descriptive vs interpretive research

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12 Interpretive research

Chapter 11 introduced interpretive research—or more specifically, interpretive case research. This chapter will explore other kinds of interpretive research. Recall that positivist or deductive methods—such as laboratory experiments and survey research—are those that are specifically intended for theory (or hypotheses) testing. Interpretive or inductive methods—such as action research and ethnography—one the other hand, are intended for theory building. Unlike a positivist method, where the researcher tests existing theoretical postulates using empirical data, in interpretive methods, the researcher tries to derive a theory about the phenomenon of interest from the existing observed data.

The term ‘interpretive research’ is often used loosely and synonymously with ‘qualitative research’, although the two concepts are quite different. Interpretive research is a research paradigm (see Chapter 3) that is based on the assumption that social reality is not singular or objective. Rather, it is shaped by human experiences and social contexts (ontology), and is therefore best studied within its sociohistoric context by reconciling the subjective interpretations of its various participants (epistemology). Because interpretive researchers view social reality as being embedded within—and therefore impossible to abstract from—their social settings, they ‘interpret’ the reality though a ‘sense-making’ process rather than a hypothesis testing process. This is in contrast to the positivist or functionalist paradigm that assumes that the reality is relatively independent of the context, can be abstracted from their contexts, and studied in a decomposable functional manner using objective techniques such as standardised measures. Whether a researcher should pursue interpretive or positivist research depends on paradigmatic considerations about the nature of the phenomenon under consideration and the best way to study it.

However, qualitative versus quantitative research refers to empirical or data-oriented considerations about the type of data to collect and how to analyse it. Qualitative research relies mostly on non-numeric data, such as interviews and observations, in contrast to quantitative research which employs numeric data such as scores and metrics. Hence, qualitative research is not amenable to statistical procedures such as regression analysis, but is coded using techniques like content analysis. Sometimes, coded qualitative data is tabulated quantitatively as frequencies of codes, but this data is not statistically analysed. Many puritan interpretive researchers reject this coding approach as a futile effort to seek consensus or objectivity in a social phenomenon which is essentially subjective.

Although interpretive research tends to rely heavily on qualitative data, quantitative data may add more precision and clearer understanding of the phenomenon of interest than qualitative data. For example, Eisenhardt (1989), [1] in her interpretive study of decision-making in high-velocity firms (discussed in the previous chapter on case research), collected numeric data on how long it took each firm to make certain strategic decisions—which ranged from approximately six weeks to 18 months—how many decision alternatives were considered for each decision, and surveyed her respondents to capture their perceptions of organisational conflict. Such numeric data helped her clearly distinguish the high-speed decision-making firms from the low-speed decision-makers without relying on respondents’ subjective perceptions, which then allowed her to examine the number of decision alternatives considered by and the extent of conflict in high-speed versus low-speed firms. Interpretive research should attempt to collect both qualitative and quantitative data pertaining to the phenomenon of interest, and so should positivist research as well. Joint use of qualitative and quantitative data—often called ‘mixed-mode design’—may lead to unique insights, and is therefore highly prized in the scientific community.

Interpretive research came into existence in the early nineteenth century—long before positivist techniques were developed—and has its roots in anthropology, sociology, psychology, linguistics, and semiotics. Many positivist researchers view interpretive research as erroneous and biased, given the subjective nature of the qualitative data collection and interpretation process employed in such research. However, since the 1970s, many positivist techniques’ failure to generate interesting insights or new knowledge has resulted in a resurgence of interest in interpretive research—albeit with exacting methods and stringent criteria to ensure the reliability and validity of interpretive inferences.

Distinctions from positivist research

In addition to the fundamental paradigmatic differences in ontological and epistemological assumptions discussed above, interpretive and positivist research differ in several other ways. First, interpretive research employs a theoretical sampling strategy, where study sites, respondents, or cases are selected based on theoretical considerations such as whether they fit the phenomenon being studied (e.g., sustainable practices can only be studied in organisations that have implemented sustainable practices), whether they possess certain characteristics that make them uniquely suited for the study (e.g., a study of the drivers of firm innovations should include some firms that are high innovators and some that are low innovators, in order to draw contrast between these firms), and so forth. In contrast, positivist research employs random sampling —or a variation of this technique—in which cases are chosen randomly from a population for the purpose of generalisability. Hence, convenience samples and small samples are considered acceptable in interpretive research—as long as they fit the nature and purpose of the study—but not in positivist research.

Second, the role of the researcher receives critical attention in interpretive research. In some methods such as ethnography, action research, and participant observation, the researcher is considered part of the social phenomenon, and their specific role and involvement in the research process must be made clear during data analysis. In other methods, such as case research, the researcher must take a ’neutral’ or unbiased stance during the data collection and analysis processes, and ensure that their personal biases or preconceptions do not taint the nature of subjective inferences derived from interpretive research. In positivist research, however, the researcher is considered to be external to and independent of the research context, and is not presumed to bias the data collection and analytic procedures.

Third, interpretive analysis is holistic and contextual, rather than being reductionist and isolationist. Interpretive interpretations tend to focus on language, signs, and meanings from the perspective of the participants involved in the social phenomenon, in contrast to statistical techniques that are employed heavily in positivist research. Rigor in interpretive research is viewed in terms of systematic and transparent approaches to data collection and analysis, rather than statistical benchmarks for construct validity or significance testing.

Lastly, data collection and analysis can proceed simultaneously and iteratively in interpretive research. For instance, the researcher may conduct an interview and code it before proceeding to the next interview. Simultaneous analysis helps the researcher correct potential flaws in the interview protocol or adjust it to capture the phenomenon of interest better. The researcher may even change their original research question if they realise that their original research questions are unlikely to generate new or useful insights. This is a valuable—but often understated—benefit of interpretive research, and is not available in positivist research, where the research project cannot be modified or changed once the data collection has started without redoing the entire project from the start.

Benefits and challenges of interpretive research

Interpretive research has several unique advantages. First, it is well-suited for exploring hidden reasons behind complex, interrelated, or multifaceted social processes—such as inter-firm relationships or inter-office politics—where quantitative evidence may be biased, inaccurate, or otherwise difficult to obtain. Second, it is often helpful for theory construction in areas with no or insufficient a priori theory. Third, it is also appropriate for studying context-specific, unique, or idiosyncratic events or processes. Fourth, interpretive research can also help uncover interesting and relevant research questions and issues for follow-up research.

At the same time, interpretive research also has its own set of challenges. First, this type of research tends to be more time and resource intensive than positivist research in data collection and analytic efforts. Too little data can lead to false or premature assumptions, while too much data may not be effectively processed by the researcher. Second, interpretive research requires well-trained researchers who are capable of seeing and interpreting complex social phenomenon from the perspectives of the embedded participants, and reconciling the diverse perspectives of these participants, without injecting their personal biases or preconceptions into their inferences. Third, all participants or data sources may not be equally credible, unbiased, or knowledgeable about the phenomenon of interest, or may have undisclosed political agendas which may lead to misleading or false impressions. Inadequate trust between the researcher and participants may hinder full and honest self-representation by participants, and such trust building takes time. It is the job of the interpretive researcher to ‘see through the smoke’ (i.e., hidden or biased agendas) and understand the true nature of the problem. Fourth, given the heavily contextualised nature of inferences drawn from interpretive research, such inferences do not lend themselves well to replicability or generalisability. Finally, interpretive research may sometimes fail to answer the research questions of interest or predict future behaviours.

Characteristics of interpretive research

All interpretive research must adhere to a common set of principles, as described below.

Naturalistic inquiry: Social phenomena must be studied within their natural setting.

Because interpretive research assumes that social phenomena are situated within—and cannot be isolated from—their social context, interpretations of such phenomena must be grounded within their sociohistorical context. This implies that contextual variables should be observed and considered in seeking explanations of a phenomenon of interest, even though context sensitivity may limit the generalisability of inferences.

Researcher as instrument: Researchers are often embedded within the social context that they are studying, and are considered part of the data collection instrument in that they must use their observational skills, their trust with the participants, and their ability to extract the correct information. Further, their personal insights, knowledge, and experiences of the social context are critical to accurately interpreting the phenomenon of interest. At the same time, researchers must be fully aware of their personal biases and preconceptions, and not let such biases interfere with their ability to present a fair and accurate portrayal of the phenomenon.

Interpretive analysis: Observations must be interpreted through the eyes of the participants embedded in the social context. Interpretation must occur at two levels. The first level involves viewing or experiencing the phenomenon from the subjective perspectives of the social participants. The second level is to understand the meaning of the participants’ experiences in order to provide a ‘thick description’ or a rich narrative story of the phenomenon of interest that can communicate why participants acted the way they did.

Use of expressive language: Documenting the verbal and non-verbal language of participants and the analysis of such language are integral components of interpretive analysis. The study must ensure that the story is viewed through the eyes of a person, and not a machine, and must depict the emotions and experiences of that person, so that readers can understand and relate to that person. Use of imageries, metaphors, sarcasm, and other figures of speech are very common in interpretive analysis.

Temporal nature: Interpretive research is often not concerned with searching for specific answers, but with understanding or ‘making sense of’ a dynamic social process as it unfolds over time. Hence, such research requires the researcher to immerse themself in the study site for an extended period of time in order to capture the entire evolution of the phenomenon of interest.

Hermeneutic circle: Interpretive interpretation is an iterative process of moving back and forth from pieces of observations (text), to the entirety of the social phenomenon (context), to reconcile their apparent discord, and to construct a theory that is consistent with the diverse subjective viewpoints and experiences of the embedded participants. Such iterations between the understanding/meaning of a phenomenon and observations must continue until ‘theoretical saturation’ is reached, whereby any additional iteration does not yield any more insight into the phenomenon of interest.

Interpretive data collection

Data is collected in interpretive research using a variety of techniques. The most frequently used technique is interviews (face-to-face, telephone, or focus groups). Interview types and strategies are discussed in detail in Chapter 9. A second technique is observation . Observational techniques include direct observation , where the researcher is a neutral and passive external observer, and is not involved in the phenomenon of interest (as in case research), and participant observation , where the researcher is an active participant in the phenomenon, and their input or mere presence influence the phenomenon being studied (as in action research). A third technique is documentation , where external and internal documents—such as memos, emails, annual reports, financial statements, newspaper articles, or websites—may be used to cast further insight into the phenomenon of interest or to corroborate other forms of evidence.

Interpretive research designs

Case research . As discussed in the previous chapter, case research is an intensive longitudinal study of a phenomenon at one or more research sites for the purpose of deriving detailed, contextualised inferences, and understanding the dynamic process underlying a phenomenon of interest. Case research is a unique research design in that it can be used in an interpretive manner to build theories, or in a positivist manner to test theories. The previous chapter on case research discusses both techniques in depth and provides illustrative exemplars. Furthermore, the case researcher is a neutral observer (direct observation) in the social setting, rather than an active participant (participant observation). As with any other interpretive approach, drawing meaningful inferences from case research depends heavily on the observational skills and integrative abilities of the researcher.

Action research . Action research is a qualitative but positivist research design aimed at theory testing rather than theory building. This is an interactive design that assumes that complex social phenomena are best understood by introducing changes, interventions, or ‘actions’ into those phenomena, and observing the outcomes of such actions on the phenomena of interest. In this method, the researcher is usually a consultant or an organisational member embedded into a social context —such as an organisation—who initiates an action in response to a social problem, and examines how their action influences the phenomenon, while also learning and generating insights about the relationship between the action and the phenomenon. Examples of actions may include organisational change programs—such as the introduction of new organisational processes, procedures, people, or technology or the replacement of old ones—initiated with the goal of improving an organisation’s performance or profitability. The researcher’s choice of actions must be based on theory, which should explain why and how such actions may bring forth the desired social change. The theory is validated by the extent to which the chosen action is successful in remedying the targeted problem. Simultaneous problem-solving and insight generation are the central feature that distinguishes action research from other research methods (which may not involve problem solving), and from consulting (which may not involve insight generation). Hence, action research is an excellent method for bridging research and practice.

There are several variations of the action research method. The most popular of these methods is participatory action research , designed by Susman and Evered (1978). [2] This method follows an action research cycle consisting of five phases: diagnosing, action-planning, action-taking, evaluating, and learning (see Figure 12.1). Diagnosing involves identifying and defining a problem in its social context. Action-planning involves identifying and evaluating alternative solutions to the problem, and deciding on a future course of action based on theoretical rationale. Action-taking is the implementation of the planned course of action. The evaluation stage examines the extent to which the initiated action is successful in resolving the original problem—i.e., whether theorised effects are indeed realised in practice. In the learning phase, the experiences and feedback from action evaluation are used to generate insights about the problem and suggest future modifications or improvements to the action. Based on action evaluation and learning, the action may be modified or adjusted to address the problem better, and the action research cycle is repeated with the modified action sequence. It is suggested that the entire action research cycle be traversed at least twice so that learning from the first cycle can be implemented in the second cycle. The primary mode of data collection is participant observation, although other techniques such as interviews and documentary evidence may be used to corroborate the researcher’s observations.

Ethnography . The ethnographic research method—derived largely from the field of anthropology—emphasises studying a phenomenon within the context of its culture. The researcher must be deeply immersed in the social culture over an extended period of time—usually eight months to two years—and should engage, observe, and record the daily life of the studied culture and its social participants within their natural setting. The primary mode of data collection is participant observation, and data analysis involves a ‘sense-making’ approach. In addition, the researcher must take extensive field notes, and narrate her experience in descriptive detail so that readers may experience the same culture as the researcher. In this method, the researcher has two roles: rely on her unique knowledge and engagement to generate insights (theory), and convince the scientific community of the transsituational nature of the studied phenomenon.

The classic example of ethnographic research is Jane Goodall’s study of primate behaviours. While living with chimpanzees in their natural habitat at Gombe National Park in Tanzania, she observed their behaviours, interacted with them, and shared their lives. During that process, she learnt and chronicled how chimpanzees seek food and shelter, how they socialise with each other, their communication patterns, their mating behaviours, and so forth. A more contemporary example of ethnographic research is Myra Bluebond-Langer’s (1996) [3] study of decision-making in families with children suffering from life-threatening illnesses, and the physical, psychological, environmental, ethical, legal, and cultural issues that influence such decision-making. The researcher followed the experiences of approximately 80 children with incurable illnesses and their families for a period of over two years. Data collection involved participant observation and formal/informal conversations with children, their parents and relatives, and healthcare providers to document their lived experience.

Phenomenology. Phenomenology is a research method that emphasises the study of conscious experiences as a way of understanding the reality around us. It is based on the ideas of early twentieth century German philosopher, Edmund Husserl, who believed that human experience is the source of all knowledge. Phenomenology is concerned with the systematic reflection and analysis of phenomena associated with conscious experiences such as human judgment, perceptions, and actions. Its goal is (appreciating and describing social reality from the diverse subjective perspectives of the participants involved, and understanding the symbolic meanings (‘deep structure’) underlying these subjective experiences. Phenomenological inquiry requires that researchers eliminate any prior assumptions and personal biases, empathise with the participant’s situation, and tune into existential dimensions of that situation so that they can fully understand the deep structures that drive the conscious thinking, feeling, and behaviour of the studied participants.

Some researchers view phenomenology as a philosophy rather than as a research method. In response to this criticism, Giorgi and Giorgi (2003) [4] developed an existential phenomenological research method to guide studies in this area. This method, illustrated in Figure 12.2, can be grouped into data collection and data analysis phases. In the data collection phase, participants embedded in a social phenomenon are interviewed to capture their subjective experiences and perspectives regarding the phenomenon under investigation. Examples of questions that may be asked include ‘Can you describe a typical day?’ or ‘Can you describe that particular incident in more detail?’. These interviews are recorded and transcribed for further analysis. During data analysis , the researcher reads the transcripts to: get a sense of the whole, and establish ‘units of significance’ that can faithfully represent participants’ subjective experiences. Examples of such units of significance are concepts such as ‘felt-space’ and ‘felt-time’, which are then used to document participants’ psychological experiences. For instance, did participants feel safe, free, trapped, or joyous when experiencing a phenomenon (‘felt-space’)? Did they feel that their experience was pressured, slow, or discontinuous (‘felt-time’)? Phenomenological analysis should take into account the participants’ temporal landscape (i.e., their sense of past, present, and future), and the researcher must transpose his/herself in an imaginary sense into the participant’s situation (i.e., temporarily live the participant’s life). The participants’ lived experience is described in the form of a narrative or using emergent themes. The analysis then delves into these themes to identify multiple layers of meaning while retaining the fragility and ambiguity of subjects’ lived experiences.

Rigor in interpretive research

While positivist research employs a ‘reductionist’ approach by simplifying social reality into parsimonious theories and laws, interpretive research attempts to interpret social reality through the subjective viewpoints of the embedded participants within the context where the reality is situated. These interpretations are heavily contextualised, and are naturally less generalisable to other contexts. However, because interpretive analysis is subjective and sensitive to the experiences and insight of the embedded researcher, it is often considered less rigorous by many positivist (functionalist) researchers. Because interpretive research is based on a different set of ontological and epistemological assumptions about social phenomena than positivist research, the positivist notions of rigor—such as reliability, internal validity, and generalisability—do not apply in a similar manner. However, Lincoln and Guba (1985) [5] provide an alternative set of criteria that can be used to judge the rigor of interpretive research.

Dependability. Interpretive research can be viewed as dependable or authentic if two researchers assessing the same phenomenon, using the same set of evidence, independently arrive at the same conclusions, or the same researcher, observing the same or a similar phenomenon at different times arrives at similar conclusions. This concept is similar to that of reliability in positivist research, with agreement between two independent researchers being similar to the notion of inter-rater reliability, and agreement between two observations of the same phenomenon by the same researcher akin to test-retest reliability. To ensure dependability, interpretive researchers must provide adequate details about their phenomenon of interest and the social context in which it is embedded, so as to allow readers to independently authenticate their interpretive inferences.

Credibility. Interpretive research can be considered credible if readers find its inferences to be believable. This concept is akin to that of internal validity in functionalistic research. The credibility of interpretive research can be improved by providing evidence of the researcher’s extended engagement in the field, by demonstrating data triangulation across subjects or data collection techniques, and by maintaining meticulous data management and analytic procedures—such as verbatim transcription of interviews, accurate records of contacts and interviews—and clear notes on theoretical and methodological decisions, that can allow an independent audit of data collection and analysis if needed.

Confirmability. Confirmability refers to the extent to which the findings reported in interpretive research can be independently confirmed by others—typically, participants. This is similar to the notion of objectivity in functionalistic research. Since interpretive research rejects the notion of an objective reality, confirmability is demonstrated in terms of ‘intersubjectivity’—i.e., if the study’s participants agree with the inferences derived by the researcher. For instance, if a study’s participants generally agree with the inferences drawn by a researcher about a phenomenon of interest—based on a review of the research paper or report—then the findings can be viewed as confirmable.

Transferability. Transferability in interpretive research refers to the extent to which the findings can be generalised to other settings. This idea is similar to that of external validity in functionalistic research. The researcher must provide rich, detailed descriptions of the research context (‘thick description’) and thoroughly describe the structures, assumptions, and processes revealed from the data so that readers can independently assess whether and to what extent the reported findings are transferable to other settings.

• Eisenhardt, K. M. (1989). Making fast strategic decisions in high-velocity environments. Academy of Management Journal , 32(3), 543–576. ↵
• Susman, G. I. and Evered, R. D. (1978) An assessment of the scientific merits of action research. Administrative Science Quarterly , 23, 582–603. ↵
• Bluebond-Langer, M. (1996). In the shadow of illness: Parents and siblings of the chronically ill child . Princeton, NJ: Princeton University Press. ↵
• Giorgi, A., & Giorgi, B. (2003). Phenomenology. In J. A. Smith (ed.), Qualitative psychology: A practical guide to research methods (pp. 25–50). London: Sage Publications ↵
• Lincoln, Y. S., & Guba, E. G. (1985). Naturalistic inquiry . Beverly Hills: Sage Publications. ↵

Social Science Research: Principles, Methods and Practices (Revised edition) Copyright © 2019 by Anol Bhattacherjee is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

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Essentials of Descriptive-Interpretive Qualitative Research

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The brief, practical texts in the Essentials of Qualitative Methods series introduce social science and psychology researchers to key approaches to capturing phenomena not easily measured quantitatively, offering exciting, nimble opportunities to gather in-depth qualitative data.

This book offers a no-nonsense, step-by-step approach to qualitative research in psychology and related fields, presenting principles for using a generic approach to descriptive-interpretive qualitative research. Based on more than 50 years of combined experience doing qualitative research on psychotherapy, the authors offer an overarching framework of best research practices common to a wide range of approaches.

About the Essentials of Qualitative Methods book series

Even for experienced researchers, selecting and correctly applying the right method can be challenging. In this groundbreaking series, leading experts in qualitative methods provide clear, crisp, and comprehensive descriptions of their approach, including its methodological integrity, and its benefits and limitations.

Each book includes numerous examples to enable readers to quickly and thoroughly grasp how to leverage these valuable methods.

Series Foreword by Clara E. Hill and Sarah Knox

• Why a Generic Descriptive-Interpretive Approach to Qualitative Research?
• Designing the Study
• Data Collection
• A Framework of Key Modes of Qualitative Data Analysis
• Writing the Manuscript
• Methodological Integrity
• Summary and Conclusions

Appendix. Example Studies

Robert Elliott, PhD, is professor of counselling at the University of Strathclyde. He received his doctorate in clinical psychology from the University of California, Los Angeles, and is professor emeritus of psychology at the University of Toledo (Ohio). He has spent most of his career as a psychotherapy researcher trying out and inventing different research methods.

He is co-author of Facilitating Emotional Change (1993), Learning Process-Experiential Psychotherapy (2004), Research Methods in Clinical Psychology (3rd ed., 2015), as well as more than 170 journal articles and book chapters.

He is past president of the Society for Psychotherapy Research and previously co-edited the journals Psychotherapy Research and Person-Centered and Experiential Psychotherapies .

Ladislav Timulak, PhD, is an associate professor at Trinity College Dublin, Ireland. He is course director of the Doctorate in Counselling Psychology course. Ladislav (or Laco for short; read Latso) is involved in the training of counselling psychologists and various psychotherapy trainings in Ireland and internationally. Laco is both an academic and a practitioner.

He is interested in research methodology and psychotherapy research, particularly the development of emotion-focused therapy. He has written six books, over 80 peer-reviewed papers, and various chapters in both his native language, Slovak, and in English.

He serves on various editorial boards and in the past served as a co-editor of Counselling Psychology Quarterly .

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• Descriptive Research | Definition, Types, Methods & Examples

Descriptive Research | Definition, Types, Methods & Examples

Published on May 15, 2019 by Shona McCombes . Revised on June 22, 2023.

Descriptive research aims to accurately and systematically describe a population, situation or phenomenon. It can answer what , where , when and how   questions , but not why questions.

A descriptive research design can use a wide variety of research methods  to investigate one or more variables . Unlike in experimental research , the researcher does not control or manipulate any of the variables, but only observes and measures them.

Table of contents

When to use a descriptive research design, descriptive research methods, other interesting articles.

Descriptive research is an appropriate choice when the research aim is to identify characteristics, frequencies, trends, and categories.

It is useful when not much is known yet about the topic or problem. Before you can research why something happens, you need to understand how, when and where it happens.

Descriptive research question examples

• How has the Amsterdam housing market changed over the past 20 years?
• Do customers of company X prefer product X or product Y?
• What are the main genetic, behavioural and morphological differences between European wildcats and domestic cats?
• What are the most popular online news sources among under-18s?
• How prevalent is disease A in population B?

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Descriptive research is usually defined as a type of quantitative research , though qualitative research can also be used for descriptive purposes. The research design should be carefully developed to ensure that the results are valid and reliable .

Survey research allows you to gather large volumes of data that can be analyzed for frequencies, averages and patterns. Common uses of surveys include:

• Describing the demographics of a country or region
• Gauging public opinion on political and social topics
• Evaluating satisfaction with a company’s products or an organization’s services

Observations

Observations allow you to gather data on behaviours and phenomena without having to rely on the honesty and accuracy of respondents. This method is often used by psychological, social and market researchers to understand how people act in real-life situations.

Observation of physical entities and phenomena is also an important part of research in the natural sciences. Before you can develop testable hypotheses , models or theories, it’s necessary to observe and systematically describe the subject under investigation.

Case studies

A case study can be used to describe the characteristics of a specific subject (such as a person, group, event or organization). Instead of gathering a large volume of data to identify patterns across time or location, case studies gather detailed data to identify the characteristics of a narrowly defined subject.

Rather than aiming to describe generalizable facts, case studies often focus on unusual or interesting cases that challenge assumptions, add complexity, or reveal something new about a research problem .

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.

• Normal distribution
• Degrees of freedom
• Null hypothesis
• Discourse analysis
• Control groups
• Mixed methods research
• Non-probability sampling
• Quantitative research
• Ecological validity

Research bias

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

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Interpretive Description (and how it differs from Qualitative Description) with Ashley Hyde, RN, PhD

Hello Qualitative Mind,

I’m honoured to welcome my friend and colleague, Ashley Hyde, RN PhD, to the blog today to speak to us about her experience using interpretive description in her research and the ways in which interpretive description differs from qualitative description (a common question). If you need a refresher on qualitative description and what it is before diving into Ashley’s post below, we wrote a blog post on this topic back in April of 2020 - you can read it here .

Let’s welcome Ashley to the Quali Q community today!

Like many graduate students or novice researchers, I (Ashley) started the research process with an idea of what I wanted to explore. My research topic (understanding the experience of choice) was grounded in my experiences as a clinician and a desire to improve care for patients and their caregivers-so off I went to find my method.

I wanted to understand how family caregivers caring for their older relatives experienced choice when accessing supportive living services (which sounds like a mouthful, I know!).

Clearly, given my focus on experiences and the concept of choice, my study was amenable to exploration through a number of different approaches. However, it was my clinical grounding and desire to find solutions to what I perceived as a clinical problem that led me to Interpretive Description.

Interpretive description was first described in detail by Dr. Sally Thorne (& team) in 1997 and was borne out of a desire to describe qualitative inquiry that was being conducted that was not necessarily congruent with more traditional approaches but was still useful, particularly in clinical disciplines like nursing. If you’ve looked into using interpretive description and are thinking parts of it sound familiar, you’re not wrong! Elements of methodological borrowing can be seen in the ways interpretive description encourages constant comparative analysis (grounded theory); appreciates multiple ways of data collection, including participation observation (ethnography); and acknowledges multiple realities contributing to the subjective human experience (phenomenology). 

So, where does the uniqueness of interpretive description lie? How is this method distinct from qualitative description? These were questions that I continued to grapple with as I approached my doctoral defence. To me, the uniqueness or defining feature rests in its emphasis on the generation of clinically relevant knowledge. Further, within the analysis process, the researcher must go beyond reporting the findings,  to interpret what their findings mean in relation to each other, and the study context. In essence, Thorne encourages users of interpretive description to, “ lead their eventual reader toward a kind of knowing that was not possible prior to your study ” (Thorne, 2016, p. 181). 

“ Thorne encourages users of interpretive description to, “lead their eventual reader toward a kind of knowing that was not possible prior to your study” (Thorne, 2016, p.181). ”

Yes, I would agree that on the surface, interpretive description appears to be a relatively generic approach to qualitative inquiry that, perhaps, is not far from its cousin, qualitative description. It is not overtly critical in nature, nor does it readily address issues of power and inequality. It doesn’t aim to generate theory, nor does it particularly encourage exploration of theory prior to starting your research. However, what it does offer is flexibility to explore clinically relevant topics, free from a predetermined theoretical mandate or worldview, and ensure the construction of data that is ultimately relevant to clinical practice and patient care. 

What do you think; do you agree with Ashley’s comment on the ways that interpretive description differs from qualitative description? We’d love to hear your thoughts! Leave us a comment or send us an email to [email protected] and let us know your thoughts on today’s post.

References:

Thorne, S. E. (2016).  Interpretive description : qualitative research for applied practice  (Second edition.). Routledge.

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An overview of interpretive phenomenology as a research methodology

Affiliation.

• 1 National University of Ireland, Galway. [email protected]
• PMID: 23909107
• DOI: 10.7748/nr2013.07.20.6.17.e315

Aim: To provide an overview of interpretive phenomenology.

Background: Phenomenology is a philosophy and a research approach. As a research approach, it is used extensively in nursing and 'interpretive' phenomenology is becoming increasingly popular.

Data sources: Online and manual searches of relevant books and electronic databases were undertaken.

Review methods: Literature review on papers on phenomenology, research and nursing (written in English) was undertaken.

Discussion: A brief outline of the origins of the concept, and the influence of 'descriptive' phenomenology on the development of interpretive phenomenology is provided. Its aim, origins and philosophical basis, including the core concepts of dasein, fore-structure/pre-understanding, world view existential themes and the hermeneutic circle, are described and the influence of these concepts in phenomenological nursing research is illustrated.

Conclusion: This paper will assist readers when deciding whether interpretive phenomenology is appropriate for their research projects.

Implications for research/practice: This paper adds to the discussion on interpretive phenomenology and helps inform readers of its use as a research methodology.

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Examining characteristics of descriptive phenomenological nursing studies: A scoping review

Shefaly shorey.

1 Alice Lee Centre for Nursing Studies, Yong Loo Lin School of Medicine, National University of Singapore, Singapore

Esperanza Debby Ng

Associated data.

Data available in article supplementary material

To evaluate the characteristics and methodology consistency in nursing research with descriptive phenomenological design.

Scoping review methodology.

Data sources

Three electronic databases (CINAHL, Embase, PubMed) were systematically searched for qualitative studies with a descriptive phenomenological design published in nursing journals between January 2021 and December 2021.

Review methods

Quality appraisal of each study was conducted using the Critical Appraisal Skills Programme checklist. Data were extracted and presented narratively based on research objective, design justification and consistency, theoretical framework, sampling method and sample size, data collection method, data analysis approach and presentation of findings.

One hundred and three studies were included in the review. Overall, the characteristics of the studies are mostly consistent with Husserl's phenomenology approach in terms of research objectives, the use of other theoretical frameworks, sampling and data collection methods. However, the findings revealed several inconsistencies between research design and data analysis techniques, the lack of design justification and the lack of mention of bracketing.

Conclusions

Apart from the need for more research and standardized guidelines to clarify the various qualitative research methods, future nurse researchers are urged to provide more methodological details when publishing a descriptive phenomenological study so that readers can examine the effectiveness and quality of the method.

What problem did the study address?

Descriptive phenomenology is increasingly used in nursing research to answer ‘what’ and ‘how’ questions in nursing science, but it is uncertain whether nurse researchers who practice descriptive phenomenology share the same understanding of the research design used.

What were the main findings?

The methodology of nursing studies published in 2021 that self‐report a descriptive phenomenology design is mostly consistent with Husserl's described approach apart from several inconsistencies between research design and data analysis techniques, the lack of design justification and the lack of mention of bracketing.

Where and on whom will the research have an impact?

Nurse researchers are recommended to justify their research design used, provide more methodological details, including bracketing process when publishing a descriptive phenomenology study. Nursing research institutions are urged to update, clarify and standardized research guidelines for different qualitative research methods.

1. INTRODUCTION

Qualitative research methods have been receiving increasing recognition in healthcare and nursing research, as it seeks to understand a natural phenomenon through the emphasis on the meaning, views and experiences of participants (Al‐Busaidi,  2008 ). As nurse researchers strive to develop knowledge that embraces the ideals of holistic nursing, it is essential for nurse researchers to understand human experiences in health and illness and explore the needs of both nurses, patients and other stakeholders (Wojnar & Swanson,  2007 ). Learning from the experiences of others allows nurse researchers to glean insights about a particular phenomenon and maximizes the effectiveness of feedback and workplace learning (Neubauer et al.,  2019 ). In recent decades, ‘phenomenology’ has become a frequently used term in nursing research and phenomenology has become a key guiding philosophy in generating nursing‐related knowledge (Koivisto et al.,  2002 ; Moi & Gjengedal,  2008 ; Woodgate et al.,  2008 ). The phenomenological method, which emphasizes on lived experiences, has been deemed the closest fit conceptually to clinical nursing research as it provides a new way to interpret the nature of individual's consciousness and is commonly used to answer ‘what’ and ‘how’ questions in nursing science (Beck,  1994 ; Lopez & Willis,  2004 ; Neubauer et al.,  2019 ).

1.1. Background

Phenomenology is rooted in the philosophical tradition developed by Edmund Husserl in the early 20th century which was later expanded on by his followers at the universities in Germany and subsequently spread to the rest of the world (Zahavi,  2003 ). Husserl's ideas about how science should be conducted resulted in the development of a descriptive phenomenological inquiry method (Cohen,  1987 ), which is aligned with the naturalism doctrine that denies a strong separation between scientific and philosophical methodologies and rejects logical positivism's focus on objective observations of external reality (Freeman,  2021 ; Neubauer et al.,  2019 ). However, Husserl's concept of phenomenology has been criticized by other existentialists and philosophers, resulting in a variation of phenomenology types, such as the more renowned Heidegger's ( 1988 ) transcendental hermeneutic phenomenology and Maurice Merleau‐Ponty's ( 1965 ) embodied phenomenology.

Husserl argued that the focus of a study should be the phenomenon perceived by the individual's consciousness and that consciousness was central to all human experience. Husserl posits that the events or life situations that humans live through are held within one's consciousness prereflectively and that humans are able to reflect, discover and access this consciousness, thus bringing forward one's lifeworld or lived experience (Willis et al.,  2016 ). The common features of lived experiences of people who underwent the same event or life situation are labelled as universal essences or eidetic structures (Lopez & Willis,  2004 ). Therefore, the goal of descriptive phenomenology is to describe the universal essence of an experience as lived, which represents the true nature of the phenomenon (Lopez & Willis,  2004 ; Willis et al.,  2016 ).

Since the description of an individual's direct lived experience is central to Husserl's phenomenology, Husserl maintained that no assumptions, a priori scientific or philosophical theory, empirical science, deductive logic procedures should inform the phenomenology's inquiry (Lopez & Willis,  2004 ; Moran,  2002 ). Another tenet of Husserl's phenomenology is that humans are ‘free agents’ uninfluenced by the social and cultural environment they lived in, and thus nurse researchers should not pay attention to the socio‐cultural contexts of people being studied (Lopez & Willis,  2004 ; Matua & Van Der Wal,  2015 ; Wojnar & Swanson,  2007 ).

In descriptive phenomenology, the researcher's goal is to achieve transcendental subjectivity, described as a state where ‘the impact of the researcher on the inquiry is constantly assessed and biases and preconceptions neutralized, so that they do not influence the object of study’ (Lopez & Willis,  2004 ). This state can be achieved through phenomenological reduction that is facilitated by epoche (the process of bracketing). Bracketing requires researchers to hold off one's ideas in abeyance or bracket off assumptions, past knowledge and understanding of a phenomenon (Ashworth,  1996 ). Various types of bracketing have been mentioned in Gearing's ( 2004 ) study, such as ideal, descriptive, existential, analytic, reflexive and pragmatic bracketing. In order to bracket off biases and preconceived notions, some researchers even suggested not conducting a literature review before the initiation of the study and not having specific research questions that could potentially be leading (Speziale & Carpenter,  2011 ). The specific process to analyse collected data varies across researchers, with the most commonly used method being Colaizzi's ( 1978 ) and Giorg’s (2003) phenomenological analysis. Colaizzi's seven‐step approach include familiarization, identifying significant statements, formulating meanings, clustering themes, developing an exhaustive description and seeking verification of the fundamental structure (Morrow et al.,  2015 ), whereas Giorgi's five‐step approach include contemplative dwelling on descriptions, identifying meaning units, identifying focal meaning, synthesize situated structural descriptions and synthesize a general structural description (Aldiabat et al.,  2021 ; Giorgi & Giorgi,  2003 ; Russell & Aquino‐Russell,  2011 ).

An issue with many qualitative studies is the lack of relationship between the methodology used and the philosophical underpinnings that are supposed to guide the process (Lopez & Willis,  2004 ; Stubblefield & Murray,  2002 ). Previous research has tried to distinguish the types of qualitative research methods by drawing theoretical and methodological comparisons between qualitative description, interpretive phenomenology, descriptive phenomenology and hermeneutic phenomenology (Lopez & Willis,  2004 ; Matua & Van Der Wal,  2015 ; Neubauer et al.,  2019 ; Reiners,  2012 ; Willis et al.,  2016 ; Wojnar & Swanson,  2007 ). While valuable, it is uncertain whether researchers who practice descriptive phenomenology share the same understanding of the research design used. Therefore, it is imperative to consolidate an updated overview and evaluate the methodological consistency of peer‐reviewed studies that claimed to have used a descriptive phenomenological approach in the nursing context. Such reviews have been done for descriptive qualitative studies (Kim et al.,  2017 ) and phenomenological studies in the nursing context (Beck,  1994 ; Norlyk & Harder,  2010 ) where methodological approaches are compared across nursing studies with the same research design. Given the constant evolution of phenomenological methods and the increasing interest in nursing research, this review aims to consolidate updated evidence and comprehensively map the characteristics and methodology used in nursing research with descriptive phenomenological design to improve standardization and inform future nursing methodological research.

2. THE REVIEW

The aim of this review was to provide an overview and to evaluate the characteristics and methodology consistency in nursing research with descriptive phenomenological design.

2.2. Design

A scoping review was conducted to identify and map all relevant evidence on the use of descriptive phenomenological design in nursing research. A scoping review design was deemed the most appropriate as it aims to ‘map the literature on a particular topic or research area and provide an opportunity to identify key concepts; gaps in the research and types and sources of evidence to inform practice, policymaking and research’ (Daudt et al.,  2013 ). This review was guided by Arksey and O′Malley's ( 2005 ) five‐stage framework: identifying the research question, identifying relevant studies, study selection, charting the data and collating, summarizing and reporting the results. This review is reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta‐Analyses (PRISMA) Extension for Scoping Reviews (Tricco et al.,  2018 ). There is no registered protocol.

2.3. Search methods

In January 2022, three electronic databases (CINAHL, Embase and Pubmed) were searched for qualitative studies with a descriptive phenomenological design published between January 2021 and December 2021 in nursing journals. Given a large number of qualitative studies, we have narrowed the search to the most recent year, 2021, to include more updated and relevant research articles. Based on a research analytics tool, the 2021 Journal Citation Reports Science Edition (Clarivate Analytics, 2021 ), 181 journals were identified under the nursing category. In addition to the journal titles, search terms generated were derived from the concept ‘descriptive phenomenological’. The sample search strategy for PubMed is available in Material S1 and the representation of nursing journals indexed in each database is available in Material S2 .

Studies were included if they (i) explicitly mentioned using a descriptive phenomenological study design or analysis in the main text, (ii) published in 2021, (iii) published in the English language and (iv) published in one of the 181 nursing journals. Studies were excluded if they (i) were not of qualitative nature, or (ii) explicitly stated the use of an interpretive or hermeneutical phenomenological approach or other qualitative design. Ambiguous studies that have ‘descriptive qualitative phenomenological’ designs or ‘descriptive qualitative grounded in phenomenological approach’ were included. Online preprints that were available as of 31 December 2021 were included. Quantitative studies, reviews, pilot studies, protocols, editorials and conference abstracts were excluded.

2.4. Study selection

References and citations from the database search were exported into a reference management software, EndNote X9 (Clarivate Analytics), where duplicates were removed. Article titles and abstracts were then screened for relevance by two reviewers independently. The full texts of shortlisted articles were downloaded and assessed for eligibility against the inclusion and exclusion criteria by two reviewers. The interrater agreement was approximately 96% and any inconsistencies were resolved through discussions between both reviewers until a mutual consensus is reached

2.5. Quality appraisal

Quality appraisal of the finalized studies was conducted by two reviewers independently using the Critical Appraisal Skills Programme (CASP) qualitative checklist (CASP, 2019 ). The CASP tool is a generic and most used tool for quality appraisal in social and healthcare‐related qualitative evidence syntheses and is also endorsed by Cochrane and World Health Organization (Long et al.,  2020 ). Therefore, the CASP tool was chosen to appraise the rigour of the qualitative studies included in this study. The CASP tool consists of 10 main questions and several subquestions that examine the clarity and appropriateness of the study aim, research design (sampling, data collection, data analysis), and the presentation of results. As the CASP was used to gauge the overall rigour of included studies, no studies were excluded based on the CASP results.

2.6. Charting the data

A tabular data extraction form was created using Microsoft Excel with reference to a previous study (Kim et al.,  2017 ). The following data were extracted from each study: First author name, country of origin, research objective, design justification and consistency, theoretical framework, sampling method and sample size, data collection method, data analysis approach and presentation of findings. Data extraction was performed by one reviewer and cross‐checked with the second reviewer. Inconsistencies were resolved through discussion until a consensus is reached.

2.7. Collating, summarizing and reporting the results

The characteristics of the included studies are summarized in frequencies and percentages. Methodological consistency within and between studies and unique features observed from the extracted data will be discussed narratively. Extracted data from each study are presented in Table S1. Ethical approval and informed consent were not sought as no participants were recruited for this study. Given a large number of included studies, the references are provided in Material S3 .

3.1. Search outcomes

The initial search yielded 335 articles. After removal of duplicates, titles and abstracts of 154 articles were screened for relevance, and 124 full‐text articles were shortlisted and assessed for eligibility, resulting in 103 finalized articles being included in the study. The PRISMA diagram summarizing the screening process is found in Figure  1 .

PRISMA flow diagram

3.2. Characteristics of included studies

Of the 103 studies, the majority was conducted in Asia ( n  = 51, 50%), and North America ( n  = 27, 25%), followed by Europe ( n  = 15, 15%), Africa ( n  = 6, 6%), Oceania (i.e. Australia) ( n  = 3, 3%) and South America ( n  = 1, 1%). Six of the studies were post‐intervention studies (Ingersgaard et al.,  2021 ; Jensen et al.,  2021 ; Jerntorp et al.,  2021 ; Macapagal et al.,  2021 ; Mathews & Anderson,  2021 ; Schumacher et al.,  2021 ) and one was a part of a larger mix‐methods study (Mohaupt et al.,  2021 ).

3.3. Quality appraisal

All studies had a clear statement of research aims, but only 65 studies (63.1%) justified the use of a descriptive phenomenological research design and 78 (75.7%) studies elaborated on the participant selection process in addition to stating the sampling method and participant eligibility criteria. Although all studies clearly stated how data were collected, 74 (71.8%) did not justify the method chosen, and only 77 (74.8%) studies discussed data saturation. The examination of the relationship between researcher and participants for potential bias and influence was reported in 63 (61.2%) studies. Ethics approval was explicitly stated in 101 (98.1%) studies and 92 (89.3%) provided a detailed description of the data analysis process. All studies reported a clear statement of findings, but only 85 (82.5%) discussed the credibility, rigour or trustworthiness of their findings. The quality appraisal for each study is presented in Material S4 , whereas a summary of the quality appraisal is available in Table  1 .

Overall frequency of CASP scoring ( N  = 103)

3.4. Research objective

Across all 103 studies, the most used verbs in research objectives or aims were “explore” ( n  = 66, 64%), “describe” ( n  = 14, 14%), “understand” ( n  = 12, 12%) and “investigate” ( n  = 10, 10%). Lesser used verbs include “assess”, “determine”, “examine”, “explain”, “highlight” and “illuminate”. Most studies focused on more generic “experiences” ( n  = 44, 43%), or “lived experiences ( n  = 36, 35%), whereas a few others looked at “perceptions”, “coping strategies”, “meaning”, “challenges”, “perspectives”, “motivations”, “needs”, “impact”, “behaviour”, “practices” and “factors” related to a certain phenomenon (e.g. Covid‐19, online learning, caregiving) ( n  = 89, 86%) or nursing interventions and practices ( n  = 6, 6%).

3.5. Research design

Out of 103 studies, 81 (79%) studies explicitly mentioned using a ‘descriptive phenomenological’ research design or approach. Four studies reported a generic phenomenological research design but used a descriptive phenomenological data analysis technique (Ghorbani et al.,  2021 ; HeydariKhayat et al.,  2021 ; Luo et al.,  2021 ; Sun et al.,  2021 ). Ten studies reported being a descriptive, qualitative, or descriptive qualitative study ‘with’ or ‘grounded in’ a phenomenological approach. Although seven studies reported adopting a qualitative or descriptive qualitative approach, they proceeded to describe a descriptive phenomenological data analysis technique by Giorgi, Colaizzi or Sundler (Al Gilani et al.,  2021 ; Macapagal et al.,  2021 ; Nuuyoma & Makhene,  2021 ; Olander et al.,  2021 ; Othman et al.,  2021 ; Ratnawati & Rizaldi,  2021 ; Sundler et al., 2021 ). However, one study (George et al.,  2021 ) used a ‘phenomenological approach with descriptive thematic analysis’ without providing references.

Although 58 nurse researchers provided a reference to justify the use of their stated research design, 64 researchers described the rationale behind their choice of research design. The length of rationale descriptions ranged from one‐liner to a full paragraph, with the gist of it being able to explore the essence of the lived experience of a specific phenomenon, especially when little is known about the phenomenon.

3.6. Theoretical framework

Nine studies had other theoretical underpinnings that are unrelated to the descriptive phenomenological design. Woodley et al. ( 2021 ) used Choi's Theory of Cultural Marginality in the conceptualization of the study's purpose and research question. Jensen et al. ( 2021 ) used the stress‐vulnerability model and transtheoretical model of change as a basis for the development of an intervention. Corcoran et al. ( 2021 ) used Benner's Novice to Expert theory to determine the inclusion criteria of the study. Two studies used Lawrence Green's Behaviour Causes theory (Ratnawati & Rizaldi,  2021 ) and the Disablement Process model to develop interview guides (Seyman & Ozcetin,  2021 ), and six studies related their findings to theoretical frameworks (continuity theory, Carper's ways of knowing theory, symptom management theory, Khantzian's self‐medication hypothesis, Habermas' system and lifeworld, theory of communicative action, behaviour causes theory, disablement process model) in the discussion section (Aldiabat et al.,  2021 ; Carrasco,  2021 ; Ghelani,  2021 ; Ratnawati & Rizaldi,  2021 ; Ravn Jakobsen et al.,  2021 ; Seyman & Ozcetin,  2021 ).

However, Seyman and Ozcetin ( 2021 ) stated that the theoretical framework ‘guided the data analysis procedure’ and ‘helped in the construction of themes and subthemes’, which may be problematic from a descriptive phenomenology standpoint. Only Ghelani ( 2021 ) provided a disclaimer that ‘preconceptions were minimized in the study design through asking open‐ended questions and using dispassionate probes which did not reflect researcher assumptions’.

3.7. Sampling

In 57 out of 103 studies (55%), researchers mentioned using a ‘purposive sampling’ method. Other researchers used snowball sampling ( n  = 5, 5%), convenience sampling ( n  = 5, 5%), criterion sampling ( n  = 3, 3%), maximum variation sampling ( n  = 2, 2%), or a combination of various sampling methods (purposive and snowball, n  = 14, 14%; purposive and criterion, n  = 1, 1%; purposive and convenience, n  = 1, 1%, purposive and systematic random sampling, n  = 1, 1%, purposive and maximum variation, n  = 1, 1%, referral sampling, n  = 1, 1%). Twelve studies did not explicitly state the sampling method used.

Overall, sample size ranged from four to 62, where focus group studies had a larger sample size range of 15–62, and studies with individual data collection methods had a sample size range of four to 43. Participant recruitment till data saturation was discussed in 77 studies.

3.8. Data collection

Data collection was primarily done through individual interviews ( n  = 89, 86%), where most were semi‐structured ( n  = 72, 70%) and some were open‐ended ( n  = 6, 6%), or unstructured ( n  = 6, 6%) interviews. The interview duration ranged from 15 to 153 min across 64 studies that reported them. Individual interviews were mainly conducted face‐to‐face ( n  = 49, 48%), through telephone calls ( n  = 9, 9%), online means ( n  = 4, 4%) or a combination of the above ( n  = 7, 7%). Twenty studies did not specify the mode of interview. Eight studies conducted focus groups which lasted between 60 and 150 min. Two focus groups were conducted face‐to‐face, two were conducted online, and four studies did not specify. Three studies had multiple data collection methods such as a combination of individual and dyadic interviews (Olander et al.,  2021 ), or individual interviews and focus groups (Mathews & Anderson,  2021 ; Othman et al.,  2021 ). Other online data collection methods included open‐ended questionnaires (Vignato et al.,  2021 ), written narrative reflective inquiry (Schuler et al.,  2021 ), written complaints documented in a report (Sundler et al., 2021 ), written descriptions and illustrative examples (Aldiabat et al.,  2021 ) sent through email.

3.9. Data analysis

For data analysis, studies often adopted Colaizzi's ( 1978 ) seven‐step phenomenological approach ( n  = 55, 53%) or Giorgi and Giorgi's ( 2003 ) five‐step phenomenological approach ( n  = 14, 14%). However, one study used a modified Colaizzi's approach (Walker et al.,  2021 ). Another study only followed four out of Giorgi's five‐step approach as its ‘overall aim was not to discover the structure of a phenomenon’ (von Essen,  2021 ). Hycner's and Moustaka's phenomenological methods were used in two studies (Makgahlela et al.,  2021 ; Rygg et al.,  2021 ). Thematic analysis procedures especially by Braun and Clark (2006), Sundler et al. ( 2019 ), Spielberg ( 1975 ) were also commonly used ( n  = 16, 16%). Other data analytical procedures used were content analysis ( n  = 3, 3%), constant comparative method ( n  = 3, 3%), framework analysis/approach ( n  = 2, 2%), discourse analysis ( n  = 1, 1%), Tsech's protocol of data analysis ( n  = 1, 1%) and Maltreud's ( 2012 ) systematic text condensation ( n  = 1, 1%). Only one study did not disclose their analysis strategy, but the data analysis process was detailed (Yildirim,  2021 ). Interpretive phenomenological approaches were described in two studies despite them stating having a descriptive phenomenological research design (Arikan Dönmez et al.,  2021 ; Kurevakwesu,  2021 ).

Bracketing or reflexivity was taken into consideration only in 47 (46%) studies, mainly through reflective journaling or taking field notes. The process of ensuring the trustworthiness and credibility of research findings was described in 82 (80%) studies.

3.10. Presentation of findings

The research findings from all studies were presented in themes and subthemes accompanied with verbatim texts. The findings were described extensively and were consistent with their research objectives.

4. DISCUSSION

This review examined the characteristics and methodology consistency in nursing research with descriptive phenomenological design through the articles published in nursing journals between January 2021 and December 2021. The consolidation of studies revealed that most studies have characteristics that adhered to key features of the Husserlian phenomenology approach. However, inconsistencies between the stated research design and data analysis technique were observed in several studies.

4.1. Consistency of characteristics with descriptive phenomenology

In general, most studies adhered to the goal of descriptive phenomenological research, to ‘explore’ and ‘describe’ the generic ‘lived experiences’ of participants, answering to the ‘what’ and ‘how’ of a phenomenon of interest (Beck,  1994 ; Lopez & Willis,  2004 ). The term ‘lived experience’ remains unique to phenomenological studies and it is recommended for researchers to use this term in their research objective.

The majority of included studies did not report the use of another theoretical framework, adhering to Husserl's stance that no a priori theoretical or phenomenological framework should inform the phenomenological inquiry (Lopez & Willis,  2004 ). A few studies reported using other theories to guide their research methodology (i.e. inclusion criteria, interview guide, data analysis) or simply discuss their findings in relation to the theory. According to Husserl, the use of other theories to translate findings into accessible disciplinary knowledge is possible, however, these theories must be bracketed during the interview process (Willis et al.,  2016 ). The bracketing of preconceptions derived from other theories was only reported by Ghelani ( 2021 ).

Most studies used a purposive sampling technique which was lauded by descriptive phenomenology researchers as it is crucial to select participants who have had rich experiences related to the phenomenon of interest and have the cognitive capacity and ability to self‐reflect and express oneself adequately either written or verbally (Groenewald,  2018 ; Kruger & Stones,  1981 ; Willis et al.,  2016 ).

In this review, the sample size of included studies ranged from four to 62. Interestingly, there are no specific guidelines for sample size in descriptive phenomenological research yet. Creswell and Miller ( 2000 ) recommended between five and 25 participants for a phenomenological study, whereas Giorgi and Giorgi ( 2008 ) recommended at least three participants. Since the aim of a descriptive phenomenological approach is to explore in‐depth individual lived experiences of a phenomenon, the sample size should be determined by the quality and completeness of the information provided instead of the number of participants (Malterud et al.,  2016 ; Todres,  2005 ). Therefore, sampling should continue until data saturation is reached, which was what 70% of the included studies had reported.

Phenomenological interviews either individually or in focus groups are the most common data collection method reported in 95% of included studies. In descriptive phenomenology, although face‐to‐face interview is preferred to elicit ‘rich first‐person accounts of experience’, various data collection tools such as written narrative, online interviews, research diaries, open‐ended interviews or open‐ended questionnaires can also be used (Elliott & Timulak,  2005 ; Marshall & Rossman,  2014 ; Morrow et al.,  2015 ). Therefore, there is no specific guideline for the type of data collection method used.

In terms of data analysis, 73% of the studies adhered to established descriptive phenomenological approaches by Colaizzi ( 1978 ), Giorgi and Giorgi ( 2003 ), Moustakas (Moustakas,  1994 ) or Hycner (Groenewald,  2018 ; Hycner,  1985 ). The thematic analysis procedure for general qualitative studies by Braun and Clarke ( 2006 ), or more recently for descriptive phenomenological studies, by Sundler et al. ( 2019 ), was second most popular. Further research is needed to validate the appropriateness of other analytical methods such as discourse analysis and framework analysis in the context of descriptive phenomenology. The downside of not using a descriptive‐phenomenology‐specific analytical approach is the potential to neglect phenomenological reduction or bracketing, which is a key feature in descriptive phenomenology research. Startlingly, only less than half of the included studies reported bracketing. Although Merleau‐Ponty ( 1965 ) argued that a complete reduction or ‘pure’ bracketing can never be fully completed, it is still a necessary and important step to enhance rigour and to enable researchers to look beyond one's preconceptions and tap directly into the essence of a phenomenon (Matua & Van Der Wal,  2015 ).

4.2. Inconsistency in research design and analysis

Although most of the included studies explicitly stated having a descriptive phenomenological design, some studies provided vague statements with undertones of other qualitative designs, such as ‘descriptive qualitative study grounded in phenomenological approach’. Apart from the lack of clarity in the stated research design, some studies that reported using a descriptive phenomenology design ended up using an interpretive phenomenological analysis, discourse analysis or framework analysis, which are not congruent to a descriptive phenomenological design. Conversely, some studies reported having a descriptive qualitative research design but adopted Giorgi's or Colaizzi's descriptive phenomenological analysis method. These inconsistencies highlighted the confusion and potential knowledge gap of nurse researchers in utilizing a descriptive phenomenological approach, which necessitates more updated research and clear guidelines for descriptive phenomenological and qualitative studies in the nursing context.

Additionally, the justification of why a descriptive phenomenological approach was appropriate was lacking in half of the included studies. It is crucial for researchers to clarify and justify their choice of approach especially when examining participants' experiences, as this can easily be addressed with other qualitative approaches as well. The justification of research design and methodology could also enhance the rigour of the study as it allows others to evaluate for the choice for internal consistency, provides transparency of choices and context to the findings (Carter & Little,  2007 ).

A summary of practical implications to promote a standardized reporting of descriptive phenomenological method in nursing research is presented in Table  2 .

Summary of practical implications on the use of descriptive phenomenology method

4.3. Limitations

Although this review was able to provide an updated overview of descriptive phenomenological methodology in nursing studies, a few limitations exist. First, the narrow inclusion of only studies written in English, the small number of databases searched and the identification of nursing journals through a research analytics tool might have limited potentially relevant nursing studies. Second, a single year limit was used due to overwhelming number of studies and to gather more updated evidence, but this may result in the omission of previous relevant studies and limit the transferability of the findings. Additionally, there was uncertainty in the inclusion of studies that were inferred as descriptive phenomenology based on the research description or data analytical methods, which may have affected the results. Lastly, our findings are highly reliant on what is reported in the published studies, therefore, the methodological data available may be limited by word limits, or specific journal specifications, leaving out certain characteristics that could affect our CASP appraisal.

5. CONCLUSION

This review examined the characteristics and methodological consistencies of descriptive phenomenological nursing studies published in the year 2021. Overall, the characteristics of the studies are mostly consistent with Husserl's phenomenology approach in terms of research objectives, the use of other theoretical frameworks, sampling and data collection methods. However, the findings revealed several inconsistencies between research design and data analysis techniques, the lack of design justification and the lack of mention of bracketing. Apart from the need for more research and standardized guidelines to clarify the various qualitative research methods, future nurse researchers are urged to provide more methodological details when publishing a descriptive phenomenological study, so that readers can examine the appropriateness of the method. We hope this scoping review will pave a path for more conscientious planning, conducting and reporting and in turn better understanding among nurse researchers while adopting a descriptive phenomenology research design.

CONFLICT OF INTEREST

Author contributions.

Shefaly Shorey was involved in conceptualization, methodology and writing—reviewing and editing of the manuscript. Esperanza Debby Ng carried out investigation, data curation and writing—original draft of the manuscript.

PEER REVIEW

The peer review history for this article is available at https://publons.com/publon/10.1111/jan.15244 .

Supporting information

Shorey, S. & Ng, E. D. (2022). Examining characteristics of descriptive phenomenological nursing studies: A scoping review . Journal of Advanced Nursing , 78 , 1968–1979. 10.1111/jan.15244 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]

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11 Descriptive and interpretive approaches to qualitative research

• Published: June 2005
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This chapter explores descriptive and interpretive approaches to qualitative research. This includes the formulation of the problem, data collection, the specifics of sampling, data analysis in descriptive/interpretive qualitative research, generation of categories, and extracting and interpreting the main findings.

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