flood of unfounded rumours and conspiracies about the Princess of Wales after her hospital operation. A significant proportion of X users (24%) also say that it is hard to pick out trustworthy news. This may be because news plays an outsized role on the platform, or because of the wide range of views expressed, further encouraged by Elon Musk, a self-declared free speech advocate, since he took over the company.

The numbers are only a bit lower in some of the largest networks such as Facebook, Instagram, YouTube, and WhatsApp, which have all been implicated in various misinformation problems too.

While there is widespread concern about different networks, it is also important to recognise that many people are confident about their ability to tell trustworthy and untrustworthy news and information apart. In fact, around half of respondents using each network say they find it easy to do so, including many younger and less educated users – even if these perceptions may or may not be based on reality. All of the major social and video platforms recognise these challenges, and have been boosting their technical and human defences, not least because of the potential for a flood of AI-generated synthetic content in this year’s elections.

In exploring country differences, we find that people in Western European countries such as Germany (see the next chart) are less confident about their ability to distinguish between trustworthy and untrustworthy information on X and TikTok than respondents in the United States. This may reflect very different official and media narratives about the balance between free speech and online harms. The EU has introduced legislation such as the Digital Services Act, imposing greater obligations on platforms in the run-up to June’s EU Parliament elections. 5  X is currently being investigated over suspected breaches of content moderation rules. 

But even within the United States, which has lower concern generally, we find sharp differences based on political beliefs. Amid bitter debates over de-platforming, some voices on the left have been calling for more restrictions and many on the right insisting on even more free speech. We see this political split clearly in the data, especially in terms of attitudes to X and to some extent YouTube.

In our data, people on the left are much more suspicious of content they see in both networks, but other platforms are seen as mostly neutral in this regard. In no other market do we see the same level of polarisation around X, but the same broad left-right dynamics are at play, with the left more uncomfortable about the societal impact of harmful online content.

In some African markets, such as Kenya, we see a significant difference in concern over TikTok compared with other popular networks such as X or WhatsApp, the most used network for news. The app has been labelled ‘a serious threat to the cultural and religious values of Kenya’ in a petition to parliament after being implicated in the sharing of adult content, misinformation, and hate speech. 6 But one other reason for TikTok’s higher score may be because most content there is posted by people they don’t know personally. WhatsApp posts tend to come from a close social circle, who are likely to be more trusted. Paradoxically, this could mean that information spread in WhatsApp carries more danger, because defences may be lower.

Fears around AI and misinformation

The last year has seen an increased incidence of so-called ‘ deepfakes ’, generated by AI including an audio recording falsely purporting to be Joe Biden asking supporters not to vote in a primary, a campaign video containing manipulated photos of Donald Trump, and artificially generated pictures of the war in the Middle East, posted by supporters of both the Palestinian and Israeli sides aimed at winning sympathy for their cause.

AI-generated (fake) pictures from the war have been widely circulated on social media

Our qualitative research suggests that, while most people do not think they have personally seen these kinds of synthetic images or videos, some younger, heavy users of social media now think they are coming across them regularly.

In the US some of our participants felt widespread use of generative AI technologies was likely to make detecting misinformation more difficult, especially around important subjects such as politics and elections; others worried about the lack of transparency and the potential for discrimination against minority groups.

Others took a more balanced view, noting that these technologies could be used to provide more relevant and useful content, while also recognising the risks.

Journalistic uses of artificial intelligence

News organisations have reported extensively on the development and impact of AI on society, but they are also starting to adopt these technologies themselves for two key reasons. First, they hope that automating behind-the-scenes processes such as transcription, copy-editing, and layout will substantially reduce costs. Secondly, AI technologies could help to personalise the content itself – making it more appealing for audiences. They need to do this without reducing audience trust, which many believe will become an increasingly critical asset in a world of abundant synthetic media.

In the last year, we have seen media companies deploying a range of AI solutions, with varying degrees of human oversight. Nordic publishers, including Schibsted, now include AI-generated ‘bullet points’ at the top of many of their titles’ stories to increase engagement. One German publisher uses an AI robot named Klara Indernach to write more than 5% of its published stories, 7  while others have deployed tools such as Midjourney or OpenAI’s Dall-E for automating graphic illustrations. Meanwhile, Digital News Report country pages from Indonesia , South Korea , Slovakia , Taiwan , and Mexico , amongst others, reference a range of experimental chatbots and avatars now presenting the news. Nat is one of three AI-generated news readers from Mexico’s Radio Fórmula, used to deliver breaking news and analysis through its website and across social media channels. 8

Nat, one of Radio Fórmula’s AI-generated news readers

Elsewhere we find content farms increasingly using AI to rewrite news, often without permission and with no human checks in the loop. Industry concerns about copyright and about potential mistakes (some of which could be caused by so-called hallucinations) are well documented, but we know less about how audiences feel about these issues and the implications for trust overall. 

Across 28 countries where we included questions, we find our survey respondents to be mostly uncomfortable with the use of AI in situations where content is created mostly by the AI with some human oversight. By contrast, there is less discomfort when AI is used to assist (human) journalists, for example in transcribing interviews or summarising materials for research. Here respondents are broadly more comfortable than uncomfortable.

Our findings, which also show that respondents in the US are significantly more comfortable about different uses of AI than those living in Europe, may be linked to the cues people are getting from the media. British press coverage of AI, for example, has been characterised as overly negative and sensationalist, 9 and UK scores for comfort with less closely monitored use of AI are the lowest in our survey (10%). By contrast, the leading role of US companies and the opportunities for jobs and growth play a bigger part in US media narratives. Across countries, comfort levels are higher with younger groups who are some of the heaviest users of AI tools such as ChatGPT.

Our research also indicates that people who tend to trust the news in general are also more likely to be comfortable with uses of AI where humans (journalists) remain in control, compared with those that don’t. We find comfort gaps ranging from 24 percentage points in the US to 10 percentage points in Mexico. Our qualitative research on AI suggests that trust will be a key issue going forward, with many participants feeling that traditional media have much to lose.

Comfort with AI is also closely related to the importance and seriousness of the subject being discussed. People say they feel less comfortable with AI-generated news on topics such as politics and crime, and more comfortable with sports, arts, or entertainment news, subjects where mistakes tend to have less serious consequences and where there is potentially more value in personalisation of the content. 

While participants were generally more concerned for some topics rather than others, there were some important nuances. For example, some could see the value in using AI to automate local election stories to provide a quicker comprehensive service, as these tended to be fact-based and didn’t involve the AI making political judgements.

Finally, we find that comfort levels about the different uses of AI tend to be higher with people who have read or heard more about it, even if many remain cautious. This suggests that, as people use the technology and find it personally useful , they may take a more balanced view of the risks and the benefits going forward.

Overall, we are still at the early stages of journalists’ usage of AI, but this also makes it a time of maximum risk for news organisations. Our data suggest that audiences are still deeply ambivalent about the use of the technology, which means that publishers need to be extremely cautious about where and how they deploy it. Wider concerns about a flood of synthetic content in online platforms means that trusted brands that use the technologies responsibly could be rewarded, but get things wrong and that trust could be easily lost. 

Gateways to news and the importance of search and aggregator portals

Publishers are not just concerned about falling referrals from social media but also about what might happen with search and other aggregators if chatbot interfaces take off. Google and Microsoft are both experimenting with integrating more direct answers to news queries generated by AI and a range of existing and new mobile apps are also looking to create new experiences that provide answers without requiring a click-through to a publisher.

It is important to note that across all markets, search and aggregators, taken together (33%), are a more important gateway to news than social media (29%) and direct access (22%). A large proportion of mobile alerts (9%) are also generated by aggregators and portals, adding to the concerns about what might happen next.

Unlike social media, search is seen as important across all age groups – 25% of under 35s also prefer to start news journeys with search – and because people are often actively looking for information, the resulting news journey tends to be more valuable for publishers than social fly-by traffic.

Looking at preferred gateways over time we find that search has been remarkably consistent while direct traffic has become less important and social has grown consistently (until this year). Beneath the averages however we do see significant differences across countries. Portals, which often incorporate search engines and mobile apps, are particularly important in parts of Asia. In Japan, Yahoo! News and Line News remain dominant, while local tech giants Naver and Daum are the key access points in South Korea – developing their own AI solutions. In the Czech Republic, Seznam has been an important local search engine, now supplemented with its own news service and also an innovator in AI. Social and video networks tend to be more important in other parts of Asia, as well as Africa and Latin America, but direct traffic still rules in a few parts of Northern Europe where intermediaries have historically played a smaller role. Publishers without regular direct access will be more vulnerable to platform changes and will inevitably find it harder to build subscription businesses. 

Even in countries with relatively strong brands such as the UK, we find significant generational differences when it comes to gateways. Older people are more likely to maintain direct connections, but in the last few years, especially since the COVID-19 pandemic, we have seen both 18–24s and now 25–35s becoming less likely to go directly to a website or app. Across markets we see the same trends with the gap between generations just as significant as country-based differences, if not more.

It is also worth noting the increasing success of mobile aggregators in some countries, many of which are increasingly powered by AI. In the United States, News Break (9%), which was founded by a Chinese tech veteran, has been growing fast with a similar market share to market leader Apple News (11%). In Asian markets, multiple aggregator apps and portals play important gateway and consumption roles, with AI features typically driving ever greater levels of personalisation.

Mobile aggregators tend to be more popular with younger news consumers and are becoming a bigger part of the picture overall, partly fuelled by notifications on relevant topics. In terms of search, there is little evidence that search traffic is drying up and it is certainly not a given that consumers will rush to adopt chatbot interfaces. Even so, publishers expect traffic from search and other gateways to be more unpredictable in the future and will be exploring alternatives with some urgency.

The business of news: subscriptions stalling?

A difficult advertising market, combined with rising costs and the decline in traffic from social media, has put more pressure on the bottom line, especially for publishers that have relied on platform distribution. These factors, together with news about US-based layoffs at the Los Angeles Times , Washington Post , NBC, Business Insider, Wall Street Journal , Condé Nast, and Sports Illustrated, recently led the New Yorker to publish an article titled: ‘Is the Media Prepared for an Extinction-Level Event?’ . The article argued that certain kinds of public interest journalism were now uneconomic and a new, more audience-focused approach was needed.

In this context, and with similar pressures all over the world, we are seeing news media looking to introduce or strengthen reader payment models such as subscription, membership, and donation. Paid models have been a rare bright spot in some of the richer countries in our survey, where publishers still have strong direct connections with readers, but have been difficult to make work elsewhere. As in previous years, our survey shows a significant proportion paying for online news in Norway (40%) and Sweden (31%) and over a fifth in the United States (22%) and Australia (21%), but much lower numbers in Germany (13%), France (11%), Japan (9%), and the UK (8%). There has been very little movement in these top line numbers in the last year. 

Proportion that paid for any online news in the last year Selected countries Via subscription/membership/donation or one-off payment

Across 20 countries, where a significant number of publishers are pushing digital subscriptions, payment levels have almost doubled since 2014 from 10% to 17%, but following a significant bump during the COVID pandemic, growth has slowed. Publishers have already signed up many of those prepared to pay, and converted some of the more intermittent payers to ongoing subscriptions or donations. But amid a cost-of-living crisis, it is proving difficult to persuade most of the public to do the same.

In most countries, we continue to see a ‘winner takes most’ market, with a few upmarket national titles scooping up a big proportion of users. In the United States, for example, the New York Times recently announced that it has over 10m subscribers (including 9.9m digital only) while the Washington Post ’s numbers have reportedly declined. Having said that, we do find a growing minority of countries where people are paying, on average, for more than one publication, including in the United States, Switzerland, Poland, and France (see table below). 

This may be because some publishers in these markets are bundling together titles in an all-access subscription (e.g., New York Times , Schibsted, Amedia, Bonnier, Mediahuis). As one example, Amedia’s +Alt product, which offers 100 newspapers, magazines, and podcasts, now accounts for 10% of Norwegian subscriptions, up 6 percentage points this year.

In Nordic countries, it is worth noting the high proportion of local titles being paid for online. In Canada, Ireland, and Switzerland, a significant proportion of subscriptions are going to foreign publishers.

Heavy discounting persists in most but not all markets

This year we have looked at the price being paid for main news subscriptions in around 20 countries and compared this with the price that the main publications are charging for news. The results show that in the US and UK a large number of people are paying a very small amount (often just a few pounds or dollars), with many likely to be on low-price trials, as we found in last year’s qualitative research. 10  In the next chart we find that well over half of those in the US who are paying for digital news report paying less than the median cost of a main subscription ($16), often much less. By contrast, in Norway, we see a different pattern with fewer people paying a very small amount and a larger number grouped around the median price, which in any case is much higher than in the US (the equivalent of $25).

The reasons for these differences become clearer when we compare the proportion that are paying the full sticker price for each brand . This allows us to estimate the proportion of subscribers in each country that are paying full price and the proportion that may be on a trial or other special deal. Using this methodology, we find significant differences between countries, with more than three-quarters (78%) in Poland paying less than full price, four in ten (46%) in the United States, but fewer in Norway (38%), Denmark (25%), and France (21%). It is not only the case that more people pay for digital news in the Nordic countries. It is also the case that fewer of them are paying a heavily discounted rate, and in Norway the median price is much higher than in other rich countries such as France, the UK, and the US.

We also asked those not currently paying, what might be a fair price, if anything? Across markets just 2% of non-payers say they would pay the equivalent of an average full price subscription, with 55% saying they wouldn’t be prepared to pay anything. That last number is a bit lower in Norway (45%) but considerably higher in the UK (69%) and Germany (68%). In a few markets in the Global South, such as Brazil, we do find more willingness to pay something, but it rarely amounts to more than the equivalent of a few US dollars.

Not every publisher can expect to make reader revenue work, in large part because much of the public basically does not believe news is worth paying for, and continues to have access to plenty of free options from both commercial, non-profit, and in some countries, public service providers. But for others, building digital subscriptions based on distinctive content is the main hope for a sustainable future. Discounting is an important part of persuading new customers to sample the product but publishers will hope that over time, once the habit is created, they can increase prices. It is likely to be a long and difficult road with few winners and many casualties along the way.

Trust levels stable – have we reached the bottom?

There is little evidence that upcoming elections or the increased prevalence of generative AI has so far had any material impact on trust in the news. Across markets, around four in ten (40%) say they trust most news most of the time, the same score as last year. Finland remains the country with the highest levels of trust (69%), Greece and Hungary (23%) have the lowest levels. Morocco, which was included in the survey for the first time, has a relatively low trust rating (31%), compared with countries elsewhere in Africa, a reflection perhaps of the fact that media control is largely in the hands of political and business elites.

Low trust scores in some other countries such as the US (32%), Argentina (30%), and France (31%) can be partly linked to high levels of polarisation and divisive debates over politics and culture.

As always, it is important to underline that our data are based on people’s perceptions of how trustworthy the media, or individual news brands, are. These scores are aggregates of subjective opinions, not an objective measure of underlying trustworthiness, and as our previous work has shown, any year-on-year changes are often at least as much about political and social factors as narrowly about the news itself. 11

This year, we have also been exploring the key factors driving trust or lack of trust in the news media. We find that high standards, a transparent approach, lack of bias, and fairness in terms of media representation are the four primary factors that influence trust. The top responses are strongly linked and are consistent across countries, ages, and political viewpoints. An overly negative or critical approach, which is much discussed by politicians when critiquing the media, is seen as the least important reason in our list, suggesting that audiences still expect journalists to ask the difficult questions.

These results may give a clear steer to media companies on how to build greater trust. Most of the public want news to be accurate, fair, avoid sensationalism, be open about any agendas and biases including lack of diversity, own up to mistakes – and not pull punches when investigating the rich and powerful. People do not necessarily agree on what this looks like in practice, or which individual brands deliver on it. But what they hope news will offer is remarkably similar across many different groups.

Audience interest in transparency and openness seems to chime with some of the ideas behind recent industry initiatives, such as the Trust Project, a non-profit initiative that encourages publishers to reveal more of their workings using so-called ‘trust indicators’, the Journalism Trust Initiative orchestrated by Reporters without Borders, and others. Some large news organisations, such as the BBC, have gone further, creating units or sub-brands that answer audience questions or aim to explain how the news is checked. BBC Verify, launched in May 2023 aims to show and share work behind the scenes to check and verify information, especially images and video content in an era where misinformation has been growing. ‘People want to know not just what we know (and don't know), but how we know it,’ says BBC News CEO Deborah Turness. Leaving aside the risk that journalists and members of the public often mean different things when talking about transparency, with the former focusing on reporting practices, the latter often on their suspicion that ulterior commercial and/or political motives are at play, our data suggest that these initiatives may not work for all audiences. Transparency is considered most important amongst those who already trust the news (84%), but much less for those are generally distrustful (68%) where there is a risk that it hardens the position of those already suspicious of a brand, if they feel that verification will not be equally applied to both sides of an argument. 12 Those that are less interested in the news are also less likely to feel that being transparent about how the news is made is important.

Attention loss, news avoidance, and news fatigue

For several years we have pointed to a number of measures that suggest growing ambivalence about the news, despite – or perhaps because of – the uncertain and chaotic times in which we live. Interest in news continues to fall in some markets, but has stabilised or increased in others, especially those like Argentina and the United States that are going through, or have recently held, elections.

The long-term trend, however, is down in every country apart from Finland, with high interest halving in some countries over the last decade (UK 70% in 2015; 38% in 2024). Women and young people make up a significant proportion of that decline.

While news interest may have stabilised a bit this year, the proportion that say they selectively avoid the news (sometimes or often) is up by 3pp this year to 39% – a full 10pp higher than it was in 2017. Notable country-based rises this year include Ireland (+10pp), Spain (+8pp), Italy (+7pp), Germany (+5pp), Finland (+5pp), the United States (+5pp), and Denmark (+4pp). The underlying reasons for this have not changed. Selective news avoiders say the news media are often repetitive and boring. Some tell us that the negative nature of the news itself makes them feel anxious and powerless.

Selected news avoidance at highest levels recorded All markets

But it is not just that the news can be depressing, it is also relentless. Across markets, the same proportion, around four in ten (39%) say they feel ‘worn out’ by the amount of news these days, up from 28% in 2019, frequently mentioning the way that coverage of wars, disasters, and politics was squeezing out other things. The increase has been greater in Spain (+18), Denmark (+16pp), Brazil (+16pp), Germany (+15pp), South Africa (+12pp), France (+9pp), and the United Kingdom (+8pp), but a little less in the United States (+3pp) where news fatigue was a bigger factor five years ago. There are no significant differences by age or education, though women (43%) are much more likely to complain about news overload than men (34%).

Since we started tracking these issues, usage of smartphones has increased, as has the number of notifications sent from apps of all kinds, perhaps contributing to the sense that the news has become hard to escape. Platforms that require volume of content to feed their algorithms are potentially another factor driving these increases. It was notable that in our industry survey, at the start of 2024, most publishers said they were planning to produce more videos, more podcasts, and more newsletters this year. 13

User needs and information gaps

Industry leaders recognise the twin challenges of news fatigue and news avoidance, especially around long-running stories such as the wars in Ukraine and Gaza. At the same time, disillusion with politics in general may be contributing to declining interest, especially with younger news consumers, as previous reports have shown. Editors are looking for new ways to cover these important stories, by making the news more accessible and engaging – as well as broadening the news agenda but without ‘dumbing down’.

One way in which publishers have been trying to square this circle has been through a ‘user needs’ model, where stories that update people about the latest news are supplemented by commissioning more that educate, inspire, provide perspective, connect, or entertain.

Originally based on audience research at the BBC, the model has been implemented by a number of news organisations around the world. In our survey this year, we asked about eight different needs included in User Needs 2.0, which are nested in four basic needs of knowledge, understanding, feeling, and doing. 14  Our findings show that the three most important user needs globally are staying up to date (‘update me’), learning more (‘educate me’), and gaining varied perspectives (‘give me perspective’). This is pretty consistent across different demographic groups, although the young are a bit more interested in stories that inspire, connect, and entertain when compared with older groups. In the United States, for example, over half (52%) of under 35s think having stories that make them feel better about the world is very or extremely important, compared with around four in ten (43%) of over 35s.

We also asked about how good the media were perceived to be at satisfying each user need. By combining these data with the data on importance, we can create what we call a User Needs Priority Index. This is a form of gap analysis, whereby we take the percentage point gap between the proportion that think a particular need is important and the proportion that think the news media do a good job of providing it and multiply this by the overall importance (as a decimal) to identify the most important gaps. Audiences say, for example, that updating is the most important need, but also think that the media do a good job in this area already. By contrast, there is a much bigger gap in providing different perspectives (e.g. more context, wider set of views) and also around news that ‘makes me feel better about the world’ (offers more hope and optimism).

News organisations may draw different conclusions from these data, depending on their own mission and target audience, but taken as a whole, it is clear news consumers would prefer to dial down the constant updating of news, while dialling up context and wider perspectives that help people better understand the world around them. Most people don’t want the news to be made more entertaining, but they do want more stories that provide more personal utility, help them connect with others, and give people a sense of hope.

Agenda and topic gaps

Adopting a user needs model is one way to address some of the issues that lie behind selective news avoidance and low engagement, but a topic-based lens may also be useful. When looking at levels of interest in different subject areas by age, we find commonalities but also some stark differences. For all age groups, local and international news are considered the most important topics, but there is less consensus around political news. This doesn’t feature in the top five for under-35s but it is a very different story for over-45s where politics remains firmly in the top three. Younger groups are more interested in the environment and climate change, as well as other subjects such as wellness, which are less of a priority for older groups.

If anything, we find even bigger gaps around gender, with men more interested in politics and sport; women more interested in health/wellness and the environment. Much of this is not new but a reminder that older, male-dominated newsrooms may not always be instinctively in tune with the needs of those who don’t look or think like them.

Beyond interest, we also asked respondents to what extent, if at all, they felt their information needs are being met around each of these topics. Across countries we find that most people feel their needs around sport and politics (and often celebrity news) are well served, while there are substantial gaps in some other areas such education, environment, mental health, and social justice.

Local news is a mixed bag. In some countries, including the United States, more than two-thirds (68%) feel that most or all of their needs are being met, despite the loss of many local newspaper titles and journalist jobs over the past decade. Our data suggest that in most countries much of the public does not share the view that there is a crisis of local news – or at least that much of the information they value is being provided by other community actors accessed via search engines or social media.

But in a few countries, notably the UK and Australia, only a little over half say their needs are being met, suggesting that in these countries at least, local news needs are being significantly underserved. These are also countries where local publishers have taken a disproportionate share of job cuts. In countries such as Portugal, Bulgaria, and Japan a higher proportion of unmet needs are largely down to lower interest in local news overall, leaving aside the important role that local news can play in supporting democracy.

Overall, we find clear differences in terms of subject preferences by age and gender which help explain why some groups are engaging less with the news or avoiding it altogether. There is no one-size-fits-all answer to these issues but improving coverage of subjects with higher interest that are currently underserved would be a good starting point.

New formats and the role of audio

Publishers are also exploring different formats as a way of addressing the engagement challenge, especially those that are less immediately reliant on platform algorithms, such as podcasts.

In the last few years, leading publishers such as the New York Times and Schibsted have joined public broadcasters in trying to build their own platforms for distribution to compete with giants like Spotify, using exclusive content or windowing strategies to drive direct traffic. Legacy print publishers have been ramping up their podcast production, finding the combination of text and audio a good fit for specialist journalistic beats, and relatively low cost compared with video. In countries such as the United Kingdom, a strong independent sector is emerging with a range of new launches for politics and economic shows this year, as well as US spin-offs for popular daily podcasts such as the News Agents. Many of the most popular podcasts are now filmed and distributed via video platforms such as YouTube, further blurring the lines between podcasts and video. Across 20 countries where we have been measuring podcast consumption since 2018, just over a third (35%) have accessed one or more podcasts in the last month, but only just over one in ten (13%) regularly use a news one. The share of podcast listening for news shows has remained roughly the same as it was seven years ago.

Podcasts continue to attract younger, richer, and better educated audiences, with news and politics shows heavily skewed towards men, partly due to the dominance of male hosts, as we reported last year. Many markets have become saturated with content, making it hard for new shows to be discovered and also for existing shows to grow audiences.

Conclusions

Our report this year sees news publishers caught in the midst of another set of far-reaching technological and behavioural changes, adding to the pressures on sustainable journalism. But it’s not just news media. The giants of the tech world such as Meta and Google are themselves facing disruption from rivals like Microsoft as well as more agile AI-driven challengers and are looking to maintain their position. In the process, they are changing the way their products work at some pace, with knock-on impacts for an increasingly delicate news ecosystem.

Some kind of platform reset is underway with more emphasis on keeping traffic within their environments and with greater focus on formats proven to drive engagement, such as video. Many newer platforms with younger user bases are far less centred on text and links than incumbent platforms, with content shaped by a multitude of (sometimes hugely popular) creators rather than by established publishers. In some cases, news is being excluded or downgraded because technology companies think it causes more trouble than it is worth. Traffic from social media and search is likely to become more unpredictable over time, but getting off the algorithmic treadmill won’t be easy.

While some media companies continue to perform well in this challenging environment, many others are struggling to convince people that their news is worth paying attention to, let alone paying for. Interest in the news has been falling, the proportion avoiding it has increased, trust remains low, and many consumers are feeling increasingly overwhelmed and confused by the amount of news. Artificial intelligence may make this situation worse, by creating a flood of low-quality content and synthetic media of dubious provenance.

But these shifts also offer a measure of hope that some publishers can establish a stronger position. If news brands are able to show that their journalism is built on accuracy, fairness, and transparency – and that humans remain in control – audiences are more likely to respond positively. Re-engaging audiences will also require publishers to rethink some of the ways that journalism has been practised in the past; to find ways to be more accessible without dumbing down; to report the world as it is whilst also giving hope; to give people different perspectives without turning it into an argument. In a world of superabundant content, success is also likely to be rooted in standing out from the crowd, to be a destination for something that the algorithm and the AI can’t provide while remaining discoverable via many different platforms. Do all that and there is at least a possibility that more people, including some younger ones, will increasingly value and trust news brands once again.

1   https://www.theguardian.com/technology/2024/mar/26/instagram-meta-political-content-opt-in-rules-threads

2   https://reutersinstitute.politics.ox.ac.uk/journalism-media-and-technology-trends-and-predictions-2024

3   While not necessarily a reliable indicator of underlying trustworthiness, such reliance on ‘realism heuristics’ also helps shape often high trust in television news versus other sources.

4   https://www.newsguardtech.com/misinformation-monitor/september-2022/

5   https://www.theguardian.com/media/2024/mar/26/tech-firms-poised-to-mass-hire-factcheckers-before-eu-elections

6   https://www.semafor.com/article/04/19/2024/tiktok-fight-in-kenya

7   https://wan-ifra.org/2023/11/ai-and-robot-writer-klara-key-todumonts-kolner-stadt-anzeiger-mediens-tech-future-as-it-switches-off-its-presses/

8   https://www.d-id.com/resources/case-study/radioformula/

9   https://www.nature.com/articles/s41599-023-02282-w

10   https://reutersinstitute.politics.ox.ac.uk/paying-news-price-conscious-consumers-look-value-amid-cost-living-crisis

11   https://reutersinstitute.politics.ox.ac.uk/trust-news-project

12   https://europeanconservative.com/articles/commentary/whos-verifying-bbc-verify/

13   https://reutersinstitute.politics.ox.ac.uk/journalism-media-and-technology-trends-and-predictions-2024

14   https://smartocto.com/research/userneeds/

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• Perspectives on trust in news
• The use of AI in journalism
• Audiences and user needs
• How much people pay for news
• The rise of news influencers
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• Methodology