what is qualitative research according to creswell 2013

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Qualitative Descriptive Methods in Health Science Research

Karen jiggins colorafi.

1 College of Nursing & Health Innovation, Arizona State University, Phoenix, AZ, USA

Bronwynne Evans

The purpose of this methodology paper is to describe an approach to qualitative design known as qualitative descriptive that is well suited to junior health sciences researchers because it can be used with a variety of theoretical approaches, sampling techniques, and data collection strategies.

Background:

It is often difficult for junior qualitative researchers to pull together the tools and resources they need to embark on a high-quality qualitative research study and to manage the volumes of data they collect during qualitative studies. This paper seeks to pull together much needed resources and provide an overview of methods.

A step-by-step guide to planning a qualitative descriptive study and analyzing the data is provided, utilizing exemplars from the authors’ research.

This paper presents steps to conducting a qualitative descriptive study under the following headings: describing the qualitative descriptive approach, designing a qualitative descriptive study, steps to data analysis, and ensuring rigor of findings.

Conclusions:

The qualitative descriptive approach results in a summary in everyday, factual language that facilitates understanding of a selected phenomenon across disciplines of health science researchers.

There is an explosion in qualitative methodologies among health science researchers because social problems lend themselves toward thoughtful exploration, such as when issues of interest are complex, have variables or concepts that are not easily measured, or involve listening to populations who have traditionally been silenced ( Creswell, 2013 ). Creswell (2013 , p. 48) suggests qualitative research is preferred when health science researchers seek to (a) share individual stories, (b) write in a literary, flexible style, (c) understand the context or setting of issues, (d) explain mechanisms or linkages in causal theories, (e) develop theories, and (f) when traditional quantitative statistical analyses do not fit the problem at hand. Typically, qualitative textbooks present learners with five approaches for qualitative inquiry: narrative, phenomenological, grounded theory, case study, and ethnography. Yet eminent researcher Margarete Sandelowski argues that in “the now vast qualitative methods literature, there is no comprehensive description of qualitative description as a distinctive method of equal standing with other qualitative methods, although it is one of the most frequently employed methodological approaches in the practice disciplines” ( Sandelowski, 2000 ). Qualitative description is especially amenable to health environments research because it provides factual responses to questions about how people feel about a particular space, what reasons they have for using features of the space, who is using particular services or functions of a space, and the factors that facilitate or hinder use.

The purpose of this methodology article is to define and outline qualitative description for health science researchers, providing a starter guide containing important primary sources for those who wish to become better acquainted with this methodological approach.

Describing the Qualitative Descriptive Approach

In two seminal articles, Sandelowski promotes the mainstream use of qualitative description ( Sandelowski, 2000 , 2010 ) as a well-developed but unacknowledged method which provides a “comprehensive summary of an event in the every day terms of those events” ( Sandelowski, 2000 , p. 336). Such studies are characterized by lower levels of interpretation than are high-inference qualitative approaches such as phenomenology or grounded theory and require a less “conceptual or otherwise highly abstract rendering of data” ( Sandelowski, 2000 , p. 335). Researchers using qualitative description “stay closer to their data and to the surface of words and events” ( Sandelowski, 2000 , p. 336) than many other methodological approaches. Qualitative descriptive studies focus on low-inference description, which increases the likelihood of agreement among multiple researchers. The difference between high and low inference approaches is not one of rigor but refers to the amount of logical reasoning required to move from a data-based premise to a conclusion. Researchers who use qualitative description may choose to use the lens of an associated interpretive theory or conceptual framework to guide their studies, but they are prepared to alter that framework as necessary during the course of the study ( Sandelowski, 2010 ). These theories and frameworks serve as conceptual hooks upon which hang study procedures, analysis, and re-presentation. Findings are presented in straightforward language that clearly describes the phenomena of interest.

Other cardinal features of the qualitative descriptive approach include (a) a broad range of choices for theoretical or philosophical orientations, (b) the use of virtually any purposive sampling technique (e.g., maximum variation, homogenous, typical case, criterion), (c) the use of observations, document review, or minimally to moderately structured interview or focus group questions, (d) content analysis and descriptive statistical analysis as data analysis techniques, and (e) the provision of a descriptive summary of the informational contents of the data organized in a way that best fits the data ( Neergaard, Olesen, Andersen, & Sondergaard, 2009 ; Sandelowski, 2000 , 2001 , 2010 ).

Designing a Qualitative Descriptive Study

Methodology.

Unlike traditional qualitative methodologies such as grounded theory, which are built upon a particular, prescribed constellation of procedures and techniques, qualitative description is grounded in the general principles of naturalistic inquiry. Lincoln and Guba suggest that naturalistic inquiry deals with the concept of truth, whereby truth is “a systematic set of beliefs, together with their accompanying methods” ( Lincoln & Guba, 1985 , p. 16). Using an often eclectic compilation of sampling, data collection, and data analysis techniques, the researcher studies something in its natural state and does not attempt to manipulate or interfere with the ordinary unfolding of events. Taken together, these practices lead to “true understanding” or “ultimate truth.” Table 1 describes design elements in two exemplar qualitative descriptive studies and serves as guide to the following discussion.

Example of Study Design Elements for Two Studies.

Theoretical Framework

Theoretical frameworks serve as organizing structures for research design: sampling, data collection, analysis, and interpretation, including coding schemes, and formatting hypothesis for further testing ( Evans, Coon, & Ume, 2011 ; Miles, Huberman, & Saldana, 2014 ; Sandelowski, 2010 ). Such frameworks affect the way in which data are ultimately viewed; qualitative description supports and allows for the use of virtually any theory ( Sandelowski, 2010 ). Creswell’s chapter on “Philosophical Assumptions and Interpretative Frameworks” (2013) is a useful place to gain understanding about how to embed a theory into a study.

Sampling choices place a boundary around the conclusions you can draw from your qualitative study and influence the confidence you and others place in them ( Miles et al., 2014 ). A hallmark of the qualitative descriptive approach is the acceptability of virtually any sampling technique (e.g., maximum variation where you aim to collect as many different cases as possible or homogenous whereby participants are mostly the same). See Miles, Huberman, and Saldana’s (2014 , p. 30) “Bounding the Collection of Data” discussion to select an appropriate and congruent purposive sampling strategy for your qualitative study.

Data Collection

In qualitative descriptive studies, data collection attempts to discover “the who, what and where of events” or experiences ( Sandelowski, 2000 , p.339). This includes, but is not limited to focus groups, individual interviews, observation, and the examination of documents or artifacts.

Data Analysis

Content analysis refers to a technique commonly used in qualitative research to analyze words or phrases in text documents. Hsieh and Shannon (2005) present three types of content analysis, any of which could be used in a qualitative descriptive study. Conventional content analysis is used in studies that aim to describe a phenomenon where exiting research and theory are limited. Data are collected from open-ended questions, read word for word, and then coded. Notes are made and codes are categorized. Directed content analysis is used in studies where existing theory or research exists: it can be used to further describe phenomena that are incomplete or would benefit from further description. Initial codes are created from theory or research and applied to data and unlabeled portions of text are given new codes. Summative content analysis is used to quantify and interpret words in context, exploring their usage. Data sources are typically seminal texts or electronic word searches.

Quantitative data can be included in qualitative descriptive studies if they aim to more adequately or fully describe the participants or phenomenon of interest. Counting is conceptualized as a “means to and end, not the end itself” by Sandelowski (2000 , p. 338) who emphasizes that careful descriptive statistical analysis is an effort to understand the content of data, not simply the means and frequencies, and results in a highly nuanced description of the patterns or regularities of the phenomenon of interest ( Sandelowski, 2000 , 2010 ). The use of validated measures can assist with generating dependable and meaningful findings, especially when the instrument (e.g., survey, questionnaire, or list of questions) used in your study has been used in others, helping to build theory, improve predictions, or make recommendations ( Miles et al., 2014 ).

Data Re-Presentation

In clear and simple terms, the “expected outcome of qualitative descriptive studies is a straight forward descriptive summary of the informational contents of data organized in a way that best fits the data” ( Sandelowski, 2000 , p. 339). Data re-presentation techniques allow for tremendous creativity and variation among researchers and studies. Several good resources are provided to spur imagination ( Miles et al., 2014 ; Munhall & Chenail, 2008 ; Wolcott, 2009 ).

Steps to Data Analysis

It is often difficult for junior health science researchers to know what to do with the volumes of data collected during a qualitative study and formal course work in traditional qualitative methods courses are typically sparse regarding the specifics of data management. It is for those reasons that this section of our article will provide a detailed description of the data analysis techniques used in qualitative descriptive methodology. The following steps are case examples of a study undertaken by one author (K.J.C.) after completing a data management course offered by another author (B.E.). Examples are offered from the two studies noted in Table 1 . It is offered in list format for general readability, but the qualitative researcher should recognize that qualitative analyses are iterative and recursive by nature.

Example of a Coding Manual.

Note . SES = socioeconomic status.

Reading from the left in Table 2 , codes were given a number and letter for use in marking sections of text. Next, the code name indicating a theme was entered in boldface type with a definition in the code immediately under it. The second column provided an exemplar of each code, along with a notation indicating where it was found in the data, so that coders could recognize instances of that particular code when they saw them.

The coding manual was tested against data gathered in a preliminary study and was revised as codes found to overlap or be missing entirely. We continued to revise it iteratively during the study as data collection and analysis proceeded and then used it to recode previously coded data. Using this procedure, it was used to revisit the data several times.

• Each transcribed document was formatted with wide right margins that allowed the investigator to apply codes and generate marginal remarks by hand. Marginal remarks are handwritten comments entered by the investigator. They represent an attempt to stay “alert” about analysis, forming ideas and recording reactions to the meaning of what is seen in the data. Marginal remarks often suggest new interpretations, leads, and connections or distinctions with other parts of the data ( Miles et al., 2014 ). Such remarks are preanalytic and add meaning and clarity to transcripts.

Level 1 Coding With Meaning Units.

• Conceptually similar codes were organized into categories (coding groups of coded themes that were increasingly abstract) through revisiting the theory framing the study (asking, “does this system of coding make sense according to the chosen theory?”). Miles et al. (2014) provide many examples for creating, categorizing, and revising codes, including highlighting a technique used by Corbin and Strauss ( Corbin & Strauss, 2015 ) that includes growing a list of codes and then applying a slightly more abstract label to the code, creating new categories of codes with each revision. This is often referred to as second-level or pattern coding, a way of grouping data into a smaller number of sets, themes, or constructs. During the analysis of data, patterns were generated and the researcher spent significant amounts of time with different categorizations, asking questions, checking relationships, and generally resisting the urge to be “locked too quickly into naming a pattern” ( Miles et al., 2014 , p. 69).
• During this phase of analysis, pattern codes were revised and redefined in the coding manual and exemplars were used to clarify the understanding of each code. Miles et al. (2014) suggest that software can be helpful during this categorization (counting) step, so lists of observed engagement behaviors were also recorded in Dedoose software ( Dedoose, 2015 ) by code so that frequencies could be captured and analyzed. Despite the assistance of Dedoose, the researcher found that hand sorting codes into themes and categories was best done on paper.

Example of an analytic memo used in qualitative description analysis.

Data Matrix.

Note . The CLOX is an executive clock drawing task that tests cognition and was used in this study with the caregiver (CG) and the care recipient (CR). The CG Strain and the CG Gain scores were derived by the researcher through a qualitative content analysis ( Evans, Coon, & Belyea, 2006 ).

• Finally, the data are re-presented in a creative but rigorous way that are judged to best fit the findings ( Miles et al., 2014 ; Sandelowski & Leeman, 2012 ; Stake, 2010 ; Wolcott, 2009 ).

Strategies for Ensuring Rigor of Findings

Many qualitative researchers do not provide enough information in their reports about the analytic strategies used to ensure verisimilitude or the “ring of truth” for the conclusions. Miles, Huberman, and Saldana (2014) outline 13 tactics for generating meaning from data and another 13 for testing or confirming findings. They also provide five standards for assessing the quality of conclusions. The techniques relied upon most heavily during a qualitative descriptive study ought to be addressed within the research report. It is important to establish “trustworthiness” and “authenticity” in qualitative research that are similar to the terms validity and reliability in quantitative research. The five standards (objectivity, dependability, credibility, transferability, and application) typically used in qualitative descriptive studies to assess quality and legitimacy (trustworthiness and authenticity) of the conclusions are discussed in the next sections ( Lincoln & Guba, 1985 ; Miles et al., 2014 ).

Objectivity

First, objectivity (confirmability) is conceptualized as relative neutrality and reasonable freedom from researcher bias and can be addressed by (a) describing the study’s methods and procedures in explicit detail, (b) sharing the sequence of data collection, analysis, and presentation methods to create an audit trail, (c) being aware of and reporting personal assumptions and potential bias, (d) retaining study data and making it available to collaborators for evaluation.

Dependability

Second, dependability (reliability or auditability) can be fostered by consistency in procedures across participants over time through various methods, including the use of semistructured interview questions and an observation data collection worksheet. Quality control ( Miles et al., 2014 ) can be fostered by:

• deriving study procedures from clearly outlined research questions and conceptual theory, so that data analysis could be linked back to theoretical constructs;
• clearly describing the investigator’s role and status at the research site;
• demonstrating parallelism in findings across sources (i.e., interview vs. observation, etc.);
• triangulation through the use of observations, interviews, and standardized measures to more adequately describe various characteristics of the sample population ( Denzin & Lincoln, 1994 );
• demonstrating consistency in data collection for all participants (i.e., using the same investigator and preprinted worksheets, asking the same questions in the same order);
• developing interview questions and observation techniques based on theory, revised, and tested during preliminary work;
• developing a coding manual a priori to guide data analysis, containing a “start list” of codes derived from the theoretical framework and relevant literature ( Fonteyn et al., 2008 ; Hsieh & Shannon, 2005 ; Miles et al., 2014 ); and
• developing a monitoring plan (fidelity) to ensure that junior researchers, especially do not go “beyond the data” ( Sandelowski, 2000 ) in interpretation. In keeping with the qualitative tradition, data analysis and collection should occur simultaneously, giving the investigator the opportunity to correct errors or make revisions.

Credibility

Third, credibility or verisimilitude (internal validity) is defined as the truth value of data: Do the findings of the study make sense ( Miles et al., 2014 , p. 312). Credibility in qualitative work promotes descriptive and evaluative understanding, which can be addressed by (a) providing context-rich “thick descriptions,” that is, the work of interpretation based on data ( Sandelowski, 2004 ), (b) checking with other practitioners or researchers that the findings “ring true,” (c) providing a comprehensive account, (d) using triangulation strategies, (e) searching for negative evidence, and (f) linking findings to a theoretical framework.

Transferability

Fourth, transferability (external validity or “fittingness”) speaks to whether the findings of your study have larger import and application to other settings or studies. This includes a discussion of generalizability. Sample to population generalizability is important to quantitative researchers and less helpful to qualitative researchers who seek more of an analytic or case-to-case transfer ( Miles et al., 2014 ). Nonetheless, transferability can be aided by (a) describing the characteristics of the participants fully so that comparisons with other groups may be made, (b) adequately describing potential threats to generalizability through sample and setting sections, (c) using theoretical sampling, (d) presenting findings that are congruent with theory, and (e) suggesting ways that findings from your study could be tested further by other researchers.

Application

Finally, Miles et al. (2014) speak to the utilization, application, or action orientation of the data. “Even if we know that a study’s findings are valid and transferable,” they write, “we still need to know what the study does for its participants and its consumers” ( Miles et al., 2014 , p. 314). To address application, findings of qualitative descriptive studies are typically made accessible to potential consumers of information through the publication of manuscripts, poster presentations, and summary reports written for consumers. In addition, qualitative descriptive study findings may stimulate further research, promote policy discussions, or suggest actual changes to a product or environment.

Implications for Practice

The qualitative description clarified and advocated by Sandelowski (2000 , 2010 ) is an excellent methodological choice for the healthcare environments designer, practitioner, or health sciences researcher because it provides rich descriptive content from the subjects’ perspective. Qualitative description allows the investigator to select from any number of theoretical frameworks, sampling strategies, and data collection techniques. The various content analysis strategies described in this paper serve to introduce the investigator to methods for data analysis that promote staying “close” to the data, thereby avoiding high-inference techniques likely challenging to the novice investigator. Finally, the devotion to thick description (interpretation based on data) and flexibility in the re-presentation of study findings is likely to produce meaningful information to designers and healthcare leaders. The practical, step-by-step nature of this article should serve as a starting guide to researchers interested in this technique as a way to answer their own burning questions.

Acknowledgments

The author would like to recognize the other members of her dissertation committee for their contributions to the study: Gerri Lamb, Karen Dorman Marek, and Robert Greenes.

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Research assistance for data analysis and manuscript development was supported by training funds from the National Institutes of Health/National Institute on Nursing Research (NIH/NINR), award T32 1T32NR012718-01 Transdisciplinary Training in Health Disparities Science (C. Keller, P.I.). The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH or the NINR. This research was supported through the Hartford Center of Gerontological Nursing Excellence at Arizona State University College of Nursing & Health Innovation.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

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Five qualitative approaches to inquiry.

1. Narrative research

2. Phenomenology research

3. Grounded theory research

4. Ethnographic research

5. Case study research

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The Author Behind the Five Approaches

John W. Creswell , PhD is an Professor of Family Medicine and Co-Director, Michigan Mixed Methods Research and Scholarship Program at the University of Michigan. He has authored numerous articles and 27 books on mixed methods research, qualitative research and research design. While at the University of Nebraska-Lincoln, he held the Clifton Endowed Professor Chair, served as director of a mixed methods research office, founded the SAGE journal, the Journal of Mixed Methods Research , and was an Adjunct Professor of Family Medicine at the University of Michigan and a consultant to the Veterans Administration health services research center. He was a Senior Fulbright Scholar to South Africa in 2008 and to Thailand in 2012. In 2011 co-led a national working group on mixed methods practices at the National Institute of Health, served as a Visiting Professor at Harvard’s School of Public Health, and received an honorary doctorate from the University of Pretoria, South Africa.  In 2014 he was the President of the Mixed Methods International Research Association.  In 2015 he joined the staff of Family Medicine at the University of Michigan.

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Research Design: Qualitative, Quantitative, and Mixed Methods Approaches

Student resources, welcome to the sage companion site for  research design ,  sixth edition.

The sixth edition of the best-selling text,  Research Design: Qualitative, Quantitative, and Mixed Methods Approaches  by  John W. Creswell  and  J. David Creswell , continues to provide clear and concise instruction for designing research projects or developing research proposals. This user-friendly text walks readers through research methods, from reviewing the literature to writing a research question and starting a hypothesis to designing the study. At each step in the process, the text addresses qualitative, quantitative, and mixed methods approaches to encourage readers to choose the approach that best fits the research question. Numerous examples draw from a wide variety of disciplines, featuring diverse philosophical ideas and modes of inquiry. Features like bullet points, numbered steps, and annotated research examples help students focus on the most important information in research design.

The  Sixth Edition  has been fully revised to reflect the 7th edition of the P ublication Manual of the American Psychological Association  with more inclusive language, updated citation styles, and updated writing suggestions. Learning objectives are now included at the start of each chapter. To help readers better achieve these learning objectives, the authors have clarified and improved the writing exercises to help readers better achieve these learning objectives. The final three chapters detailing qualitative, quantitative, and mixed methods now have a parallel structure so readers can better compare and contrast these approaches. Chapter 10 on mixed methods in particular has been restructured to reflect the latest developments in mixed methods and best practices. New research examples throughout help capture and demonstrate new trends in research.

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Creswell, J. W. (2014). Research Design: Qualitative, Quantitative and Mixed Methods Approaches (4th ed.). Thousand Oaks, CA: Sage

The book Research Design: Qualitative, Quantitative and Mixed Methods Approaches by Creswell (2014) covers three approaches-qualitative, quantitative and mixed methods. This educational book is informative and illustrative and is equally beneficial for students, teachers and researchers. Readers should have basic knowledge of research for better understanding of this book. There are two parts of the book. Part 1 (chapter 1-4) consists of steps for developing research proposal and part II (chapter 5-10) explains how to develop a research proposal or write a research report. A summary is given at the end of every chapter that helps the reader to recapitulate the ideas. Moreover, writing exercises and suggested readings at the end of every chapter are useful for the readers. Chapter 1 opens with-definition of research approaches and the author gives his opinion that selection of a research approach is based on the nature of the research problem, researchers' experience and the audience of the study. The author defines qualitative, quantitative and mixed methods research. A distinction is made between quantitative and qualitative research approaches. The author believes that interest in qualitative research increased in the latter half of the 20th century. The worldviews, Fraenkel, Wallen and Hyun (2012) and Onwuegbuzie and Leech (2005) call them paradigms, have been explained. Sometimes, the use of language becomes too philosophical and technical. This is probably because the author had to explain some technical terms.

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Conducting a well-established research requires deep knowledge about the research designs. Doing research can be likened to jumping into the sea which may transform into a huge ocean if the researcher is not experienced. As a PhD candidate and a novice researcher, I believe that the book "Research Design: Qualitative, Quantitative and Mixed Methods Approaches" by J.W. Creswell is a true reference guide for novice researchers since it is the most comprehensive and informative source with its reader-friendly structure.

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John W. Creswell was previously a professor in educational psychology in the University of Nebraska–Lincoln. He moved to the University of Michigan in 2015 as a professor in the Department of Family Medicine. He has published many articles and close to 27 books on mixed methods. Professor Creswell is also one of the founding members of the Journal of Mixed Methods Research. He was a Fulbright scholar in South Africa in 2008 and Thailand in 2012. In 2011, he served as a visiting professor in the School of Public Health of Harvard University. In 2014, he became the Chairman of the Mixed Methods International Research Association. Professor Creswell has a personal website called “Mixed Methods Research” at http://johnwcreswell.com/. The site contains the information about his background, his own blog, consulting works and published books. He also posted replies questions from academic researchers and practitioners in the blog.

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There are a number of approaches used in this research method design. The purpose of this chapter is to design the methodology of the research approach through mixed types of research techniques. The research approach also supports the researcher on how to come across the research result findings. In this chapter, the general design of the research and the methods used for data collection are explained in detail. It includes three main parts. The first part gives a highlight about the dissertation design. The second part discusses about qualitative and quantitative data collection methods. The last part illustrates the general research framework. The purpose of this section is to indicate how the research was conducted throughout the study periods.

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John Creswell on the Value of the Qualitative Approach

John W. Creswell

Say the name John Creswell in the presence of social and behavioral scientists and almost immediately you’ll start hearing fond remembrances of one or more of his books on qualitative methodology, quite likely on the mixed methods approach for which he’s been an apostle. And what an apostle – he’s written 28 books on mixed methods research, qualitative research and research design.

That loving response by students past and present, and the track record it represents, has been validated anew by the Textbook and Academic Authors Association (TAA), which this year is honoring one of Creswell’s most popular texts with its McGuffey Longevity Award, which honors well-written, well-research,, well-designed – and most importantly, well-received –books that have been in print for at least 15 years.

In honoring the book, the TAA judges cited two of the attributes that have long marked Creswell’s work, robust research design and absolute accessibility. “ Qualitative Inquiry and Research Design , ” the judges wrote, “ dependably reveals the research design path and provides navigational aids. No doubt it will continue to encourage more generations of researchers to embrace excellent qualitative research because of these attributes.” Taking advantage of the honor, we asked both Creswell and Poth about their work on the book, about trends in methods, and about their own academic journeys. John Creswell’s answers are below; read Cheryl Poth’s reflections on methodology and being asked to join up with a giant whose workshop “changed the course” of her career by clicking here..

Creswell is a professor of family medicine and co-director of the Michigan Mixed Methods Research and Scholarship Program at the University of Michigan. While at the University of Nebraska-Lincoln, he held the Clifton Endowed   Professor Chair, served as director of a mixed methods research office, founded the SAGE journal, the  Journal of Mixed Methods Research , and was an adjunct professor of family medicine at the University of Michigan and a consultant to the Veterans Administration.

The market has spoken as to whether your books — not just this one!– are successes. But from your vantage point, why are your books, and this one in particular, a success?

Over the years I have learned from readers that my books are successful because I simplify and clarify the basic research ideas so that a reader can easily learn how to conduct research. I have also been described as a clear, concise writer, and in my books, I share what has actually worked for me in research and talk about my own studies. This lends a personal touch to the writing. One of the best compliments I received for my writing came from a reader who asked me if I still practiced water aerobics because I had brought in as an example something from my water aerobics class in one of my books. What resonated with this person was my personal experience that helped the reader understand and remember my point about doing research.

What have you learned in between each edition?

I have learned how important ethics is in doing qualitative research and continue to expand my ethics discussion with each new edition. I have also learned that 5 approaches might be expanded to include more approaches, such as participatory action research and discourse analysis. But five approaches seems to be enough for the present moment, and I do not want to keep expanding the content of the book.

W hat was the original reason you wrote this particular book on the five approaches, as opposed to a different way to explain qualitative inquiry and research design?

I felt that qualitative research was not simply one type of design but many possibilities for the researcher. This was especially true after the early 1990s when specific books were being published on types of qualitative designs, such as grounded theory, phenomenology, and case studies. I felt that the researcher needed to select from among the different types of designs, and that my book could present the possibilities so that the researcher could make an informed decision as to what type of qualitative design would be best for their project. Thus, the Qualitative Inquiry and Research Design book put five approaches side-by-side so that a researcher might decide which approach was best for their project.

What was, or is, your own biggest stumbling block in deploying qualitative research methodology?

For many years I needed to convince researchers of the value of qualitative research. The approach to research had been primarily quantitative, statistically oriented research. So my challenge was to create the best argument possible for the value of qualitative research and why it was useful as an approach to research. This involved talking about how hearing the voices of participants was important, how specific words used by participants were important, and how the setting or context of the research situation was valuable to know. Today, I find that I have less to justify the use of qualitative research and focus more on how to actually employ the approach in an actual study.

While you’re certainly best-known in these parts for your advocacy and support of qualitative inquiry and mixed methods, your ‘day job’ is as a professor of family medicine. [He was a Senior Fulbright Scholar to South Africa in 2008 and to Thailand in 2012. In 2011, he co-led a national working group on mixed methods practices at the National Institutes of Health, served as a visiting professor at Harvard’s School of Public Health, and received an honorary doctorate from the University of Pretoria, South Africa.] Would you outline the overlap between those two spheres?

In family medicine at Michigan, I am a full-time researcher helping faculty and students prepare their research applications for funding sources. I also provide workshops on qualitative and mixed methods research. So in my day job at Michigan, I am continually employing my ideas about how to conduct good research. At Michigan I do not teach formal graduate courses, but my workshops do provide a teaching opportunity for me

While I know all the tips and approaches are valuable, if you were told to write a book with only one tip for research design, what would it be?

The one tip I would provide is to think about the parts of conducting research – the problem, the data collection, the data analysis, the interpretation – and consider how these parts interact. All of my books take the position that the “process of research” is fundamental to conducting and writing about research, and that a good research study portrays the interaction among all of the parts of research

While receiving an excellence award is certainly an honor in itself, what sort of actionable information does being recognized for having a text that has stood the test of time provide for your own writing/textbook creation?

With all of my new editions to my research books, I think that I am up to 28 books now, the question is, “Do I write another book?” I cannot answer this question right now, although I would like to write (and am writing my memoir) a literary book. Recognition gives me the incentive to continue writing more books, whether academic or literary in form. The habit of writing has certainly set in for me, and I am such that I will continue. The award just encourages me onward.

Michael Todd

Social Science Space editor Michael Todd is a long-time newspaper editor and reporter whose beats included the U.S. military, primary and secondary education, government, and business. He entered the magazine world in 2006 as the managing editor of Hispanic Business. He joined the Miller-McCune Center for Research, Media and Public Policy and its magazine Miller-McCune (renamed Pacific Standard in 2012), where he served as web editor and later as senior staff writer focusing on covering the environmental and social sciences. During his time with the Miller-McCune Center, he regularly participated in media training courses for scientists in collaboration with the Communication Partnership for Science and the Sea (COMPASS), Stanford’s Aldo Leopold Leadership Institute, and individual research institutions.

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According to the National Science Foundation, the percentage of American adults with a great deal of trust in the scientific community dropped […]

Watch a Social Scientist Reflect on the Russian Invasion of Ukraine

“It’s very hard,” explains Sir Lawrence Freedman, “to motivate people when they’re going backwards.”

Dispatches from Social and Behavioral Scientists on COVID

Has the ongoing COVID-19 pandemic impacted how social and behavioral scientists view and conduct research? If so, how exactly? And what are […]