qualitative research abstract sample

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GUIDANCE ON SUBMISSION OF QUALITATIVE RESEARCH ABSTRACTS

General guidance

Authors should refer to the general information and guidelines contained in the Society’s “Guidance for Submission of Abstracts”. The general guidance therein applies to qualitative research abstracts. This includes the maximum permitted limit of 250 words, and the instruction that abstracts should be structured. In keeping with all submissions to the Society, subsequent presentation must reflect and elaborate on the abstract. Research studies or findings not referred to in the abstract should not be presented.

This document contains specific guidance on the content of qualitative research abstracts.

How guidance on content is to be applied by authors and Council.

Council recognises that the nature of qualitative research makes its comprehensive communication within short abstracts a challenge.  Therefore, whilst the key areas to be included within abstracts are set out below, it is recognised that emphasis on each area will vary in different cases, and that not every listed sub-area will be covered.  Certain elements are likely to receive greater attention at the time of presentation than within the abstract.  In particular, presentation of the paper should include sufficient empirical data to allow judgement of the conclusions drawn.

Content of abstracts

• Research question/objective and design: clear statement of the research question/objective and its relevance. Methodological or theoretical perspectives should be clearly outlined.
• Population and sampling: who the subjects were and what sampling strategies were used .
• Methods of data collection: clear exposition of data collection: access, selection, method of collection, type of data, relationship of researcher to subjects/setting (what data were collected, from where/whom, by whom)
• Quality of data and analysis: strategies to enhance quality of data analysis e.g. triangulation, respondent validation; and to enhance validity e.g. attention to negative cases, consideration of alternative explanations, team analysis, peer review panels
• Application of critical thinking to analysis: attention to the influence of the researcher on data collected and on analysis. Critical approach to the status of data collected
• Theoretical and empirical context: evidence that design and analysis take into account and add to previous knowledge
• Conclusions: justified in relation to data collected, sufficient original data presented to substantiate interpretations, reasoned consideration of transferability  to groups/settings beyond those studied

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Home » Research Paper Abstract – Writing Guide and Examples

Research Paper Abstract – Writing Guide and Examples

Table of Contents

Research Paper Abstract

Research Paper Abstract is a brief summary of a research pape r that describes the study’s purpose, methods, findings, and conclusions . It is often the first section of the paper that readers encounter, and its purpose is to provide a concise and accurate overview of the paper’s content. The typical length of an abstract is usually around 150-250 words, and it should be written in a concise and clear manner.

Research Paper Abstract Structure

The structure of a research paper abstract usually includes the following elements:

• Background or Introduction: Briefly describe the problem or research question that the study addresses.
• Methods : Explain the methodology used to conduct the study, including the participants, materials, and procedures.
• Results : Summarize the main findings of the study, including statistical analyses and key outcomes.
• Conclusions : Discuss the implications of the study’s findings and their significance for the field, as well as any limitations or future directions for research.
• Keywords : List a few keywords that describe the main topics or themes of the research.

How to Write Research Paper Abstract

Here are the steps to follow when writing a research paper abstract:

• Start by reading your paper: Before you write an abstract, you should have a complete understanding of your paper. Read through the paper carefully, making sure you understand the purpose, methods, results, and conclusions.
• Identify the key components : Identify the key components of your paper, such as the research question, methods used, results obtained, and conclusion reached.
• Write a draft: Write a draft of your abstract, using concise and clear language. Make sure to include all the important information, but keep it short and to the point. A good rule of thumb is to keep your abstract between 150-250 words.
• Use clear and concise language : Use clear and concise language to explain the purpose of your study, the methods used, the results obtained, and the conclusions drawn.
• Emphasize your findings: Emphasize your findings in the abstract, highlighting the key results and the significance of your study.
• Revise and edit: Once you have a draft, revise and edit it to ensure that it is clear, concise, and free from errors.
• Check the formatting: Finally, check the formatting of your abstract to make sure it meets the requirements of the journal or conference where you plan to submit it.

Research Paper Abstract Examples

Research Paper Abstract Examples could be following:

Title : “The Effectiveness of Cognitive-Behavioral Therapy for Treating Anxiety Disorders: A Meta-Analysis”

Abstract : This meta-analysis examines the effectiveness of cognitive-behavioral therapy (CBT) in treating anxiety disorders. Through the analysis of 20 randomized controlled trials, we found that CBT is a highly effective treatment for anxiety disorders, with large effect sizes across a range of anxiety disorders, including generalized anxiety disorder, panic disorder, and social anxiety disorder. Our findings support the use of CBT as a first-line treatment for anxiety disorders and highlight the importance of further research to identify the mechanisms underlying its effectiveness.

Title : “Exploring the Role of Parental Involvement in Children’s Education: A Qualitative Study”

Abstract : This qualitative study explores the role of parental involvement in children’s education. Through in-depth interviews with 20 parents of children in elementary school, we found that parental involvement takes many forms, including volunteering in the classroom, helping with homework, and communicating with teachers. We also found that parental involvement is influenced by a range of factors, including parent and child characteristics, school culture, and socio-economic status. Our findings suggest that schools and educators should prioritize building strong partnerships with parents to support children’s academic success.

Title : “The Impact of Exercise on Cognitive Function in Older Adults: A Systematic Review and Meta-Analysis”

Abstract : This paper presents a systematic review and meta-analysis of the existing literature on the impact of exercise on cognitive function in older adults. Through the analysis of 25 randomized controlled trials, we found that exercise is associated with significant improvements in cognitive function, particularly in the domains of executive function and attention. Our findings highlight the potential of exercise as a non-pharmacological intervention to support cognitive health in older adults.

When to Write Research Paper Abstract

The abstract of a research paper should typically be written after you have completed the main body of the paper. This is because the abstract is intended to provide a brief summary of the key points and findings of the research, and you can’t do that until you have completed the research and written about it in detail.

Once you have completed your research paper, you can begin writing your abstract. It is important to remember that the abstract should be a concise summary of your research paper, and should be written in a way that is easy to understand for readers who may not have expertise in your specific area of research.

Purpose of Research Paper Abstract

The purpose of a research paper abstract is to provide a concise summary of the key points and findings of a research paper. It is typically a brief paragraph or two that appears at the beginning of the paper, before the introduction, and is intended to give readers a quick overview of the paper’s content.

The abstract should include a brief statement of the research problem, the methods used to investigate the problem, the key results and findings, and the main conclusions and implications of the research. It should be written in a clear and concise manner, avoiding jargon and technical language, and should be understandable to a broad audience.

The abstract serves as a way to quickly and easily communicate the main points of a research paper to potential readers, such as academics, researchers, and students, who may be looking for information on a particular topic. It can also help researchers determine whether a paper is relevant to their own research interests and whether they should read the full paper.

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Guide to Qualitative Research Proposal Abstract

Rachel r.n..

• July 20, 2024
• How to Guides

When you’re diving into the world of qualitative research, one of the first hurdles you’ll face is writing a research proposal abstract. This short but crucial piece of writing can make or break your chances of getting your research project approved. But don’t worry – we’re here to break it down for you in simple terms.

An abstract is like a movie trailer for your research proposal. It gives readers a quick peek at what your study is all about, why it matters, and how you plan to do it. In this guide, we’ll walk you through everything you need to know about crafting a top-notch qualitative research proposal abstract.

What You'll Learn

What is a Qualitative Research Proposal Abstract?

A qualitative research proposal abstract is a brief summary of your planned research project. It’s usually around 150-300 words long (though this can vary depending on requirements) and gives readers a clear idea of what your research is about without them having to read the entire proposal.

Think of it as an elevator pitch for your research. If you had just 30 seconds to explain your project to someone, what would you say? That’s essentially what your abstract should cover.

Why is the Abstract Important?

You might be wondering, “Why should I spend so much time on such a short piece of writing?” Well, there are several reasons:

• First Impressions: Your abstract is often the first (and sometimes only) thing people read about your research. It’s your chance to grab their attention and make them want to know more.
• Time-Saver: Many people, especially busy academics or research committee members, use abstracts to quickly decide if they want to read the full proposal.
• Searchability: Abstracts are often used in databases , making it easier for other researchers to find your work.
• Clarity Check: Writing an abstract forces you to boil down your research to its essence, which can help you clarify your own thoughts about the project.

Key Components of a Qualitative Research Proposal Abstract

Now that we understand why abstracts are important, let’s break down what should go into one. A good qualitative research proposal abstract typically includes the following elements:

1. Research Problem or Question

This is where you state what you’re investigating. What’s the issue or question that your research aims to address? For example:

“This study explores how first-generation college students navigate the challenges of higher education.”

2. Purpose of the Study

Here, you explain why you’re doing this research. What do you hope to achieve? For instance:

“The purpose of this research is to gain a deeper understanding of the unique experiences and needs of first-generation college students to inform more effective support strategies.”

3. Research Design and Methods

Briefly describe how you plan to conduct your research. What approach are you using? How will you collect data? For example:

“Using a phenomenological approach, this study will conduct in-depth interviews with 20 first-generation college students from diverse backgrounds.”

4. Potential Significance

Explain why your research matters. How might it contribute to your field or benefit society? For instance:

“This research could provide valuable insights for universities to develop more targeted support programs, potentially improving retention rates and academic success among first-generation students.”

5. Keywords (Optional)

Some abstracts include a list of keywords at the end. These are key terms related to your research that can help others find your work in databases. For example:

“Keywords: first-generation students, higher education, student support, qualitative research”

Steps to Write an Effective Qualitative Research Proposal Abstract

Now that we know what goes into an abstract, let’s walk through the process of writing one:

Step 1: Write Your Full Proposal First

It might seem counterintuitive, but it’s often easier to write your abstract after you’ve completed your full research proposal. This way, you have a clear understanding of all aspects of your project.

Step 2: Identify the Key Points

Go through your proposal and highlight the most important points in each section. What’s the core of your research problem? What are the main aspects of your methodology? What are the potential impacts of your study?

Step 3: Draft Your Abstract

Using the key points you’ve identified, start writing your abstract. Remember to include all the key components we discussed earlier.

Step 4: Revise and Refine

Once you have a draft, read it over carefully. Is it clear and concise? Does it accurately represent your research? Make any necessary revisions.

Step 5: Check the Word Count

Make sure your abstract fits within the required word limit. If it’s too long, look for places where you can be more concise without losing important information.

Step 6: Proofread

Finally, carefully proofread your abstract. Check for any grammar or spelling errors, and make sure every word counts.

Example of a Qualitative Research Proposal Abstract

Let’s look at a full example of a qualitative research proposal abstract:

“This study explores the experiences of LGBTQ+ youth in rural high schools, focusing on their perceptions of school climate and support systems. Despite increasing acceptance of LGBTQ+ individuals in many areas, rural LGBTQ+ youth often face unique challenges that are understudied. Using a grounded theory approach, this research will conduct semi-structured interviews with 15-20 LGBTQ+ high school students from rural areas in the Midwest. The study aims to identify common themes in their experiences, challenges they face, and strategies they use to navigate their school environments. Findings from this research could inform the development of more effective support programs for LGBTQ+ youth in rural schools and contribute to broader discussions about inclusivity in education. By giving voice to this often-overlooked population, this study has the potential to impact educational policies and practices, ultimately working towards creating more supportive school environments for all students.

Keywords: LGBTQ+ youth, rural education, school climate, qualitative research”

Common Mistakes to Avoid in Qualitative Research Proposal Abstracts

Even experienced researchers can sometimes stumble when writing abstracts. Here are some common pitfalls to watch out for:

1. Being Too Vague

Your abstract should be specific about your research. Avoid general statements that could apply to any study in your field.

Bad example: “This study looks at education issues.” Better example: “This study examines the impact of project-based learning on student engagement in middle school science classes.”

2. Including Too Much Detail

While you want to be specific, remember that an abstract is a summary. You don’t need to explain every aspect of your methodology or list all your expected outcomes.

Bad example: “We will conduct interviews on Mondays and Wednesdays from 3-5pm in the school library, asking participants 27 questions about their experiences…” Better example: “Data will be collected through semi-structured interviews with participants in a school setting.”

3. Using Jargon or Technical Language

Remember, your abstract might be read by people outside your specific field. Use clear, straightforward language that a general academic audience can understand.

Bad example: “This study utilizes a hermeneutic phenomenological approach to elucidate the lived experiences of participants.” Better example: “This study uses in-depth interviews to understand participants’ personal experiences and perspectives.”

4. Forgetting to Mention the Significance

Always include why your research matters. What gap in knowledge are you filling? How might your findings be used?

Bad example: “This study looks at teaching methods in elementary schools.” Better example: “This study examines innovative teaching methods in elementary schools, aiming to identify strategies that could improve student learning outcomes and inform teacher training programs.”

5. Not Following Guidelines

Different institutions or publications may have specific requirements for abstracts. Always check and follow the guidelines provided.

6. Failing to Proofread

Typos or grammatical errors in your abstract can make a bad first impression. Always proofread carefully, and consider having someone else review it too.

Tips for Writing a Standout Qualitative Research Proposal Abstract

Now that we’ve covered the basics and common mistakes, here are some tips to take your abstract from good to great:

1. Start Strong

Your first sentence should grab the reader’s attention and clearly state what your research is about. For example:

“In an era of increasing digital connectivity, this study explores how elderly individuals in rural communities experience and adapt to technological changes in healthcare delivery.”

2. Use Active Voice

Active voice makes your writing more direct and engaging. Instead of “The experiences of participants will be examined,” try “We will examine participants’ experiences.”

3. Be Concise

Every word in your abstract should earn its place. Look for places where you can say the same thing in fewer words.

4. Highlight What’s Unique

What makes your research stand out? Is it a new approach to an old problem? A focus on an understudied population? Make sure this comes across in your abstract.

5. End with Impact

Your last sentence should leave a lasting impression. Emphasize the potential significance or applications of your research.

6. Use Keywords Strategically

If you’re including keywords, choose terms that researchers in your field might use when searching for studies like yours.

7. Write for Your Audience

Consider who will be reading your abstract. What information is most important to them? What might pique their interest?

8. Revise, Revise, Revise

Don’t expect to nail it on the first try. Write a draft, step away from it, then come back with fresh eyes to revise.

The Role of Abstracts in Different Contexts

It’s worth noting that the role and format of abstracts can vary depending on the context. Let’s explore a few different scenarios:

Conference Proposals

When submitting a proposal to present at a conference, your abstract might be all the selection committee has to judge your work. In this case, you’ll want to:

• Clearly state the relevance of your research to the conference theme
• Highlight the innovative aspects of your work
• Give a clear indication of what attendees will learn from your presentation

Thesis or Dissertation Proposals

For a thesis or dissertation proposal, your abstract might need to be more comprehensive. You might need to include:

• A brief background on the existing literature
• More detail on your theoretical framework
• An indication of the expected timeline for your research

Grant Applications

When applying for research grants, your abstract needs to convince the funding body that your research is worth investing in. Consider:

• Emphasizing the potential impact of your research
• Clearly stating how the grant money will be used
• Highlighting any innovative methods or approaches you’ll be using

Journal Article Submissions

For journal articles, the abstract often determines whether a reader will choose to read the full article. In this case:

• Ensure your abstract accurately represents the content of your article
• Include key findings or conclusions (which you wouldn’t do in a proposal abstract)
• Follow the specific guidelines provided by the journal

Adapting Your Abstract for Different Audiences

Remember that your abstract might be read by people with varying levels of expertise in your field. Consider creating different versions of your abstract for different audiences:

For Experts in Your Field

• You can use more technical language
• Focus on how your research builds on or challenges existing work in the field
• Emphasize the theoretical or methodological contributions of your study

For a General Academic Audience

• Use more accessible language
• Provide more context for why your research question is important
• Emphasize the broader implications or applications of your work

For Non-Academic Audiences

• Avoid jargon entirely
• Focus on the real-world relevance of your research
• Emphasize potential practical applications or policy implications

The Abstract Writing Process: A Personal Approach

Writing an abstract can be a challenging but rewarding process. Here’s a personal approach you might find helpful:

• Brain Dump: Start by writing down everything you think should go in the abstract, without worrying about word count or organization.
• Organize: Group similar ideas together and start to create a logical flow.
• Prioritize: Identify the most crucial elements that must be included.
• Draft: Write a full draft, aiming to include all the key components we’ve discussed.
• Step Away: Take a break – even a day or two if possible.
• Revise with Fresh Eyes: Come back and read your draft with a critical eye. What’s unclear? What’s unnecessary?
• Get Feedback: Ask a colleague or mentor to read your abstract and provide feedback.
• Final Polish: Make final revisions based on feedback and give it one last proofread.

Remember, writing is a process. Your first draft doesn’t have to be perfect – the important thing is to get your ideas down on paper and then refine them.

Related Articles

How to Critically Appraise a Research Article

How to Write a Comprehensive PhD Research Proposal in Sociology

The qualitative research proposal

Components of a Research Proposal

Frequently Asked Questions (FAQs)

To wrap up our comprehensive guide, let’s address some common questions about qualitative research proposal abstracts:

1. How long should my abstract be?

The length of your abstract can vary depending on the requirements of your institution or the publication you’re submitting to. Typically, abstracts range from 150 to 300 words. Always check the specific guidelines provided.

2. Should I include citations in my abstract?

Generally, abstracts do not include citations. The abstract should focus on your original work. If you must reference a particular study, try to do so without a formal citation.

3. Can I use the first person in my abstract?

This can depend on the norms in your field and the guidelines you’re following. In many cases, it’s acceptable to use first person in qualitative research abstracts. If in doubt, check with your advisor or the submission guidelines.

4. How is a qualitative research abstract different from a quantitative one?

Qualitative research abstracts typically focus more on describing the research problem, methodology, and potential significance, rather than on specific numerical results. They often use words like “explore,” “understand,” or “describe” to indicate the nature of the research.

5. Should I include my research questions in the abstract?

If you have space, including your main research question can be helpful. However, if you’re tight on word count, you can often convey the essence of your research question through your problem statement and purpose.

6. How do I know if my abstract is good enough?

A good abstract clearly conveys the what, why, and how of your research in a concise manner. If someone can understand the essence of your study after reading your abstract, you’re on the right track. Getting feedback from others can also help you assess and improve your abstract.

7. Can I use the same abstract for different purposes (e.g., conference and grant application)?

While the core content might be similar, it’s usually best to tailor your abstract for each specific purpose. A conference abstract might focus more on what attendees will learn, while a grant application abstract might emphasize the potential impact of the research.

8. How much detail should I include about my methodology?

You should include enough information about your methodology for readers to understand your general approach, but not so much that it dominates the abstract. Usually, a sentence or two about your method is sufficient.

9. Is it okay to use acronyms in my abstract?

It’s generally best to avoid acronyms in abstracts unless they are very widely known in your field. If you must use an acronym, spell it out the first time you use it.

10. How different should my abstract be from my introduction?

While your abstract and introduction may cover similar ground, your abstract should be a stand-alone summary of your entire proposal. Your introduction, on the other hand, provides more context and leads into the detailed proposal.

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• Recommendations for Designing and Reviewing Qualitative Research in Psychology: Promoting Methodological Integrity (PDF, 166KB) February 2017 by Heidi M. Levitt, Sue L. Motulsky, Fredrick J. Wertz, Susan L. Morrow, and Joseph G. Ponterotto
• Racial Microaggression Experiences and Coping Strategies of Black Women in Corporate Leadership (PDF, 132KB) August 2015 by Aisha M. B. Holder, Margo A. Jackson, and Joseph G. Ponterotto
• The Lived Experience of Homeless Youth: A Narrative Approach (PDF, 109KB) February 2015 by Erin E. Toolis and Phillip L. Hammack
• Lifetime Activism, Marginality, and Psychology: Narratives of Lifelong Feminist Activists Committed to Social Change (PDF, 93KB) August 2014 by Anjali Dutt and Shelly Grabe
• Qualitative Inquiry in the History of Psychology (PDF, 82KB) February 2014 by Frederick J. Wertz

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Methodology

• 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.

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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The Dissertation Abstract: 101

How to write a clear & concise abstract (with examples).

By:   Madeline Fink (MSc) Reviewed By: Derek Jansen (MBA)   | June 2020

So, you’ve (finally) finished your thesis or dissertation or thesis. Now it’s time to write up your abstract (sometimes also called the executive summary). If you’re here, chances are you’re not quite sure what you need to cover in this section, or how to go about writing it. Fear not – we’ll explain it all in plain language , step by step , with clear examples .

Overview: The Dissertation/Thesis Abstract

• What exactly is a dissertation (or thesis) abstract
• What’s the purpose and function of the abstract
• Why is the abstract so important
• How to write a high-quality dissertation abstract
• Example/sample of a quality abstract
• Quick tips to write a high-quality dissertation abstract

What is an abstract?

Simply put, the abstract in a dissertation or thesis is a short (but well structured) summary that outlines the most important points of your research (i.e. the key takeaways). The abstract is usually 1 paragraph or about 300-500 words long (about one page), but but this can vary between universities.

A quick note regarding terminology – strictly speaking, an abstract and an executive summary are two different things when it comes to academic publications. Typically, an abstract only states what the research will be about, but doesn’t explore the findings – whereas an executive summary covers both . However, in the context of a dissertation or thesis, the abstract usually covers both, providing a summary of the full project.

In terms of content, a good dissertation abstract usually covers the following points:

• The purpose of the research (what’s it about and why’s that important)
• The methodology (how you carried out the research)
• The key research findings (what answers you found)
• The implications of these findings (what these answers mean)

We’ll explain each of these in more detail a little later in this post. Buckle up.

What’s the purpose of the abstract?

A dissertation abstract has two main functions:

The first purpose is to  inform potential readers  of the main idea of your research without them having to read your entire piece of work. Specifically, it needs to communicate what your research is about (what were you trying to find out) and what your findings were . When readers are deciding whether to read your dissertation or thesis, the abstract is the first part they’ll consider. 

The second purpose of the abstract is to  inform search engines and dissertation databases  as they index your dissertation or thesis. The keywords and phrases in your abstract (as well as your keyword list) will often be used by these search engines to categorize your work and make it accessible to users. 

Simply put, your abstract is your shopfront display window – it’s what passers-by (both human and digital) will look at before deciding to step inside. 

Why’s it so important?

The short answer – because most people don’t have time to read your full dissertation or thesis! Time is money, after all…

If you think back to when you undertook your literature review , you’ll quickly realise just how important abstracts are! Researchers reviewing the literature on any given topic face a mountain of reading, so they need to optimise their approach. A good dissertation abstract gives the reader a “TLDR” version of your work – it helps them decide whether to continue to read it in its entirety. So, your abstract, as your shopfront display window, needs to “sell” your research to time-poor readers.

You might be thinking, “but I don’t plan to publish my dissertation”. Even so, you still need to provide an impactful abstract for your markers. Your ability to concisely summarise your work is one of the things they’re assessing, so it’s vital to invest time and effort into crafting an enticing shop window.  

A good abstract also has an added purpose for grad students . As a freshly minted graduate, your dissertation or thesis is often your most significant professional accomplishment and highlights where your unique expertise lies. Potential employers who want to know about this expertise are likely to only read the abstract (as opposed to reading your entire document) – so it needs to be good!

Think about it this way – if your thesis or dissertation were a book, then the abstract would be the blurb on the back cover. For better or worse, readers will absolutely judge your book by its cover .

How to write your abstract

As we touched on earlier, your abstract should cover four important aspects of your research: the purpose , methodology , findings , and implications . Therefore, the structure of your dissertation or thesis abstract needs to reflect these four essentials, in the same order.  Let’s take a closer look at each of them, step by step:

Step 1: Describe the purpose and value of your research

Here you need to concisely explain the purpose and value of your research. In other words, you need to explain what your research set out to discover and why that’s important. When stating the purpose of research, you need to clearly discuss the following:

• What were your research aims and research questions ?
• Why were these aims and questions important?

It’s essential to make this section extremely clear, concise and convincing . As the opening section, this is where you’ll “hook” your reader (marker) in and get them interested in your project. If you don’t put in the effort here, you’ll likely lose their interest.

Step 2: Briefly outline your study’s methodology

In this part of your abstract, you need to very briefly explain how you went about answering your research questions . In other words, what research design and methodology you adopted in your research. Some important questions to address here include:

• Did you take a qualitative or quantitative approach ?
• Who/what did your sample consist of?
• How did you collect your data?
• How did you analyse your data?

Simply put, this section needs to address the “ how ” of your research. It doesn’t need to be lengthy (this is just a summary, after all), but it should clearly address the four questions above.

Need a helping hand?

Step 3: Present your key findings

Next, you need to briefly highlight the key findings . Your research likely produced a wealth of data and findings, so there may be a temptation to ramble here. However, this section is just about the key findings – in other words, the answers to the original questions that you set out to address.

Again, brevity and clarity are important here. You need to concisely present the most important findings for your reader.

Step 4: Describe the implications of your research

Have you ever found yourself reading through a large report, struggling to figure out what all the findings mean in terms of the bigger picture? Well, that’s the purpose of the implications section – to highlight the “so what?” of your research. 

In this part of your abstract, you should address the following questions:

• What is the impact of your research findings on the industry /field investigated? In other words, what’s the impact on the “real world”. 
• What is the impact of your findings on the existing body of knowledge ? For example, do they support the existing research?
• What might your findings mean for future research conducted on your topic?

If you include these four essential ingredients in your dissertation abstract, you’ll be on headed in a good direction.

Example: Dissertation/thesis abstract

Here is an example of an abstract from a master’s thesis, with the purpose , methods , findings , and implications colour coded.

The U.S. citizenship application process is a legal and symbolic journey shaped by many cultural processes. This research project aims to bring to light the experiences of immigrants and citizenship applicants living in Dallas, Texas, to promote a better understanding of Dallas’ increasingly diverse population. Additionally, the purpose of this project is to provide insights to a specific client, the office of Dallas Welcoming Communities and Immigrant Affairs, about Dallas’ lawful permanent residents who are eligible for citizenship and their reasons for pursuing citizenship status . The data for this project was collected through observation at various citizenship workshops and community events, as well as through semi-structured interviews with 14 U.S. citizenship applicants . Reasons for applying for U.S. citizenship discussed in this project include a desire for membership in U.S. society, access to better educational and economic opportunities, improved ease of travel and the desire to vote. Barriers to the citizenship process discussed in this project include the amount of time one must dedicate to the application, lack of clear knowledge about the process and the financial cost of the application. Other themes include the effects of capital on applicant’s experience with the citizenship process, symbolic meanings of citizenship, transnationalism and ideas of deserving and undeserving surrounding the issues of residency and U.S. citizenship. These findings indicate the need for educational resources and mentorship for Dallas-area residents applying for U.S. citizenship, as well as a need for local government programs that foster a sense of community among citizenship applicants and their neighbours.

Practical tips for writing your abstract

When crafting the abstract for your dissertation or thesis, the most powerful technique you can use is to try and put yourself in the shoes of a potential reader. Assume the reader is not an expert in the field, but is interested in the research area. In other words, write for the intelligent layman, not for the seasoned topic expert. 

Start by trying to answer the question “why should I read this dissertation?”

Remember the WWHS.

Make sure you include the  what , why ,  how , and  so what  of your research in your abstract:

• What you studied (who and where are included in this part)
• Why the topic was important
• How you designed your study (i.e. your research methodology)
• So what were the big findings and implications of your research

Keep it simple.

Use terminology appropriate to your field of study, but don’t overload your abstract with big words and jargon that cloud the meaning and make your writing difficult to digest. A good abstract should appeal to all levels of potential readers and should be a (relatively) easy read. Remember, you need to write for the intelligent layman.

Be specific.

When writing your abstract, clearly outline your most important findings and insights and don’t worry about “giving away” too much about your research – there’s no need to withhold information. This is the one way your abstract is not like a blurb on the back of a book – the reader should be able to clearly understand the key takeaways of your thesis or dissertation after reading the abstract. Of course, if they then want more detail, they need to step into the restaurant and try out the menu.

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 ...

20 Comments

This was so very useful, thank you Caroline.

Much appreciated.

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This was really useful in writing the abstract for my dissertation. Thank you Caroline.

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Fabulous information – succinct, simple information which made my life easier after the most stressful and rewarding 21 months of completing this Masters Degree.

Very clear, specific and to the point guidance. Thanks a lot. Keep helping people 🙂

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I am so grateful for the tips. I am very optimistic in coming up with a winning abstract for my dessertation, thanks to you.

Thank you! First time writing anything this long!

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User Research

Aug 19, 2024 • 17 minutes read

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

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

Armin Tanovic

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

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

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

Qualitative UX research made easy

Conduct qualitative research with Maze, analyze data instantly, and get rich, descriptive insights that drive decision-making.

7 Qualitative research methods: An overview

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

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

1. User interviews

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

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

When to use user interviews

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

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

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

How to conduct user interviews: The basics

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

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

User interviews: A qualitative research example

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

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

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

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

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

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

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

2. Focus groups

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

When to use focus groups

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

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

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

How to conduct focus group studies: The basics

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

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

Focus groups: A qualitative research example

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

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

Time to talk to users.

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

A dialog develops:

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

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

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

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

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

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

3. Ethnographic research

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

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

When to use ethnographic research

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

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

How to conduct ethnographic research:

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

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

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

Ethnographic research: A qualitative research example

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

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

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

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

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

4. Qualitative observation

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

When to qualitative observation

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

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

How to conduct qualitative observation:

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

Qualitative observation: An qualitative research example

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

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

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

5. Case study research

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

When to use case studies

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

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

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

How to conduct case studies:

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

Case study research: A qualitative research example

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

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

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

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

6. Secondary research

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

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

When to use secondary research

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

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

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

How to conduct secondary research:

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

Secondary research: A qualitative research example

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

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

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

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

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

7. Open-ended surveys

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

When to use open-ended surveys

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

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

How to conduct open-ended surveys:

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

Open-ended surveys: A qualitative research example

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

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

The questions you ask your users:

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

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

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

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

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

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

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

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

Conduct qualitative research with Maze

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

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

The answer is with a user research tool like Maze.

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

Frequently asked questions about qualitative research examples

What is qualitative research?

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

Can a study be both qualitative and quantitative?

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

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

Is qualitative or quantitative research better?

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

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

What are some approaches to qualitative research?

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

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

Qualitative research design (JARS–Qual)

JARS–Qual, developed in 2018, mark the first time APA Style has included qualitative standards. They outline what should be reported in qualitative research manuscripts to make the review process easier.

The seventh edition of the Publication Manual also includes content on qualitative studies, including standards for journal article reporting, considerations for sharing qualitative data, and a description of case studies as a type of qualitative article.

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• Primary qualitative research
• Qualitative meta-analyses
• Qualitative Design Reporting Standards (JARS-Qual) (PDF, 141KB) Information recommended for inclusion in manuscripts that report primary qualitative research
• Qualitative Meta-Analysis Reporting Standards (PDF, 119KB) Information recommended for inclusion in manuscripts that report qualitative meta-analyses

For more information on how these standards were created, read Journal Article Reporting Standards for Qualitative Primary, Qualitative Meta-Analytic, and Mixed Methods Research in Psychology .

• Quantitative design standards
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18 Qualitative Research Examples

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Qualitative research is an approach to scientific research that involves using observation to gather and analyze non-numerical, in-depth, and well-contextualized datasets.

It serves as an integral part of academic, professional, and even daily decision-making processes (Baxter & Jack, 2008).

Methods of qualitative research encompass a wide range of techniques, from in-depth personal encounters, like ethnographies (studying cultures in-depth) and autoethnographies (examining one’s own cultural experiences), to collection of diverse perspectives on topics through methods like interviewing focus groups (gatherings of individuals to discuss specific topics).

Qualitative Research Examples

1. ethnography.

Definition: Ethnography is a qualitative research design aimed at exploring cultural phenomena. Rooted in the discipline of anthropology , this research approach investigates the social interactions, behaviors, and perceptions within groups, communities, or organizations.

Ethnographic research is characterized by extended observation of the group, often through direct participation, in the participants’ environment. An ethnographer typically lives with the study group for extended periods, intricately observing their everyday lives (Khan, 2014).

It aims to present a complete, detailed and accurate picture of the observed social life, rituals, symbols, and values from the perspective of the study group.

Example of Ethnographic Research

Title: “ The Everyday Lives of Men: An Ethnographic Investigation of Young Adult Male Identity “

Citation: Evans, J. (2010). The Everyday Lives of Men: An Ethnographic Investigation of Young Adult Male Identity. Peter Lang.

Overview: This study by Evans (2010) provides a rich narrative of young adult male identity as experienced in everyday life. The author immersed himself among a group of young men, participating in their activities and cultivating a deep understanding of their lifestyle, values, and motivations. This research exemplified the ethnographic approach, revealing complexities of the subjects’ identities and societal roles, which could hardly be accessed through other qualitative research designs.

Read my Full Guide on Ethnography Here

2. Autoethnography

Definition: Autoethnography is an approach to qualitative research where the researcher uses their own personal experiences to extend the understanding of a certain group, culture, or setting. Essentially, it allows for the exploration of self within the context of social phenomena.

Unlike traditional ethnography, which focuses on the study of others, autoethnography turns the ethnographic gaze inward, allowing the researcher to use their personal experiences within a culture as rich qualitative data (Durham, 2019).

The objective is to critically appraise one’s personal experiences as they navigate and negotiate cultural, political, and social meanings. The researcher becomes both the observer and the participant, intertwining personal and cultural experiences in the research.

Example of Autoethnographic Research

Title: “ A Day In The Life Of An NHS Nurse “

Citation: Osben, J. (2019). A day in the life of a NHS nurse in 21st Century Britain: An auto-ethnography. The Journal of Autoethnography for Health & Social Care. 1(1).

Overview: This study presents an autoethnography of a day in the life of an NHS nurse (who, of course, is also the researcher). The author uses the research to achieve reflexivity, with the researcher concluding: “Scrutinising my practice and situating it within a wider contextual backdrop has compelled me to significantly increase my level of scrutiny into the driving forces that influence my practice.”

Read my Full Guide on Autoethnography Here

3. Semi-Structured Interviews

Definition: Semi-structured interviews stand as one of the most frequently used methods in qualitative research. These interviews are planned and utilize a set of pre-established questions, but also allow for the interviewer to steer the conversation in other directions based on the responses given by the interviewee.

In semi-structured interviews, the interviewer prepares a guide that outlines the focal points of the discussion. However, the interview is flexible, allowing for more in-depth probing if the interviewer deems it necessary (Qu, & Dumay, 2011). This style of interviewing strikes a balance between structured ones which might limit the discussion, and unstructured ones, which could lack focus.

Example of Semi-Structured Interview Research

Title: “ Factors influencing adherence to cancer treatment in older adults with cancer: a systematic review “

Citation: Puts, M., et al. (2014). Factors influencing adherence to cancer treatment in older adults with cancer: a systematic review. Annals of oncology, 25 (3), 564-577.

Overview: Puts et al. (2014) executed an extensive systematic review in which they conducted semi-structured interviews with older adults suffering from cancer to examine the factors influencing their adherence to cancer treatment. The findings suggested that various factors, including side effects, faith in healthcare professionals, and social support have substantial impacts on treatment adherence. This research demonstrates how semi-structured interviews can provide rich and profound insights into the subjective experiences of patients.

4. Focus Groups

Definition: Focus groups are a qualitative research method that involves organized discussion with a selected group of individuals to gain their perspectives on a specific concept, product, or phenomenon. Typically, these discussions are guided by a moderator.

During a focus group session, the moderator has a list of questions or topics to discuss, and participants are encouraged to interact with each other (Morgan, 2010). This interactivity can stimulate more information and provide a broader understanding of the issue under scrutiny. The open format allows participants to ask questions and respond freely, offering invaluable insights into attitudes, experiences, and group norms.

Example of Focus Group Research

Title: “ Perspectives of Older Adults on Aging Well: A Focus Group Study “

Citation: Halaweh, H., Dahlin-Ivanoff, S., Svantesson, U., & Willén, C. (2018). Perspectives of older adults on aging well: a focus group study. Journal of aging research .

Overview: This study aimed to explore what older adults (aged 60 years and older) perceived to be ‘aging well’. The researchers identified three major themes from their focus group interviews: a sense of well-being, having good physical health, and preserving good mental health. The findings highlight the importance of factors such as positive emotions, social engagement, physical activity, healthy eating habits, and maintaining independence in promoting aging well among older adults.

5. Phenomenology

Definition: Phenomenology, a qualitative research method, involves the examination of lived experiences to gain an in-depth understanding of the essence or underlying meanings of a phenomenon.

The focus of phenomenology lies in meticulously describing participants’ conscious experiences related to the chosen phenomenon (Padilla-Díaz, 2015).

In a phenomenological study, the researcher collects detailed, first-hand perspectives of the participants, typically via in-depth interviews, and then uses various strategies to interpret and structure these experiences, ultimately revealing essential themes (Creswell, 2013). This approach focuses on the perspective of individuals experiencing the phenomenon, seeking to explore, clarify, and understand the meanings they attach to those experiences.

Example of Phenomenology Research

Title: “ A phenomenological approach to experiences with technology: current state, promise, and future directions for research ”

Citation: Cilesiz, S. (2011). A phenomenological approach to experiences with technology: Current state, promise, and future directions for research. Educational Technology Research and Development, 59 , 487-510.

Overview: A phenomenological approach to experiences with technology by Sebnem Cilesiz represents a good starting point for formulating a phenomenological study. With its focus on the ‘essence of experience’, this piece presents methodological, reliability, validity, and data analysis techniques that phenomenologists use to explain how people experience technology in their everyday lives.

6. Grounded Theory

Definition: Grounded theory is a systematic methodology in qualitative research that typically applies inductive reasoning . The primary aim is to develop a theoretical explanation or framework for a process, action, or interaction grounded in, and arising from, empirical data (Birks & Mills, 2015).

In grounded theory, data collection and analysis work together in a recursive process. The researcher collects data, analyses it, and then collects more data based on the evolving understanding of the research context. This ongoing process continues until a comprehensive theory that represents the data and the associated phenomenon emerges – a point known as theoretical saturation (Charmaz, 2014).

Example of Grounded Theory Research

Title: “ Student Engagement in High School Classrooms from the Perspective of Flow Theory “

Citation: Shernoff, D. J., Csikszentmihalyi, M., Shneider, B., & Shernoff, E. S. (2003). Student engagement in high school classrooms from the perspective of flow theory. School Psychology Quarterly, 18 (2), 158–176.

Overview: Shernoff and colleagues (2003) used grounded theory to explore student engagement in high school classrooms. The researchers collected data through student self-reports, interviews, and observations. Key findings revealed that academic challenge, student autonomy, and teacher support emerged as the most significant factors influencing students’ engagement, demonstrating how grounded theory can illuminate complex dynamics within real-world contexts.

7. Narrative Research

Definition: Narrative research is a qualitative research method dedicated to storytelling and understanding how individuals experience the world. It focuses on studying an individual’s life and experiences as narrated by that individual (Polkinghorne, 2013).

In narrative research, the researcher collects data through methods such as interviews, observations , and document analysis. The emphasis is on the stories told by participants – narratives that reflect their experiences, thoughts, and feelings.

These stories are then interpreted by the researcher, who attempts to understand the meaning the participant attributes to these experiences (Josselson, 2011).

Example of Narrative Research

Title: “Narrative Structures and the Language of the Self”

Citation: McAdams, D. P., Josselson, R., & Lieblich, A. (2006). Identity and story: Creating self in narrative . American Psychological Association.

Overview: In this innovative study, McAdams et al. (2006) employed narrative research to explore how individuals construct their identities through the stories they tell about themselves. By examining personal narratives, the researchers discerned patterns associated with characters, motivations, conflicts, and resolutions, contributing valuable insights about the relationship between narrative and individual identity.

8. Case Study Research

Definition: Case study research is a qualitative research method that involves an in-depth investigation of a single instance or event: a case. These ‘cases’ can range from individuals, groups, or entities to specific projects, programs, or strategies (Creswell, 2013).

The case study method typically uses multiple sources of information for comprehensive contextual analysis. It aims to explore and understand the complexity and uniqueness of a particular case in a real-world context (Merriam & Tisdell, 2015). This investigation could result in a detailed description of the case, a process for its development, or an exploration of a related issue or problem.

Example of Case Study Research

Title: “ Teacher’s Role in Fostering Preschoolers’ Computational Thinking: An Exploratory Case Study “

Citation: Wang, X. C., Choi, Y., Benson, K., Eggleston, C., & Weber, D. (2021). Teacher’s role in fostering preschoolers’ computational thinking: An exploratory case study. Early Education and Development , 32 (1), 26-48.

Overview: This study investigates the role of teachers in promoting computational thinking skills in preschoolers. The study utilized a qualitative case study methodology to examine the computational thinking scaffolding strategies employed by a teacher interacting with three preschoolers in a small group setting. The findings highlight the importance of teachers’ guidance in fostering computational thinking practices such as problem reformulation/decomposition, systematic testing, and debugging.

Read about some Famous Case Studies in Psychology Here

9. Participant Observation

Definition: Participant observation has the researcher immerse themselves in a group or community setting to observe the behavior of its members. It is similar to ethnography, but generally, the researcher isn’t embedded for a long period of time.

The researcher, being a participant, engages in daily activities, interactions, and events as a way of conducting a detailed study of a particular social phenomenon (Kawulich, 2005).

The method involves long-term engagement in the field, maintaining detailed records of observed events, informal interviews, direct participation, and reflexivity. This approach allows for a holistic view of the participants’ lived experiences, behaviours, and interactions within their everyday environment (Dewalt, 2011).

Example of Participant Observation Research

Title: Conflict in the boardroom: a participant observation study of supervisory board dynamics

Citation: Heemskerk, E. M., Heemskerk, K., & Wats, M. M. (2017). Conflict in the boardroom: a participant observation study of supervisory board dynamics. Journal of Management & Governance , 21 , 233-263.

Overview: This study examined how conflicts within corporate boards affect their performance. The researchers used a participant observation method, where they actively engaged with 11 supervisory boards and observed their dynamics. They found that having a shared understanding of the board’s role called a common framework, improved performance by reducing relationship conflicts, encouraging task conflicts, and minimizing conflicts between the board and CEO.

10. Non-Participant Observation

Definition: Non-participant observation is a qualitative research method in which the researcher observes the phenomena of interest without actively participating in the situation, setting, or community being studied.

This method allows the researcher to maintain a position of distance, as they are solely an observer and not a participant in the activities being observed (Kawulich, 2005).

During non-participant observation, the researcher typically records field notes on the actions, interactions, and behaviors observed , focusing on specific aspects of the situation deemed relevant to the research question.

This could include verbal and nonverbal communication , activities, interactions, and environmental contexts (Angrosino, 2007). They could also use video or audio recordings or other methods to collect data.

Example of Non-Participant Observation Research

Title: Mental Health Nurses’ attitudes towards mental illness and recovery-oriented practice in acute inpatient psychiatric units: A non-participant observation study

Citation: Sreeram, A., Cross, W. M., & Townsin, L. (2023). Mental Health Nurses’ attitudes towards mental illness and recovery‐oriented practice in acute inpatient psychiatric units: A non‐participant observation study. International Journal of Mental Health Nursing .

Overview: This study investigated the attitudes of mental health nurses towards mental illness and recovery-oriented practice in acute inpatient psychiatric units. The researchers used a non-participant observation method, meaning they observed the nurses without directly participating in their activities. The findings shed light on the nurses’ perspectives and behaviors, providing valuable insights into their attitudes toward mental health and recovery-focused care in these settings.

11. Content Analysis

Definition: Content Analysis involves scrutinizing textual, visual, or spoken content to categorize and quantify information. The goal is to identify patterns, themes, biases, or other characteristics (Hsieh & Shannon, 2005).

Content Analysis is widely used in various disciplines for a multitude of purposes. Researchers typically use this method to distill large amounts of unstructured data, like interview transcripts, newspaper articles, or social media posts, into manageable and meaningful chunks.

When wielded appropriately, Content Analysis can illuminate the density and frequency of certain themes within a dataset, provide insights into how specific terms or concepts are applied contextually, and offer inferences about the meanings of their content and use (Duriau, Reger, & Pfarrer, 2007).

Example of Content Analysis

Title: Framing European politics: A content analysis of press and television news .

Citation: Semetko, H. A., & Valkenburg, P. M. (2000). Framing European politics: A content analysis of press and television news. Journal of Communication, 50 (2), 93-109.

Overview: This study analyzed press and television news articles about European politics using a method called content analysis. The researchers examined the prevalence of different “frames” in the news, which are ways of presenting information to shape audience perceptions. They found that the most common frames were attribution of responsibility, conflict, economic consequences, human interest, and morality.

Read my Full Guide on Content Analysis Here

12. Discourse Analysis

Definition: Discourse Analysis, a qualitative research method, interprets the meanings, functions, and coherence of certain languages in context.

Discourse analysis is typically understood through social constructionism, critical theory , and poststructuralism and used for understanding how language constructs social concepts (Cheek, 2004).

Discourse Analysis offers great breadth, providing tools to examine spoken or written language, often beyond the level of the sentence. It enables researchers to scrutinize how text and talk articulate social and political interactions and hierarchies.

Insight can be garnered from different conversations, institutional text, and media coverage to understand how topics are addressed or framed within a specific social context (Jorgensen & Phillips, 2002).

Example of Discourse Analysis

Title: The construction of teacher identities in educational policy documents: A critical discourse analysis

Citation: Thomas, S. (2005). The construction of teacher identities in educational policy documents: A critical discourse analysis. Critical Studies in Education, 46 (2), 25-44.

Overview: The author examines how an education policy in one state of Australia positions teacher professionalism and teacher identities. While there are competing discourses about professional identity, the policy framework privileges a  narrative that frames the ‘good’ teacher as one that accepts ever-tightening control and regulation over their professional practice.

Read my Full Guide on Discourse Analysis Here

13. Action Research

Definition: Action Research is a qualitative research technique that is employed to bring about change while simultaneously studying the process and results of that change.

This method involves a cyclical process of fact-finding, action, evaluation, and reflection (Greenwood & Levin, 2016).

Typically, Action Research is used in the fields of education, social sciences , and community development. The process isn’t just about resolving an issue but also developing knowledge that can be used in the future to address similar or related problems.

The researcher plays an active role in the research process, which is normally broken down into four steps: 

• developing a plan to improve what is currently being done
• implementing the plan
• observing the effects of the plan, and
• reflecting upon these effects (Smith, 2010).

Example of Action Research

Title: Using Digital Sandbox Gaming to Improve Creativity Within Boys’ Writing

Citation: Ellison, M., & Drew, C. (2020). Using digital sandbox gaming to improve creativity within boys’ writing. Journal of Research in Childhood Education , 34 (2), 277-287.

Overview: This was a research study one of my research students completed in his own classroom under my supervision. He implemented a digital game-based approach to literacy teaching with boys and interviewed his students to see if the use of games as stimuli for storytelling helped draw them into the learning experience.

Read my Full Guide on Action Research Here

14. Semiotic Analysis

Definition: Semiotic Analysis is a qualitative method of research that interprets signs and symbols in communication to understand sociocultural phenomena. It stems from semiotics, the study of signs and symbols and their use or interpretation (Chandler, 2017).

In a Semiotic Analysis, signs (anything that represents something else) are interpreted based on their significance and the role they play in representing ideas.

This type of research often involves the examination of images, sounds, and word choice to uncover the embedded sociocultural meanings. For example, an advertisement for a car might be studied to learn more about societal views on masculinity or success (Berger, 2010).

Example of Semiotic Research

Title: Shielding the learned body: a semiotic analysis of school badges in New South Wales, Australia

Citation: Symes, C. (2023). Shielding the learned body: a semiotic analysis of school badges in New South Wales, Australia. Semiotica , 2023 (250), 167-190.

Overview: This study examines school badges in New South Wales, Australia, and explores their significance through a semiotic analysis. The badges, which are part of the school’s visual identity, are seen as symbolic representations that convey meanings. The analysis reveals that these badges often draw on heraldic models, incorporating elements like colors, names, motifs, and mottoes that reflect local culture and history, thus connecting students to their national identity. Additionally, the study highlights how some schools have shifted from traditional badges to modern logos and slogans, reflecting a more business-oriented approach.

15. Qualitative Longitudinal Studies

Definition: Qualitative Longitudinal Studies are a research method that involves repeated observation of the same items over an extended period of time.

Unlike a snapshot perspective, this method aims to piece together individual histories and examine the influences and impacts of change (Neale, 2019).

Qualitative Longitudinal Studies provide an in-depth understanding of change as it happens, including changes in people’s lives, their perceptions, and their behaviors.

For instance, this method could be used to follow a group of students through their schooling years to understand the evolution of their learning behaviors and attitudes towards education (Saldaña, 2003).

Example of Qualitative Longitudinal Research

Title: Patient and caregiver perspectives on managing pain in advanced cancer: a qualitative longitudinal study

Citation: Hackett, J., Godfrey, M., & Bennett, M. I. (2016). Patient and caregiver perspectives on managing pain in advanced cancer: a qualitative longitudinal study.  Palliative medicine ,  30 (8), 711-719.

Overview: This article examines how patients and their caregivers manage pain in advanced cancer through a qualitative longitudinal study. The researchers interviewed patients and caregivers at two different time points and collected audio diaries to gain insights into their experiences, making this study longitudinal.

Read my Full Guide on Longitudinal Research Here

16. Open-Ended Surveys

Definition: Open-Ended Surveys are a type of qualitative research method where respondents provide answers in their own words. Unlike closed-ended surveys, which limit responses to predefined options, open-ended surveys allow for expansive and unsolicited explanations (Fink, 2013).

Open-ended surveys are commonly used in a range of fields, from market research to social studies. As they don’t force respondents into predefined response categories, these surveys help to draw out rich, detailed data that might uncover new variables or ideas.

For example, an open-ended survey might be used to understand customer opinions about a new product or service (Lavrakas, 2008).

Contrast this to a quantitative closed-ended survey, like a Likert scale, which could theoretically help us to come up with generalizable data but is restricted by the questions on the questionnaire, meaning new and surprising data and insights can’t emerge from the survey results in the same way.

Example of Open-Ended Survey Research

Title: Advantages and disadvantages of technology in relationships: Findings from an open-ended survey

Citation: Hertlein, K. M., & Ancheta, K. (2014). Advantages and disadvantages of technology in relationships: Findings from an open-ended survey.  The Qualitative Report ,  19 (11), 1-11.

Overview: This article examines the advantages and disadvantages of technology in couple relationships through an open-ended survey method. Researchers analyzed responses from 410 undergraduate students to understand how technology affects relationships. They found that technology can contribute to relationship development, management, and enhancement, but it can also create challenges such as distancing, lack of clarity, and impaired trust.

17. Naturalistic Observation

Definition: Naturalistic Observation is a type of qualitative research method that involves observing individuals in their natural environments without interference or manipulation by the researcher.

Naturalistic observation is often used when conducting research on behaviors that cannot be controlled or manipulated in a laboratory setting (Kawulich, 2005).

It is frequently used in the fields of psychology, sociology, and anthropology. For instance, to understand the social dynamics in a schoolyard, a researcher could spend time observing the children interact during their recess, noting their behaviors, interactions, and conflicts without imposing their presence on the children’s activities (Forsyth, 2010).

Example of Naturalistic Observation Research

Title: Dispositional mindfulness in daily life: A naturalistic observation study

Citation: Kaplan, D. M., Raison, C. L., Milek, A., Tackman, A. M., Pace, T. W., & Mehl, M. R. (2018). Dispositional mindfulness in daily life: A naturalistic observation study. PloS one , 13 (11), e0206029.

Overview: In this study, researchers conducted two studies: one exploring assumptions about mindfulness and behavior, and the other using naturalistic observation to examine actual behavioral manifestations of mindfulness. They found that trait mindfulness is associated with a heightened perceptual focus in conversations, suggesting that being mindful is expressed primarily through sharpened attention rather than observable behavioral or social differences.

Read my Full Guide on Naturalistic Observation Here

18. Photo-Elicitation

Definition: Photo-elicitation utilizes photographs as a means to trigger discussions and evoke responses during interviews. This strategy aids in bringing out topics of discussion that may not emerge through verbal prompting alone (Harper, 2002).

Traditionally, Photo-Elicitation has been useful in various fields such as education, psychology, and sociology. The method involves the researcher or participants taking photographs, which are then used as prompts for discussion.

For instance, a researcher studying urban environmental issues might invite participants to photograph areas in their neighborhood that they perceive as environmentally detrimental, and then discuss each photo in depth (Clark-Ibáñez, 2004).

Example of Photo-Elicitation Research

Title: Early adolescent food routines: A photo-elicitation study

Citation: Green, E. M., Spivak, C., & Dollahite, J. S. (2021). Early adolescent food routines: A photo-elicitation study. Appetite, 158 .

Overview: This study focused on early adolescents (ages 10-14) and their food routines. Researchers conducted in-depth interviews using a photo-elicitation approach, where participants took photos related to their food choices and experiences. Through analysis, the study identified various routines and three main themes: family, settings, and meals/foods consumed, revealing how early adolescents view and are influenced by their eating routines.

Features of Qualitative Research

Qualitative research is a research method focused on understanding the meaning individuals or groups attribute to a social or human problem (Creswell, 2013).

Some key features of this method include:

• Naturalistic Inquiry: Qualitative research happens in the natural setting of the phenomena, aiming to understand “real world” situations (Patton, 2015). This immersion in the field or subject allows the researcher to gather a deep understanding of the subject matter.
• Emphasis on Process: It aims to understand how events unfold over time rather than focusing solely on outcomes (Merriam & Tisdell, 2015). The process-oriented nature of qualitative research allows researchers to investigate sequences, timing, and changes.
• Interpretive: It involves interpreting and making sense of phenomena in terms of the meanings people assign to them (Denzin & Lincoln, 2011). This interpretive element allows for rich, nuanced insights into human behavior and experiences.
• Holistic Perspective: Qualitative research seeks to understand the whole phenomenon rather than focusing on individual components (Creswell, 2013). It emphasizes the complex interplay of factors, providing a richer, more nuanced view of the research subject.
• Prioritizes Depth over Breadth: Qualitative research favors depth of understanding over breadth, typically involving a smaller but more focused sample size (Hennink, Hutter, & Bailey, 2020). This enables detailed exploration of the phenomena of interest, often leading to rich and complex data.

Qualitative vs Quantitative Research

Qualitative research centers on exploring and understanding the meaning individuals or groups attribute to a social or human problem (Creswell, 2013).

It involves an in-depth approach to the subject matter, aiming to capture the richness and complexity of human experience.

Examples include conducting interviews, observing behaviors, or analyzing text and images.

There are strengths inherent in this approach. In its focus on understanding subjective experiences and interpretations, qualitative research can yield rich and detailed data that quantitative research may overlook (Denzin & Lincoln, 2011).

Additionally, qualitative research is adaptive, allowing the researcher to respond to new directions and insights as they emerge during the research process.

However, there are also limitations. Because of the interpretive nature of this research, findings may not be generalizable to a broader population (Marshall & Rossman, 2014). Well-designed quantitative research, on the other hand, can be generalizable.

Moreover, the reliability and validity of qualitative data can be challenging to establish due to its subjective nature, unlike quantitative research, which is ideally more objective.

Compare Qualitative and Quantitative Research Methodologies in This Guide Here

In conclusion, qualitative research methods provide distinctive ways to explore social phenomena and understand nuances that quantitative approaches might overlook. Each method, from Ethnography to Photo-Elicitation, presents its strengths and weaknesses but they all offer valuable means of investigating complex, real-world situations. The goal for the researcher is not to find a definitive tool, but to employ the method best suited for their research questions and the context at hand (Almalki, 2016). Above all, these methods underscore the richness of human experience and deepen our understanding of the world around us.

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Qualitative Research Designs, Sample Size and Saturation: Is Enough Always Enough?

2021, Journal of Advocacy, Research and Education

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Enhancing maternal health service utilization among highly vulnerable pregnant women through a human-centered design process: Study protocol for a quasi-experimental study in Oromia, Ethiopia

Bee-Ah Kang Roles: Conceptualization, Methodology, Project Administration, Writing – Original Draft Preparation, Writing – Review & Editing Habtamu Tamene Roles: Conceptualization, Investigation, Methodology, Project Administration, Supervision, Validation, Writing – Original Draft Preparation Yihunie Lakew Roles: Investigation, Methodology, Supervision, Validation, Writing – Original Draft Preparation Daryl Stephens Roles: Writing – Review & Editing Rajiv Rimal Roles: Conceptualization, Funding Acquisition, Methodology, Project Administration, Supervision, Writing – Original Draft Preparation

Disproportionate uptake of and access to maternal and child health services remain significant challenges across and within countries. Differing geographic, economic, environmental, and social factors contribute to varying degrees of vulnerabilities among individuals, which manifest as disparities in maternal and newborn health outcomes. Designing solutions according to need is vital to improve maternal and child health outcomes. In this paper, we describe our study protocol on evaluating the effectiveness of an intervention package developed through a human-centered design (HCD) process in improving maternal health service uptake among vulnerable pregnant women in rural areas of Ethiopia.

The study has two distinct phases. For both phases, solutions will be developed leveraging HCD approaches to improve institutional delivery and antenatal care uptake among vulnerable pregnant women. Final solutions will be implemented in collaboration with community health workers and health officers. A community-based, quasi-experimental, mixed-method study design is used to assess differences between intervention and control arms. A panel sample will be enrolled after screening for pregnancy and vulnerability level and surveyed at baseline and midline in Phase 1. In Phase 2, a post-only study will be conducted in the same intervention and control sites. Pregnant women will receive refined solutions for six months, which will be evaluated using end-line assessment. Qualitative interviews will be conducted among vulnerable pregnant women and healthcare providers.

Conclusions and Implications

Our sequential approach to evaluating initial solutions, which in turn will be used to inform the enhancement of solutions, will provide practical insights into how solutions are accepted among vulnerable women and how they can be better integrated into women’s lives and health systems. Our findings on program effectiveness and implementation research will be disseminated to the Ethiopian Ministry of Health and its partners to inform large-scale implementation at the national level.

maternal and child health, vulnerability, human-centered design, research protocol

Introduction

Reducing maternal mortality ratio (MMR) has been one of the major priorities on the global health agenda. With the launch of the Sustainable Development Goals (SDG) in 2015, the World Health Organization (WHO) and partners reached a consensus on endorsing Target 3.1 that aims to reduce the global MMR to less than 70 per 100,000 livebirths by 2030. The target has shown a steady progress with its 34.3% reduction between 2000 and 2020 1 . However, such aggregated outcomes in health indicators often obscure disparities across countries and within sub-regions.

Ethiopia has shown steady improvements in many maternal and child health indicators over the past two decades. In 2000, the MMR was 871 deaths per 100,000 livebirths, and declined to 412 in 2016 2 . Between 2005 and 2019, under-5 mortality also decreased by 52% 3 . Despite this substantial progress, Ethiopia faces persistent health challenges. The MMR in-country accounts for 3.6% of global maternal mortalities 4 . Twenty-five percent of female deaths from the 2016 data were found to be from pregnancy-related causes 2 , and the neonatal mortality rate also increased by four points per 1,000 livebirths between 2016 and 2019 3 .

To achieve faster and more equitable improvements in maternal and child health outcomes, the government of Ethiopia has implemented a three-tiered health system with an intensive Health Extension Program, which takes a community-based approach to improving health knowledge, health-related skills, and access to primary healthcare 5 . In addition, the Health System Transformation Plan (HSTP-II) is being implemented from 2020 to 2025 with an overall objective to improve the population’s health status by accelerating progress towards universal health coverage, protecting populations during health emergencies, transforming woredas toward zero home delivery, and improving health system responsiveness 6 . The HSTP-II has a target to reduce the MMR to 279 per 100,000 live births and under-5 and neonatal mortalities to 44 and 21 per 1,000 live births, respectively 6 . Under these national goals, providing pregnant women with essential maternal health services, including institutional delivery (i.e., childbirth occurred at health facilities with skilled birth attendants), antenatal care (ANC), and iron and folic acid (IFA) supplementation, has been a key strategy for optimizing maternal and child health outcomes in Ethiopia. These maternal health services can significantly reduce the risk of maternal, perinatal and neonatal mortality in low- and middle-income countries (LMICs) and alleviate health disparities worldwide 7 – 9 .

Nevertheless, there remains an urgent need to address disproportionate uptake of and access to maternal health services in Ethiopia. Taking institutional delivery coverage as an example, women’s use of health facilities for childbirth greatly varies by region and sociodemographic characteristics. With the national average being approximately 48%, the percentage of institutional delivery use ranges from 23.3% in Somali Region to 94.8% in Addis Ababa, the capital city 3 . Also, 79% of women in the lowest wealth quintile delivered a baby at home; the corresponding figure for women in the highest wealth quintile was 14%. Parity is also associated with home delivery: women having six or more births are more likely to deliver at home, compared to those delivering for the first time.

Prior evidence suggests that women’s use of maternal health services is shaped by multiple factors at the socio-ecological continuum. Barriers to maternal health service uptake among pregnant women reside at multiple levels, including at the individual level (having poor knowledge of obstetric complications and danger signs, low risk perceptions, high parity, and no birth preparedness plans) 10 – 12 , social level (social and gender norms, support from family, decision-making power) 11 , 13 , 14 , cultural level (respect for elders, perception about pregnancy-related matters as women’s privacy, relationship with traditional birth attendants in the community) 3 , 15 – 17 , structural level (distance to health facilities, transportation and road infrastructure, costs for traveling) 11 , 15 , 18 , and those that are service-related (lack of services that respect women’s privacy and preferences, disrespectful treatment by health workers, and staff and medical supply shortages) 10 , 15 , 19 , 20 .

Understanding vulnerabilities of key target populations has important implications for developing and implementing tailored programs and policies 21 . Nevertheless, less attention has been paid to how vulnerability is defined, conceptualized and operationalized in the realm of maternal health service coverage 22 . Indeed, despite remarkable improvements in disease-focused service coverage, global health programs have been highlighted as neglecting inequity by not reaching the most disadvantaged population, straining weak local health systems, and distorting local health priorities and agendas 23 , 24 . Our project is based on the assumption that accurate and comprehensive assessment of vulnerability in maternal service uptake can help identify vulnerable pregnant women with the lowest likelihood of accessing necessary health services, which will subsequently help generate evidence and provide guidance on effective policies and interventions. Therefore, identifying the most vulnerable pregnant women and engaging them in program development would enhance the applicability, viability, and effectiveness of an intervention. Adopting user-oriented strategies, our study attempts to render vulnerable pregnant women an opportunity to take ownership of their problems and participate in generating solutions with the study team to cater to their unique needs, challenges, and hopes.

Furthermore, we argue for the need for conducting implementation research, given that determining true program effectiveness necessitates evidence on how an intervention fits in “real world” settings beyond a controlled study environment. Implementation research is distinguished from monitoring or process evaluation efforts due to its focused goals to explore 1) a program’s likelihood of being adopted and scaled up in real-world settings, 2) contextual factors that may facilitate or hinder implementation, 3) implementation strategies (rather than intervention strategies), 4) and the engagement of stakeholders to achieve successful implementation 25 . Well-designed implementation research provides an insight into whether an intervention would likely be integrated into its target environment, and more broadly, into health systems beyond study duration and scope. Implementation research also generates evidence that helps policy makers and implementers foresee challenges, contributing to saving costs and resources for future programs. Although there is no scientific consensus on what elements and principles are necessary for conducting implementation research, the WHO guide 26 encourages researchers to outline implementation research questions, use a framework that describes implementation research outcomes, and select a study design and methods that are most pertinent to understand how implementation occurs in a given context.

Study objectives

The objective of this study is to evaluate the effectiveness of an intervention package, developed through a human-centered design (HCD) process, in improving maternal health service (institutional delivery and ANC) uptake among highly vulnerable pregnant women living in rural areas of Ethiopia. Specifically, the study objectives are:

1. To assess whether changes in women from baseline to end-line in the intervention arm are significantly greater than corresponding changes in the control arm in the following outcomes: (a) institutional delivery and (b) ANC visits.

2. To explore how social and behavioral factors, including social norms, gender norms, women’s empowerment, and spousal dynamics, are associated with maternal health service uptake.

3. To understand the extent to which the intervention meets key implementation research outcomes, including fidelity, acceptability, feasibility, and sustainability, among pregnant women and health workers in the intervention arm.

Study setting

Our study sites are in Oromia, the most populous region in Ethiopia. Within this region, we selected two woredas (administrative units below the zone, which is below the region) for our intervention sites. Sirraro and Shalla woredas were selected as intervention arms, and Gera and Shebe woredas as control arms. The study sites were not randomly selected due to the on-going security issues in Ethiopia.

Study design

A community-based quasi-experimental study design was chosen to assess differences in key variables between the intervention and control arms. We chose a quasi-experimental design for several reasons. We lacked information about clear randomization unit given the characteristics of individuals or clusters (woredas), and it was likely that many woredas in Oromia region are not homogenous towards our outcomes of interest. Another reason was due to resource constraints, as we did not have a sufficient number of woredas in our study to conduct a randomized trial design. The study included two waves of data collection from a panel of recruited pregnant women at Phase 1. We attempt to leverage Phase 1 findings to inform the development of study tools and identify factors affecting implementation to provide insights into the improvement our intervention at Phase 2. This study is registered at ClinicalTrial.gov (NCT05907720).

We conducted the baseline survey of pregnant women enrolled in intervention and control arms in January 2024 and are in the process of conducting a midline assessment for Phase 1. After the baseline survey, we implemented a set of HCD prototype solutions in the intervention arm only, keeping standard of usual care intact in the control arm. After the 4-month period of HCD solution implementation, we are conducting the midline survey among the same women in the panel from both the intervention and control arms. The midline assessment includes in-depth interviews with purposively selected pregnant women from the panel and health workers who engaged in implementation.

In Phase 2, we will conduct a post-only study with a new sample of vulnerable pregnant women who will be recruited after the implementation of refined HCD solutions. We will apply the same recruitement procedures as those for Phase 1. We will compare outcomes between the intervention and control arms at end-line, and the end-line findings will also be compared with baseline to identify whether refined solutions bring greater impact than initial solutions did in Phase 1. Thus, our overall study design includes a total of three assessments, baseline and midline assessments in Phase 1 and end-line assessment in Phase 2. The study design is further described in Figure 1 .

Figure 1. Quasi-experimental evaluation study among vulnerable pregnant women.

Our primary target participants are vulnerable pregnant women aged 15–49. For consent administration, we segmented adult pregnant women aged 19 and above, pregnant adolescent girls aged 15–18, and service providers. Service providers, such as midwives, Health Extension Workers (HEWs) and Health Development Armies (HDAs) who engage in the study will be recruited for qualitative assessment at midline (Phase 1) and end-line (Phase 2). Table 1 below summarizes inclusion and exclusion criteria for each sample population.

Table 1. Summary of inclusion and exclusion criteria of study sample.

Sample size calculation

We considered institutional delivery (a major outcome variable) as a basis for the sample size calculation. To estimate sample size, we took account of our longitudinal design that measures the same subjects before and after the intervention and assumed an intervention effect of 9% in improving institutional delivery beyond the current 48% 3 . Assuming a p-value of 0.05, interclass correlation coefficient (ICC) of 0.009, a power of 80%, a total of 240 pregnant women from the intervention arm and another 240 pregnant women from the control arm are needed, for a total sample size of 480 pregnant women in each study phase. The assumptions of sample size also took account of feasibility and sample characteristics. The number of enumeration areas (EAs) this phase can reach is 80 per study arm, and approximately 5 women are expected to be eligible in each EA. Based on the cross-sectional study design in Phase 2, we assumed 9% detectable difference between the study arms with an 80% power, which led to a sample of 531 for each study arm, taking account of 10% non-response rate. Approximately 106 EAs will be reached from given the number of eligible women in each EA. Both intervention and control arms will have an equal sample size in each phase, having 1:1 ratio of women between the intervention and control arms. As such, the total number of women to recruit across study phases is 1542.

For qualitative assessments, a total of 32 health workers engaged in implementation will be purposively sampled for in-depth interviews at post-intervention assessment in each phase. The interviews with health workers will explore the feasibility, acceptability, and scalability of the prototype solutions along with perceived program effects. An equal number of health workers will be interviewed at midline (post-intervention of Phase 1) and end-line (post-intervention of Phase 2). The interviewees selected for Phase 2 may be the same service providers recruited from Phase 1 depending on their availability and engagement in the program. We have chosen 32 as the target sample size based on our best estimate about achieving data saturation. In each phase, we will also interview 20 pregnant women from the panel who recently delivered and were exposed to our HCD solutions. The qualitative iterviews will be conducted only in the intervention sites.

Recruitment

After obtaining a list of all interested women from HEWs and HDAs, data collectors will visit the women in person to screen their pregnancy status and vulnerability level to assess their eligibility. With the woman’s verbal consent, the data collector will administer the pregnancy screening tool to identify her pregnancy status. Only women 5+ months of pregnancy and aged 15–49 are considered eligible. If eligible, she will then be screened for her vulnerability level, assessed through the vulnerability screening tool. Those considered to be moderately to highly vulnerable are eligible and entered into the sampling frame. All responses to the screening questions will be entered into the data collectors’ mobile phone application that automatically determines pregnant women’s eligibility during the visit. Women who score at most 13 out of the maximum 20 vulnerability screening questions will be identified for the study participant. For the qualitative assessment, recently delivered women who receive our intervention and health workers in the intervention sites will be recruited. Purposive selection of the sample will take into account the extent to which women are exposed to the intervention. We will prioritize recruiting women in earlier gestational ages (5 th month or earlier) since women in late pregnancy terms may not be fully exposed to our solutions.

All eligible women will be entered into our sampling frame. After listing eligible pregnant women, we aim to recruit approximately three women per EA to achieve our target sample size. If an EA has five or fewer eligible women, they will be all contacted for recruitment. If there are more pregnant women than the minimum required number of pregnant women, we will randomly select the required number. If a woman is not interested or available for participation, we will contact the next randomly selected woman for recruitment. Recruitment will continue until our sample size is reached, expanding to other EAs if necessary. Recruitment in Phase 1 has been completed in this way, and Phase 2 recruitment will follow this procedure.

Data collection and measurement

Survey interview . All participant from Phase 1 and 2 will undergo a one-on-one survey interview to assess sociodemographic information, psychological factors, social and structural factors, and maternal health service utilization. A structured interview will be administered by a local data collector in the local language. The survey will capture the self-reported place of the most recent childbirth along with uptake and frequency of ANC visits during the most recent pregnancy. Secondary outcomes include knowledge, attitudes, and perceptions about maternal health service utilization, social norms, gender norms, spousal dynamics, decision-making, and community and structural factors. Midline (post-intervention in Phase 1) and end-line (post-intervention in Phase 2) assessments will additionally include questions measuring program exposure.

Qualitative interview . Purposively selected women from the study participants (n=20) along with health workers (n=32) engaged in the program will participate in an in-depth interview. Given the 4-month duration of program implementation among pregnant women in their 5 th or higher months of pregnancy, interviews will be administered to recently delivered women inquiring about their perceived effects of the intervention on the place of childbirth and ANC uptake during pregnancy. Additionally, the interview guides for women and health workers will contain question around key implementation research outcomes, including acceptability and feasibility, to identify any similarities and differences arising across different types of interview participants.

Intervention

HCD workshop procedure . In Phase 1, prior to the HCD process, an extensive desk review and secondary data analysis were conducted to identify key drivers of vulnerability affecting uptakes of maternal and child health services. Vulnerability driving factors, such as women's illiteracy, distance from health facilities, high parity, decision making power, exposure to media, and lack of household assets were identified as major barriers to maternal health service use. Based on these factors, a vulnerability screening algorithm was developed to identify the target population of rural vulnerable pregnant women. From the evidence synthesis, the two initial design challenges focusing on ANC and institutional delivery were also prioritized: 1) reimagining how to support pregnant women to attend ANC, and 2) reimagining how to support pregnant women to deliver in a health center. Then, a five-stage design thinking process was implemented, using empathy, definition, ideation, prototyping, and testing stages. In this process, we engaged key stakeholders, such as vulnerable pregnant women, their husbands, and healthcare providers in co-creation workshops.

The co-creation workshops were separately organized for vulnerable pregnant women, husbands of vulnerable pregnant women, and healthcare providers to form homogeneous groups and avoid power dynamics for better flow of information and ideas. A total of eight design teams, each comprising six to eight design team members, went through the design thinking process for three days. A core team that involved senior design staff further synthesized the outputs of the workshops. Insights around limited household support for pregnant women, low awareness on importance of healthcare services, demotivated healthcare providers, and poor service quality were harvested from these workshops.

Development of HCD solutions . In the prototyping phase, our team prioritized potential prototype solutions based on an impact and feasibility matrix. The matrix served as a grading system to narrow down prototype solutions from those that were initially ideated among workshop participants based on the two dimensions. According to participants’ perceived impact (low or high) of solutions on institutional and ANC uptake, along with perceived feasibility level (less or more likely to be implemented) pertaining to resource constraints, three solutions were selected: audio programs that encourage couple communication, visual print materials, and home-to-home visits by community health workers.

The study team developed two pre-recorded audio programs containing real stories of pregnant women in the local language of the target area. The first audio session focuses on the importance of ANC through the narration of a couple's story, highlighting their communication and the husband's support in household tasks, as well as accompanying the wife to ANC visits. The second audio session focuses on the importance of institutional delivery from a story of a pregnant woman. It describes her first childbirth at home, which was a painful and difficult experience. The story then progresses to her second childbirth experience at a health facility, where she was well-prepared and supported by her husband. Furthermore, the solutions included two visual print materials (pamphlets) with contents that reinforced the audio messages about ANC and institutional delivery. These prototypes were tested through focus group discussions with pregnant women, their husbands, and community volunteers, and then refined based on user feedback. All five of the design thinking stages were implemented in the two study sites (Shalla and Siraro) of Oromia regional state.

For Phase 2, we aim to leverage implementation research data obtained from midline qualitative interviews at Phase 1 to finalize our HCD plans. Solutions from Phase 1 will be revisited by a newly organized design team to collectively explore the most effective and feasible implementation strategies. We will conduct the five-stage HCD process, sharing Phase 1 findings with workshop participants and engaging prior end-users. Since Phase 2 will focus on refining and strengthening the existing solutions, some of the HCD activities (e.g., “How Might We” statements and ideation) are expected to center around establishing strategies for improving the materials, delivery, and format of the solutions, ultimately to integrate our solutions into the existing health system.

Implementation plan

As part of the implementation of the interventions in Phase 1, the study team conducted an orientation training for HEWs and HDAs (known as Hadha Gare locally) to equip them with the skills needed to identify vulnerable pregnant women using a vulnerability screening tool and to effectively implement the solutions. The prototype solutions were delivered by the trained HDAs with the help of HEWs for a duration of four months from February to May 2024.

Prior to implementation, HDAs identified vulnerable pregnant women within their catchment area. They then scheduled an appointment to facilitate family discussions about the prototype solutions. The audio programs and print materials were intended to be delivered throughout five home visits by HDAs. For women whose gestational age was high (8-9 months), we aimed to provide audio and print materials on institutional delivery only through three home visits.

In the first visit, HDAs provided the household with an audio device containing the pre-recorded ANC program and gave instructions on how to engage in couple communication. After two to three days, HDAs revisited the household to inquire about questions or concerns from the couple, collected the device, and provided a print material to reinforce the audio content. HDAs then conducted a third visit to gather feedback from the couple and provided the second audio device that contains a story of institutional delivery. At the fourth visit, HDAs collected the second device and provided the second print material to reinforce institutional delivery messages from the audio program. Finally, HDAs conducted the follow-up visit, encouraging the pregnant woman to utilize health services until she delivers and addressing remaining concerns among the couple. All of the home visits required husbands’ presence given that the solutions were designed to facilitate couple communication, which would in turn optimize male involvement in maternal health service potentially through shifting social and gender norms.

To ensure seamless implementation of the interventions, the study team conducted close monitoring of activities that included site review meetings with implementing partners at the primary health care unit (PHCU) level and on-site supportive supervision to identify gaps, provide technical support, and address any identified implementation challenges. Key implementation outcome indicators, such as the number of pregnant women reached with ANC and institutional delivery audio programs and print materials, were regularly collected through the KoboCollect mobile platform.

The Phase 2 implementation plan may follow a similar procedure. Detailed plans will be determined based on information about how the current implementation scheme was acceptable and feasible among health workers and implementing partners. Specifically, the Phase 1 qualitative interview data on implementation research indicators will inform Phase 2 strategies.

Data analysis plan

Quantitative data analysis . First, we will conduct a series of bivariate tests, including chi-square and t-tests, across treatment and control arms based on baseline and endline data. The purpose of conducting bivariate tests is to identify differences between the study arms for each potential confounding factors, given the possibility of quasi-experimental design not ensuring baseline matching between intervention and control arms. If any differences are observed, they will be controlled for in subsequent regression analyses. We will also identify types of missing data to determine whether missingness occurs in a systematic manner, which will help us determine the appropriate remedial measure to adopt.

Since this project will conduct various implementation activities at the PHCU level, the analysis will take account of clustering at the level. Further, because kebeles (akin to villages) are clustered within PHCUs, we will also consider clustering at the kebele level. Given the nested nature of this study, multi-level modeling (MLM) is considered appropriate because it provides both cluster-specific and population-averaged estimates simultaneously by defining both random effects and fixed effects, respectively. Prior studies that represented similar scenarios, however, have shown that estimated coefficients and standard errors are usually not biased, even with a sample size as low as 5 to 10 at Level 1 27 , 28 , and with many independent variables and interaction terms 29 .

Nevertheless, this study will use an MLM framework to assess the intervention effect based on a difference-in-difference analysis by computing differences between baseline and midline within each arm, and then test this difference between intervention and control arms. A fixed effects model will first be used to observe this effect of the intervention. Kebele and PHCU will then be included as random intercepts to account for clustering within these levels. The estimated variance for random effects will show the amount of variability in the outcome that is explained by the clusters (i.e., how much of institutional delivery uptake is attributed to a kebele). If the coefficient of the interaction term is significant with the significant model fit, we will observe significant program effects. The identical analyses will be conducted with 4+ANC visits as the outcome variable. Other covariates will be included by comparing goodness-of-fit statistics (e.g., AIC, BIC) to improve the model fit. Proper model specification and diagnostic tests will be conducted to enhance the robustness of the results. Phase 2 data analysis focus on comparing service utilization between intervention and control arms. Since we expect that study effectiveness will be stronger in Phase 2 with the implementation of enhanced solutions, we will additionally compare the study outcomes with baseline at Phase 1, controlling for potential key covariates including women’s education, parity, financial stability, geographical areas, and distance to health facilities.

Qualitative data analysis

Translated transcripts of the in-depth interviews will be uploaded to a qualitative software package that will be used to facilitate data management and organization. After reading over a few of the interview scripts for each type of stakeholder, two analytical frameworks (one for pregnant women and one for health providers) will be developed using deductive and inductive approaches. The frameworks will describe themes, any sub-themes, codes, and illustrative quotes that would supplement each identified theme/sub-theme. Along with the interview data, field notes from monitoring visits, scheduled 4 times throughout implementation, will additionally reviewed since they can provide rich context for the implementation process itself. Field notes would capture the trajectory of implementation as to how stakeholders engage with the process over time and whether specific implementation strategies would effectively address any challenges arising from the field.

Codes related to implementation research outcomes will be pre-defined, but iterative coding will allow new ideas to emerge. Other themes related to change in social factors are expected to emerge from data and will be identified through a process of open coding. Throughout the coding process, memo writing will be conducted simultaneously. Memo writing refers to systematic and continuous note-making during analysis 30 . While it has been primarily used in grounded theory, it is useful for a wide variety of qualitative methods because it provides researchers with an opportunity to critically reflect on how they view and treat data as well as any changes in decisions made 31 . Iterative coding and memo writing would enable constant comparisons of the data and other reflections over the course of the analysis. Two to three coders will analyze the data to achieve inter-coder reliability. The qualitative data management and analysis will adhere to the Consolidated criteria for reporting qualitative research (COREQ) guideline 32 .

Ethics approval

This study was approved on October 5, 2023 by the Ethiopian Public Health Institute (EPHI), a governmental public health institution located in Addis Ababa, Ethiopia (EPHI-IRB-510-2023). The first phase of the study was also reviewed and approved by the Johns Hopkins Bloomberg School of Public Health Institutional Review Board (IRB00024473) on July 18, 2023, and the approval was extended for Phase 2 on July 16, 2024. In order to conduct HCD processes, we obtained ethical approval for public health practice by the Johns Hopkins Bloomberg School of Public Health Institutional Review Board (IRB00023366) on January 4, 2023. Any changes to study protocol will be communicated with these regulatory entities for approval immediately.

Study dissemination

We will disseminate our work at conferences and peer-reviewed academic journals. We will also share our findings with program stakeholders, including government officials, health workers, and community workers.

Participant consent and confidentiality

All participants will be interviewed at their convenient location to ensure privacy. Informed consent will be obtained in Amharic or Afaan Oromo by local data collectors who are externally hired and trained by the Center for Communication Programs (CCP) Ethiopia study team. Data collectors will read the consent document to participants, who will then give verbal consent. Participants under the age of 19 are required to obtain the permission of one parent or legal guardian. Obtaining verbal consent is considered appropriate given the low level of literacy and education among study participants. The ethics committees from the team’s primary institutions approved administrating verbal consent. All data from participants will be de-identified by the study team and stored in secure, password-protected computers accessible only by the study team and its affiliates.

Discussions

The primary goal of the study is to determine whether, and to what extent, an intervention designed and implemented by adopting human-centered design principles can improve institutional delivery and 4+ ANC visits. While many interventions have been conducted to make an impact on these outcomes, two features of the current work are particularly noteworthy. First, the project adopts HCD principles throughout the life of the intervention, from the initial program design phase all the way to implementation and evaluation. A recent review indicates that most interventions identified as adopting HCD approaches do not do so in a holistic manner, limiting the HCD component predominantly to intervention design (Kang et al., under review). While adopting HCD principles throughout the project is often time consuming, requiring frequent reappraisals and adjustments, this project will provide some indications about the strengths (and limitations) of this approach to inform future projects.

The second innovative aspect of the current project is the extra effort we are expending on reaching women perceived to be most vulnerable. Given the high maternal mortality rate in Ethiopia, one can make the case that most women in the country are, in fact, vulnerable. Nevertheless, we make important distinctions between those who are vulnerable, writ large, and those whose individual, social, cultural, and environmental realities intersect in particularly devastating ways.

The rationale for this approach is our observation that, although maternal health outcomes are steadily improving in Ethiopia, there is a group of women who need support and approaches that are different from those being used to reach the larger majority, and we need interventions specifically tailored for this most-at-risk group. It is this belief that has resulted in a particular design of our study: we only include women whose vulnerability scores are moderate to high. It is likely that this approach requires extra resources, particularly if the most vulnerable women are geographically dispersed from each other and from the health services that they need to access. We suspect, however, that in the long run, these extra resources will turn out to be highly cost-effective, and we hope that dimensions will be designed to assess the cost-effectiveness and cost benefit of this approach.

The HCD solutions we are implementing in this project (e.g., delivering audio devices and supporting print materials) are, indeed, rather labor intensive and involve the adoption and distribution of new hardware. This intensity and the tailored approach, we anticipate, will be impactful among women who are exposed to the intervention. From a scale-up perspective, however, this may appear to be an approach that the government would be reluctant to adopt, given the required training and resources. We note that this approach is not meant to be scaled up for everyone; rather, the idea is that, for women whose life circumstances put them at the highest levels of risk, we need alternative approaches: ones that may be cost intensive but are, nevertheless, cost-effective. We hope to shed light on this tension between intervention intensity and its scale-up potential through the findings and recommendations that will emerge from this study.

Study status

Our study is currently at the post-intervention evaluation stage of Phase 1. We completed the baseline data collection and intervention implementation. The midline (post-intervention) assessment of Phase 1 is ongoing.

Data availability statement

No data are associated with this article.

Extended data

OSF: Enhancing maternal health service utilization among highly vulnerable pregnant women through a human-centered design process: Study protocol for a quasi-experimental study in Oromia, Ethiopia. https://doi.org/10.17605/osf.io/cmnps 33 .

This project contains the following underlying data:

Appendix 1_Screening Tool. Pregnancy and vulnerability screening tool.

Appendix 2_Survey questionnaire. Baseline and midline survey guide.

Appendix 3_Qualitative guide Phase 1_Pregnant women. Qualitative questionnaire for pregnant women.

Appendix 4-6_Qualitative guide Phase 1_Providers. Qualitative questionnaire for health care providers.

Reporting guidelines

OSF: SPIRIT Checklist for “Enhancing maternal health service utilization among highly vulnerable pregnant women through a human-centered design process: Study protocol for a quasi-experimental study in Oromia, Ethiopia.” https://doi.org/10.17605/osf.io/cmnps 33 .

Data are available under the terms of the Creative Commons Zero "No rights reserved" data waiver (CC0 1.0 Public domain dedication).

Acknowledgements

The authors would like to thank Nandita Kapadia-Kundu, Sanjanthi Velu, and Paula Stauffer for contributing to study planning and Biruk Melaku Ayalew and Tewabech Tesfalegn Sheno for facilitating the HCD process and all workshop attendees in Phase 1.

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