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• What Is Qualitative Research? | Methods & Examples

What Is Qualitative Research? | Methods & Examples

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

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

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

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

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

Table of contents

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

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

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

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

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

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

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

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

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

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

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

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

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

• Flexibility

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

• Natural settings

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

• Meaningful insights

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

• Generation of new ideas

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

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

• Unreliability

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

• Subjectivity

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

• Limited generalizability

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

• Labor-intensive

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

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

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

Research bias

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

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

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

There are five common approaches to qualitative research :

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

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

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

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

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

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Tips for a qualitative dissertation

Veronika Williams

17 October 2017

Tips for students

This blog is part of a series for Evidence-Based Health Care MSc students undertaking their dissertations.

Undertaking an MSc dissertation in Evidence-Based Health Care (EBHC) may be your first hands-on experience of doing qualitative research. I chatted to Dr. Veronika Williams, an experienced qualitative researcher, and tutor on the EBHC programme, to find out her top tips for producing a high-quality qualitative EBHC thesis.

1) Make the switch from a quantitative to a qualitative mindset

It’s not just about replacing numbers with words. Doing qualitative research requires you to adopt a different way of seeing and interpreting the world around you. Veronika asks her students to reflect on positivist and interpretivist approaches: If you come from a scientific or medical background, positivism is often the unacknowledged status quo. Be open to considering there are alternative ways to generate and understand knowledge.

2) Reflect on your role

Quantitative research strives to produce “clean” data unbiased by the context in which it was generated.  With qualitative methods, this is neither possible nor desirable.  Students should reflect on how their background and personal views shape the way they collect and analyse their data. This will not only add to the transparency of your work but will also help you interpret your findings.

3)  Don’t forget the theory

Qualitative researchers use theories as a lens through which they understand the world around them. Veronika suggests that students consider the theoretical underpinning to their own research at the earliest stages. You can read an article about why theories are useful in qualitative research  here.

4) Think about depth rather than breadth

Qualitative research is all about developing a deep and insightful understanding of the phenomenon/ concept you are studying. Be realistic about what you can achieve given the time constraints of an MSc.  Veronika suggests that collecting and analysing a smaller dataset well is preferable to producing a superficial, rushed analysis of a larger dataset.

5) Blur the boundaries between data collection, analysis and writing up

Veronika strongly recommends keeping a research diary or using memos to jot down your ideas as your research progresses. Not only do these add to your audit trail, these entries will help contribute to your first draft and the process of moving towards theoretical thinking. Qualitative researchers move back and forward between their dataset and manuscript as their ideas develop. This enriches their understanding and allows emerging theories to be explored.

6) Move beyond the descriptive

When analysing interviews, for example, it can be tempting to think that having coded your transcripts you are nearly there. This is not the case!  You need to move beyond the descriptive codes to conceptual themes and theoretical thinking in order to produce a high-quality thesis.  Veronika warns against falling into the pitfall of thinking writing up is, “Two interviews said this whilst three interviewees said that”.

7) It’s not just about the average experience

When analysing your data, consider the outliers or negative cases, for example, those that found the intervention unacceptable.  Although in the minority, these respondents will often provide more meaningful insight into the phenomenon or concept you are trying to study.

8) Bounce ideas

Veronika recommends sharing your emerging ideas and findings with someone else, maybe with a different background or perspective. This isn’t about getting to the “right answer” rather it offers you the chance to refine your thinking.  Be sure, though, to fully acknowledge their contribution in your thesis.

9) Be selective

In can be a challenge to meet the dissertation word limit.  It won’t be possible to present all the themes generated by your dataset so focus! Use quotes from across your dataset that best encapsulate the themes you are presenting.  Display additional data in the appendix.  For example, Veronika suggests illustrating how you moved from your coding framework to your themes.

10) Don’t panic!

There will be a stage during analysis and write up when it seems undoable.  Unlike quantitative researchers who begin analysis with a clear plan, qualitative research is more of a journey. Everything will fall into place by the end.  Be sure, though, to allow yourself enough time to make sense of the rich data qualitative research generates.

Related course:

Qualitative research methods.

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• Finding the gap
• Developing research questions
• Epistemology
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• Methodology and Methods
• Recruiting participants
• Planning your analysis
• Writing your research proposal
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• Reliability and validity
• Approaches to quantitative research
• Developing a theoretical framework
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Qualitative research

In this section on Qualitative Research  you can find out about:

You might also want to consult our other sections on  Planning your research ,  Quantitative research  and  Writing up research , and check out the Additional resources .

• << Previous: Approaches to quantitative research
• Next: Developing a theoretical framework >>

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How To Write The Results/Findings Chapter

For qualitative studies (dissertations & theses).

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

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

Overview: Qualitative Results Chapter

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

What exactly is the results chapter?

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

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

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

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

What should you include in the results chapter?

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

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

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

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

Need a helping hand?

How do I write the results chapter?

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

Section 1: Introduction

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

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

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

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

Section 2: Body

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

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

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

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

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

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

Section 3: Concluding summary

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

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

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

Tips for writing an A-grade results chapter

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

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

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

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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 ...

22 Comments

This was extremely helpful. Thanks a lot guys

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

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

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

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

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

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

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

this was very useful, Thank you.

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

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

Very useful, well explained. Many thanks.

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

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

Thanks a lot, it is really helpful

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

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

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

Very helpful thank you.

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

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

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

Do I need to include literature/references in my findings chapter?

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• v.84(1); 2020 Jan

A Review of the Quality Indicators of Rigor in Qualitative Research

Jessica l. johnson.

a William Carey University School of Pharmacy, Biloxi, Mississippi

Donna Adkins

Sheila chauvin.

b Louisiana State University, School of Medicine, New Orleans, Louisiana

Attributes of rigor and quality and suggested best practices for qualitative research design as they relate to the steps of designing, conducting, and reporting qualitative research in health professions educational scholarship are presented. A research question must be clear and focused and supported by a strong conceptual framework, both of which contribute to the selection of appropriate research methods that enhance trustworthiness and minimize researcher bias inherent in qualitative methodologies. Qualitative data collection and analyses are often modified through an iterative approach to answering the research question. Researcher reflexivity, essentially a researcher’s insight into their own biases and rationale for decision-making as the study progresses, is critical to rigor. This article reviews common standards of rigor, quality scholarship criteria, and best practices for qualitative research from design through dissemination.

INTRODUCTION

Within the past 20 years, qualitative research in health professions education has increased significantly, both in practice and publication. Today, one can pick up most any issue of a wide variety of health professions education journals and find at least one article that includes some type of qualitative research, whether a full study or the inclusion of a qualitative component within a quantitative or mixed methods study. Simultaneously, there have been recurrent calls for enhancing rigor and quality in qualitative research.

As members of the academic community, we share responsibility for ensuring rigor in qualitative research, whether as researchers who design and implement, manuscript reviewers who critique, colleagues who discuss and learn from each other, or scholarly teachers who draw upon results to enhance and innovate education. Therefore, the purpose of this article is to summarize standards of rigor and suggested best practices for designing, conducting, and reporting high-quality qualitative research. To begin, Denzin and Lincoln’s definition of qualitative research, a long-standing cornerstone in the field, provides a useful foundation for summarizing quality standards and best practices:

Qualitative research involves the studied use and collection of a variety of empirical materials – case study; personal experience; introspection; life story; interview; artifacts; cultural texts and productions; observational, historical, interactional, and visual texts – that describe the routine and problematic moments and meanings in individual lives. Accordingly, qualitative researchers deploy a wide range of interconnected interpretative practices, hoping always to get a better understanding of the subject matter at hand. It is understood, however, that each practice makes the world visible in a different way. Hence there is frequently a commitment to using more than one interpretative practice in any study. 1

In recent years, multiple publications have synthesized quality criteria and recommendations for use by researchers and peer reviewers alike, often in the form of checklists. 2-6 Some authors have raised concerns about the use of such checklists and adherence to strict, universal criteria because they do not afford sufficient flexibility to accommodate the diverse approaches and multiple interpretive practices often represented in qualitative studies. 7-11 They argue that a strict focus on using checklists of specific technical criteria may stifle the diversity and multiplicity of practices that are so much a part of achieving quality and rigor within the qualitative paradigm. As an alternative, some of these authors have published best practice guidelines for use by researchers and peer reviewers to achieve and assess methodological rigor and research quality. 12,13

Some journals within the field of health professions education have also established best practice guidance, as opposed to strict criteria or a checklist, for qualitative research. These have been disseminated as guiding questions or evaluation categories. In 2015, Academic Medicine produced an expanded second edition of a researcher/author manual that includes specific criteria with extensive explanations and examples. 14 Still others have disseminated best practice guidelines through a series of methodological articles within journal publications. 2

In this article, attributes of rigor and quality and suggested best practices are presented as they relate to the steps of designing, conducting, and reporting qualitative research in a step-wise approach.

BEST PRACTICES: STEP-WISE APPROACH

Step 1: identifying a research topic.

Identifying and developing a research topic is comprised of two major tasks: formulating a research question, and developing a conceptual framework to support the study. Formulating a research question is often stimulated by real-life observations, experiences, or events in the researcher’s local setting that reflect a perplexing problem begging for systematic inquiry. The research question begins as a problem statement or set of propositions that describe the relationship among certain concepts, behaviors, or experiences. Agee 15 and others 16,17 note that initial questions are usually too broad in focus and too vague regarding the specific context of the study to be answerable and researchable. Creswell reminds us that initial qualitative research questions guide inquiry, but they often change as the author’s understanding of the issue develops throughout the study. 16 Developing and refining a primary research question focused on both the phenomena of interest and the context in which it is situated is essential to research rigor and quality.

Glassick, Huber, and Maeroff identified six criteria applicable to assessing the quality of scholarship. 18,19 Now commonly referred to as the Glassick Criteria ( Table 1 ), these critical attributes outline the essential elements of any scholarly approach and serve as a general research framework for developing research questions and designing studies. The first two criteria, clear purpose and adequate preparation, are directly related to formulating effective research questions and a strong conceptual framework.

Glassick’s Criteria for Assessing the Quality of Scholarship of a Research Study 18

Generating and refining a qualitative research question requires thorough, systematic, and iterative review of the literature, and the use of those results to establish a clear context and foundation for the question and study design. Using an iterative approach, relevant concepts, principles, theories or models, and prior evidence are identified to establish what is known, and more importantly, what is not known. The iterative process contributes to forming a better research question, the criteria for which can be abbreviated by the acronym FINER, ie, f easible, i nteresting, n ovel, e thical, and r elevant, that is answerable and researchable, in terms of research focus, context specificity, and the availability of time, logistics, and resources to carry out the study. Developing a FINER research question is critical to study rigor and quality and should not be rushed, as all other aspects of research design depend on the focus and clarity of the research question(s) guiding the study. 15 Agee provides clear and worthwhile additional guidance for developing qualitative research questions. 15

Reflexivity, the idea that a researcher’s preconceptions and biases can influence decisions and actions throughout qualitative research activities, is a critical aspect of rigor even at the earliest stages of the study. A researcher’s background, beliefs, and experiences may affect any aspect of the research from choosing which specific question to investigate through determining how to present the results. Therefore, even at this early stage, the potential effect of researcher bias and any ethical considerations should be acknowledged and addressed. That is, how will the question’s influence on study design affect participants’ lives, position the researcher in relationship with others, or require specific methods for addressing potential areas of research bias and ethical considerations?

A conceptual framework is then actively constructed to provide a logical and convincing argument for the research. The framework defines and justifies the research question, the methodology selected to answer that question, and the perspectives from which interpretation of results and conclusions will be made. 5,6,20 Developing a well-integrated conceptual framework is essential to establishing a research topic based upon a thorough and integrated review of relevant literature (addressing Glassick criteria #1 and #2: clear purpose and adequate preparation). Key concepts, principles, assumptions, best practices, and theories are identified, defined, and integrated in ways that clearly demonstrate the problem statement and corresponding research question are answerable, researchable, and important to advancing thinking and practice.

Ringsted, Hodges, and Sherpbier describe three essential parts to an effective conceptual framework: theories and/or concepts and principles relevant to the phenomenon of interest; what is known and unknown from prior work, observations, and examples; and the researcher’s observations, ideas, and suppositions regarding the research problem statement and question. 21 Lingard describes four types of unknowns to pursue during literature review: what no one knows; what is not yet well understood; what controversy or conflicting results, understandings, or perspectives exist; and what are unproven assumptions. 22 In qualitative research, these unknowns are critical to achieving a well-developed conceptual framework and a corresponding rigorous study design.

Recent contributions from Ravitch and colleagues present best practices in developing frameworks for conceptual and methodological coherence within a study design, regardless of the research approach. 23,24 Their recommendations and arguments are highly relevant to qualitative research. Figure 1 reflects the primary components of a conceptual framework adapted from Ravitch and Carl 23 and how all components contribute to decisions regarding research design, implementation, and applications of results to future thinking, study, and practice. Notice that each element of the framework interacts with and influences other elements in a dynamic and interactive process from the beginning to the end of a research project. The intersecting bidirectional arrows represent direct relationships between elements as they relate to specific aspects of a qualitative research study.

Adaptation of Ravitch and Carl’s Components of a Conceptual Framework 23

Maxwell also provides useful guidance for developing an effective conceptual framework specific to the qualitative research paradigm. 17 The 2015 second edition of the Review Criteria for Research Manuscripts 14 and work by Ravitch and colleagues 23,24 provide specific guidance for applying the conceptual framework to each stage of the research process to enhance rigor and quality. Quality criteria for assessing a study’s problem statement, conceptual framework, and research question include the following: introduction builds a logical case and provides context for the problem statement; problem statement is clear and well-articulated; conceptual framework is explicit and justified; research purpose and/or question is clearly stated; and constructs being investigated are clearly identified and presented. 14,24,25 As best practice guidelines, these criteria facilitate quality and rigor while providing sufficient flexibility in how each is achieved and demonstrated.

While a conceptual framework is important to rigor in qualitative research, Huberman and Miles caution qualitative researchers about developing and using a framework to the extent that it influences qualitative design deductively because this would violate the very principles of induction that define the qualitative research paradigm. 25 Our profession’s recent emphasis on a holistic admissions process for pharmacy students provides a reasonable example of inductive and deductive reasoning and their respective applications in qualitative and quantitative research studies. Principles of inductive reasoning are applied when a qualitative research study examines a representative group of competent pharmacy professionals to generate a theory about essential cognitive and affective skills for patient-centered care. Deductive reasoning could then be applied to design a hypothesis-driven prospective study that compares the outcomes of two cohorts of students, one group admitted using traditional criteria and one admitted based on a holistic admissions process revised to value the affective skills of applicants. Essentially, the qualitative researcher must carefully generate a conceptual framework that guides the research question and study design without allowing the conceptual framework to become so rigid as to dictate a testable hypothesis, which is the founding principle of deductive reasoning. 26

Step 2: Qualitative Study Design

The development of a strong conceptual framework facilitates selection of appropriate study methods to minimize the bias inherent in qualitative studies and help readers to trust the research and the researcher (see Glassick criteria #3 in Table 1 ). Although researchers can employ great flexibility in the selection of study methods, inclusion of best practice methods for assuring the rigor and trustworthiness of results is critical to study design. Lincoln and Guba outline four criteria for establishing the overall trustworthiness of qualitative research results: credibility, the researcher ensures and imparts to the reader supporting evidence that the results accurately represent what was studied; transferability, the researcher provides detailed contextual information such that readers can determine whether the results are applicable to their or other situations; dependability, the researcher describes the study process in sufficient detail that the work could be repeated; confirmability, the researcher ensures and communicates to the reader that the results are based on and reflective of the information gathered from the participants and not the interpretations or bias of the researcher. 27

Specific best practice methods used in the sampling and data collection processes to increase the rigor and trustworthiness of qualitative research include: clear rationale for sampling design decisions, determination of data saturation, ethics in research design, member checking, prolonged engagement with and persistent observation of study participants, and triangulation of data sources. 28

Qualitative research is focused on making sense of lived, observed phenomenon in a specific context with specifically selected individuals, rather than attempting to generalize from sample to population. Therefore, sampling design in qualitative research is not random but defined purposively to include the most appropriate participants in the most appropriate context for answering the research question. Qualitative researchers recognize that certain participants are more likely to be “rich” with data or insight than others, and therefore, more relevant and useful in achieving the research purpose and answering the question at hand. The conceptual framework contributes directly to determining sample definitions, size, and recruitment of participants. A typical best practice is purposive sampling methods, and when appropriate, convenience sampling may be justified. 29

Purposive sampling reflects intentional selection of research participants to optimize data sources for answering the research question. For example, the research question may be best answered by persons who have particular experience (critical case sampling) or certain expertise (key informant sampling). Similarly, additional participants may be referred for participation by active participants (snowball sampling) or may be selected to represent either similar or opposing viewpoints (confirming or disconfirming samples). Again, the process of developing and using a strong conceptual framework to guide and justify methodological decisions, in this case defining and establishing the study sample, is critical to rigor and quality. 30 Convenience sampling, using the most accessible research participants, is the least rigorous approach to defining a study sample and may result in low accuracy, poor representativeness, low credibility, and lack of transferability of study results.

Qualitative studies typically reflect designs in which data collection and analysis are done concurrently, with results of ongoing analysis informing continuing data collection. Determination of a final sample size is largely based on having sufficient opportunity to collect relevant data until new information is no longer emerging from data collection, new coding is not feasible, and/or no new themes are emerging; that is, reaching data saturation , a common standard of rigor for data collection in qualitative studies . Thus, accurately predicting a sample size during the planning phases of qualitative research can be challenging. 30 Care should be taken that sufficient quantity (think thick description) and quality (think rich description) of data have been collected prior to concluding that data saturation has been achieved. A poor decision regarding sample size is a direct consequence of sampling strategy and quality of data generated, which leaves the researcher unable to fully answer the research question in sufficient depth. 30

Though data saturation is probably the most common terminology used to describe the achievement of sufficient sample size, it does not apply to all study designs. For example, one could argue that in some approaches to qualitative research, data collection could continue infinitely if the event continues infinitely. In education, we often anecdotally observe variations in the personality and structure of a class of students, and as generations of students continue to evolve with time, so too would the data generated from observing each successive class. In such situations, data saturation might never be achieved. Conversely, the number of participants available for inclusion in a sample may be small and some risk of not reaching data saturation may be unavoidable. Thus, the idea of fully achieving data saturation may be unrealistic when applied to some populations or research questions. In other instances, attrition and factors related to time and resources may contribute to not reaching data saturation within the limits of the study. By being transparent in the process and reporting of results when saturation may not have been possible, the resulting data may still contribute to the field and to further inquiry. Replication of the study using other samples and conducting additional types of follow-up studies are other options for better understanding the research phenomenon at hand. 31

In addition to defining the sample and selecting participants, other considerations related to sampling bias may impact the quantity and quality of data generated and therefore the quality of the study result. These include: methods of recruiting, procedures for informed consent, timing of the interviews in relation to experience or emotion, procedures for ensuring participant anonymity/confidentiality, interview setting, and methods of recording/transcribing the data. Any of these factors could potentially change the nature of the relationship between the researcher and the study participants and influence the trustworthiness of data collected or the study result. Thus, ongoing application of previously mentioned researcher reflexivity is critical to the rigor of the study and quality of sampling. 29,30

Common qualitative data collection methods used in health professions education include interview, direct observation methods, and textual/document analysis. Given the unique and often highly sensitive nature of data being collected by the researcher, trustworthiness is an essential component of the researcher-participant relationship. Ethical conduct refers to how moral principles and values are part of the research process. Participants’ perceptions of ethical conduct are fundamental to a relationship likely to generate high quality data. During each step of the research process, care must be taken to protect the confidentiality of participants and shield them from harm relating to issues of respect and dignity. Researchers must be respectful of the participants’ contributions and quotes, and results must be reported truthfully and honestly. 8

Interview methods range from highly structured to increase dependability or completely open-ended to allow for interviewers to clarify a participant’s response for increased credibility and confirmability. Regardless, interview protocols and structure are often modified or refined, based on concurrent data collection and analysis processes to support or refute preliminary interpretations and refine focus and continuing inquiry. Researcher reflexivity, or acknowledgement of researcher bias, is absolutely critical to the credibility and trustworthiness of data collection and analysis in such study designs. 32

Interviews should be recorded and transcribed verbatim prior to coding and analysis. 28 Member checking, a common standard of rigor, is a practice to increase study credibility and confirmability that involves asking a research subject to verify the transcription of an interview. 1,16,28 The research subject is asked to verify the completeness and accuracy of an interview transcript to ensure the transcript truthfully reflects the meaning and intent of the subject’s contribution.

Prolonged engagement involves the researcher gaining familiarity and understanding of the culture and context surrounding the persons or situations being studied. This strategy supports reflexivity, allowing the researcher to determine how they themselves may be a source of bias during the data collection process by altering the nature of how individuals behave or interact with others in the presence of the researcher. Facial expressions, spoken language, body language, style of dress, age, race, gender, social status, culture, and the researcher’s relationship with the participants may potentially influence either participants’ responses or how the researcher interprets those responses. 33 “Fitting in” by demonstrating an appreciation and understanding of the cultural norms of the population being studied potentially allows the researcher to obtain more open and honest responses from participants. However, if the research participants or topic are too familiar or personal, this may also influence data collection or analysis and interpretation of the results. 33 The possible applications of this section to faculty research with student participants in the context of pharmacy education are obvious, and researcher reflexivity is critical to rigor.

Some researchers using observational methods adopt a strategy of direct field observation, while others play partial or full participant roles in the activity being observed. In both observation scenarios, it is impossible to separate the researcher from the environment, and researcher reflexivity is essential. The pros and cons of observation approach, relative to the research question and study purpose, should be evaluated by the researcher, and the justification for the observational strategy selected should be made clear. 34 Regardless of the researcher’s degree of visibility to the study participants, persistent observation of the targeted sample is critical to the confirmability standard and to achieving data saturation. That is, study conclusions must be clearly grounded in persistent phenomena witnessed during the study, rather than on a fluke event. 28

Researchers acknowledge that observational methodologies are limited by the reality that the researcher carries a bias in determining what is observed, what is recorded, how it is recorded, and how it is transcribed for analysis. A study’s conceptual framework is critical to achieving rigor and quality and provides guidance in developing predetermined notions or plans for what to observe, how to record, and how to minimize the influence of potential bias. 34 Researcher notes should be recorded as soon as possible after the observation event to optimize accuracy. The more detailed and complete the notes, the more accurate and useful they can be in data analysis or in auditing processes for enhancing rigor in the interpretation phase of the study. 34

Triangulation is among the common standards of rigor applied within the qualitative research paradigm. Data triangulation is used to identify convergence of data obtained through multiple data sources and methods (eg, observation field notes and interview transcripts) to avoid or minimize error or bias and optimize accuracy in data collection and analysis processes. 33,35,36

Again, researcher practice in reflexivity throughout research processes is integral to rigor in study design and implementation. Researchers must demonstrate attention to appropriate methods and reflective critique, which are represented in both core elements of the conceptual framework ( Figure 1 ) and Glassick criteria ( Table 1 ). In so doing, the researcher will be well-prepared to justify sampling design and data collection decisions to manuscript reviewers and, ultimately, readers.

Step 3: Data Analysis

In many qualitative studies, data collection runs concurrently with data analysis. Specific standards of rigor are commonly used to ensure trustworthiness and integrity within the data analysis process, including use of computer software, peer review, audit trail, triangulation, and negative case analysis.

Management and analyses of qualitative data from written text, observational field notes, and interview transcriptions may be accomplished using manual methods or the assistance of computer software applications for coding and analysis. When managing very large data sets or complex study designs, computer software can be very helpful to assist researchers in coding, sorting, organizing, and weighting data elements. Software applications can facilitate ease in calculating semi-quantitative descriptive statistics, such as counts of specific events, that can be used as evidence that the researcher’s analysis is based on a representative majority of data collected ( inclusivism ) rather than focusing on selected rarities ( anecdotalism ). Using software to code data can also make it easier to identify deviant cases, detect coding errors, and estimate interrater reliability among multiple coders. 37 While such software helps to manage data, the actual analyses and interpretation still reside with the researcher.

Peer review, another common standard of rigor, is a process by which researchers invite an independent third-party researcher to analyze a detailed audit trail maintained by the study author. The audit trail methodically describes the step-by-step processes and decision-making throughout the study. Review of this audit trail occurs prior to manuscript development and enhances study confirmability. 1,16 The peer reviewer offers a critique of the study methods and validation of the conclusions drawn by the author as a thorough check on researcher bias.

Triangulation also plays a role in data analysis, as the term can also be used to describe how multiple sources of data can be used to confirm or refute interpretation, assertions, themes, and study conclusions. If a theme or theory can be arrived at and validated using multiple sources of data, the result of the study has greater credibility and confirmability. 16,33,36 Should any competing or controversial theories emerge during data collection or analysis, it is vital to the credibility and trustworthiness of the study that the author disclose and explore those negative cases. Negative case analysis refers to actively seeking out and scrutinizing data that do not fit or support the researcher’s interpretation of the data. 16

The use of best practices applying to data collection and data analysis facilitates the full examination of data relative to the study purpose and research question and helps to prevent premature closure of the study. Rather than stopping at the initial identification of literal, first-level assertion statements and themes, authors must progress to interpreting how results relate to, revise, or expand the conceptual framework, or offer an improved theory or model for explaining the study phenomenon of interest. Closing the loop on data collection is critical and is achieved when thorough and valid analysis can be linked back to the conceptual framework, as addressed in the next section.

Step 4: Drawing Valid Conclusions

Lingard and Kennedy 38 succinctly state that the purpose of qualitative research is to deepen one’s understanding of specific perspectives, observations, experiences, or events evidenced through the behaviors or products of individuals and groups as they are situated in specific contexts or circumstances. Conclusions generated from study results should enhance the conceptual framework, or contribute to a new theory or model development, and are most often situated within the discussion and conclusion sections of a manuscript.

The discussion section should include interpretation of the results and recommendations for practice. Interpretations should go beyond first-level results or literal description of observed behaviors, patterns, and themes from analysis. The author’s challenge is to provide a complete and thorough examination and explanation of how specific results relate to each other, contribute to answering the research question, and achieve the primary purpose of the research endeavor. The discussion should “close the loop” by integrating study results and analysis with the original conceptual framework. The discussion section should also provide a parsimonious narrative or graphical explanation and interpretation of study results that enhances understanding of the targeted phenomena.

The conclusion section should provide an overall picture or synopsis of the study, including its important and unique contributions to the field from the perspective of both conceptual and practical significance. The conclusion should also include personal and theoretical perspectives and future directions for research. Together, the discussion and conclusion should include responses to the larger questions of the study’s contributions, such as: So what? Why do these results matter? What next?

The strength of conclusions is dependent upon the extent to which standards of rigor and best practices were demonstrated in design, data collection, data analysis, and interpretation, as described in previous sections of this article. 4,12,17,23,24 Quality and rigor expectations for drawing valid conclusions and generating new theories are reflected in the following essential features of rigor and quality, which include: “Close the loop” to clearly link research questions, study design, data collection and analysis, and interpretation of results. Reflect effective integration of the study results with the conceptual framework and explain results in ways that relate, support, elaborate, and/or challenge conclusions of prior scholarship. Descriptions of new or enhanced frameworks or models are clear and effectively grounded in the study results and conclusions. Practical or theoretical implications are effectively discussed, including guidance for future studies. Limitations and issues of reflexivity and ethics are clearly and explicitly described, including references to actions taken to address these areas. 3,4,12,14

Step 5: Reporting Research Results

Key to quality reporting of qualitative research results are clarity, organization, completeness, accuracy, and conciseness in communicating the results to the reader of the research manuscript. O’Brien and others 4 proposed a standardized framework specifically for reporting qualitative studies known as the Standards for Reporting Qualitative Research (SRQR, Table 2 ). This framework provides detailed explanations of what should be reported in each of 21 sections of a qualitative research manuscript. While the SRQR does not explicitly mention a conceptual framework, the descriptions and table footnote clarification for the introduction and problem statement reflect the essential elements and focus of a conceptual framework. Ultimately, readers of published work determine levels of credibility, trustworthiness, and the like. A manuscript reviewer, the first reader of a study report, has the responsibility and privilege of providing critique and guidance to authors regarding achievement of quality criteria, execution and reporting of standards of rigor, and the extent to which meaningful contributions to thinking and practice in the field are presented. 13,39

An Adaptation of the 21 Elements of O’Brien and Colleagues’ Standards for Reporting Qualitative Research (SRQR) 4

Authors must avoid language heavy with connotations or adjectives that insert the researcher’s opinion into the database or manuscript. 14,40 The researcher should be as neutral and objective as possible in interpreting data and in presenting results. Thick and rich descriptions, where robust descriptive language is used to provide sufficient contextual information, enable the reader to determine credibility, transferability, dependability, and confirmability .

The process of demonstrating the credibility of research is rooted in honest and transparent reporting of how biases and other possible confounders were identified and addressed throughout study processes. Such reporting, first described within the study’s conceptual framework, should be revisited in reporting the work. Confounders may include the researcher’s training and previous experiences, personal connections to the background theory, access to the study population, and funding sources. These elements and processes are best represented in Glassick’s criteria for effective presentation and reflective critique ( Table 1 , criteria 5 and 6). Transferability is communicated, in part, through description of sampling factors such as: geographical location of the study, number and characteristics of participants, and the timeframe of data collection and analysis. 40 Such descriptions also contribute to the credibility of the results and readers’ determination of transfer to their and other contexts. To ensure dependability, the research method must be reported in detail such that the reader can determine proper research practices have been followed and that future researchers can repeat the study. 40 The confirmability of the results is influenced by reducing or at a minimum explaining any researcher influence on the result by applying and meeting standards of rigor such as member checking, triangulation, and peer review. 29,33

In qualitative studies, the researcher is often the primary instrument for data collection. Any researcher biases not adequately addressed or errors in judgement can affect the quality of data and subsequent research results. 33 Thus, due to the creative interpretative and contextually bound nature of qualitative studies, the application of standards of rigor and adherence to systematic processes well-documented in an audit trail are essential. The application of rigor and quality criteria extend beyond the researcher and are also important to effective peer review processes within a study and for scholarly dissemination. The goal of rigor in qualitative research can be described as ensuring that the research design, method, and conclusions are explicit, public, replicable, open to critique, and free of bias. 41 Rigor in the research process and results are achieved when each element of study methodology is systematic and transparent through complete, methodical, and accurate reporting. 33 Beginning the study with a well-developed conceptual framework and active use of both researcher reflexivity and rigorous peer review during study implementation can drive both study rigor and quality.

As the number of published qualitative studies in health professions educational research increases, it is important for our community of health care educators to keep in mind the unique aspects of rigor in qualitative studies presented here. Qualitative researchers should select and apply any of the above referenced study methods and research practices, as appropriate to the research question, to achieve rigor and quality. As in any research paradigm, the goal of quality and rigor in qualitative research is to minimize the risk of bias and maximize the accuracy and credibility of research results. Rigor is best achieved through thoughtful and deliberate planning, diligent and ongoing application of researcher reflexivity, and honest communication between the researcher and the audience regarding the study and its results.

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Data analysis in qualitative research, theertha raj, august 30, 2024.

While numbers tell us "what" and "how much," qualitative data reveals the crucial "why" and "how." But let's face it - turning mountains of text, images, and observations into meaningful insights can be daunting.

This guide dives deep into the art and science of how to analyze qualitative data. We'll explore cutting-edge techniques, free qualitative data analysis software, and strategies to make your analysis more rigorous and insightful. Expect practical, actionable advice on qualitative data analysis methods, whether you're a seasoned researcher looking to refine your skills or a team leader aiming to extract more value from your qualitative data.

What is qualitative data?

Qualitative data is non-numerical information that describes qualities or characteristics. It includes text, images, audio, and video. 

This data type captures complex human experiences, behaviors, and opinions that numbers alone can't express.

A qualitative data example can include interview transcripts, open-ended survey responses, field notes from observations, social media posts and customer reviews

Importance of qualitative data

Qualitative data is vital for several reasons:

• It provides a deep, nuanced understanding of complex phenomena.
• It captures the 'why' behind behaviors and opinions.
• It allows for unexpected discoveries and new research directions.
• It puts people's experiences and perspectives at the forefront.
• It enhances quantitative findings with depth and detail.

What is data analysis in qualitative research?

Data analysis in qualitative research is the process of examining and interpreting non-numerical data to uncover patterns, themes, and insights. It aims to make sense of rich, detailed information gathered through methods like interviews, focus groups, or observations.

This analysis moves beyond simple description. It seeks to understand the underlying meanings, contexts, and relationships within the data. The goal is to create a coherent narrative that answers research questions and generates new knowledge.

How is qualitative data analysis different from quantitative data analysis?

Qualitative and quantitative data analyses differ in several key ways:

• Data type: Qualitative analysis uses non-numerical data (text, images), while quantitative analysis uses numerical data.
• Approach: Qualitative analysis is inductive and exploratory. Quantitative analysis is deductive and confirmatory.
• Sample size: Qualitative studies often use smaller samples. Quantitative studies typically need larger samples for statistical validity.
• Depth vs. breadth: Qualitative analysis provides in-depth insights about a few cases. Quantitative analysis offers broader insights across many cases.
• Subjectivity: Qualitative analysis involves more subjective interpretation. Quantitative analysis aims for objective, statistical measures.

What are the 3 main components of qualitative data analysis?

The three main components of qualitative data analysis are:

• Data reduction: Simplifying and focusing the raw data through coding and categorization.
• Data display: Organizing the reduced data into visual formats like matrices, charts, or networks.
• Conclusion drawing/verification: Interpreting the displayed data and verifying the conclusions.

These components aren't linear steps. Instead, they form an iterative process where researchers move back and forth between them throughout the analysis.

How do you write a qualitative analysis?

Step 1: organize your data.

Start with bringing all your qualitative research data in one place. A repository can be of immense help here. Transcribe interviews , compile field notes, and gather all relevant materials.

Immerse yourself in the data. Read through everything multiple times.

Step 2: Code & identify themes

Identify and label key concepts, themes, or patterns. Group related codes into broader themes or categories. Try to connect themes to tell a coherent story that answers your research questions.

Pick out direct quotes from your data to illustrate key points.

Step 3: Interpret and reflect

Explain what your results mean in the context of your research and existing literature.

Als discuss, identify and try to eliminate potential biases or limitations in your analysis. 

Summarize main insights and their implications.

What are the 5 qualitative data analysis methods?

Thematic Analysis Identifying, analyzing, and reporting patterns (themes) within data.

Content Analysis Systematically categorizing and counting the occurrence of specific elements in text.

Grounded Theory Developing theory from data through iterative coding and analysis.

Discourse Analysis Examining language use and meaning in social contexts.

Narrative Analysis Interpreting stories and personal accounts to understand experiences and meanings.

Each method suits different research goals and data types. Researchers often combine methods for comprehensive analysis.

What are the 4 data collection methods in qualitative research?

When it comes to collecting qualitative data, researchers primarily rely on four methods.

• Interviews : One-on-one conversations to gather in-depth information.
• Focus Groups : Group discussions to explore collective opinions and experiences.
• Observations : Watching and recording behaviors in natural settings.
• Document Analysis : Examining existing texts, images, or artifacts.

Researchers often use multiple methods to gain a comprehensive understanding of their topic.

How is qualitative data analysis measured?

Unlike quantitative data, qualitative data analysis isn't measured in traditional numerical terms. Instead, its quality is evaluated based on several criteria. 

Trustworthiness is key, encompassing the credibility, transferability, dependability, and confirmability of the findings. The rigor of the analysis - the thoroughness and care taken in data collection and analysis - is another crucial factor. 

Transparency in documenting the analysis process and decision-making is essential, as is reflexivity - acknowledging and examining the researcher's own biases and influences. 

Employing techniques like member checking and triangulation all contribute to the strength of qualitative analysis.

Benefits of qualitative data analysis

The benefits of qualitative data analysis are numerous. It uncovers rich, nuanced understanding of complex phenomena and allows for unexpected discoveries and new research directions. 

By capturing the 'why' behind behaviors and opinions, qualitative data analysis methods provide crucial context. 

Qualitative analysis can also lead to new theoretical frameworks or hypotheses and enhances quantitative findings with depth and detail. It's particularly adept at capturing cultural nuances that might be missed in quantitative studies.

Challenges of Qualitative Data Analysis

Researchers face several challenges when conducting qualitative data analysis. 

Managing and making sense of large volumes of rich, complex data can lead to data overload. Maintaining consistent coding across large datasets or between multiple coders can be difficult. 

There's a delicate balance to strike between providing enough context and maintaining focus on analysis. Recognizing and mitigating researcher biases in data interpretation is an ongoing challenge. 

The learning curve for qualitative data analysis software can be steep and time-consuming. Ethical considerations, particularly around protecting participant anonymity while presenting rich, detailed data, require careful navigation. Integrating different types of data from various sources can be complex. Time management is crucial, as researchers must balance the depth of analysis with project timelines and resources. Finally, communicating complex qualitative insights in clear, compelling ways can be challenging.

Best Software to Analyze Qualitative Data

G2 rating: 4.6/5

Pricing: Starts at $30 monthly.

Looppanel is an AI-powered research assistant and repository platform that can make it 5x faster to get to insights, by automating all the manual, tedious parts of your job. 

Here’s how Looppanel’s features can help with qualitative data analysis:

• Automatic Transcription: Quickly turn speech into accurate text; it works across 8 languages and even heavy accents, with over 90% accuracy.
• AI Note-Taking: The research assistant can join you on calls and take notes, as well as automatically sort your notes based on your interview questions.
• Automatic Tagging: Easily tag and organize your data with free AI tools.
• Insight Generation: Create shareable insights that fit right into your other tools.
• Repository Search: Run Google-like searches within your projects and calls to find a data snippet/quote in seconds
• Smart Summary: Ask the AI a question on your research, and it will give you an answer, using extracts from your data as citations.

Looppanel’s focus on automating research tasks makes it perfect for researchers who want to save time and work smarter.

G2 rating: 4.7/5

Pricing: Free version available, with the Plus version costing $20 monthly.

ChatGPT, developed by OpenAI, offers a range of capabilities for qualitative data analysis including:

• Document analysis : It can easily extract and analyze text from various file formats.
• Summarization : GPT can condense lengthy documents into concise summaries.
• Advanced Data Analysis (ADA) : For paid users, Chat-GPT offers quantitative analysis of data documents.
• Sentiment analysis: Although not Chat-GPT’s specialty, it can still perform basic sentiment analysis on text data.

ChatGPT's versatility makes it valuable for researchers who need quick insights from diverse text sources.

How to use ChatGPT for qualitative data analysis

ChatGPT can be a handy sidekick in your qualitative analysis, if you do the following:

• Use it to summarize long documents or transcripts
• Ask it to identify key themes in your data
• Use it for basic sentiment analysis
• Have it generate potential codes based on your research questions
• Use it to brainstorm interpretations of your findings

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Atlas.ti is a powerful platform built for detailed qualitative and mixed-methods research, offering a lot of capabilities for running both quantitative and qualitative research.

It’s key data analysis features include:

• Multi-format Support: Analyze text, PDFs, images, audio, video, and geo data all within one platform.
• AI-Powered Coding: Uses AI to suggest codes and summarize documents.
• Collaboration Tools: Ideal for teams working on complex research projects.
• Data Visualization: Create network views and other visualizations to showcase relationships in your data.

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NVivo is another powerful platform for qualitative and mixed-methods research. It’s analysis features include:

• Data Import and Organization: Easily manage different data types, including text, audio, and video.
• AI-Powered Coding: Speeds up the coding process with machine learning.
• Visualization Tools: Create charts, graphs, and diagrams to represent your findings.
• Collaboration Features: Suitable for team-based research projects.

NVivo combines AI capabilities with traditional qualitative analysis tools, making it versatile for various research needs.

Can Excel do qualitative data analysis?

Excel can be a handy tool for qualitative data analysis, especially if you're just starting out or working on a smaller project. While it's not specialized qualitative data analysis software, you can use it to organize your data, maybe putting different themes in different columns. It's good for basic coding, where you label bits of text with keywords. You can use its filter feature to focus on specific themes. Excel can also create simple charts to visualize your findings. But for bigger or more complex projects, you might want to look into software designed specifically for qualitative data analysis. These tools often have more advanced features that can save you time and help you dig deeper into your data.

How do you show qualitative analysis?

Showing qualitative data analysis is about telling the story of your data. In qualitative data analysis methods, we use quotes from interviews or documents to back up our points. Create charts or mind maps to show how different ideas connect, which is a common practice in data analysis in qualitative research. Group your findings into themes that make sense. Then, write it all up in a way that flows, explaining what you found and why it matters.

What is the best way to analyze qualitative data?

There's no one-size-fits-all approach to how to analyze qualitative data, but there are some tried-and-true steps. 

Start by getting your data in order. Then, read through it a few times to get familiar with it. As you go, start marking important bits with codes - this is a fundamental qualitative data analysis method. Group similar codes into bigger themes. Look for patterns in these themes - how do they connect? 

Finally, think about what it all means in the bigger picture of your research. Remember, it's okay to go back and forth between these steps as you dig deeper into your data. Qualitative data analysis software can be a big help in this process, especially for managing large amounts of data.

In qualitative methods of test analysis, what do test developers do to generate data?

Test developers in qualitative research might sit down with people for in-depth chats or run group discussions, which are key qualitative data analysis methods. They often use surveys with open-ended questions that let people express themselves freely. Sometimes, they'll observe people in their natural environment, taking notes on what they see. They might also dig into existing documents or artifacts that relate to their topic. The goal is to gather rich, detailed information that helps them understand the full picture, which is crucial in data analysis in qualitative research.

Which is not a purpose of reflexivity during qualitative data analysis?

Reflexivity in qualitative data analysis isn't about proving you're completely objective. That's not the goal. Instead, it's about being honest about who you are as a researcher. It's recognizing that your own experiences and views might influence how you see the data. By being upfront about this, you actually make your research more trustworthy. It's also a way to dig deeper into your data, seeing things you might have missed at first glance. This self-awareness is a crucial part of qualitative data analysis methods.

What is a qualitative data analysis example?

A simple example is analyzing customer feedback for a new product. You might collect feedback, read through responses, create codes like "ease of use" or "design," and group similar codes into themes. You'd then identify patterns and support findings with specific quotes. This process helps transform raw feedback into actionable insights.

How to analyze qualitative data from a survey?

First, gather all your responses in one place. Read through them to get a feel for what people are saying. Then, start labeling responses with codes - short descriptions of what each bit is about. This coding process is a fundamental qualitative data analysis method. Group similar codes into bigger themes. Look for patterns in these themes. Are certain ideas coming up a lot? Do different groups of people have different views? Use actual quotes from your survey to back up what you're seeing. Think about how your findings relate to your original research questions. 

Which one is better, NVivo or Atlas.ti?

NVivo is known for being user-friendly and great for team projects. Atlas.ti shines when it comes to visual mapping of concepts and handling geographic data. Both can handle a variety of data types and have powerful tools for qualitative data analysis. The best way to decide is to try out both if you can. 

While these are powerful tools, the core of qualitative data analysis still relies on your analytical skills and understanding of qualitative data analysis methods.

Do I need to use NVivo for qualitative data analysis?

You don't necessarily need NVivo for qualitative data analysis, but it can definitely make your life easier, especially for bigger projects. Think of it like using a power tool versus a hand tool - you can get the job done either way, but the power tool might save you time and effort. For smaller projects or if you're just starting out, you might be fine with simpler tools or even free qualitative data analysis software. But if you're dealing with lots of data, or if you need to collaborate with a team, or if you want to do more complex analysis, then specialized qualitative data analysis software like NVivo can be a big help. It's all about finding the right tool for your specific research needs and the qualitative data analysis methods you're using.

Here’s a guide that can help you decide.

How to use NVivo for qualitative data analysis

First, you import all your data - interviews, documents, videos, whatever you've got. Then you start creating "nodes," which are like folders for different themes or ideas in your data. As you read through your material, you highlight bits that relate to these themes and file them under the right nodes. NVivo lets you easily search through all this organized data, find connections between different themes, and even create visual maps of how everything relates.

How much does NVivo cost?

NVivo's pricing isn't one-size-fits-all. They offer different plans for individuals, teams, and large organizations, but they don't publish their prices openly. Contact the team here for a custom quote.

What are the four steps of qualitative data analysis?

While qualitative data analysis is often iterative, it generally follows these four main steps:

1. Data Collection: Gathering raw data through interviews, observations, or documents.

2. Data Preparation: Organizing and transcribing the collected data.

3. Data Coding: Identifying and labeling important concepts or themes in the data.

4. Interpretation: Drawing meaning from the coded data and developing insights.

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Qualitative Research

What is qualitative research.

Qualitative research is a methodology focused on collecting and analyzing descriptive, non-numerical data to understand complex human behavior, experiences, and social phenomena. This approach utilizes techniques such as interviews, focus groups, and observations to explore the underlying reasons, motivations, and meanings behind actions and decisions. Unlike quantitative research, which focuses on measuring and quantifying data, qualitative research delves into the 'why' and 'how' of human behavior, providing rich, contextual insights that reveal deeper patterns and relationships.

The Basic Idea

Ever heard of the saying “quality over quantity”? Well, some researchers feel the same way!

Imagine you are conducting a study looking at consumer behavior for buying potato chips. You’re interested in seeing which factors influence a customer’s choice between purchasing Doritos and Pringles. While you could conduct quantitative research and measure the number of bags purchased, this data alone wouldn’t explain why consumers choose one chip brand over the other; it would just tell you what they are purchasing. To gather more meaningful data, you may conduct interviews or surveys, asking people about their chip preferences and what draws them to one brand over another. Is it the taste of the chips? The font or color of the bag? This qualitative approach dives deeper to uncover why one potato chip is more popular than the other and can help companies make the adjustments that count.

Qualitative research, as seen in the example above, can provide greater insight into behavior, going beyond numbers to understand people’s experiences, attitudes, and perceptions. It helps us to grasp the meaning behind decisions, rather than just describing them. As human behavior is often difficult to qualify, qualitative research is a useful tool for solving complex problems or as a starting point to generate new ideas for research. Qualitative methods are used across all types of research—from consumer behavior to education, healthcare, behavioral science, and everywhere in between!

At its core, qualitative research is exploratory—rather than coming up with a hypothesis and gathering numerical data to support it, qualitative research begins with open-ended questions. Instead of asking “Which chip brand do consumers buy more frequently?”, qualitative research asks “Why do consumers choose one chip brand over another?”. Common methods to obtain qualitative data include focus groups, unstructured interviews, and surveys. From the data gathered, researchers then can make hypotheses and move on to investigating them. 

It’s important to note that qualitative and quantitative research are not two opposing methods, but rather two halves of a whole. Most of the best studies leverage both kinds of research by collecting objective, quantitative data, and using qualitative research to gain greater insight into what the numbers reveal.

You may have heard the world is made up of atoms and molecules, but it’s really made up of stories. When you sit with an individual that’s been here, you can give quantitative data a qualitative overlay. – William Turner, 16th century British scientist 1

Quantitative Research: A research method that involves collecting and analyzing numerical data to test hypotheses, identify patterns, and predict outcomes.

Exploratory Research: An initial study used to investigate a problem that is not clearly defined, helping to clarify concepts and improve research design.

Positivism: A scientific approach that emphasizes empirical evidence and objectivity, often involving the testing of hypotheses based on observable data. 2 

Phenomenology: A research approach that emphasizes the first-person point of view, placing importance on how people perceive, experience, and interpret the world around them. 3

Social Interaction Theory: A theoretical perspective that people make sense of their social worlds by the exchange of meaning through language and symbols. 4

Critical Theory: A worldview that there is no unitary or objective “truth” about people that can be discovered, as human experience is shaped by social, cultural, and historical contexts that influences reality and society. 5

Empirical research: A method of gaining knowledge through direct observation and experimentation, relying on real-world data to test theories. 

Paradigm shift: A fundamental change in the basic assumptions and methodologies of a scientific discipline, leading to the adoption of a new framework. 2

Interpretive/descriptive approach: A methodology that focuses on understanding the meanings people assign to their experiences, often using qualitative methods.

Unstructured interviews: A free-flowing conversation between researcher and participant without predetermined questions that must be asked to all participants. Instead, the researcher poses questions depending on the flow of the interview. 6

Focus Group: Group interviews where a researcher asks questions to guide a conversation between participants who are encouraged to share their ideas and information, leading to detailed insights and diverse perspectives on a specific topic.

Grounded theory : A qualitative methodology that generates a theory directly from data collected through iterative analysis.

When social sciences started to emerge in the 17th and 18th centuries, researchers wanted to apply the same quantitative approach that was used in the natural sciences. At this time, there was a predominant belief that human behavior could be numerically analyzed to find objective patterns and would be generalizable to similar people and situations. Using scientific means to understand society is known as a positivist approach. However, in the early 20th century, both natural and social scientists started to criticize this traditional view of research as being too reductive. 2  

In his book, The Structure of Scientific Revolutions, American philosopher Thomas Kuhn identified that a major paradigm shift was starting to occur. Earlier methods of science were being questioned and replaced with new ways of approaching research which suggested that true objectivity was not possible when studying human behavior. Rather, the importance of context meant research on one group could not be generalized to all groups. 2 Numbers alone were deemed insufficient for understanding the environment surrounding human behavior which was now seen as a crucial piece of the puzzle. Along with this paradigm shift, Western scholars began to take an interest in ethnography , wanting to understand the customs, practices, and behaviors of other cultures. 

Qualitative research became more prominent throughout the 20th century, expanding beyond anthropology and ethnography to being applied across all forms of research; in science, psychology, marketing—the list goes on. Paul Felix Lazarsfield, Austrian-American sociologist and mathematician often known as the father of qualitative research, popularized new methods such as unstructured interviews and group discussions. 7 During the 1940s, Lazarfield brought attention to the fact that humans are not always rational decision-makers, making them difficult to understand through numerical data alone.

The 1920s saw the invention of symbolic interaction theory, developed by George Herbert Mead. Symbolic interaction theory posits society as the product of shared symbols such as language. People attach meanings to these symbols which impacts the way they understand and communicate with the world around them, helping to create and maintain a society. 4 Critical theory was also developed in the 1920s at the University of Frankfurt Institute for Social Research. Following the challenge of positivism, critical theory is a worldview that there is no unitary or objective “truth” about people that can be discovered, as human experience is shaped by social, cultural, and historical contexts. By shedding light on the human experience, it hopes to highlight the role of power, ideology, and social structures in shaping humans, and using this knowledge to create change. 5

Other formalized theories were proposed during the 20th century, such as grounded theory , where researchers started gathering data to form a hypothesis, rather than the other way around. This represented a stark contrast to positivist approaches that had dominated the 17th and 18th centuries.

The 1950s marked a shift toward a more interpretive and descriptive approach which factored in how people make sense of their subjective reality and attach meaning to it. 2 Researchers began to recognize that the why of human behavior was just as important as the what . Max Weber, a German sociologist, laid the foundation of the interpretive approach through the concept of Verstehen (which in English translates to understanding), emphasizing the importance of interpreting the significance people attach to their behavior. 8 With the shift to an interpretive and descriptive approach came the rise of phenomenology, which emphasizes first-person experiences by studying how individuals perceive, experience, and interpret the world around them. 

Today, in the age of big data, qualitative research has boomed, as advancements in digital tools allow researchers to gather vast amounts of data (both qualitative and quantitative), helping us better understand complex social phenomena. Social media patterns can be analyzed to understand public sentiment, consumer behavior, and cultural trends to grasp how people attach subjective meaning to their reality. There is even an emerging field of digital ethnography which is entirely focused on how humans interact and communicate in virtual environments!

Thomas Kuhn

American philosopher who suggested that science does not evolve through merely an addition of knowledge by compiling new learnings onto existing theories, but instead undergoes paradigm shifts where new theories and methodologies replace old ones. In this way, Kuhn suggested that science is a reflection of a community at a particular point in time. 9

Paul Felix Lazarsfeld

Often referred to as the father of qualitative research, Austrian-American sociologist and mathematician Paul Lazarsfield helped to develop modern empirical methods of conducting research in the social sciences such as surveys, opinion polling, and panel studies. Lazarsfeld was best known for combining qualitative and quantitative research to explore America's voting habits and behaviors related to mass communication, such as newspapers, magazines, and radios. 10  

German sociologist and political economist known for his sociological approach of “Verstehen” which emphasized the need to understand individuals or groups by exploring the meanings that people attach to their decisions. While previously, qualitative researchers in ethnography acted like an outside observer to explain behavior from their point of view, Weber believed that an empathetic understanding of behavior, that explored both intent and context, was crucial to truly understanding behavior. 11  

George Herbert Mead

Widely recognized as the father of symbolic interaction theory, Mead was an American philosopher and sociologist who took an interest in how spoken language and symbols contribute to one’s idea of self, and to society at large. 4

Consequences

Humans are incredibly complex beings, whose behaviors cannot always be reduced to mere numbers and statistics. Qualitative research acknowledges this inherent complexity and can be used to better capture the diversity of human and social realities. 

Qualitative research is also more flexible—it allows researchers to pivot as they uncover new insights. Instead of approaching the study with predetermined hypotheses, oftentimes, researchers let the data speak for itself and are not limited by a set of predefined questions. It can highlight new areas that a researcher hadn’t even thought of exploring. 

By providing a deeper explanation of not only what we do, but why we do it, qualitative research can be used to inform policy-making, educational practices, healthcare approaches, and marketing tactics. For instance, while quantitative research tells us how many people are smokers, qualitative research explores what, exactly, is driving them to smoke in the first place. If the research reveals that it is because they are unaware of the gravity of the consequences, efforts can be made to emphasize the risks, such as by placing warnings on cigarette cartons. 

Finally, qualitative research helps to amplify the voices of marginalized or underrepresented groups. Researchers who embrace a true “Verstehen” mentality resist applying their own worldview to the subjects they study, but instead seek to understand the meaning people attach to their own behaviors. In bringing forward other worldviews, qualitative research can help to shift perceptions and increase awareness of social issues. For example, while quantitative research may show that mental health conditions are more prevalent for a certain group, along with the access they have to mental health resources, qualitative research is able to explain the lived experiences of these individuals and uncover what barriers they are facing to getting help. This qualitative approach can support governments and health organizations to better design mental health services tailored to the communities they exist in.

Controversies

Qualitative research aims to understand an individual’s lived experience, which although provides deeper insights, can make it hard to generalize to a larger population. While someone in a focus group could say they pick Doritos over Pringles because they prefer the packaging, it’s difficult for a researcher to know if this is universally applicable, or just one person’s preference. 12 This challenge makes it difficult to replicate qualitative research because it involves context-specific findings and subjective interpretation. 

Moreover, there can be bias in sample selection when conducting qualitative research. Individuals who put themselves forward to be part of a focus group or interview may hold strong opinions they want to share, making the insights gathered from their answers not necessarily reflective of the general population. 13 People may also give answers that they think researchers are looking for leading to skewed results, which is a common example of the observer expectancy effect . 

However, the bias in this interaction can go both ways. While researchers are encouraged to embrace “Verstehen,” there is a possibility that they project their own views onto their participants. For example, if an American researcher is studying eating habits in China and observes someone burping, they may attribute this behavior to rudeness—when in fact, burping can be a sign that you have enjoyed your meal and it is a compliment to the chef. One way to mitigate this risk is through thick description , noting a great amount of contextual detail in their observations. Another way to minimize the researcher’s bias on their observations is through member checking , returning results to participants to check if they feel they accurately capture their experience.

Another drawback of qualitative research is that it is time-consuming. Focus groups and unstructured interviews take longer and are more difficult to logistically arrange, and the data gathered is harder to analyze as it goes beyond numerical data. While advances in technology alleviate some of these labor-intensive processes, they still require more resources. 

Many of these drawbacks can be mitigated through a mixed-method approach, combining both qualitative and quantitative research. Qualitative research can be a good starting point, giving depth and contextual understanding to a behavior, before turning to quantitative data to see if the results are generalizable. Or, the opposite direction can be used—quantitative research can show us the “what,” identifying patterns and correlations, and researchers can then better understand the “why” behind behavior by leveraging qualitative methods. Triangulation —using multiple datasets, methods, or theories—is another way to help researchers avoid bias. 

Linking Adult Behaviors to Childhood Experiences

In the mid-1980s, an obesity program at the KP San Diego Department of Preventive Medicine had a high dropout rate. What was interesting is that a majority of the dropouts were successfully losing weight, posing the question of why they were leaving the program in the first place. In this instance, greater investigation was required to understand the why behind their behaviors.

Researchers conducted in-depth interviews with almost 200 dropouts, finding that many of them had experienced childhood abuse that had led to obesity. In this unfortunate scenario, obesity was a consequence of another problem, rather than the root problem itself. This led Dr. Vincent J. Felitti, who was working for the department, to launch the Adverse Childhood Experiences (ACE) Study, aimed at exploring how childhood experiences impact adult health status. 

Felitti and the Department of Preventive Medicine studied over 17,000 adults with health plans that revealed a strong relationship between emotional experiences as children and negative health behaviors as adults, such as obesity, smoking, and intravenous drug use. This study demonstrates the importance of qualitative research to uncover correlations that would not be discovered by merely looking at numerical data. 14  

Understanding Voter Turnout

Voting is usually considered an important part of political participation in a democracy. However, voter turnout is an issue in many countries, including the US. While quantitative research can tell us how many people vote, it does not provide insights into why people choose to vote or not.

With this in mind, Dawn Merdelin Johnson, a PhD student in philosophy at Walden University, explored how public corruption has impacted voter turnout in Cook County, Illinois. Johnson conducted semi-structured telephone interviews to understand factors that contribute to low voter turnout and the impact of public corruption on voting behaviors. Johnson found that public corruption leads to voters believing public officials prioritize their own well-being over the good of the people, leading to distrust in candidates and the overall political system, and thus making people less likely to vote. Other themes revealed that to increase voter turnout, voting should be more convenient and supply more information about the candidates to help people make more informed decisions.

From these findings, Johnson suggested that the County could experience greater voter turnout through the development of an anti-corruption agency, improved voter registration and maintenance, and enhanced voting accessibility. These initiatives would boost voting engagement and positively impact democratic participation. 15

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• Versta Research. (n.d.). Bridging the quantitative-qualitative gap . Versta Research. Retrieved August 17, 2024, from https://verstaresearch.com/newsletters/bridging-the-quantitative-qualitative-gap/
• Merriam, S. B., & Tisdell, E. J. (2015). Qualitative research: A guide to design and implementation (4th ed.). Jossey-Bass.
• Smith, D. W. (2018). Phenomenology. In E. N. Zalta (Ed.), Stanford Encyclopedia of Philosophy . Retrieved from https://plato.stanford.edu/entries/phenomenology/#HistVariPhen
• Nickerson, C. (2023, October 16). Symbolic interaction theory . Simply Psychology. https://www.simplypsychology.org/symbolic-interaction-theory.html
• DePoy, E., & Gitlin, L. N. (2016). Introduction to research (5th ed.). Elsevier.
• ATLAS.ti. (n.d.). Unstructured interviews . ATLAS.ti. Retrieved August 17, 2024, from https://atlasti.com/research-hub/unstructured-interviews
• O'Connor, O. (2020, August 14). The history of qualitative research . Medium. https://oliconner.medium.com/the-history-of-qualitative-research-f6e07c58e439
• Sociology Institute. (n.d.). Max Weber: Interpretive sociology & legacy . Sociology Institute. Retrieved August 18, 2024, from https://sociology.institute/introduction-to-sociology/max-weber-interpretive-sociology-legacy
• Kuhn, T. S. (2012). The structure of scientific revolutions (4th ed.). University of Chicago Press.
• Encyclopaedia Britannica. (n.d.). Paul Felix Lazarsfeld . Encyclopaedia Britannica. Retrieved August 17, 2024, from https://www.britannica.com/biography/Paul-Felix-Lazarsfeld
• Nickerson, C. (2019). Verstehen in Sociology: Empathetic Understanding . Simply Psychology. Retrieved August 18, 2024, from: https://www.simplypsychology.org/verstehen.html
• Omniconvert. (2021, October 4). Qualitative research: Definition, methodology, limitations, and examples . Omniconvert. https://www.omniconvert.com/blog/qualitative-research-definition-methodology-limitation-examples/
• Vaughan, T. (2021, August 5). 10 advantages and disadvantages of qualitative research . Poppulo. https://www.poppulo.com/blog/10-advantages-and-disadvantages-of-qualitative-research
• Felitti, V. J. (2002). The relation between adverse childhood experiences and adult health: Turning gold into lead. The Permanente Journal, 6 (1), 44–47. https://www.thepermanentejournal.org/doi/10.7812/TPP/02.994
• Johnson, D. M. (2024). Voters' perception of public corruption and low voter turnout: A qualitative case study of Cook County (Doctoral dissertation). Walden University.

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Speaker 1: In this video, we're going to look at the ever popular qualitative analysis method, thematic analysis. We'll unpack what thematic analysis is, explore its strengths and weaknesses, and explain when and when not to use it. By the end of the video, you'll have a clearer understanding of thematic analysis so that you can approach your research project with confidence. By the way, if you're currently working on a dissertation or thesis or research project, be sure to grab our free dissertation templates to help fast-track your write-up. These tried and tested templates provide a detailed roadmap to guide you through each chapter, section by section. If that sounds helpful, you can find the link in the description down below. So, first things first, what is thematic analysis? Well, as the name suggests, thematic analysis, or TA for short, is a qualitative analysis method focused on identifying patterns, themes, and meanings within a data set. Breaking that down a little, TA involves interpreting language-based data to uncover categories or themes that relate to the research aims and research questions of the study. This data could be taken from interview transcripts, open-ended survey responses, or even social media posts. In other words, thematic analysis can be used on both primary and secondary data. Let's look at an example to make things a little more tangible. Assume you're researching customer sentiment toward a newly launched product line. Using thematic analysis, you could review open-ended survey responses from a sample of consumers looking for similarities, patterns, and categories in the data. These patterns would form a foundation for the development of an initial set of themes. You'd then reduce and synthesize these themes by filtering them through the lens of your specific research aims until you have a small number of key themes that help answer your research questions. By the way, if you're not familiar with the concept of research aims and research questions, be sure to check out our primer video covering that. Link in the description. Now that we've defined what thematic analysis is, let's unpack the different forms that TA can take, specifically inductive and deductive. Your choice of approach will make a big difference to the analysis process, so it's important to understand the difference. Let's take a look at each of them. First up is inductive thematic analysis. This type of TA is completely bottom-up, inductive in terms of approach. In other words, the codes and themes will emerge exclusively from your analysis of the data as you work through it rather than being determined beforehand. This makes it a relatively flexible approach as you can adjust, remove, or add codes and themes as you become more familiar with your data. For example, you could use inductive TA to conduct research on staff experiences of a new office space. In this case, you'd conduct interviews and begin developing codes based on the initial patterns you observe. You could then adjust or change these codes on an iterative basis as you become more familiar with the full data set, following which you develop your themes. By the way, if you're not familiar with the process of qualitative coding, we've got a dedicated video covering that. As always, the link is in the description. Next up, we've got deductive thematic analysis. Contrasted to the inductive option, deductive TA uses predetermined, tightly defined codes. These codes, often referred to as a priori codes, are typically drawn from the study's theoretical framework, as well as empirical research and the researcher's knowledge of the situation. Typically, these codes would be compiled into a codebook where each code would be clearly defined and scoped. As an example, your research might aim to assess constituent opinions regarding local government policy. Applying deductive thematic analysis here would involve developing a list of tightly defined codes in advance based on existing theory and knowledge. Those codes would then be compiled into a codebook and applied to interview data collected from constituents. Importantly, throughout the coding and analysis process, those codes and their descriptions would remain fixed. It's worth mentioning that deductive thematic analysis can be undertaken both individually or by multiple researchers. The latter is referred to as coding reliability TA. As the name suggests, this approach aims to achieve a high level of reliability with regard to the application of codes. By having multiple researchers apply the same set of codes to the same data set, inconsistencies in interpretation can be ironed out and a higher level of reliability can be reached. By the way, qualitative coding is something that we regularly help students with here at Grad Coach, so if you'd like a helping hand with your research project, be sure to check out the link that's down in the description. All right, we've covered quite a lot here. To recap, thematic analysis can be conducted using either an inductive approach where your codes naturally emerge from the data or a deductive approach where your codes are independently or collaboratively developed before analyzing the data. So now that we've unpacked the different types of thematic analysis, it's important to understand the broader strengths and weaknesses of this method so that you know when and when not to use it. One of the main strengths of thematic analysis is the relative simplicity with which you can derive codes and themes and, by extension, conclusions. Whether you take an inductive or a deductive approach, identifying codes and themes can be an easier process with thematic analysis than with some other methods. Discourse analysis, for example, requires both an in-depth analysis of the data and a strong understanding of the context in which that data was collected, demanding a significant time investment. Flexibility is another major strength of thematic analysis. The relatively generic focus on identifying patterns and themes allows TA to be used on a broad range of research topics and data types. Whether you're undertaking a small sociological study with a handful of participants or a large market research project with hundreds of participants, thematic analysis can be equally effective. Given these attributes, thematic analysis is best used in projects where the research aims involve identifying similarities and patterns across a wide range of data. This makes it particularly useful for research topics centered on understanding patterns of meaning expressed in thoughts, beliefs, and opinions. For example, research focused on identifying the thoughts and feelings of an audience in response to a new ad campaign might utilize TA to find patterns in participant responses. All that said, just like any analysis method, thematic analysis has its shortcomings and isn't suitable for every project. First, the inherent flexibility of TA also means that results can at times be kind of vague and imprecise. In other words, the broad applicability of this method means that the patterns and themes you draw from your data can potentially lack the sensitivity to incorporate text and contradiction. Second is the problem of inconsistency and lack of rigor. Put another way, the simplicity of thematic analysis can sometimes mean it's a little too crude for more delicate research aims. Specifically, the focus on identifying patterns and themes can lead to results that lack nuance. For example, even an inductive thematic analysis applied to a sample of just 10 participants might overlook some of the subtle nuances of participant responses in favor of identifying generalized themes. It could also miss fine details in language and expression that might reveal counterintuitive but more accurate implications. All that said, thematic analysis is still a useful method in many cases, but it's important to assess whether it fits your needs. So think carefully about what you're trying to achieve with your research project. In other words, your research aims and research questions. And be sure to explore all the options before choosing an analysis method. If you need some inspiration, we've got a video that unpacks the most popular qualitative analysis methods. Link is in the description. If you're enjoying this video so far, please help us out by hitting that like button. You can also subscribe for loads of plain language actionable advice. If you're new to research, check out our free dissertation writing course, which covers everything you need to get started on your research project. As always, links in the description. Okay, that was a lot. So let's do a quick recap. Thematic analysis is a qualitative analysis method focused on identifying patterns of meaning as themes within data, whether primary or secondary. As we've discussed, there are two overarching types of thematic analysis. Inductive TA, in which the codes emerge from an initial review of the data itself and are revised as you become increasingly familiar with the data. And deductive TA, in which the codes are determined beforehand based on a combination of the theoretical and or conceptual framework, empirical studies, and prior knowledge. As with all things, thematic analysis has its strengths and weaknesses and based on those is generally most appropriate for research focused on identifying patterns in data and drawing conclusions in relation to those. If you liked the video, please hit that like button to help more students find this content. For more videos like this one, check out the Grad Coach channel and make sure you subscribe for plain language, actionable research tips and advice every week. Also, if you're looking for one-on-one support with your dissertation, thesis, or research project, be sure to check out our private coaching service where we hold your hand throughout the research process step by step. You can learn more about that and book a free initial consultation at gradcoach.com.

• Open access
• Published: 02 September 2024

Components of safe nursing care in the intensive care units: a qualitative study

• Mozhdeh Tajari 1 ,
• Tahereh Ashktorab 2 &
• Abbas Ebadi 3  

BMC Nursing volume  23 , Article number:  613 ( 2024 ) Cite this article

Metrics details

Patient safety is a global health issue that affects patients worldwide. Providing safe care in the intensive care units (ICUs) is one of the most crucial tasks for nurses. Numerous factors can impact the capacity of nurses to deliver safe care within ICUs. Consequently, this study was undertaken with the aim of identifying the components of safe nursing care in ICUs.

The current research constitutes a qualitative conventional content analysis study conducted from January 2022 to June 2022. The study participants comprised nurses, intensivists, nurse responsible for patient safety, paramedic, patients, and patients’ family member, totaling 21 individuals selected through purposive sampling. Data collection involved individual, in-depth, and semi-structured interviews. Subsequently, data analysis was performed utilizing the approach outlined by Graneheim and Lundman (Nurse Educ Today 24(2):105–12, 2004), leading to the identification of participants’ perspectives.

Three themes were identified as components of safe nursing care in ICUs. These themes include professional behavior (with categories: Implementation of policies, organizing communication, professional ethics), holistic care (with categories: systematic care, comprehensive care of all systems), and safety-oriented organization (with categories: human resource management and safe environment).

Conclusions

The findings of this study underscore the significance of advocating for safe nursing practices in ICUs by emphasizing professional conduct, holistic care, and safety-focused organizational structures. These results align with existing research, suggesting that by introducing tailored interventions and tactics informed by these elements, a safer environment for nursing care can be established for ICUs patients.

Peer Review reports

One of the most crucial indicatorsof quality care is safety (Atashzadeh Shoorideh et al. [ 1 ]). Safety refers to the prevention of all unintentional or intentional harm, such as injury or death due to adverse medication reactions, patient misidentification, or nosocomial infections by healthcare providers (Butler and Hupp [ 2 ]). Recently defined by the World Health Organization in 2021, patient safety is a framework of organized activities that establish cultures, processes, behaviors, technologies, and environments within healthcare organizations. This framework aims to consistently and effectively identify risks, preventable harm, and reduce the likelihood of their occurrence (Organization [ 3 ]).

Unsafe care has significantly contributed to serious medical accidents worldwide (AL-Mugheed et al. [ 4 ]), and the social cost of patient injuries has been reported to be in the trillions of dollars annually (Organization [ 3 ]). Hospital-acquired serious injuries account for 6% of occupied hospital beds and about 7 million hospital admissions per year (Butler and Hupp [ 2 ]). Evidence shows that patient safety is a global health concern that affects patients worldwide, including both developed and developing countries (Austin et al. [ 5 ]).

Patient safety is even more crucial in intensive care units (ICUs) because they are among the most critical hospital units where nurses play a vital role (Mahmoudi [ 6 ]). In these units, the risk of adverse events is heightened due to factors such as the complexity of the patient’s condition and treatment, the presence of numerous electronic devices and equipment, patients’ lack of awareness, and their reliance on nurses and life-support equipment (Marzban et al. [ 7 ]). Apart from patients, nurses also face unique challenges like high job stress, extended working hours, burnout, dissatisfaction, moral dilemmas, conflicts with patients’ families, and decisions regarding end-of-life care (LeClaire et al. [ 8 ]).

According to a study conducted in Brazil, factors affecting patient safety in relation to nursing staff included the workload of staff, training and professional qualification of staff, teamwork, contractual employment, lack of job security, and destructive behaviors (Oliveira et al. [ 9 ]). In the study by Naderi et al. (Naderi [ 10 ])in Iran, the factors affecting patient safety include human resources status, management and organization, interaction and teamwork, medications, equipment, medical environment, patient-related factors, improving patient quality and safety, importance of documentation, evaluation and monitoring, medical errors, and barriers and challenges (Naderi [ 10 ]). In a study by Lima et al. (D’Lima et al. [ 11 ]), concepts obtained in relation to employee risk perception and patient safety included employee individual factors (sub-theme including pragmatism versus perfectionism), team factors (two sub-themes including team dynamics and interdisciplinary tensions), unit factors (sub-theme including achieving dynamic balance), and organizational factors (sub-theme including risk perception) (D’Lima et al. [ 11 ]). Another study identified factors such as nurse error awareness, nurse well-being, teamwork, non-punitive environment, work management, hospital leadership, and ICU leadership as effective factors for safe ICU care (Garrouste-Orgeas et al. [ 12 ]).

Vaismoradi (Vaismoradi [ 13 ])conducted a grounded theory study in Iran, presenting strategies aimed at enhancing safe care. These strategies encompassed altering attitudes and performance, eliminating organizational obstacles, fostering a culture of teamwork, enhancing the influence of nursing leadership, and cultivating a culture centered on safe nursing care. Furthermore, Vaismoradi emphasized the importance of redefining safe care and conducting guiding research in this domain as highly impactful strategies (Vaismoradi [ 13 ]).

Despite the existing researches in the realm of factors and elements associated with patient safety, a noticeable gap in within high-risk and critical units like ICUs is evident. Through the implementation of more targeted studies, it is possible to pinpoint the components of safe nursing care in ICUs that align with the cultural contexts and healthcare systems of different countries. The outcomes of this research at a micro level of management can serve as valuable resources for the education and training of nursing students and professionals, while at a macro level, they can inform the development and implementation of healthcare policies. Hence, this study was initiated with the aim of identifying the components of safe nursing care in ICUs.

Materials and methods

Study design and setting.

The present study is a conventional content analysis approach, carried out from January 2022 to June 2022. The research was conducted in 8 hospitals affiliated with three medical sciences universities in Tehran, the capital of Iran.

Participants

Through purposive sampling, a total of 21 participants were selected for interviews. The participants included 7 nurses, 2 head nurses, 1 clinical supervisor, 1 nurse responsible for patient safety, 5 intensivists, 2 patients, 1 patient family member (patient’s son), 1 patient safety officer from the Ministry of Health, Treatment, and Medical Education, and 1 paramedic. The initial participant selected for the study was a nurse who met the inclusion criteria, possessed extensive experience, and demonstrated effective communication skills. Subsequent participants were chosen based on the data collected from each participant.

Data collection

In this research, data was gathered through individual, in-depth and semi-structured interviews with individuals who met the specified inclusion criteria. interviews were conducted by the first author and recorded using a mobile device with the participants’ consent.

The inclusion criteria for the healthcare personnel involved having a minimum of two years of professional experience in the ICU or in units associated with patient safety. The selection of the two-year threshold was based on the completion of the mandatory manpower plan course and the acquisition of sufficient experience and knowledge. Patients were included if they had a Glasgow Coma Score (GCS) of 15, demonstrated clear speech abilities, and received approval from the ICU intensivist to participate in the interview.

The researcher took into account the diversity of participants in terms of gender, educational background, job position, and work experience, particularly in relation to the nurses. Data collection persisted until data saturation was achieved, and no new codes emerged. A concluding interview was carried out to confirm data saturation. Field notes were utilized for selecting subsequent samples and extracting the codes. During the initial meeting or telephone conversation, the study’s aims were elucidated to the 21 participants. In a subsequent communication, participants conveyed their decision to either agree or decline participation. Upon agreement, interview schedules were arranged. Notably, only one intensivist declined to participate. All interviews were conducted either at the hospital or the workplace. Prior to interviewing patients, consent was obtained from the intensivist, and schedules were coordinated with the head nurse of ICU to ensure minimal disruption to patient care and treatment processes.

The interviews comprised four parts: initial open questions, main questions, follow-up questions, and closed questions. The formulation of the questions was guided by the interview guide and involved consultation with members of the research team. Subsequently, a pilot interview was carried out to identify any weaknesses, leading to a redesign of the questions (Kallio et al. [ 14 ]) (Table 1 ).

Data analysis

Data analysis was conducted by the research team, which comprised a nursing doctoral student (first author) and two nursing professors (second and third authors). The first author performed the data analysis, whereas the remaining authors reviewed and made revisions to the codes, subcategories, and categories. The analysis procedures were conducted utilizing the conventional content analysis approach, following the guidelines proposed by Graniheim and Lundman (Graneheim and Lundman [ 15 ]).

Preparation phase

During this phase, decontextualization was conducted in the following manner. Initially, the interviews, and field notes were transcribed using Word software and thoroughly reviewed to capture the main idea. Subsequently, the semantic units were identified and coded. It is important to highlight that the participants were assigned names based on the sequence of the interviews to uphold anonymity. For instance, the first participant was designated as number 1, while the final participant was denoted as number 21.

Organizing phase

Through ongoing comparisons of codes and categories and iterative recategorization during the study meetings with the research team members, a total of 1997 codes were initially identified. Subsequently, through a process of reviewing the extracted codes multiple times, eliminating duplicates, and consolidating similar items, the number of codes was ultimately reduced to 1770. Initially, the codes were organized into subcategories, followed by the extraction of categories from the integration of these subcategories. Finally, themes were derived from the integration of categories. Ultimately, a comprehensive definition of the concept under investigation along with its associated structures was provided.

Reporting phase

During this phase, the processes of sampling, data collection, data analysis, and the subsequent results were documented and reported.

Data integrity and robustness

In this study, the trustworthiness of the results was enhanced by considering strategies in line with Lincoln and Guba’s four criteria for qualitative studies (Lincoln and Guba [ 16 ]).

Credibility: The credibility of this study is supported by the extensive experience of the first author in the research topic. She conducted her Master’s thesis on medication errors in critical care units and has accumulated numerous years of experience working in ICU as a nurse and head nurse. The data collection period was appropriately extended to ensure the researcher’s continued involvement in the study process. Participant selection aimed for maximum diversity in age, gender, work experience, and educational level. Data collection methods included in-depth interviews and field notes. The research process was overseen by a doctoral student in nursing with expertise in qualitative research. The interviews and initial coding were reviewed and approved by the participants, with any ambiguities promptly addressed. The complete transcripts of the interviews, along with the coding, were initially forwarded to the primary author. Following the incorporation of the feedback, the revised text was then shared with the secondary author for further input. The process of assigning codes to subcategories, identifying categories, and developing themes was carried out consistently throughout.

Transferability: This criterion pertains to the richness of descriptive data. In an effort to maximize transferability, participants were purposefully selected from various positions and across different ICUs, such as internal medicine, neurology, surgery, and trauma.

Dependability: It was ensured through the utilization of various data collection methods such as interviews and field notes, along with continuous analysis and precise documentation of all analysis stages. As the current research formed part of a doctoral thesis, all research phases, data analyses, and findings were documented in 6-month reports and reviewed by four referees.

Confirmability: To ensure confirmability, the researcher documented their preconceptions about the study subject to separate them and prevent bias. Additionally, during data collection, the researcher refrained from reviewing the findings of related or similar studies.

The Ethical Committee of Tehran Islamic Azad University of Medical Sciences, approved the study protocol (IR.IAU.TMU.REC.1399.481). Written informed consent was obtained from all the participant, and data confidentiality was guaranteed in accordance with rules and regulations, and consistent with the requirements of the Ethical Committee that approved the study. The participants were informed about the possible duration of the interviews, the freedom and authority to stop the interview whenever they felt necessary, how to maintain confidentiality of the information, and how the results of the study would be used.

The mean age of the participants in this study was 41.80 years, while the mean work experience of the health care members was 17. 16 years. The demographic characteristics of the participants are delineated in Table  2 .

The average duration of the interviews was 36.42 min, with a maximum duration of 80 min and a minimum duration of 20 min. A total of 1770 codes were extracted and categorized into 43 subcategories. These subcategories were further integrated to form 7 categories, and from these categories, 3 themes were identified (Table  3 ).

• Professional behavior

Participants in this study viewed Implementation of policies, organizing communication with team members, patients, and their families, and adherence to professional ethics as key components of professional behavior.

Implementation of policies

Implementation of policies was identified by all participants as a critical component of ensuring safe care and was frequently emphasized during the interviews. This encompassed various aspects such as appropriate execution of nursing procedure, Safe mechanical ventilation, Safe Medication Administration, Safe blood transfusion, Safe restraint, Proper care of patient connections, pain control, preventing falls, delirium, and deep vein thrombosis, adhering to infection control protocols, ensuring safe patient transfers, and obtaining informed consent. Given the extensive range of subcategories and the constraints on presenting all the details, we will highlight select quotes from a few of these subcategories.

For instance, with regard to the proper execution of protocols, one of the nurses stated:

“Less experienced nurses use the wrong routines of more experienced nurses and this becomes a habit. It is essential to assess the patient, review the doctor’s orders. In certain circumstances, the patient may have specific requirements, such as altering the dressing or removing a drain.” (Participant No. 8).

The nurse responsible for patient safety commented on the importance of safe blood transfusions.

“For blood transfusion, it is ensured that the nurse carefully matches the specifications of the blood bag with the patient’s wristband. Additionally, two nurses verify the blood bag. Patients are monitored regularly during transfusions to detect any side effects. They are also educated about potential side effects of blood transfusions and instructed on appropriate actions to take if such side effects manifest.” (Participant No. 5).

One of the intensivists commented on the inadequate management of the patient’s pain.

“Some nurses administer only muscle relaxants to patients before invasive procedures, which can be distressing. When patients are unable to move but still feel pain, it is crucial for healthcare providers to understand that muscle relaxants should be administered alongside painkillers. Prioritizing pain management for patients should be the primary concern for healthcare professionals.” (Participant No. 4).

One of the patients admitted to the ICU articulated his perception of infection control compliance in the following manner:

“Some nurses frequently disinfected their hands, although we did not observe this practice. It is possible that I overlooked it as well. Even the doctors engage in this behavior. was a doctor who visited the bed adjacent to mine. He touched various surfaces and then proceeded to examine me.” (Participant No 12).

Organizing communication

Participants highlighted various ways in which communication impacts safe nursing care in the ICU. This resulted in the identification of categories stemming from the integration of subcategories such as shift delivery using the ISBAR technique, proper utilization of identification wristbands, accurate documentation, communication with patients, and Inadequate team communication.

For instance, one of the head nurses described her encounter with the ISBAR technique as follows.

“Sometimes in the evening and night shifts, nurses may not follow protocols and not use the ISBAR technique for shift delivery and the next day we find many errors and failures.” (Participant No. 2).

The nurse responsible for patient safety emphasized the importance of proper utilization of identification wristbands.

“The identification wristband plays a crucial role in healthcare settings. Regrettably, there are instances where individuals overlook its significance. One of the key purposes of the wristband is to accurately identify the patient. An incident occurred where a mismatch between the blood bag and the patient’s bracelet led to an incorrect transfusion being administered.” (Participant No. 5).

In relation to inadequate team communication, an intensivist expressed the following viewpoint:

“When the patient had a fever in the middle of the night, the nurse did not report it. Later I found out that she was afraid of waking me up.” (Participant No. 4).

Professional ethics

Participants identified adherence to the principles of professional ethics as a prerequisite and integral part of safe nursing care. This category was formed from the subcategories of respecting patient privacy, human dignity, conscience and professional commitment.

Regarding respecting patient privacy, one of the ICU patients described her experience as follows:

“The first night, the nurses were gentlemen and they were very careful not to make me feel uncomfortable. The blanket was taken off me and I felt that my body was visible. They came to cover my body without me telling them. Or when he wanted to see the operation site, he would just push the blanket aside so that I wouldn’t be tortured. I don’t think anything made me happier at that moment. That’s what security means. It means that I feel.”  (Participant No. 12).

One of the nurses said the following about human dignity:

“When we are safe in the working environment, we are trained and respected by our superiors, we are guided, we do our work correctly and we also provide safe care. But if you are not respected as a person and your health is not protected, you don’t care about that department and that hospital. You just want to finish your shift and leave”. (Participant No. 11).

One of the intensivists commented on Conscience and work commitment as follows:

“A conscientious patient may express his wishes by sighing and moaning and making noise. Or, for example, report to our manager that we are neglecting him, but patients with a low level of consciousness may be neglected. It is up to us and our conscience to provide complete, accurate and correct care. Sometimes doctors and nurses can show inattention and immorality towards these patients”. (Participant No. 18).

• Holistic care

In addition to professional behavior, the participants mentioned other things to ensure the safe nursing care of ICU patients, which led to the formation of this theme with categories of systematic care and comprehensive care of all systems.

Systematic care

The participants were of the opinion that the implementation of the steps of the nursing process is one of the main conditions for the provision of safe care to patients. This category was formed from the subcategories of initial patient assessment, nursing diagnoses, planning, evaluation of care, continuous care and protection from harm and acquired complications.

The patient safety officer in the Ministry of Health, Treatment and Medical Education commented on the importance of the initial assessment of the patient:

“The initial assessment can lead to the safety of the patient. Whether they have an allergy or not. Whether they are at risk of falling or not. If it is assessed correctly, it can prevent future incidents. and determine the conditions of care. We need to see at what level the patient entered hospital and at what level they should be discharged. The side effects of the medication given to the patient should be reviewed. The nurse should deal with these issues”. (Participant No. 6).

One of the nurses pointed out the importance of care evaluation:

“At the beginning of my career, if the patient was in pain, I would give painkillers and I didn’t care whether the pain was controlled or not. Care evaluation brings reassurance to the patient. It means I go back and see if my care was useful or not”. (Participant No. 1).

One of the nurses with years of experience working in the ICU pointed out the importance of continuity of care:

“In my opinion, less attention is paid to the discussion of continuing care for terminal patients. Most ICU patients, because they are unlikely to return to their lives, often do not receive the necessary care, or it is not provided in a very accurate and safe way. For example, infection control is not followed. Medication administration protocols are not followed, or they may not administer many of the patient's medications. They do not do the gavage on time and say that it has no effect on the treatment. Somehow they let the patient die”. (Participant No. 13).

Comprehensive care of all systems

The participants believed that taking care of all body systems and paying attention to the patient’s body and mind is a guarantee of safe nursing care. This category was formed from the subcategories of respiratory care, digestive and nutritional care, nervous system care, genitourinary care, cardiovascular and haemodynamic care, skin and mucous membrane care, and attention to the mental, psychological and emotional state of the patient.

In terms of respiratory care, one of the expert nurses describes his performance as follows :

“I listen to the patient’s breathing at the very beginning of the shift. I look for the presence of distress in the patient. Whether he has rales or not. The chest is bilateral. And it goes up and down symmetrically. I look at the results of the ABG and even the colour and type of secretions. Because the change in the colour of the secretions can be due to pneumonia”. (Participant No. 7).

One of the head nurses also said about genitourinary care:

“Sometimes when a patient has oliguria, the nurse does not analyse to understand the cause of the oliguria. She quickly gives the patient furosemide. I have seen a lot of inexperienced staff. I tell them about the catheter route first and check the condition of the bladder. Then I check the amount of fluids given and the patient’s CVP. Then check the status of medications and tests. Finally, I report it to the intensivist doctor for a tell order or a I request to visit the patient. Don’t go to the last treatment first”. (Participant No. 2).

One of the patients also mentioned that paying attention to the mental, psychological and emotional state of the patient and their family is an important part of safe care:

“In those first moments I was scared and anxious because the nurse’s words and explanations were very good and calmed me down. After two days of feeling better, I really wanted to see my partner. Seeing my wife was more important to me than anything else. My heart was broken. Everything made me cry. But seeing my wife gave me peace. Even though it was short. I don’t know. Why did some allow it and others didn’t? I don’t know if it’s legal or not, but it seems to be a matter of taste”. (Participant No. 12).

Safety oriented organization

Participants believe that nurses’ efforts to provide safe care to patients depend on a safety focused organization. This content consists of human resource management and safe environment categories.

Human resource management

Employing qualified human resources, monitoring the performance of human resources, error reporting and control, arrangement of human resources, sufficient human resources supply, Providing general and specific training to human resources.

This category was formed from the subcategories of employing qualified human resources, monitoring the performance of human resources, error reporting and control, arrangement of human resources, sufficient human resources supply, Providing general and specific training to human resources..

Regarding the employing qualified human resources, the nurse responsible for patient safety said:

“We have a selection committee that asks questions of the nurses. Once they are accepted, the training starts. Ten hours of important safety and infection control instructions and report writing. We train them and then they go through 70 h of training under the supervision of the ICU supervisor. The supervisor fills in three checklists for each nurse, covering behavioral, general and specialist skills, and sends them to us. If he gets the required number of points, he starts work, otherwise the training has to be repeated”. (Participant No. 5).

The statement of one of the nurses regarding the arrangement of human resources was as follows:

“If I am in charge of the shift, I will divide the work carefully and I will try to arrange it in such a way that it is fair and each nurse has both patient with lots of work and with little work. Not that a nurse should have "two busy patients or two patients with little work”. I try not to give complicated patients to new and inexperienced nurses who cannot manage the patient”. (Participant No. 10).

One of the nurses, related to the sufficient human resources supply, said:

“Nurses’ salaries are paid late, their salaries are not commensurate with their work. There is no justice in the workplace, there is discrimination. There is job dissatisfaction. There is little encouragement and a lot of punishment. All of this prevents safe patient care. Besides, the nurse loses her motivation. That’s why I want to leave.”  (Participant No. 13).

Safe environment

This category was formed from the subcategories of safe equipment and safe structure.

With regard to safe equipment, the patient safety officer in the Ministry of Health, Treatment and Medical Education said:

“To provide safe care, the equipment must be safe. And then we expect safe care from the nurse. If our bed is not safe, how can we expect the nurse to prevent falls? If we have a lack of wavy mattress , how can we expect nurses to prevent pressure sores?”  (Participant No. 6).

Also, the statement of the nurse responsible for patient safety regarding the safe structure was as follows:

“The patient’s safety must be ensured from the moment they arrive at the hospital. From the elevators and the stairs to the door and the wall, etc . In the ICU, the conditions are more specific. In our hospital’s intensive care unit, one of the beds is placed in a corner where the nurse cannot see it. They always put an extra bed in front of this unit. Every time a patient has a CPR code in that unit, it takes a few minutes to remove the extra bed and bring the crash cart into the unit. Exactly, the golden time of CPR is lost”. (Participant No. 5).

The participants in this study have delineated the components of safe nursing care in the ICUs through the aforementioned scenarios. Consequently, drawing from the outcomes of this investigation, safe nursing care can be delineated as follows: Safe nursing care in the ICU is characterized by a holistic care that encompasses systematic and comprehensive care. In delivering such care, nurses exhibit professional behavior by implementation of policies, organizing communication with patients and peers, and upholding professional ethics. In a safety-oriented organization, safe nursing care is evidenced by the establishment of a safe environment and the effective management of human resources.

The present study was conducted with the aim of identifying the components of safe nursing care in the ICUs. Three themes were identified: professional behavior, systematic care, and safety-oriented organization. In this section, the results are compared and discussed with other studies.

The theme of professional behavior emerged by combining the categories implementation of policies, organizing communication, and professional ethics. The participants believe that safe care depends not only on following policies but also on adhering to the principles of professional ethics and organizing communication with all team members and patients.

In term of implementation of policies, Williams et al. concluded that adherence to guidelines can lead to faster diagnosis of sepsis (Williams [ 17 ]), and improves patient safety in medication prescribing (Nouhi et al. [ 18 ]). The results of the study by Santos et al. (Santos [ 19 ]) in Brazil showed that adherence to clinical guidelines leads to better outcomes in patient restraint, positive effect on pain and delirium (Carrothers et al. [ 20 ]; , Thomas et al. [ 21 ]), prevention of falls (Tuma et al. [ 22 ]), and prevention of deep vein thrombosis (Malhotra et al. [ 23 ]). However, it has been argued that adherence to guidelines may jeopardize the autonomy of the nurse, and the nurse may not be able to manage the situation effectively at times not foreseen in the guidelines (Barnard [ 24 ]). For this reason, it seems that, in addition to following the established guidelines, the nurse should have creativity and decision-making power, and be able to identify and prepare for possible out-of-procedure cases for the implementation of each procedure. In the present study, pain control was identified as one of the factors of safe care in the ICU, and most of the participants repeatedly mentioned the pain experience of patients hospitalized in the ICU; in the study conducted in the United States, more than 50% of patients on mechanical ventilation had experienced pain (Fink et al. [ 25 ]). However, in a Norwegian study, only 10% of ICU patients reported pain at rest and 27% reported pain during repositioning (Olsen et al. [ 26 ]). This discrepancy may be due to differences in facilities, equipment, quality of drugs, pain control protocols and nursing methods. It appears that many of the subcategories identified in the professional behavior theme as components of safe care have been introduced and confirmed in other studies. And the results of this study support the previous findings. However, it should be noted that the identification of these components does not necessarily guarantee their implementation, and their implementation requires multilateral planning. For example, despite the importance of safe drug therapy, Ateshzadeh et al. (Atashzadeh Shoorideh et al. [ 1 ])) showed that the level of compliance with drug administration standards was only 2.6% in hospitals under the University of Medical Sciences A in Tehran and 9.4% in hospitals under the University of Medical Sciences B (Atashzadeh Shoorideh et al. [ 1 ]). Regarding infection control, Randa et al. showed that nurses’ performance in hand washing, wearing gowns, gloves and masks was far from the standards (Randa et al. [ 27 ]). Another study found that only 10.83% of nurses avoided incorrect connections (Bayatmanesh et al. [ 28 ]).

The results of this study showed that organizing communication between nurses and other members of the care team is as effective as implementing policies. Haddeland et al. (Haddeland et al. [ 29 ])in Norway demonstrated the importance and need to improve the use of the ISBAR tool to improve patient safety. They concluded that it is essential that healthcare professionals work together to ensure that everyone has the same situational awareness and that good clinical practice is developed and maintained. Correct use of identification wristbands (Barbosa et al. [ 30 ]), accurate recording of all information related to investigations, interventions and their evaluation (Aldawood et al. [ 31 ]), and communication with the patient (Danis [ 32 ])are effective in improving patient safety. The results of the present study are supported by previous studies. In Iran, Abdi et al. (Abdi et al. [ 33 ])concluded that poor communication and lack of team spirit had a negative impact on patient safety (Abdi et al. [ 33 ]). In Saudi Arabia, Al-Dawood et al. (Aldawood et al. [ 31 ])showed that poor team communication was one of the barriers to reducing patient safety in the ICU. Ensuring effective communication is critical to maintaining patient safety and can be achieved by implementing standard communication protocols, providing regular training and education on effective communication, and promoting a culture of collaboration and teamwork (Muller et al. [ 34 ]). Despite the importance of communication to patient safety, the results of evaluations in Iran are disappointing. A review study by Moghadam et al. (Moghadam et al. [ 35 ]), which surveyed Iranian hospitals on the implementation of mandatory patient safety standards, found that the implementation of mandatory standards in the area of ‘interaction with patients and society’ received the lowest score.

According to the results of this research, the principles of professional ethics are necessary to ensure patient safety. The results of studies have shown that things such as respect for privacy (Timmins et al. [ 36 ]), respect for human dignity and worth (Sugarman [ 37 ]; , Smith and Cole [ 38 ]), conscience (Herzer and Pronovost [ 39 ])and professional commitment (Teng et al. [ 40 ]; , Al-Hamdan et al. [ 41 ])are the principles of safe care. The results of the study by Mohammadi et al. (Mohammadi [ 42 ]) in Iran on safe care in ICUs and its relationship with moral courage showed that there is a significant relationship between moral courage and the principles of safe care. In line with previous studies, the present study showed that professional ethics is an important component of safe care in ICUs.

The present study identified holistic care as another effective factor in providing safe care. Holistic care is the systematic and comprehensive care of all systems of the patient’s body. These findings support previous research highlighting the importance of systems thinking and safe care in improving patient safety and overall quality of care (Moazez et al. [ 43 ]). Based on the findings of the study by Wick et al. (Wick et al. [ 44 ]), comprehensive care that addresses the physical, emotional, social and spiritual needs of patients was introduced as a solution to improve outcomes and patient satisfaction. In the study on the design of safe nursing care tools by Rashvand et al. (Rashvand et al. [ 45 ]), attention to the physical needs and attention to the psychological needs of patients were introduced as the main factors of safe nursing care. In addition to the aforementioned studies, the findings of this study are consistent with the holistic and widely used theories in nursing. These include Martha Rogers’ theory, Margaret Newman’s theory and Watson’s theory. A comprehensive review of holistic theories shows that holistic nursing is a two-way human relationship process in which the nurse is attentive, purposeful and alert in the process of caring for the patient as a whole. The result is an improvement in the nurse’s and patient’s sense of wellbeing, quality of care and ultimately patient safety (Yazdi and Talebi [ 46 ]).

In addition to the cases mentioned, the results of this study show the importance of promoting safe care in ICUs through a safety-oriented organizational approach. The creation of a safe environment is also directly related to the safety of the structure and the provision of safe equipment. In line with the present study, Naderi et al. (Naderi [ 10 ])also introduced in their study the state of human resources, management and organization, interaction and teamwork, equipment, environment, and evaluation and monitoring as the main factors affecting patient safety in the hospital (Naderi [ 10 ]). In the study by Lima et al. (D’Lima et al. [ 11 ]), organizational factors were identified as a threat to patient safety. This means that when employees perceive a risk from the organization, they stop providing safe care to patients. In Oliveira et al.’s study (Oliveira et al. [ 9 ]), employee workload, training and professional qualifications, teamwork, contractual employment, lack of job security and disruptive behavior were introduced as factors that interfere with patient safety. In the theoretical model of safe care presented by Vaismoradi (Vaismoradi [ 13 ]) the removal of organizational barriers was identified as one of the strategies to improve patient safety . Thus, based on the results of the present study and other studies, it can be said that healthcare organizations play an important role in patient safety.

Research limitations

One of the limitations of the current study was the absence of theories related to patient safety, which compelled the researchers to resort to the conventional content analysis method.

Another limitation was the lack of specific studies in ICU departments, which made it difficult to compare the present study with similar studies.

In the present study, despite the use of observations and field notes, the primary method of data collection was interviewing the participants. In future studies, incorporating other data collection methods can enhance the depth of the study.

The researcher’s extensive background in working in the intensive care unit as a nurse and head nurse, along with their familiarity with non-safe care practices, posed a risk of introducing bias. To mitigate this bias during the interviews, the researcher endeavored to adopt a listening role and formulate questions in accordance with the interview guide.

A significant portion of the patients admitted to the ICU did not qualify for inclusion in the study as a result of their diminished level of consciousness, reliance on mechanical ventilation, and administration of sedative and hypnotic medications. Identifying suitable participants proved challenging, necessitating extensive consultations and diligent follow-up by the researcher.

Patients exhibited caution in sharing their negative experiences due to concerns about potential repercussions from staff. Building trust to encourage open communication without self-censorship proved to be a lengthy endeavor. In addition, in one particular case, the patient expressed concern about the proximity of her bed to the nursing station, fearing that her conversations would be overheard by the nursing staff. Consequently, in adherence to the patient’s comfort and in consultation with the anesthesiologist, the interview was relocated to a different room to ensure confidentiality and optimal clinical conditions.

Due to the COVID-19 pandemic and the associated restrictions on patient visits, access to the patient’s family was difficult. The researcher had to make several attempts to make appointments for interviews.

The provision of safe care in the ICU is influenced by various components. According to the findings of this study, nurses exhibit professional behavior, such as implementation of policies, organizing communication with team members, patients, and their families, and adherence to professional ethics. They also demonstrate holistic care by following the nursing process and considering the entire system. Conversely, healthcare organizations play a crucial role in ensuring safe care by providing appropriate equipment and maintaining environmental safety. A safety-focused organization can enhance the delivery of safe care to patients in the ICU by offering a secure environment and reliable equipment. This not only ensures patient safety but also boosts staff efficiency, reduces error risks, and ultimately enhances patient outcomes and overall care quality. Healthcare organizations can establish conditions for safe patient care by recruiting suitable staff, monitoring their performance, and addressing their training requirements. Competent nurses, through the provision of comprehensive and systematic care, can deliver safe and high-quality services to patients. It is imperative to emphasize that achieving the desired outcomes necessitates collaborative efforts among healthcare organizations, nurses, and other healthcare professionals.

Availability of data and materials

Due to university policies, the datasets generated and utilized for the present study are not publically accessible but are available from the corresponding author upon justifiable request.

Abbreviations

Intensive Care Unit

Glasgow Coma Score

Identify, Situation, Background, Assessment, Recommendation

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Acknowledgments

The present study is part of the findings of the doctoral thesis, which was completed after obtaining the necessary permissions from Tehran Islamic Azad University of Medical Sciences. The research team would like to thank the staff of this university and all the participants in this research.

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M.T, T.A and A.E contributed in study design. M.T contributed in data collection and wrote the manuscript. T.A, and A.E analyzed the data and revised the manuscript. All of the authors proved the final version of manuscript.

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Tajari, M., Ashktorab, T. & Ebadi, A. Components of safe nursing care in the intensive care units: a qualitative study. BMC Nurs 23 , 613 (2024). https://doi.org/10.1186/s12912-024-02281-5

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Understanding medical students’ transition to and development in clerkship education: a qualitative study using grounded theory

• Hyo Jeong Lee   ORCID: orcid.org/0000-0001-8764-6610 1 ,
• Do-Hwan Kim   ORCID: orcid.org/0000-0003-4137-7130 1 &
• Ye Ji Kang   ORCID: orcid.org/0000-0003-1711-2394 2  

BMC Medical Education volume  24 , Article number:  910 ( 2024 ) Cite this article

Metrics details

Medical students perceive the transition to clerkship education as stressful and challenging and view themselves as novices during their rotation in clerkship education. The developmental perspective is thus important because the transition to clerkship supports rather than hinders growth. Accordingly, this study examines medical students’ transition to clerkship and their developmental features.

In-depth interviews were conducted with 18 medical students or graduates who had completed clerkships as medical students. Based on Straussian grounded theory, the collected data were analyzed in terms of the differences between pre- and post-clerkship education.

Our data analysis revealed five stages of the transition process: “anticipation and anxiety,” “reality check,” “seeking solutions,” “practical application,” and “transition and stability.” The core category, that is, “growing up from being students to being student doctors,” was driven by patients who perceived the participants as student doctors. Meanwhile, the participants recognized that having a solution that is agreed upon by colleagues was more important than knowing the correct answer. The participants undergoing the transition to clerkship showed developmental features divided into three categories: personal, social, and professional. Specifically, they attempted to balance clerkship and life through personal development, learned to navigate around the hospital and reduced tension through social development, and developed clinical competencies focused on efficiency through professional development.

Conclusions

This study explores the process of students’ transition to clerkship education and the developmental features that emerge during this period. The students were motivated by patients who perceived them as student doctors. Through the transition, they maintained a work-life balance and adapted to hospitals but developed an overly doctor-centered attitude by cultivating clinical competencies with a focus on efficiency. To develop them into medical professionals, it is essential to assist their transition and cultivate a patient-centered attitude.

Peer Review reports

The transition to clerkship education marks the first time that medical students will experience the role of being doctors and is an important stage for them to grow into doctors who think and act according to the values of their profession in clinical settings [ 1 , 2 ]. Students who have entered clerkship education move away from the systematic and structured medical school environment to a hospital setting where apprenticeship and experiential learning methods are common and students face a variety of tasks that are markedly different from those in the pre-clinical education period, including communication with patients and their families, cooperation with medical staff, and self-management [ 3 , 4 ]. In other words, the transition to clinical practice education involves understanding the context of the new environment, socializing to meet societal standards, and exerting considerable effort toward adapting to the complex environment [ 5 , 6 ].

The transition to clerkship is known to be a difficult period for medical students as they face stressful and challenging tasks as part of the undergraduate medical curricula [ 7 ]. Many students express concerns that their lack of clinical knowledge and skills could potentially harm patients [ 7 ]. In addition, the increased workload causes physical and mental fatigue, and students experience difficulties in self-management and time management [ 8 ]. Accordingly, universities offer a transition course to help students in their transition from pre-clinical to clinical education. Nevertheless, students struggle to adapt to the culture of medical teams, including interacting with supervisors, professors, residents, and interns; and learning how to work effectively [ 3 , 9 ]. Furthermore, students still perceive the transition as “disruptive” [ 10 ] and a “big leap” that needs to be overcome [ 9 ].

Examining the developmental perspective of the transition to clerkship education is crucial in medical education. The purpose of clerkship education is to provide students with hands-on clinical experience and to facilitate their development into proficient medical professionals. Despite its importance, current research primarily focuses on bridging the gap between pre-clerkship and clerkship education by enhancing students’ preparation while paying little attention to their developmental experiences during this transition [ 11 ]. Consequently, each new rotation often leaves students feeling like novices, impeding their progress and weakening their sense of direction [ 12 ]. This recurring sense of starting over can slow the transition process, potentially hindering overall growth [ 13 ].

Socialization during clerkship plays a crucial role in the formation of professional identities, which has a direct impact on care quality and patient outcomes. Students who develop a strong professional identity are more likely to be confident, communicate well, and understand their roles and responsibilities, which are essential to high-quality patient care [ 14 ]. However, recent studies have focused on students’ experiences in a single specialty without considering the temporal aspect, which limits the generalizability of the findings to students in other specialties [ 9 , 10 ]. Therefore, it is necessary to comprehensively understand the developmental processes across various specialties during the transition to clerkship. This understanding not only enhances the current state of clerkship education but also informs the development of targeted improvement strategies through an evaluation of educational outcomes and achievements.

In summary, the developmental perspective of the transition to clerkship education is vital. By emphasizing the growth experiences of students, we can optimize medical education to foster continuous development and the formation of professional identities during the transition phase, which in turn leads to improved patient care and academic success. Accordingly, our study aims to explore the transition process by evaluating not only medical students’ experience in their transition to clerkship education but also the developmental features they gain through the transition. Our research questions are as follows: First, how do medical students transition into clerkship education? Second, what developmental features do medical students cultivate as they transition to clerkship education?

Study design

This study utilized the Straussian Grounded Theory (Straussian GT) to deeply understand the process of transition to clerkship education for Korean medical students and to consider their development through this process. Straussian GT, developed by Strauss and Corbin, offers structured instructions for coding and analysis that include a literature review, allowing for a comprehensive examination of intricate social phenomena from multiple perspectives [ 15 ]. Unlike the classical GT by Glaser, which emphasizes emergent theory without pre-existing frameworks, the Straussian GT permits a more structured approach and integrates existing theoretical concepts into the analysis [ 16 ]. This methodology is particularly suitable for our study as it facilitates the exploration of the complex clerkship education environment, where students, supervisors, patients, and guardians coexist and interact. To capture the students’ vivid experiences of this education, we conducted semi-structured interviews. The entirety of this study followed COREQ (Consolidated Criteria for Reporting Qualitative Research) guidelines [ 17 ].

Study context

We conducted this study in the context of Korean medical schools. Traditionally, clerkship education in Korea is block clerkship, which lasts two years and begins in the fifth year of medical school. During that time, students work full time in hospitals and participate in clinical practice, notably rotating across specialties such as internal medicine, surgery, pediatrics, and psychiatry, for 2 to 12 weeks. Decisions regarding the order of rotation through various specialties and the grouping with peers are mainly made administratively, giving students minimal control over these decisions.

Data collection and participants

We recruited 18 participants who had at least 3 months of clerkship education as student doctors from two separate universities. We used purposeful sampling to select two knowledgeable and experienced individuals from the early research participants who could provide in-depth answers to the research problems. The initial plan was primarily to target third-year medical students who had recently entered clerkship education to ensure the vividness of their data. However, two pilot interviews revealed that, on average, the transition to clerkship education takes 3 to 6 months. Hence, we shifted to the selection of participants who had received clerkship education in at least two specialties, students in their final year of medical school, and graduates within a year of graduation. Given that numerous environmental influences could impair recall, we chose this one-year time limit to attract graduates with recent experience.

Data collection involved conducting semi-structured interviews to explore the experiences related to the transition to a clerkship in depth. The participants were asked about “expectations and concerns about clerkship education before it begins,” “overall encounters in the early stages of clerkship education,” and “features perceived to contribute to the successful transition to clerkship education.” The grounds for these factors are provided accordingly. The interviews were conducted over a span of two months, specifically between March and April 2023, with each interview lasting 50–90 min. Afterwards, we repeated the selection and recruitment of the next data collection targets using theoretical sampling, based on the theoretical concepts that emerged from the collected data [ 15 ]. We repeatedly performed sampling and analysis until we reached theoretical saturation, indicating the accumulation of appropriate data and the unnecessary need for additional data collection [ 18 ].

Data analysis and trustworthiness

The collected data were analyzed in terms of the transition process and the differences that emerged between pre- and post- clerkship education. The recorded interview file and the researcher’s notes were transcribed using Naver Clova Note. The data were then analyzed by grounded theory using the qualitative research software MAXQDA20 (VERBI GmbH, Berlin, Germany, 2019). All collected data were categorized into concepts that could represent ideas and phenomena through line-by-line analysis. Constant comparative methods were used as the data were collected and analyzed. These methods involve a continuous comparison of the phenomena, concepts, and categories being studied. They also help form theories by elaborating abstract categories through the clarification of similarities and differences and understanding of their relationships. After all the data were collected, each set was synthesized and analyzed within the entire framework.

The following strategies were used to ensure the validity and reliability of the data analysis [ 18 ]. First, while coding, we tried to systematically compare phenomena by comparing them with existing theories and literature. Using this technique, we attempted to grasp the attributes and dimensions that might have been missed in the data analysis process [ 15 ]. Second, expert reviews were conducted. In this study, one researcher with qualitative research experience and another who was familiar with the research subject and had expertise in related fields were asked to review the validity of the data and results. Third, we conducted a member check to enhance the trustworthiness of the study. We provided a summary of the preliminary findings to the participants, asking them to review and provide feedback on the accuracy of their views and experiences. This process ensured that the data analysis accurately reflected the participants’ perspectives, thereby strengthening the credibility and dependability of the results.

Ethics statement

This study was approved by the Institutional Review Board of Hanyang University (HYUIRB-202304-008-1). Before the interview, the participants were presented with a thorough explanation of the research purpose and interview content. They were then requested to sign a “Research Participation Consent Form,” and the interviews proceeded only after obtaining their consent.

We interviewed nine third-year medical students, seven fourth-year medical students, and two interns who were less than a year after graduation. They received clerkship training at two different universities. Table  1 provides their detailed demographic characteristics. According to the statements of the study participants, they went through five steps to become student doctors. Comparing themselves to their earlier selves, they observed significant changes and growth, ultimately reaching a transition where they could assume the role of student doctors. This data analysis divided the study’s results into two distinct parts: (1) the process of transitioning to clerkship education, and (2) the students’ developmental features through the transition.

Part 1. process of transition to clerkship education

The data analysis revealed the core category as “growing up from being students to being student doctors.” It also identified the five stages of the transition to clerkship education: “anticipation and anxiety,” “reality check,” “seeking solutions,” “practical application,” and “transition and stability.”

The first stage was “anticipation and anxiety.” The participants felt both excited and anxious before their clerkship education started. They looked forward to having more leisure time than they did during the pre-clinical period, but they were also nervous about getting to know new people. In particular, they were worried that they might unintentionally harm a patient because of their lack of expertise. Nevertheless, in the field, they expected vivid and rich learning.

The participants then entered the “reality check” stage as their clerkship education began. At this stage, the participants reported perplexing experiences that differed from their expectations. In an unfamiliar medical setting, the participants observed that even the professors could not focus and were puzzled about their position. Furthermore, they regarded themselves as “non-medical personnel” who were comparable to patients. However, actual patients did recognize them as medical staff, and this perception developed the participants’ sense of obligation but became a burden as well. Consequently, the participants understood that they needed qualifications beyond their student status to perform the role of doctors. To achieve these qualifications, they exerted effort to identify the competencies that they lacked.

The participants who identified their competencies entered the “seeking solutions” stage to explore the ways to improve them. The search for improvement measures was divided into the individual and group levels. First, at the individual level, the participants attempted to address a problem by going to the library to look for textbooks or by utilizing a database to find the original text. In addition, they used image training to alleviate their fear when confronted with an operating room or a patient and to raise the degree of preparation for responding flexibly to any situation. The participants progressively recovered their diminished confidence as a result of this approach. Meanwhile, they addressed problems that could not be solved by data search by closely observing the interaction between supervisors and members of the medical team. Furthermore, they attempted to observe and use their colleagues’ performance abilities.

The group level entails looking for someone who can solve a problem when a solution cannot be reached through individual effort. In this case, the participants frequently worked with their colleagues to address problems and would ask interns or residents. In some cases, they would ask for help from their supervisors, but such an approach is extremely rare. Therefore, the accuracy of a solution sought could not be verified easily. Nevertheless, the participants appreciated coming up with a solution that was agreed upon by their colleagues.

After completing the search for improvements, the research participants entered the fourth stage, “practical application,” and applied and practiced the measures sought in the previous phase in actual scenarios. At this stage, the participants reported striving to avoid stuttering when interacting with patients or using a forceful tone to give the impression of being a student doctor with expertise rather than an inexperienced student.

In the final stage, “transition and stability,” the participants repeated the process of identifying and executing improvements as well as developing their identities as student doctors. At this stage, the participants would have successfully transitioned to clerkship education and entered the stable phase.

The speed of the transition to clerkship education differed depending on the participants’ prior clerkship experience and the characteristics of the patients they met. Participants with more opportunities for clerkship and positive patient experiences (i.e., patients being receptive to student involvement) tended to transition more quickly. Conversely, participants with fewer engagement opportunities or negative patient experiences (i.e., patients were reluctant towards student involvement) took longer to transition. One participant described his experience as follows: “The patient I met when I started my internal medicine clerkship must have been upset. When I first spoke to him , I sensed it. I conducted the consultation as instructed by the professor , but the patient rejected me. After that , I was reluctant to conduct consultations. A few weeks later , during the hematologic oncology rotation , the professor’s educational goal was for us to conduct daily patient consultations and provide care like a doctor. I only went once , but this time , the patient was kind and cooperative instead of being difficult. Then I thought , “It’s okay; it’s worth trying.” After that , I consulted with patients more often until they were discharged. (Participant N)” The longer it took to reach the transition, the more they reverted to the second step, “reality check,” in a continuous process of seeking and applying solutions. Through this repetitive process, participants gradually moved beyond the student and established their identity as “student doctors,” a preliminary stage of medical practice.

In summary, the participants reported that their desire to manage the increasing responsibilities and burdens of clinical practice motivated their transition to clerkship education. They repeatedly identified problems and formulated and implemented improvement measures. As a result, they not only transitioned to clerkship education and acclimated to the educational environment, but also grew into student doctors. Figure  1 ; Table  2 present the specific contents and quotes for each step.

The process of transitioning to clerkship education

Part 2. students’ developmental features through transition

The second result pertained to the developmental features of students who have entered the transition and stability stages. These developmental features were divided into three categories: “personal,” “social,” and “professional.” Personal development involved balancing clerkship and life; “social development” included changes in relationships among members and adaptability to the medical environment; and “professional development” featured content on growing up as a student doctor and how to perform the role. They identified themselves in a way that matched their first appearance after being transferred to clerkship. The developmental features of the students who have entered the stable phase through the transition are discussed in the next section. Table  3 summarizes the contents and quotes.

Personal development

Securing personal time.

Securing personal time means that as the participants became accustomed to clerkship education, the time to prepare for clerkship became shorter, and the individual time increased in proportion. Specifically, they reported changes such as shortened time to read the handover or solve tasks such as case reports from 3 days to 3 h. This shortened time generated personal time, which was used for self-development or to completely rest or recharge by meeting friends.

Building resilience

Building resilience means being able to quickly forget the feelings they experienced while participating in clerkships. It was identified as one of the major features that contributed to the participants’ improved quality of life. One participant stated that when she was scolded by a professor, she was depressed all day, even after going home, but she was eventually able to overcome it quickly (Participant A). In a repeated clerkship environment, the participants were able to quickly overcome the distress caused by their mistakes and did not hold on to the negative emotions or shock that arose from situation.

Social development

Bridging the psychological gap with professors.

The participants who recognized that they had reached the transition mentioned that unlike before, the psychological gap between them and their professors had narrowed through clerkship education. To date, pre-clerkship lessons have been conducted in classrooms with more than 100 students. Hence, for the participants, their professors were like “lecturers,” and conversing with them and asking them questions were difficult. However, they acknowledged that the intimate engagement with professors softened their view of the latter. In particular, they began to view their professors not as authoritative and hierarchical creatures or as senior doctors with more knowledge but as humans who had emotions like them.

Adjusting to hospital life

The participants felt accustomed to hospital life as dressing and using hospital facilities became natural for them. They noted that wearing practical clothes such as gowns before their transition felt like borrowing someone else’s clothes, but at their current state, it was no longer awkward. Furthermore, they used to hesitate to go to the ward for water or to use the employees’ restaurant, but at this point, they could use these facilities naturally. One participant stated that he felt completely familiar with the hospital after seeing himself clearly providing directions to patients. Some participants said that hospital life was still awkward but that if it went as described above, they would feel totally adapted to and transition to clerkship education.

• Professional development

Developing a student doctor identity

The participants shifted from being “the same non-medical personnel” to forming relationships with patients as “student doctors” through the transition to clerkship education. Initially, the participants were anxious and hesitant when consulting and examining patients, but over time, they were able to play a role in understanding their patients’ status as student doctors.

Enhancing patient communication skills

One of the features of the transition was enhancing participants’ patient communication skills. Previously, most participants not only wrote and memorized patient consultation scripts but also rushed to ask questions about memorized topics rather than listening to them while interacting with patients. However, with enhanced communication skills, they no longer wrote scripts and were able to make eye contact with patients, talk with them, and freely think of follow-up questions based on patients’ responses. In fact, some participants said that they were indeed fearful during their first time, but through constant practice, their communication with patients became more enjoyable (Participant E).

Improving clinical efficiency

The participants gained clinical reasoning skills, particularly efficiency-oriented clinical abilities related to clinical consultations, as they transitioned to clerkship education. They became acquainted with the reasoning process of listening to symptoms and inferring diseases instead of thinking about likely symptoms based on the disease. They initially acted and responded attentively during physical examinations or consultations, taking into account their patients’ pain or condition. Over time, they learned to focus on conducting consultations swiftly and accurately rather than examining their patients’ emotions.

From a developmental point of view, this study explored how students form their professional identity as student doctors and what developmental characteristics they show through the transition to clerkship education. Based on the results, the transition process and the features that developed can be discussed in two ways.

Process of transition to clerkship

The participants’ transition process revealed significant growth into “student doctors.” This process involved five stages: anticipation and anxiety, reality check, seeking solutions, practical application, and transition and stability. This finding is significant in that it reveals the process by which students establish their professional identity. Previous studies have elucidated the process of adapting to an organization as a newcomer [ 19 ] and have also investigated factors or perceptions that influence this transition process, such as inadequate preparation [ 10 ]. Our research, however, uncovers the detailed stages through which students develop into student doctors via self-discovery and problem-solving.

Central to the transition process was the interaction with patients. The students were motivated by the patient, who recognized himself as a student doctor and attempted to establish an identity as one. For example, one participant reported feeling a great sense of responsibility when he saw the patient struggling emotionally during the initial practice and taking his role seriously. This is an experience-oriented curriculum in which clerkship education takes place through dynamic interactions between members within a systematic structure [ 20 ], and in particular, interactions with patients prove that students are important not only to acquire knowledge, skills, and attitudes based on learning experiences for individual patients in real situations but also to form their identity as doctors [ 21 ].

However, not all patient experiences lead to positive outcomes. Participants who interacted with patients willing to contribute to student education during clerkships were able to transition more quickly due to favorable responses and positive communication. Conversely, participants faced challenges in effectively communicating with patients who were unwilling to participate in student education, resulting in repeated attempts to identify and implement improvement measures that delayed the transition to clerkship education. Moreover, students often experience anxiety in clinical settings, such as patient consultations, due to a lack of clear understanding and readiness for their roles [ 22 ], and this insecurity is further exacerbated by inadequate supervision [ 23 ]. In the current medical environment, where expectations for quality medical services are growing, student participation is likely to face skepticism [ 24 , 25 ]. To prevent students from experiencing severe negative experiences in clerkship, professors should intervene appropriately to ensure patients accommodate students and help form a constructive learning community [ 26 , 27 , 28 ].

Another noteworthy observation is the students’ tendency to solve problems through discussions with colleagues rather than seeking help from professors. They valued having a common, agreed-upon solution as much as knowing the correct answer, and they perceived asking supervisors for help as something to avoid. We can discuss this behavior from a cultural perspective.

In Asian cultures, relationships play a significant role in influencing behavior [ 29 ]. Combined with the hierarchical and closed nature of medical groups, students may fear that making an unfavorable impression on a professor could adversely affect their future [ 30 ]. This hierarchical relationship extends beyond the university into their professional careers, emphasizing the importance of reputation management as perceived through the professor’s eyes [ 31 , 32 ]. As a result, students often felt burdened to maintain a professional appearance and were highly conscious of their evaluator-evaluatee relationship with their professors. Their perception of asking questions as annoying likely stemmed from this hesitation [ 3 , 8 , 33 ]. Consequently, this structure may deter students from interacting directly with professors, leading them to rely more on peer support.

While peer interactions can strengthen their relationships, there is a risk of students acquiring inaccurate information due to their lack of expertise and difficulty in discerning the validity and usefulness of medical evidence [ 34 ]. This can hinder the development of expertise and skills, ultimately impacting their professional identity as physicians [ 19 , 28 ]. Therefore, fostering an environment where students can actively communicate and challenge rigid cultural norms is crucial for effective medical education [ 10 , 35 ].

Students’ developmental features through transition

Students grew up balancing clerkship and life, adapting to the hospital environment, and developing efficient and professional clinical competencies during the transition to clerkship education. These developments improve students’ adaptability, which is an important factor in their effective performance as future healthcare professionals [ 1 , 4 , 11 ]. To date, research has focused on increasing readiness by exploring gaps in pre- and post-clinical practice training [ 10 , 11 ]. However, our work focuses on examining students’ features during the transition to clerkship education and discussing the implications.

First, personal development demonstrates how students constantly strive to balance practice and life during clinical practice. With the recent emphasis on the concept of work-life balance [ 36 ], students recognize clerkship as a kind of work and seek to flexibly cope with stress and improve their quality of life [ 37 ]. They use their leisure time and reduced time spent preparing for clerkship to recharge or meet friends, and they develop resilience to maintain psychological stability. This is crucial because healthcare settings frequently expose not only students but also medical staff to the risk of physical and mental fatigue and burnout [ 7 , 8 , 24 ]. Therefore, practicing self-management, such as time management and flexible coping with stress during the clerkship education, can also greatly benefit professional socialization [ 10 ].

Second, with regard to social development, the participants recognized adaptation to the hospital environment as a crucial factor for the transition to clerkship education. The participants gained confidence as members of the hospital by becoming acquainted with facilities and locations of the hospital. This result differs from those of previous studies that reported the lack of clinical knowledge and skills as the cause of difficult conversion [ 38 , 39 , 40 ]. Until now, the preparatory curriculum for the transition primarily focused on basic clinical skills, communication, physical examination, and other topics related to the national examination, resulting in relatively limited awareness and information about the hospital’s work environment [ 41 ]. It could have made the students feel that clinical practice education was a difficult process [ 9 , 10 ]. However, it is necessary to review the content composition of the transition course, as students require useful and practical tips for clinical practice training, such as detailed job descriptions, in addition to clinical knowledge [ 13 ].

Furthermore, the participants felt the professors were more humane and accessible, although they were still difficult, which reduced the psychological distance between them. This contributed to creating an environment where students can reduce tension in the hospital and move around without being overly conscious of their surroundings. For example, there were many students who were nervous to be polite when meeting professors, but the tension decreased as the psychological distance decreased. This allowed students to move confidently within the hospital, get the necessary information more easily, and adapt faster to the hospital’s facilities and environment.

Finally, students achieved professional development through the cultivation of clinical competencies with a focus on efficiency. Specifically, their professional development mainly consisted of clinical competencies that could be objectively identified. Some participants mentioned that they were able to reflect on the characteristics of a good doctor as perceived by patients, but many others mentioned the reduction in patient consultation time as a key factor in a successful transition. Participants, who initially focused on patients’ emotions such as pain, gradually came to understand symptoms through concise questions. They developed an attitude that was unaffected by patients’ emotions and experienced a sense of bonding with doctors as a result of these changes. The overly skill-centered clerkship education may have led the participants to adopt a doctor-centered attitude instead of a patient-centered one [ 42 , 43 ]. However, patient-centered healthcare is important because it not only contributes to improving patients’ health outcomes, increasing patient satisfaction, and strengthening the trust relationship between patients and their healthcare providers, but also enhances doctor’s the job satisfaction [ 44 ]. Therefore, clerkship education should be improved to cultivate doctors who can not only develop the capacity to objectively identify diseases but also empathize with patients and have a subjective perspective on diseases [ 5 ].

Implications for medical education

Based on the results of this study, we derive several practical implications for improving clerkship education.

Firstly, we suggest implementing a faculty development program that offers guidance on conducting clerkship education. Guiding students through the transition process and sharing their difficulties will help professors reflect on how to manage a clerkship and adopt a learner-centered perspective. These efforts will provide opportunities for students to experience clinical practice in a constructive environment with appropriate supervision.

Second, we propose changing the content of the transition course before students enter clerkship education. Providing practical information about the clerkship, including the hospital’s structure and system, as well as lectures related to medical knowledge or skills, will be helpful for a successful transition [ 9 , 10 ]. Additionally, similar to the faculty development program, including information on what students will experience after entering clerkship education will help reduce their initial confusion and increase their adaptability.

Finally, we suggest creating a clerkship environment that fosters patient-centered attitudes. To achieve this, involving patients as active partners or mentors can be considered. Patients’ active participation in education can enhance students’ understanding of diseases and patient experiences, as well as provide insights into the professional values expected by society from doctors [ 45 , 46 ]. Furthermore, it can be a useful strategy, as involving patients who explicitly agreed to participate in student education can reduce the student’s feelings of rejection and increase the patient’s satisfaction with their treatment [ 26 ].

Limitation and avenues for future research

The limitations of this study and suggestions for future studies are as follows: First, we observed that the participants reached the transition to clerkship education at varying speeds, but we did not analyze the specific causes and types in detail. Therefore, to further understand the factors affecting the transition and the steps involved, we propose a follow-up study to verify the causes and types by conducting additional interviews. Second, this study limited its scope to experiences in block-type clinical practice and did not investigate students’ experiences in longitudinal integrated clerkship or mixed clerkship education. Longitudinal integrated clerkship provides a unique learning environment in which students develop clinical competencies by establishing a longitudinal relationship with patients; therefore, block-type clinical practice and conversion experiences may differ [ 47 ]. Accordingly, examining students’ conversion experiences in various clinical practice education models can contribute significantly to improving the overall clerkship education. Nevertheless, this study is significant because it presents the process of students’ transition to clerkship education as well as the meaning of the features that develop through this transition.

This study explores the process of students’ transition to clerkship education and the developmental features that emerge during this period. The students, motivated by patients who perceive them as student doctors, navigate through this transition by repeatedly identifying their problems and implementing improvement plans. Throughout this process, they balance their personal lives with clinical work, adapt to the hospital environment, and develop efficient and professional clinical competencies. These developments improve their adaptability and readiness for future healthcare roles.

Data availability

The datasets of this article are available from the corresponding author on reasonable request.

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Conceptualization: Lee HJ. Data curation: Lee HJ. Formal analysis: Lee HJ, Kang YJ, and Kim DH. Investigation: Lee HJ, Kang YJ, and Kim DH. Methodology: Lee HJ, Kang YJ, Kim DH. Software: Lee HJ. Validation: Lee HJ, Kang YJ, and Kim DH. Writing - original draft: Lee HJ. Writing - review & editing: Lee HJ, Kang YJ, and Kim DH.

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Lee, H.J., Kim, DH. & Kang, Y.J. Understanding medical students’ transition to and development in clerkship education: a qualitative study using grounded theory. BMC Med Educ 24 , 910 (2024). https://doi.org/10.1186/s12909-024-05778-4

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DOI : https://doi.org/10.1186/s12909-024-05778-4

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BMC Medical Education

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