qualitative research peer reviewed articles

Qualitative Study

Affiliations.

• 1 University of Nebraska Medical Center
• 2 GDB Research and Statistical Consulting
• 3 GDB Research and Statistical Consulting/McLaren Macomb Hospital
• PMID: 29262162
• Bookshelf ID: NBK470395

Qualitative research is a type of research that explores and provides deeper insights into real-world problems. Instead of collecting numerical data points or intervene or introduce treatments just like in quantitative research, qualitative research helps generate hypotheses as well as further investigate and understand quantitative data. Qualitative research gathers participants' experiences, perceptions, and behavior. It answers the hows and whys instead of how many or how much. It could be structured as a stand-alone study, purely relying on qualitative data or it could be part of mixed-methods research that combines qualitative and quantitative data. This review introduces the readers to some basic concepts, definitions, terminology, and application of qualitative research.

Qualitative research at its core, ask open-ended questions whose answers are not easily put into numbers such as ‘how’ and ‘why’. Due to the open-ended nature of the research questions at hand, qualitative research design is often not linear in the same way quantitative design is. One of the strengths of qualitative research is its ability to explain processes and patterns of human behavior that can be difficult to quantify. Phenomena such as experiences, attitudes, and behaviors can be difficult to accurately capture quantitatively, whereas a qualitative approach allows participants themselves to explain how, why, or what they were thinking, feeling, and experiencing at a certain time or during an event of interest. Quantifying qualitative data certainly is possible, but at its core, qualitative data is looking for themes and patterns that can be difficult to quantify and it is important to ensure that the context and narrative of qualitative work are not lost by trying to quantify something that is not meant to be quantified.

However, while qualitative research is sometimes placed in opposition to quantitative research, where they are necessarily opposites and therefore ‘compete’ against each other and the philosophical paradigms associated with each, qualitative and quantitative work are not necessarily opposites nor are they incompatible. While qualitative and quantitative approaches are different, they are not necessarily opposites, and they are certainly not mutually exclusive. For instance, qualitative research can help expand and deepen understanding of data or results obtained from quantitative analysis. For example, say a quantitative analysis has determined that there is a correlation between length of stay and level of patient satisfaction, but why does this correlation exist? This dual-focus scenario shows one way in which qualitative and quantitative research could be integrated together.

Examples of Qualitative Research Approaches

Ethnography

Ethnography as a research design has its origins in social and cultural anthropology, and involves the researcher being directly immersed in the participant’s environment. Through this immersion, the ethnographer can use a variety of data collection techniques with the aim of being able to produce a comprehensive account of the social phenomena that occurred during the research period. That is to say, the researcher’s aim with ethnography is to immerse themselves into the research population and come out of it with accounts of actions, behaviors, events, etc. through the eyes of someone involved in the population. Direct involvement of the researcher with the target population is one benefit of ethnographic research because it can then be possible to find data that is otherwise very difficult to extract and record.

Grounded Theory

Grounded Theory is the “generation of a theoretical model through the experience of observing a study population and developing a comparative analysis of their speech and behavior.” As opposed to quantitative research which is deductive and tests or verifies an existing theory, grounded theory research is inductive and therefore lends itself to research that is aiming to study social interactions or experiences. In essence, Grounded Theory’s goal is to explain for example how and why an event occurs or how and why people might behave a certain way. Through observing the population, a researcher using the Grounded Theory approach can then develop a theory to explain the phenomena of interest.

Phenomenology

Phenomenology is defined as the “study of the meaning of phenomena or the study of the particular”. At first glance, it might seem that Grounded Theory and Phenomenology are quite similar, but upon careful examination, the differences can be seen. At its core, phenomenology looks to investigate experiences from the perspective of the individual. Phenomenology is essentially looking into the ‘lived experiences’ of the participants and aims to examine how and why participants behaved a certain way, from their perspective . Herein lies one of the main differences between Grounded Theory and Phenomenology. Grounded Theory aims to develop a theory for social phenomena through an examination of various data sources whereas Phenomenology focuses on describing and explaining an event or phenomena from the perspective of those who have experienced it.

Narrative Research

One of qualitative research’s strengths lies in its ability to tell a story, often from the perspective of those directly involved in it. Reporting on qualitative research involves including details and descriptions of the setting involved and quotes from participants. This detail is called ‘thick’ or ‘rich’ description and is a strength of qualitative research. Narrative research is rife with the possibilities of ‘thick’ description as this approach weaves together a sequence of events, usually from just one or two individuals, in the hopes of creating a cohesive story, or narrative. While it might seem like a waste of time to focus on such a specific, individual level, understanding one or two people’s narratives for an event or phenomenon can help to inform researchers about the influences that helped shape that narrative. The tension or conflict of differing narratives can be “opportunities for innovation”.

Research Paradigm

Research paradigms are the assumptions, norms, and standards that underpin different approaches to research. Essentially, research paradigms are the ‘worldview’ that inform research. It is valuable for researchers, both qualitative and quantitative, to understand what paradigm they are working within because understanding the theoretical basis of research paradigms allows researchers to understand the strengths and weaknesses of the approach being used and adjust accordingly. Different paradigms have different ontology and epistemologies . Ontology is defined as the "assumptions about the nature of reality” whereas epistemology is defined as the “assumptions about the nature of knowledge” that inform the work researchers do. It is important to understand the ontological and epistemological foundations of the research paradigm researchers are working within to allow for a full understanding of the approach being used and the assumptions that underpin the approach as a whole. Further, it is crucial that researchers understand their own ontological and epistemological assumptions about the world in general because their assumptions about the world will necessarily impact how they interact with research. A discussion of the research paradigm is not complete without describing positivist, postpositivist, and constructivist philosophies.

Positivist vs Postpositivist

To further understand qualitative research, we need to discuss positivist and postpositivist frameworks. Positivism is a philosophy that the scientific method can and should be applied to social as well as natural sciences. Essentially, positivist thinking insists that the social sciences should use natural science methods in its research which stems from positivist ontology that there is an objective reality that exists that is fully independent of our perception of the world as individuals. Quantitative research is rooted in positivist philosophy, which can be seen in the value it places on concepts such as causality, generalizability, and replicability.

Conversely, postpositivists argue that social reality can never be one hundred percent explained but it could be approximated. Indeed, qualitative researchers have been insisting that there are “fundamental limits to the extent to which the methods and procedures of the natural sciences could be applied to the social world” and therefore postpositivist philosophy is often associated with qualitative research. An example of positivist versus postpositivist values in research might be that positivist philosophies value hypothesis-testing, whereas postpositivist philosophies value the ability to formulate a substantive theory.

Constructivist

Constructivism is a subcategory of postpositivism. Most researchers invested in postpositivist research are constructivist as well, meaning they think there is no objective external reality that exists but rather that reality is constructed. Constructivism is a theoretical lens that emphasizes the dynamic nature of our world. “Constructivism contends that individuals’ views are directly influenced by their experiences, and it is these individual experiences and views that shape their perspective of reality”. Essentially, Constructivist thought focuses on how ‘reality’ is not a fixed certainty and experiences, interactions, and backgrounds give people a unique view of the world. Constructivism contends, unlike in positivist views, that there is not necessarily an ‘objective’ reality we all experience. This is the ‘relativist’ ontological view that reality and the world we live in are dynamic and socially constructed. Therefore, qualitative scientific knowledge can be inductive as well as deductive.”

So why is it important to understand the differences in assumptions that different philosophies and approaches to research have? Fundamentally, the assumptions underpinning the research tools a researcher selects provide an overall base for the assumptions the rest of the research will have and can even change the role of the researcher themselves. For example, is the researcher an ‘objective’ observer such as in positivist quantitative work? Or is the researcher an active participant in the research itself, as in postpositivist qualitative work? Understanding the philosophical base of the research undertaken allows researchers to fully understand the implications of their work and their role within the research, as well as reflect on their own positionality and bias as it pertains to the research they are conducting.

Data Sampling

The better the sample represents the intended study population, the more likely the researcher is to encompass the varying factors at play. The following are examples of participant sampling and selection:

Purposive sampling- selection based on the researcher’s rationale in terms of being the most informative.

Criterion sampling-selection based on pre-identified factors.

Convenience sampling- selection based on availability.

Snowball sampling- the selection is by referral from other participants or people who know potential participants.

Extreme case sampling- targeted selection of rare cases.

Typical case sampling-selection based on regular or average participants.

Data Collection and Analysis

Qualitative research uses several techniques including interviews, focus groups, and observation. [1] [2] [3] Interviews may be unstructured, with open-ended questions on a topic and the interviewer adapts to the responses. Structured interviews have a predetermined number of questions that every participant is asked. It is usually one on one and is appropriate for sensitive topics or topics needing an in-depth exploration. Focus groups are often held with 8-12 target participants and are used when group dynamics and collective views on a topic are desired. Researchers can be a participant-observer to share the experiences of the subject or a non-participant or detached observer.

While quantitative research design prescribes a controlled environment for data collection, qualitative data collection may be in a central location or in the environment of the participants, depending on the study goals and design. Qualitative research could amount to a large amount of data. Data is transcribed which may then be coded manually or with the use of Computer Assisted Qualitative Data Analysis Software or CAQDAS such as ATLAS.ti or NVivo.

After the coding process, qualitative research results could be in various formats. It could be a synthesis and interpretation presented with excerpts from the data. Results also could be in the form of themes and theory or model development.

Dissemination

To standardize and facilitate the dissemination of qualitative research outcomes, the healthcare team can use two reporting standards. The Consolidated Criteria for Reporting Qualitative Research or COREQ is a 32-item checklist for interviews and focus groups. The Standards for Reporting Qualitative Research (SRQR) is a checklist covering a wider range of qualitative research.

Examples of Application

Many times a research question will start with qualitative research. The qualitative research will help generate the research hypothesis which can be tested with quantitative methods. After the data is collected and analyzed with quantitative methods, a set of qualitative methods can be used to dive deeper into the data for a better understanding of what the numbers truly mean and their implications. The qualitative methods can then help clarify the quantitative data and also help refine the hypothesis for future research. Furthermore, with qualitative research researchers can explore subjects that are poorly studied with quantitative methods. These include opinions, individual's actions, and social science research.

A good qualitative study design starts with a goal or objective. This should be clearly defined or stated. The target population needs to be specified. A method for obtaining information from the study population must be carefully detailed to ensure there are no omissions of part of the target population. A proper collection method should be selected which will help obtain the desired information without overly limiting the collected data because many times, the information sought is not well compartmentalized or obtained. Finally, the design should ensure adequate methods for analyzing the data. An example may help better clarify some of the various aspects of qualitative research.

A researcher wants to decrease the number of teenagers who smoke in their community. The researcher could begin by asking current teen smokers why they started smoking through structured or unstructured interviews (qualitative research). The researcher can also get together a group of current teenage smokers and conduct a focus group to help brainstorm factors that may have prevented them from starting to smoke (qualitative research).

In this example, the researcher has used qualitative research methods (interviews and focus groups) to generate a list of ideas of both why teens start to smoke as well as factors that may have prevented them from starting to smoke. Next, the researcher compiles this data. The research found that, hypothetically, peer pressure, health issues, cost, being considered “cool,” and rebellious behavior all might increase or decrease the likelihood of teens starting to smoke.

The researcher creates a survey asking teen participants to rank how important each of the above factors is in either starting smoking (for current smokers) or not smoking (for current non-smokers). This survey provides specific numbers (ranked importance of each factor) and is thus a quantitative research tool.

The researcher can use the results of the survey to focus efforts on the one or two highest-ranked factors. Let us say the researcher found that health was the major factor that keeps teens from starting to smoke, and peer pressure was the major factor that contributed to teens to start smoking. The researcher can go back to qualitative research methods to dive deeper into each of these for more information. The researcher wants to focus on how to keep teens from starting to smoke, so they focus on the peer pressure aspect.

The researcher can conduct interviews and/or focus groups (qualitative research) about what types and forms of peer pressure are commonly encountered, where the peer pressure comes from, and where smoking first starts. The researcher hypothetically finds that peer pressure often occurs after school at the local teen hangouts, mostly the local park. The researcher also hypothetically finds that peer pressure comes from older, current smokers who provide the cigarettes.

The researcher could further explore this observation made at the local teen hangouts (qualitative research) and take notes regarding who is smoking, who is not, and what observable factors are at play for peer pressure of smoking. The researcher finds a local park where many local teenagers hang out and see that a shady, overgrown area of the park is where the smokers tend to hang out. The researcher notes the smoking teenagers buy their cigarettes from a local convenience store adjacent to the park where the clerk does not check identification before selling cigarettes. These observations fall under qualitative research.

If the researcher returns to the park and counts how many individuals smoke in each region of the park, this numerical data would be quantitative research. Based on the researcher's efforts thus far, they conclude that local teen smoking and teenagers who start to smoke may decrease if there are fewer overgrown areas of the park and the local convenience store does not sell cigarettes to underage individuals.

The researcher could try to have the parks department reassess the shady areas to make them less conducive to the smokers or identify how to limit the sales of cigarettes to underage individuals by the convenience store. The researcher would then cycle back to qualitative methods of asking at-risk population their perceptions of the changes, what factors are still at play, as well as quantitative research that includes teen smoking rates in the community, the incidence of new teen smokers, among others.

Copyright © 2024, StatPearls Publishing LLC.

• Introduction
• Issues of Concern
• Clinical Significance
• Enhancing Healthcare Team Outcomes
• Review Questions

Publication types

• Study Guide

What is Qualitative in Research

• Review Essay
• Open access
• Published: 28 October 2021
• Volume 44 , pages 599–608, ( 2021 )

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• Patrik Aspers 1 &
• Ugo Corte 2  

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In this text we respond and elaborate on the four comments addressing our original article. In that piece we define qualitative research as an “iterative process in which improved understanding to the scientific community is achieved by making new significant distinctions resulting from getting closer to the phenomenon studied.” In light of the comments, we identify three positions in relation to our contribution: (1) to not define qualitative research; (2) to work with one definition for each study or approach of “qualitative research” which is predominantly left implicit; (3) to systematically define qualitative research. This article elaborates on these positions and argues that a definition is a point of departure for researchers, including those reflecting on, or researching, the fields of qualitative and quantitative research. The proposed definition can be used both as a standard of evaluation as well as a catalyst for discussions on how to evaluate and innovate different styles of work.

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What is Qualitative in Qualitative Research

Patrik Aspers & Ugo Corte

What is “Qualitative” in Qualitative Research? Why the Answer Does not Matter but the Question is Important

Mario L. Small

Unsettling Definitions of Qualitative Research

Japonica Brown-Saracino

Avoid common mistakes on your manuscript.

The editors of Qualitative Sociology have given us the opportunity not only to receive comments by a group of particularly qualified scholars who engage with our text in a constructive fashion, but also to reply, and thereby to clarify our position. We have read the four essays that comment on our article What is qualitative in qualitative research (Aspers and Corte 2019 ) with great interest. Japonica Brown-Saracino, Paul Lichterman, Jennifer Reich, and Mario Luis Small agree that what we do is new. We are grateful for the engagement that the four commenters show with our text.

Our article is based on a standard approach: we pose a question drawing on our personal experiences and knowledge of the field, make systematic selections from existing literature, identify, collect and analyze data, read key texts closely, make interpretations, move between theory and evidence to connect them, and ultimately present a definition: “ qualitative research as an iterative process in which improved understanding to the scientific community is achieved by making new significant distinctions resulting from getting closer to the phenomenon studied” (Aspers and Corte 2019 , 139) . We acknowledge that there are different qualitative characteristics of research, meaning that we do not merely operate with a binary code of qualitative versus non-qualitative research. Our definition is an attempt to make a new distinction that clarifies what is qualitative in qualitative research and which is useful to the scientific community. Consequently, our work is in line with the definition that we have proposed.

Given the interest that our contribution has already generated, it is reasonable to argue that the new distinction we put forth is also significant . As researchers we make claims about significance, but it is always the audience—other scientists—who decide whether the contribution is significant or not. Iteration means that one goes back and forth between theory and evidence, and improved understanding refers to the epistemic gains of a study. To achieve this improved understanding by pursuing qualitative research, it is necessary that one gets close to the empirical material. When these four components are combined, we speak of qualitative research.

The four commentators welcome our text, which does not imply that they agree with all of the arguments we advance. In what follows, we single out some of the most important critiques we received and provide a reply aiming to push the conversation about qualitative research forward.

Why a Definition?

We appreciate that all critics have engaged closely with our definition. One main point of convergence between them is that one should not try to define qualitative research. Small ( Forthcoming ) asks rhetorically: “Is producing a single definition a good idea?” He justifies his concern by pointing out that the term is used to describe both different practices (different kinds of studies) and three elements (types of data; data collection, and analysis). Similarly, both Brown-Saracino ( Forthcoming ) and Lichterman, ( Forthcoming ) argue that not only there is no single entity called qualitative research—a view that we share, but instead, that definitions change over time. For Small, producing a single definition for a field as diverse as sociology, or the social sciences for that matter, is restrictive, a point which is also, albeit differently, shared by Brown-Saracino. Brown-Saracino asserts that our endeavor “might calcify boundaries, stifle innovation, and prevent recognition of areas of common ground across areas that many of us have long assumed to be disparate.” Hence, one should not define what is qualitative, because definitions may harm development. Both Small and Brown-Saracino say that we are drawing boundaries between qualitative and quantitative approaches and overstate differences between them. Yet, part of our intent was the opposite: to build bridges between different approaches by arguing that the ‘qualitative’ feature of research pertains both quantitative and qualitative methodologies, which may use and even combine different methods.

In light of these comments we need to elaborate our argument. Moreover, it is important not to maintain hard lines that may lead to scientific tribalism. Nonetheless, the critique of our—or any other definition of qualitative research—typically implies that there is something “there,” but that we have not captured it correctly with our definition. Thus, the critique that we should not define qualitative research comes with an implicit contradiction. If all agree that there is something called “qualitative research,” even if it is only something that is not quantitative, this still presumes that there is something called “qualitative.” Had we done research on any other topic it would probably have been requested by reviewers to define what we are talking about. The same criteria should apply also when we turn the researcher’s gaze on to our own practice.

Moreover, it is doubtful that our commentators would claim that qualitative research can be “anything,” as the more Dadaistic interpretation by Paul Feyerabend ( 1976 ) would have it. But without referring to the realist view of Karl Popper ( 1963 , 232–3) and his ideas of verisimilitude (i.e., that we get close to the truth) we have tried to spell out what we see as an account of the phenomenology of “qualitative.” We identify three positions in relation to the issue of definition of qualitative research:

We should not define qualitative research.

We can work with one definition for each study or approach of “qualitative research,” which is predominantly left implicit.

We can try to systematically define qualitative research.

Obviously, we have embraced and practiced position 3 in reaction to the current state of the field which is largely dominated by position 2--namely that what is qualitative research is open to a large variety of “definitions.” The critical points of our commentators explicitly or implicitly argue in favor of position 1, or perhaps position 2. Our claim that a definition can help researchers sort good from less good research has triggered criticism. Below, we elaborate on this issue.

We maintain that a definition is a valid starting point useful for junior scholars to learn more about what is qualitative and what is quantitative, and for more advanced researchers it may feature as a point of departure to make improvements, for instance, in clarifying their epistemological positions and goals. But we could have done a better job in clarifying our position. Nonetheless, we contend that change and improvement at this late stage of development in social sciences is partially related to and dependent upon pushing against or building upon clear benchmarks, such as the definition that we have formulated. We acknowledge that “definitions might evolve or diversify over time,” as Brown-Saracino suggests. Still, surely social scientists can keep two things in mind at the same time: an existing definition may be useful, but new research may change it. This becomes evident if one applies our definition to the definition itself: our definition is not immune to work that leads to new qualitative distinctions! Having said this, we are happy to see that all four comments profit from getting in close contact with the definition. This means that our definition and the article offer the reader an opportunity to think with (Fine and Corte 2022 ) or, as Small writes, “forces the reader to think.” We believe that both in principle and in practice, we all agree that clarity and definitions are scientific virtues.

What can a Definition Enable?

While we agree with several points in Small’s essay, we disagree on others. Our underlying assumption is that we can build on existing knowledge, albeit not in the way positivism envisioned it. It follows that work which is primarily descriptive, evocative, political, or generally aimed at social change may entail new knowledge, but it does not fit well within the frame within which we operate in this piece. The existence of different kinds of work, each of which relies on different standards of evaluation—which are often unclear and consequential, especially to graduate students and junior scholars (see Corte and Irwin 2017 )—brings us to another point highlighted by both Small and Lichterman: can the definition be used to differentiate good from lesser good kinds of work?

Small argues that while our article promises to develop a standard of evaluation, it fails to do so. We agree: our definition does not specify the exact criteria of what is good and what is poor research. Our definition demarcates qualitative research from non-qualitative by spelling out the qualitative elements of research, which advances a criterion of evaluation. In addition, there is definitely research that meets the characteristics of being qualitative, but that is uninteresting, irrelevant, or essentially useless (see Alvesson et al. 2017 on “gap spotting,” for instance). What is good or not good research  is to be decided in an ongoing scientific discussion led by those who actively contribute to the development of a field. A definition, nonetheless, can serve as a point of reference to evaluate scholarly work, and it can also serve as a guideline to demarcate what is qualitative from what it is not.

A Good Definition?

Even if one accepts that there should be a definition of qualitative research, and thinks that such a definition could be useful, it does not follow that one must accept our definition. Small identifies what he sees a paradox in our text, namely that we both speak of qualitative research in general and of qualitative elements in different research activities. The term qualitative, as we note and as Small specifies, is used to describe different things: from small n studies to studies of organizations, states, or other units conceptualized as case studies and analyzed quantitatively as well as qualitatively. We are grateful for this observation, which is correct. We failed to properly address this issue in the original text.

As we discuss in the article, the elements used in our definitions (distinctions, process, closeness, and improved understanding) are present in all kinds of research, even quantitative. Perhaps the title of our article should have been: “What is Qualitative in Research?” Our position is that only when all the elements of the definition are applied can one speak of qualitative research. Hence, the first order constructs (i.e., the constructs the actors in the field have made) (Aspers 2009 ) of, for example, “qualitative observations,” may indeed refer to observations that make qualitative distinction in the Aristotelian sense on which we rely. Still, if these qualitative observations are commensurated with a ratio-scale (i.e., get reduced to numbers) this research can no longer be called “qualitative.” It is for this reason that we say that, to refer to first order constructs, “quantitative” research processes entail “qualitative” elements. This research is, as it were, partially qualitative, but it is not, taken together, qualitative research. Brown-Saracino raises a similar point in relation to her own and others works that combine “qualitative” and “quantitative” research. We do not think that one is inherently better, yet we agree with the general idea that qualitative research is particularly useful in identifying research questions and formulating theories (distinctions) that, at a later point should, when possible, be tested quantitatively on larger samples (cf. Small 2005 ). It is our hope that, with our clarification above, it will be easier for researchers to understand what one is and what one is not doing. We also hope that our study will stimulate further dialogue and collaboration between researchers who primarily work within different traditions.

Small wonders if a researcher who tries to replicate a “qualitative” study (according to our definition) is doing qualitative research. The person is certainly doing research, and some elements are likely conducted in a qualitative fashion according to our definition, for example if the method of in-depth fieldwork is employed. But regardless of the method used, and regardless of whether the person finds new things, if the result is binary coded as either confirming or disconfirming existing research, qualitative research is not being conducted because no new distinction is offered. Imagine the same study being replicated for the 20 th time. Surely the researcher must use the same “qualitative” methods (to use the first order construct). It may even excite a large academic audience, but it would not count as qualitative research according to our definition. Our definition requires both that the research process has made use of all its elements, but it also requires the acceptance by the audience. Having said this, in practice, it is more likely that such a study would also report new distinctions that are acknowledged by an audience. If such a study is reviewed and published, these are additional indicators that the new distinctions are considered significant, at least to some extent: how much research space it opens up, and how much it helps other researchers continue the discussion by formulating their own questions and making their own claims (Collins 1998 , 31), whether by agreeing with it by applying it, by refining it (Snow et al. 2003 ), or by disagreeing and identifying new ways forward. There are two key characteristics that make a contribution relevant: newness and usefulness (Csikszentmihalyi 1996 ), both of which are related to the established state of knowledge within a field. Relatedly, Small asks: “Is newness enough? What does a new distinction that does not improve understanding look like?” There are also other indicators that demarcate whether a contribution is significant and to what extent. Some of these indicators include the number of citations a piece of work generates, the reputation of the journal or press where the work is published, and how widely the contribution is used—for instance, across specializations within the same discipline, or across different fields (i.e., different ways of valuation and evaluation) (Aspers and Beckert 2011 ) of scientific output. In principle, if a contribution ends up being used in an area where it would have unlikely been used, then one may further argue for its significance.

As it is implicit in our work when we talk about distinctions, we refer to theory building, albeit appreciating different conceptualizations and uses of the term theory (Abend 2008 ) and ways to achieve it (e.g., Zerubavel 2020 ). Brown-Saracino writes that our project may hold “the unintended consequence of limiting exploratory research designs and methodological innovations.” While we cannot predict the impact of our research, we are certainly in favor of experimentation and different styles of work. In line with David Snow, Calvin Morrill and Leon Anderson ( 2003 , 184), we argue that many qualitative researchers start their projects being underprepared in theory and theory development, oftentimes with the goal of describing, and leaving alone the black box of theory, or postponing it to later phases of the project. Our definition, along with the work by those authors and others on theory development, can be one way to heighten the chances researchers can make distinctions and develop theory.

Lichterman argues that we are not giving enough weight to interpretation and that we should relate more strongly to the larger project of the Geistenwissenschaften . We agree that interpretation is a key element in qualitative research, and we draw on Hans-Georg Gadamer ( 1988 ) who refined the idea of the hermeneutic circle.

Another critique, raised by Reich ( Forthcoming ), is that positionality is a key element of qualitative research. That in working towards a definition, we have “overlooked much of the methodological writings and contributions of women, scholars of color, and queer scholars” that could have enriched our definition, especially regarding “getting closer to the phenomenon studied.” Surely, the way we have searched for and included references means that we have ‘excluded’ the vast majority of research and researchers who do qualitative work. However, we have not included texts by some authors in our sample based on any specific characteristics or according to any specific position. This critique is valid only if Reich shows more explicitly what this inclusion would add to our definition.

Though we agree with much of what Reich says, for example about the role of bodies and reflexivity in ethnographic work, the idea of positionality as a normative notion is problematic. At least since Gadamer wrote in the early 1960s (1988), it is clear that there are no interpretations ‘from nowhere.’ Who one is cannot be bracketed in an interpretation of what has occurred. The scientific value of this more identity- and positionality-oriented research that accounts also of the positionality of the interpreter, is essentially already well acknowledged. Reflection is not just something that qualitative researcher do; it is a general aspect of research. Ethnographic researchers may need certain skills to get close and understand the phenomenon they study, yet they also need to maintain distance. As Fine and Hallett write: “The ethnographic stranger is uniquely positioned to be a broker in connecting the field with the academy, bringing the site into theory and, perhaps, permitting the academy to consider joint action with previously distant actors” (Fine and Hallett 2014 , 195). Moreover, Brown-Saracino illustrates well what it means to get close, and we too see that ethnography, in various forms and ways, is useful as other qualitative activities. Though ethnographic research cannot be quantitative, qualitative work is broader than solely ethnographic research. Furthermore, reflexivity is not something that one has to do when doing qualitative research, but something one does as a researcher.

Reich’s second point is more important. The claim is that if the standpoint-oriented argument is completely accepted, it will most likely violate what we see as the essence of research. We warned in our article that qualitative research may be treated as less scientific than quantitative within academia, but also in the general public, if too many in academia claim to be doing “qualitative research” while they are in fact telling stories, engaging in activism, or writing like journalists. Such approaches are extra problematic if only some people with certain characteristics are viewed as the only legitimate producers of certain types of knowledge. If these tendencies are fueled, it is not merely the definition of “qualitative” that is at stake, but what the great majority see as research in general. Science cannot reach “The Truth,” but if one gives up the idea communal and universal nature of scientific knowledge production and even a pragmatic notion of truth, much of its value and rationale of science as an independent sphere in society is lost (Merton 1973 ; Weber 1985 ). Ralf Dahrendorf framed this form of publicness by writing that: “Science is always a concert, a contrapuntal chorus of the many who are engaged in it. Insofar as truth exists at all, it exists not as a possession of the individual scholar, but as the net result of scientific interchange” (1968, 242–3). The issue of knowledge is a serious matter, but it is also another debate which relates to social sciences being low consensus fields (Collins 1994 ; Fuchs 1992 ; Parker and Corte 2017 , 276) in which the proliferation of journals and lack of agreement about common definitions, research methods, and interpretations of data contributes to knowledge fragmentation. To abandon the idea of community may also cause confusion, and piecemeal contributions while affording academics a means to communicate with a restricted in-group who speak their own small language and share their views among others of the same tribe, but without neither the risk nor possibility of gaining general public recognition. In contrast, we see knowledge as something public, that, ideal-typically, “can be seen and heard by everybody” (Arendt 1988 , 50), reflecting a pragmatic consensual approach to knowledge, but with this argument we are way beyond the theme of our article.

Our concern with qualitative research was triggered by the external critique of what is qualitative research and current debates in social science. Our definition, which deliberately tries to avoid making the use of a specific method or technique the essence of qualitative, can be used as a point of reference. In all the replies by Brown-Saracino, Lichterman, Reich, and Small, several examples of practices that are in line with our definition are given. Thus, the definition can be used to understand the practice of research, but it would also allow researchers to deliberately deviate from it and develop it. We are happy to see that all commentators have used our definition to move further, and in this pragmatic way the definition has already proved its value.

New research should be devoted to delineating standards and measures of evaluation for different kinds of work such as the those we have identified above: theoretical, descriptive, evocative, political, or aimed at social change (see Brady and Collier 2004; Ragin et al. 2004 ; Van Maanen 2011 ). And those standards could respectively be based upon scientific or stylistic advancement and social and societal impact. Footnote 1 Different work should be evaluated in relation to their respective canons, goals, and audiences, and there is certainly much to gain from learning from other perspectives. Relatedly, being fully aware of the research logics of both qualitative and quantitative traditions (Small 2005 ) is also an advantage for improving both of them and to spur further collaboration. Bringing further clarity on these points will ultimately improve different traditions, foster creativity potentially leading to innovative projects, and be useful both to younger researchers and established scholars.

The last two terms refer to whether the impacts are more micro as related to agency, or macro, as related to structural changes. An example of the latter kind is Matthew Desmond’s Eviction (2016) having substantial societal impact on public policy discussions, raising and researching a broader range of housing issues in the US. A case of the former is Arlie Hochchild’s studies on emotional labor of women in the workplace (1983) and her more recent book on the alienation of white, working-class Americans (2016).

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Acknowledgements

The authors are grateful for comments by Gary Alan Fine, Jukka Gronow, and John Parker.

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Aspers, P., Corte, U. What is Qualitative in Research. Qual Sociol 44 , 599–608 (2021). https://doi.org/10.1007/s11133-021-09497-w

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Social distancing requirements resulted in many people working from home in the United Kingdom during the COVID-19 pandemic. The topic of working from home was often discussed in the media and online during the pandemic, but little was known about how quality of life (QOL) and remote working interfaced. The purpose of this study was to describe QOL while working from home during the COVID-19 pandemic. The novel topic, unique methodological approach of the General Online Qualitative Study ( D’Abundo & Franco, 2022a), and the strategic Social Distancing Sampling ( D’Abundo & Franco, 2022c) resulted in significant participation throughout the world (n = 709). The United Kingdom subset of participants (n = 234) is the focus of this article. This big qual, large qualitative study (n >100) included the principal investigator-developed, open-ended, online questionnaire entitled the “Quality of Life Home Workplace Questionnaire (QOLHWQ)” and demographic questions. Data were collected peak-pandemic from July to September 2020. Most participants cited increased QOL due to having more time with family/kids/partners/pets, a more comfortable work environment while being at home, and less commuting to work. The most cited issue associated with negative QOL was social isolation. As restrictions have been lifted and public health emergency declarations have been terminated during the post-peak era of the COVID-19 pandemic, the potential for future public health emergencies requiring social distancing still exists. To promote QOL and work-life balance for employees working remotely in the United Kingdom, stakeholders could develop social support networks and create effective planning initiatives to prevent social isolation and maximize the benefits of remote working experiences for both employees and organizations.

Keywords: qualitative research, quality of life, remote work, telework, United Kingdom, work from home.

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This essay reviews classic works on the philosophy of science and contemporary pedagogical guides to scientific inquiry in order to present a discussion of the three logics that underlie qualitative research in political science. The first logic, epistemology, relates to the essence of research as a scientific endeavor and is framed as a debate between positivist and interpretivist orientations within the discipline of political science. The second logic, ontology, relates to the approach that research takes to investigating the empirical world and is framed as a debate between positivist qualitative and quantitative orientations, which together constitute the vast majority of mainstream researchers within the discipline. The third logic, methodology, relates to the means by which research aspires to reach its scientific ends and is framed as a debate among positivist qualitative orientations. Additionally, the essay discusses the present state of qualitative research in the discipline of political science, reviews the various ways in which qualitative research is defined in the relevant literature, addresses the limitations and trade-offs that are inherently associated with the aforementioned logics of qualitative research, explores multimethod approaches to remedying these issues, and proposes avenues for acquiring further information on the topics discussed.

Keywords: qualitative research, epistemology, ontology, methodology

This paper examines the phenomenology of diagnostic crossover in eating disorders, the movement within or between feeding and eating disorder subtypes or diagnoses over time, in two young women who experienced multiple changes in eating disorder diagnosis over 5 years. Using interpretative phenomenological analysis, this study found that transitioning between different diagnostic labels, specifically between bulimia nervosa and anorexia nervosa binge/purge subtype, was experienced as disempowering, stigmatizing, and unhelpful. The findings in this study offer novel evidence that, from the perspective of individuals diagnosed with EDs, using BMI as an indicator of the presence, severity, or change of an ED may have adverse consequences for well-being and recovery and may lead to mischaracterization or misclassification of health status. The narratives discussed in this paper highlight the need for more person-centered practices in the context of diagnostic crossover. Including the perspectives of those with lived experience can help care providers working with individuals with eating disorders gain an in-depth understanding of the potential personal impact of diagnosis changing and inform discussions around developing person-focused diagnostic practices.

Keywords: feeding and eating disorders, bulimia nervosa, diagnostic labels, diagnostic crossover, illness narrative

Often among the first witnesses to child trauma, educators and therapists are on the frontline of an unfolding and multi-pronged occupational crisis. For educators, lack of support and secondary traumatic stress (STS) appear to be contributing to an epidemic in professional attrition. Similarly, therapists who do not prioritize self-care can feel depleted of energy and optimism. The purpose of this phenomenological study was to examine how bearing witness to the traumatic narratives of children impacts similar helping professionals. The study also sought to extrapolate the similarities and differences between compassion fatigue and secondary trauma across these two disciplines. Exploring the common factors and subjective individual experiences related to occupational stress across these two fields may foster a more complete picture of the delicate nature of working with traumatized children and the importance of successful self-care strategies. Utilizing Constructivist Self-Development Theory (CSDT) and focus group interviews, the study explores the significant risk of STS facing both educators and therapists.

Keywords: qualitative, secondary traumatic stress, self-care, child trauma, educators, therapists.

This study explored the lived experiences of residents of the Gulf Coast in the USA during Hurricane Katrina, which made landfall in August 2005 and caused insurmountable destruction throughout the area. A heuristic process and thematic analysis were employed to draw observations and conclusions about the lived experiences of each participant and make meaning through similar thoughts, feelings, and themes that emerged in the analysis of the data. Six themes emerged: (1) fear, (2) loss, (3) anger, (4) support, (5) spirituality, and (6) resilience. The results of this study allude to the possible psychological outcomes as a result of experiencing a traumatic event and provide an outline of what the psychological experience of trauma might entail. The current research suggests that preparedness and expectation are key to resilience and that people who feel that they have power over their situation fare better than those who do not.

Keywords: mass trauma, resilience, loss, natural disaster, mental health.

Women from rural, low-income backgrounds holding positions within the academy are the exception and not the rule. Most women faculty in the academy are from urban/suburban areas and middle- and upper-income family backgrounds. As women faculty who do not represent this norm, our primary goal with this article is to focus on the unique barriers we experienced as girls from rural, low-income areas in K-12 schools that influenced the possibilities for successfully transitioning to and engaging with higher education. We employed a qualitative duoethnographic and narrative research design to respond to the research questions, and we generated our data through semi-structured, critical, ethnographic dialogic conversations. Our duoethnographic-narrative analyses revealed six major themes: (1) independence and other   benefits of having a working-class mom; (2) crashing into middle-class norms and expectations; (3) lucking and falling into college; (4) fish out of water; (5) overcompensating, playing middle class, walking on eggshells, and pushing back; and (6) transitioning from a working-class kid to a working class academic, which we discuss in relation to our own educational attainment.

Keywords: rurality, working-class, educational attainment, duoethnography, higher education, women.

This article draws on the findings of a qualitative study that focused on the perspectives of four Indian American mothers of youth with developmental disabilities on the process of transitioning from school to post-school environments. Data were collected through in-depth ethnographic interviews. The findings indicate that in their efforts to support their youth with developmental disabilities, the mothers themselves navigate multiple transitions across countries, constructs, dreams, systems of schooling, and services. The mothers’ perspectives have to be understood against the larger context of their experiences as citizens of this country as well as members of the South Asian diaspora. The mothers’ views on services, their journey, their dreams for their youth, and their interpretation of the ideas anchored in current conversations on transition are continually evolving. Their attempts to maintain their resilience and their indigenous understandings while simultaneously negotiating their experiences in the United States with supporting their youth are discussed.  

Keywords: Indian-American mothers, transitioning, diaspora, disability, dreams.

This study explored the influence of yoga on practitioners’ lives ‘off the mat’ through a phenomenological lens. Central to the study was the lived experience of yoga in a purposive sample of self-identified New Zealand practitioners (n=38; 89.5% female; aged 18 to 65 years; 60.5% aged 36 to 55 years). The study’s aim was to explore whether habitual yoga practitioners experience any pro-health downstream effects of their practice ‘off the mat’ via their lived experience of yoga. A qualitative mixed methodology was applied via a phenomenological lens that explicitly acknowledged the researcher’s own experience of the research topic. Qualitative methods comprised an open-ended online survey for all participants (n=38), followed by in-depth semi-structured interviews (n=8) on a randomized subset. Quantitative methods included online outcome measures (health habits, self-efficacy, interoceptive awareness, and physical activity), practice component data (tenure, dose, yoga styles, yoga teacher status, meditation frequency), and socio-demographics. This paper highlights the qualitative findings emerging from participant narratives. Reported benefits of practice included the provision of a filter through which to engage with life and the experience of self-regulation and mindfulness ‘off the mat’. Practitioners experienced yoga as a self-sustaining positive resource via self-regulation guided by an embodied awareness. The key narrative to emerge was an attunement to embodiment through movement. Embodied movement can elicit self-regulatory pathways that support health behavior.

Keywords: embodiment, habit, interoception, mindfulness, movement practice, qualitative, self-regulation, yoga.

Historically and in the present day, Black women’s positionality in the U.S. has paradoxically situated them in a society where they are both intrinsically essential and treated as expendable. This positionality, known as gendered racism, manifests commonly in professional environments and results in myriad harms. In response, Black women have developed, honed, and practiced a range of coping styles to mitigate the insidious effects of gendered racism. While often effective in the short-term, these techniques frequently complicate Black women’s well-being. For Black female clinicians who experience gendered racism and work on the frontlines of community mental health, myriad bio-psycho-social-spiritual harms compound. This project provided an opportunity for Black female clinicians from across the U.S. to share their experiences during the dual pandemics of COVID-19 and anti-Black violence. I conducted in-depth interviews with clinicians (n=14) between the ages of 30 and 58. Using the Listening Guide voice-centered approach to data generation and analysis, I identified four voices to help answer this project’s central question: How do you experience being a Black female clinician in the U.S.? The voices of self, pride, vigilance, and mediating narrated the complex ways participants experienced their workplaces. This complexity seemed to be context-specific, depending on whether the clinicians worked in predominantly White workplaces (PWW), a mix of PWW and private practice, or private practice exclusively. Participants who worked only in PWW experienced the greatest stress, oppression, and burnout risk, while participants who worked exclusively in private practice reported more joy, more authenticity, and more job satisfaction. These findings have implications for mentoring, supporting, and retaining Black female clinicians.

Keywords: Black female clinicians, professional experiences, gendered racism, Listening Guide voice-centered approach.

The purpose of this article is to speak directly to the paucity of research regarding Dominican American women and identity narratives. To do so, this article uses the Listening Guide Method of Qualitative Inquiry (Gilligan, et al., 2006) to explore how 1.5 and second-generation Dominican American women narrated their experiences of individual identity within American cultural contexts and constructs. The results draw from the emergence of themes across six participant interviews and showed two distinct voices: The Voice of Cultural Explanation and the Tides of Dominican American Female Identity. Narrative examples from five participants are offered to illustrate where 1.5 and second-generation Dominican American women negotiate their identity narratives at the intersection of their Dominican and American selves. The article offers two conclusions. One, that participant women use the Voice of Cultural Explanation in order to discuss their identity as reflected within the broad cultural tensions of their daily lives. Two, that the Tides of Dominican American Female Identity are used to express strong emotions that manifest within their personal narratives as the unwanted distance from either the Dominican or American parts of their person.

Keywords: Dominican American, women, identity, the Listening Guide, narratives

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• Published: 27 May 2020

How to use and assess qualitative research methods

• Loraine Busetto   ORCID: orcid.org/0000-0002-9228-7875 1 ,
• Wolfgang Wick 1 , 2 &
• Christoph Gumbinger 1  

Neurological Research and Practice volume  2 , Article number:  14 ( 2020 ) Cite this article

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This paper aims to provide an overview of the use and assessment of qualitative research methods in the health sciences. Qualitative research can be defined as the study of the nature of phenomena and is especially appropriate for answering questions of why something is (not) observed, assessing complex multi-component interventions, and focussing on intervention improvement. The most common methods of data collection are document study, (non-) participant observations, semi-structured interviews and focus groups. For data analysis, field-notes and audio-recordings are transcribed into protocols and transcripts, and coded using qualitative data management software. Criteria such as checklists, reflexivity, sampling strategies, piloting, co-coding, member-checking and stakeholder involvement can be used to enhance and assess the quality of the research conducted. Using qualitative in addition to quantitative designs will equip us with better tools to address a greater range of research problems, and to fill in blind spots in current neurological research and practice.

The aim of this paper is to provide an overview of qualitative research methods, including hands-on information on how they can be used, reported and assessed. This article is intended for beginning qualitative researchers in the health sciences as well as experienced quantitative researchers who wish to broaden their understanding of qualitative research.

What is qualitative research?

Qualitative research is defined as “the study of the nature of phenomena”, including “their quality, different manifestations, the context in which they appear or the perspectives from which they can be perceived” , but excluding “their range, frequency and place in an objectively determined chain of cause and effect” [ 1 ]. This formal definition can be complemented with a more pragmatic rule of thumb: qualitative research generally includes data in form of words rather than numbers [ 2 ].

Why conduct qualitative research?

Because some research questions cannot be answered using (only) quantitative methods. For example, one Australian study addressed the issue of why patients from Aboriginal communities often present late or not at all to specialist services offered by tertiary care hospitals. Using qualitative interviews with patients and staff, it found one of the most significant access barriers to be transportation problems, including some towns and communities simply not having a bus service to the hospital [ 3 ]. A quantitative study could have measured the number of patients over time or even looked at possible explanatory factors – but only those previously known or suspected to be of relevance. To discover reasons for observed patterns, especially the invisible or surprising ones, qualitative designs are needed.

While qualitative research is common in other fields, it is still relatively underrepresented in health services research. The latter field is more traditionally rooted in the evidence-based-medicine paradigm, as seen in " research that involves testing the effectiveness of various strategies to achieve changes in clinical practice, preferably applying randomised controlled trial study designs (...) " [ 4 ]. This focus on quantitative research and specifically randomised controlled trials (RCT) is visible in the idea of a hierarchy of research evidence which assumes that some research designs are objectively better than others, and that choosing a "lesser" design is only acceptable when the better ones are not practically or ethically feasible [ 5 , 6 ]. Others, however, argue that an objective hierarchy does not exist, and that, instead, the research design and methods should be chosen to fit the specific research question at hand – "questions before methods" [ 2 , 7 , 8 , 9 ]. This means that even when an RCT is possible, some research problems require a different design that is better suited to addressing them. Arguing in JAMA, Berwick uses the example of rapid response teams in hospitals, which he describes as " a complex, multicomponent intervention – essentially a process of social change" susceptible to a range of different context factors including leadership or organisation history. According to him, "[in] such complex terrain, the RCT is an impoverished way to learn. Critics who use it as a truth standard in this context are incorrect" [ 8 ] . Instead of limiting oneself to RCTs, Berwick recommends embracing a wider range of methods , including qualitative ones, which for "these specific applications, (...) are not compromises in learning how to improve; they are superior" [ 8 ].

Research problems that can be approached particularly well using qualitative methods include assessing complex multi-component interventions or systems (of change), addressing questions beyond “what works”, towards “what works for whom when, how and why”, and focussing on intervention improvement rather than accreditation [ 7 , 9 , 10 , 11 , 12 ]. Using qualitative methods can also help shed light on the “softer” side of medical treatment. For example, while quantitative trials can measure the costs and benefits of neuro-oncological treatment in terms of survival rates or adverse effects, qualitative research can help provide a better understanding of patient or caregiver stress, visibility of illness or out-of-pocket expenses.

How to conduct qualitative research?

Given that qualitative research is characterised by flexibility, openness and responsivity to context, the steps of data collection and analysis are not as separate and consecutive as they tend to be in quantitative research [ 13 , 14 ]. As Fossey puts it : “sampling, data collection, analysis and interpretation are related to each other in a cyclical (iterative) manner, rather than following one after another in a stepwise approach” [ 15 ]. The researcher can make educated decisions with regard to the choice of method, how they are implemented, and to which and how many units they are applied [ 13 ]. As shown in Fig.  1 , this can involve several back-and-forth steps between data collection and analysis where new insights and experiences can lead to adaption and expansion of the original plan. Some insights may also necessitate a revision of the research question and/or the research design as a whole. The process ends when saturation is achieved, i.e. when no relevant new information can be found (see also below: sampling and saturation). For reasons of transparency, it is essential for all decisions as well as the underlying reasoning to be well-documented.

Iterative research process

While it is not always explicitly addressed, qualitative methods reflect a different underlying research paradigm than quantitative research (e.g. constructivism or interpretivism as opposed to positivism). The choice of methods can be based on the respective underlying substantive theory or theoretical framework used by the researcher [ 2 ].

Data collection

The methods of qualitative data collection most commonly used in health research are document study, observations, semi-structured interviews and focus groups [ 1 , 14 , 16 , 17 ].

Document study

Document study (also called document analysis) refers to the review by the researcher of written materials [ 14 ]. These can include personal and non-personal documents such as archives, annual reports, guidelines, policy documents, diaries or letters.

Observations

Observations are particularly useful to gain insights into a certain setting and actual behaviour – as opposed to reported behaviour or opinions [ 13 ]. Qualitative observations can be either participant or non-participant in nature. In participant observations, the observer is part of the observed setting, for example a nurse working in an intensive care unit [ 18 ]. In non-participant observations, the observer is “on the outside looking in”, i.e. present in but not part of the situation, trying not to influence the setting by their presence. Observations can be planned (e.g. for 3 h during the day or night shift) or ad hoc (e.g. as soon as a stroke patient arrives at the emergency room). During the observation, the observer takes notes on everything or certain pre-determined parts of what is happening around them, for example focusing on physician-patient interactions or communication between different professional groups. Written notes can be taken during or after the observations, depending on feasibility (which is usually lower during participant observations) and acceptability (e.g. when the observer is perceived to be judging the observed). Afterwards, these field notes are transcribed into observation protocols. If more than one observer was involved, field notes are taken independently, but notes can be consolidated into one protocol after discussions. Advantages of conducting observations include minimising the distance between the researcher and the researched, the potential discovery of topics that the researcher did not realise were relevant and gaining deeper insights into the real-world dimensions of the research problem at hand [ 18 ].

Semi-structured interviews

Hijmans & Kuyper describe qualitative interviews as “an exchange with an informal character, a conversation with a goal” [ 19 ]. Interviews are used to gain insights into a person’s subjective experiences, opinions and motivations – as opposed to facts or behaviours [ 13 ]. Interviews can be distinguished by the degree to which they are structured (i.e. a questionnaire), open (e.g. free conversation or autobiographical interviews) or semi-structured [ 2 , 13 ]. Semi-structured interviews are characterized by open-ended questions and the use of an interview guide (or topic guide/list) in which the broad areas of interest, sometimes including sub-questions, are defined [ 19 ]. The pre-defined topics in the interview guide can be derived from the literature, previous research or a preliminary method of data collection, e.g. document study or observations. The topic list is usually adapted and improved at the start of the data collection process as the interviewer learns more about the field [ 20 ]. Across interviews the focus on the different (blocks of) questions may differ and some questions may be skipped altogether (e.g. if the interviewee is not able or willing to answer the questions or for concerns about the total length of the interview) [ 20 ]. Qualitative interviews are usually not conducted in written format as it impedes on the interactive component of the method [ 20 ]. In comparison to written surveys, qualitative interviews have the advantage of being interactive and allowing for unexpected topics to emerge and to be taken up by the researcher. This can also help overcome a provider or researcher-centred bias often found in written surveys, which by nature, can only measure what is already known or expected to be of relevance to the researcher. Interviews can be audio- or video-taped; but sometimes it is only feasible or acceptable for the interviewer to take written notes [ 14 , 16 , 20 ].

Focus groups

Focus groups are group interviews to explore participants’ expertise and experiences, including explorations of how and why people behave in certain ways [ 1 ]. Focus groups usually consist of 6–8 people and are led by an experienced moderator following a topic guide or “script” [ 21 ]. They can involve an observer who takes note of the non-verbal aspects of the situation, possibly using an observation guide [ 21 ]. Depending on researchers’ and participants’ preferences, the discussions can be audio- or video-taped and transcribed afterwards [ 21 ]. Focus groups are useful for bringing together homogeneous (to a lesser extent heterogeneous) groups of participants with relevant expertise and experience on a given topic on which they can share detailed information [ 21 ]. Focus groups are a relatively easy, fast and inexpensive method to gain access to information on interactions in a given group, i.e. “the sharing and comparing” among participants [ 21 ]. Disadvantages include less control over the process and a lesser extent to which each individual may participate. Moreover, focus group moderators need experience, as do those tasked with the analysis of the resulting data. Focus groups can be less appropriate for discussing sensitive topics that participants might be reluctant to disclose in a group setting [ 13 ]. Moreover, attention must be paid to the emergence of “groupthink” as well as possible power dynamics within the group, e.g. when patients are awed or intimidated by health professionals.

Choosing the “right” method

As explained above, the school of thought underlying qualitative research assumes no objective hierarchy of evidence and methods. This means that each choice of single or combined methods has to be based on the research question that needs to be answered and a critical assessment with regard to whether or to what extent the chosen method can accomplish this – i.e. the “fit” between question and method [ 14 ]. It is necessary for these decisions to be documented when they are being made, and to be critically discussed when reporting methods and results.

Let us assume that our research aim is to examine the (clinical) processes around acute endovascular treatment (EVT), from the patient’s arrival at the emergency room to recanalization, with the aim to identify possible causes for delay and/or other causes for sub-optimal treatment outcome. As a first step, we could conduct a document study of the relevant standard operating procedures (SOPs) for this phase of care – are they up-to-date and in line with current guidelines? Do they contain any mistakes, irregularities or uncertainties that could cause delays or other problems? Regardless of the answers to these questions, the results have to be interpreted based on what they are: a written outline of what care processes in this hospital should look like. If we want to know what they actually look like in practice, we can conduct observations of the processes described in the SOPs. These results can (and should) be analysed in themselves, but also in comparison to the results of the document analysis, especially as regards relevant discrepancies. Do the SOPs outline specific tests for which no equipment can be observed or tasks to be performed by specialized nurses who are not present during the observation? It might also be possible that the written SOP is outdated, but the actual care provided is in line with current best practice. In order to find out why these discrepancies exist, it can be useful to conduct interviews. Are the physicians simply not aware of the SOPs (because their existence is limited to the hospital’s intranet) or do they actively disagree with them or does the infrastructure make it impossible to provide the care as described? Another rationale for adding interviews is that some situations (or all of their possible variations for different patient groups or the day, night or weekend shift) cannot practically or ethically be observed. In this case, it is possible to ask those involved to report on their actions – being aware that this is not the same as the actual observation. A senior physician’s or hospital manager’s description of certain situations might differ from a nurse’s or junior physician’s one, maybe because they intentionally misrepresent facts or maybe because different aspects of the process are visible or important to them. In some cases, it can also be relevant to consider to whom the interviewee is disclosing this information – someone they trust, someone they are otherwise not connected to, or someone they suspect or are aware of being in a potentially “dangerous” power relationship to them. Lastly, a focus group could be conducted with representatives of the relevant professional groups to explore how and why exactly they provide care around EVT. The discussion might reveal discrepancies (between SOPs and actual care or between different physicians) and motivations to the researchers as well as to the focus group members that they might not have been aware of themselves. For the focus group to deliver relevant information, attention has to be paid to its composition and conduct, for example, to make sure that all participants feel safe to disclose sensitive or potentially problematic information or that the discussion is not dominated by (senior) physicians only. The resulting combination of data collection methods is shown in Fig.  2 .

Possible combination of data collection methods

Attributions for icons: “Book” by Serhii Smirnov, “Interview” by Adrien Coquet, FR, “Magnifying Glass” by anggun, ID, “Business communication” by Vectors Market; all from the Noun Project

The combination of multiple data source as described for this example can be referred to as “triangulation”, in which multiple measurements are carried out from different angles to achieve a more comprehensive understanding of the phenomenon under study [ 22 , 23 ].

Data analysis

To analyse the data collected through observations, interviews and focus groups these need to be transcribed into protocols and transcripts (see Fig.  3 ). Interviews and focus groups can be transcribed verbatim , with or without annotations for behaviour (e.g. laughing, crying, pausing) and with or without phonetic transcription of dialects and filler words, depending on what is expected or known to be relevant for the analysis. In the next step, the protocols and transcripts are coded , that is, marked (or tagged, labelled) with one or more short descriptors of the content of a sentence or paragraph [ 2 , 15 , 23 ]. Jansen describes coding as “connecting the raw data with “theoretical” terms” [ 20 ]. In a more practical sense, coding makes raw data sortable. This makes it possible to extract and examine all segments describing, say, a tele-neurology consultation from multiple data sources (e.g. SOPs, emergency room observations, staff and patient interview). In a process of synthesis and abstraction, the codes are then grouped, summarised and/or categorised [ 15 , 20 ]. The end product of the coding or analysis process is a descriptive theory of the behavioural pattern under investigation [ 20 ]. The coding process is performed using qualitative data management software, the most common ones being InVivo, MaxQDA and Atlas.ti. It should be noted that these are data management tools which support the analysis performed by the researcher(s) [ 14 ].

From data collection to data analysis

Attributions for icons: see Fig. 2 , also “Speech to text” by Trevor Dsouza, “Field Notes” by Mike O’Brien, US, “Voice Record” by ProSymbols, US, “Inspection” by Made, AU, and “Cloud” by Graphic Tigers; all from the Noun Project

How to report qualitative research?

Protocols of qualitative research can be published separately and in advance of the study results. However, the aim is not the same as in RCT protocols, i.e. to pre-define and set in stone the research questions and primary or secondary endpoints. Rather, it is a way to describe the research methods in detail, which might not be possible in the results paper given journals’ word limits. Qualitative research papers are usually longer than their quantitative counterparts to allow for deep understanding and so-called “thick description”. In the methods section, the focus is on transparency of the methods used, including why, how and by whom they were implemented in the specific study setting, so as to enable a discussion of whether and how this may have influenced data collection, analysis and interpretation. The results section usually starts with a paragraph outlining the main findings, followed by more detailed descriptions of, for example, the commonalities, discrepancies or exceptions per category [ 20 ]. Here it is important to support main findings by relevant quotations, which may add information, context, emphasis or real-life examples [ 20 , 23 ]. It is subject to debate in the field whether it is relevant to state the exact number or percentage of respondents supporting a certain statement (e.g. “Five interviewees expressed negative feelings towards XYZ”) [ 21 ].

How to combine qualitative with quantitative research?

Qualitative methods can be combined with other methods in multi- or mixed methods designs, which “[employ] two or more different methods [ …] within the same study or research program rather than confining the research to one single method” [ 24 ]. Reasons for combining methods can be diverse, including triangulation for corroboration of findings, complementarity for illustration and clarification of results, expansion to extend the breadth and range of the study, explanation of (unexpected) results generated with one method with the help of another, or offsetting the weakness of one method with the strength of another [ 1 , 17 , 24 , 25 , 26 ]. The resulting designs can be classified according to when, why and how the different quantitative and/or qualitative data strands are combined. The three most common types of mixed method designs are the convergent parallel design , the explanatory sequential design and the exploratory sequential design. The designs with examples are shown in Fig.  4 .

Three common mixed methods designs

In the convergent parallel design, a qualitative study is conducted in parallel to and independently of a quantitative study, and the results of both studies are compared and combined at the stage of interpretation of results. Using the above example of EVT provision, this could entail setting up a quantitative EVT registry to measure process times and patient outcomes in parallel to conducting the qualitative research outlined above, and then comparing results. Amongst other things, this would make it possible to assess whether interview respondents’ subjective impressions of patients receiving good care match modified Rankin Scores at follow-up, or whether observed delays in care provision are exceptions or the rule when compared to door-to-needle times as documented in the registry. In the explanatory sequential design, a quantitative study is carried out first, followed by a qualitative study to help explain the results from the quantitative study. This would be an appropriate design if the registry alone had revealed relevant delays in door-to-needle times and the qualitative study would be used to understand where and why these occurred, and how they could be improved. In the exploratory design, the qualitative study is carried out first and its results help informing and building the quantitative study in the next step [ 26 ]. If the qualitative study around EVT provision had shown a high level of dissatisfaction among the staff members involved, a quantitative questionnaire investigating staff satisfaction could be set up in the next step, informed by the qualitative study on which topics dissatisfaction had been expressed. Amongst other things, the questionnaire design would make it possible to widen the reach of the research to more respondents from different (types of) hospitals, regions, countries or settings, and to conduct sub-group analyses for different professional groups.

How to assess qualitative research?

A variety of assessment criteria and lists have been developed for qualitative research, ranging in their focus and comprehensiveness [ 14 , 17 , 27 ]. However, none of these has been elevated to the “gold standard” in the field. In the following, we therefore focus on a set of commonly used assessment criteria that, from a practical standpoint, a researcher can look for when assessing a qualitative research report or paper.

Assessors should check the authors’ use of and adherence to the relevant reporting checklists (e.g. Standards for Reporting Qualitative Research (SRQR)) to make sure all items that are relevant for this type of research are addressed [ 23 , 28 ]. Discussions of quantitative measures in addition to or instead of these qualitative measures can be a sign of lower quality of the research (paper). Providing and adhering to a checklist for qualitative research contributes to an important quality criterion for qualitative research, namely transparency [ 15 , 17 , 23 ].

Reflexivity

While methodological transparency and complete reporting is relevant for all types of research, some additional criteria must be taken into account for qualitative research. This includes what is called reflexivity, i.e. sensitivity to the relationship between the researcher and the researched, including how contact was established and maintained, or the background and experience of the researcher(s) involved in data collection and analysis. Depending on the research question and population to be researched this can be limited to professional experience, but it may also include gender, age or ethnicity [ 17 , 27 ]. These details are relevant because in qualitative research, as opposed to quantitative research, the researcher as a person cannot be isolated from the research process [ 23 ]. It may influence the conversation when an interviewed patient speaks to an interviewer who is a physician, or when an interviewee is asked to discuss a gynaecological procedure with a male interviewer, and therefore the reader must be made aware of these details [ 19 ].

Sampling and saturation

The aim of qualitative sampling is for all variants of the objects of observation that are deemed relevant for the study to be present in the sample “ to see the issue and its meanings from as many angles as possible” [ 1 , 16 , 19 , 20 , 27 ] , and to ensure “information-richness [ 15 ]. An iterative sampling approach is advised, in which data collection (e.g. five interviews) is followed by data analysis, followed by more data collection to find variants that are lacking in the current sample. This process continues until no new (relevant) information can be found and further sampling becomes redundant – which is called saturation [ 1 , 15 ] . In other words: qualitative data collection finds its end point not a priori , but when the research team determines that saturation has been reached [ 29 , 30 ].

This is also the reason why most qualitative studies use deliberate instead of random sampling strategies. This is generally referred to as “ purposive sampling” , in which researchers pre-define which types of participants or cases they need to include so as to cover all variations that are expected to be of relevance, based on the literature, previous experience or theory (i.e. theoretical sampling) [ 14 , 20 ]. Other types of purposive sampling include (but are not limited to) maximum variation sampling, critical case sampling or extreme or deviant case sampling [ 2 ]. In the above EVT example, a purposive sample could include all relevant professional groups and/or all relevant stakeholders (patients, relatives) and/or all relevant times of observation (day, night and weekend shift).

Assessors of qualitative research should check whether the considerations underlying the sampling strategy were sound and whether or how researchers tried to adapt and improve their strategies in stepwise or cyclical approaches between data collection and analysis to achieve saturation [ 14 ].

Good qualitative research is iterative in nature, i.e. it goes back and forth between data collection and analysis, revising and improving the approach where necessary. One example of this are pilot interviews, where different aspects of the interview (especially the interview guide, but also, for example, the site of the interview or whether the interview can be audio-recorded) are tested with a small number of respondents, evaluated and revised [ 19 ]. In doing so, the interviewer learns which wording or types of questions work best, or which is the best length of an interview with patients who have trouble concentrating for an extended time. Of course, the same reasoning applies to observations or focus groups which can also be piloted.

Ideally, coding should be performed by at least two researchers, especially at the beginning of the coding process when a common approach must be defined, including the establishment of a useful coding list (or tree), and when a common meaning of individual codes must be established [ 23 ]. An initial sub-set or all transcripts can be coded independently by the coders and then compared and consolidated after regular discussions in the research team. This is to make sure that codes are applied consistently to the research data.

Member checking

Member checking, also called respondent validation , refers to the practice of checking back with study respondents to see if the research is in line with their views [ 14 , 27 ]. This can happen after data collection or analysis or when first results are available [ 23 ]. For example, interviewees can be provided with (summaries of) their transcripts and asked whether they believe this to be a complete representation of their views or whether they would like to clarify or elaborate on their responses [ 17 ]. Respondents’ feedback on these issues then becomes part of the data collection and analysis [ 27 ].

Stakeholder involvement

In those niches where qualitative approaches have been able to evolve and grow, a new trend has seen the inclusion of patients and their representatives not only as study participants (i.e. “members”, see above) but as consultants to and active participants in the broader research process [ 31 , 32 , 33 ]. The underlying assumption is that patients and other stakeholders hold unique perspectives and experiences that add value beyond their own single story, making the research more relevant and beneficial to researchers, study participants and (future) patients alike [ 34 , 35 ]. Using the example of patients on or nearing dialysis, a recent scoping review found that 80% of clinical research did not address the top 10 research priorities identified by patients and caregivers [ 32 , 36 ]. In this sense, the involvement of the relevant stakeholders, especially patients and relatives, is increasingly being seen as a quality indicator in and of itself.

How not to assess qualitative research

The above overview does not include certain items that are routine in assessments of quantitative research. What follows is a non-exhaustive, non-representative, experience-based list of the quantitative criteria often applied to the assessment of qualitative research, as well as an explanation of the limited usefulness of these endeavours.

Protocol adherence

Given the openness and flexibility of qualitative research, it should not be assessed by how well it adheres to pre-determined and fixed strategies – in other words: its rigidity. Instead, the assessor should look for signs of adaptation and refinement based on lessons learned from earlier steps in the research process.

Sample size

For the reasons explained above, qualitative research does not require specific sample sizes, nor does it require that the sample size be determined a priori [ 1 , 14 , 27 , 37 , 38 , 39 ]. Sample size can only be a useful quality indicator when related to the research purpose, the chosen methodology and the composition of the sample, i.e. who was included and why.

Randomisation

While some authors argue that randomisation can be used in qualitative research, this is not commonly the case, as neither its feasibility nor its necessity or usefulness has been convincingly established for qualitative research [ 13 , 27 ]. Relevant disadvantages include the negative impact of a too large sample size as well as the possibility (or probability) of selecting “ quiet, uncooperative or inarticulate individuals ” [ 17 ]. Qualitative studies do not use control groups, either.

Interrater reliability, variability and other “objectivity checks”

The concept of “interrater reliability” is sometimes used in qualitative research to assess to which extent the coding approach overlaps between the two co-coders. However, it is not clear what this measure tells us about the quality of the analysis [ 23 ]. This means that these scores can be included in qualitative research reports, preferably with some additional information on what the score means for the analysis, but it is not a requirement. Relatedly, it is not relevant for the quality or “objectivity” of qualitative research to separate those who recruited the study participants and collected and analysed the data. Experiences even show that it might be better to have the same person or team perform all of these tasks [ 20 ]. First, when researchers introduce themselves during recruitment this can enhance trust when the interview takes place days or weeks later with the same researcher. Second, when the audio-recording is transcribed for analysis, the researcher conducting the interviews will usually remember the interviewee and the specific interview situation during data analysis. This might be helpful in providing additional context information for interpretation of data, e.g. on whether something might have been meant as a joke [ 18 ].

Not being quantitative research

Being qualitative research instead of quantitative research should not be used as an assessment criterion if it is used irrespectively of the research problem at hand. Similarly, qualitative research should not be required to be combined with quantitative research per se – unless mixed methods research is judged as inherently better than single-method research. In this case, the same criterion should be applied for quantitative studies without a qualitative component.

The main take-away points of this paper are summarised in Table 1 . We aimed to show that, if conducted well, qualitative research can answer specific research questions that cannot to be adequately answered using (only) quantitative designs. Seeing qualitative and quantitative methods as equal will help us become more aware and critical of the “fit” between the research problem and our chosen methods: I can conduct an RCT to determine the reasons for transportation delays of acute stroke patients – but should I? It also provides us with a greater range of tools to tackle a greater range of research problems more appropriately and successfully, filling in the blind spots on one half of the methodological spectrum to better address the whole complexity of neurological research and practice.

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Abbreviations

Endovascular treatment

Randomised Controlled Trial

Standard Operating Procedure

Standards for Reporting Qualitative Research

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Busetto, L., Wick, W. & Gumbinger, C. How to use and assess qualitative research methods. Neurol. Res. Pract. 2 , 14 (2020). https://doi.org/10.1186/s42466-020-00059-z

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Research Article

A Qualitative Study of the Context of Child and Adolescent Substance Use Initiation and Patterns of Use in the First Year for Early and Later Initiators

* E-mail: [email protected]

Affiliation Psychology Department, Dickinson College, Carlisle, Pennsylvania, United States of America

• Sharon Kingston, 
• Maya Rose, 
• Julian Cohen-Serrins, 
• Emily Knight

• Published: January 25, 2017
• https://doi.org/10.1371/journal.pone.0170794
• Reader Comments

Individuals who initiate substance use before high school are at higher risk of negative outcomes. Eighty-six young adults between the ages of 18 and 28 participated in semi-structured qualitative interviews focused on the circumstances surrounding participants’ first use of substances and their pattern of use in the year following initiation in order to investigate similarities and differences between early versus later initiators. Initiation and use among early initiators were more likely to be encouraged by poor parental monitoring or active facilitation of use by parents. Early initiators were more likely to report risky patterns of use such as daily use and using alone. The data suggest that interventions targeting this population should focus on improving parental monitoring and decreasing positive parental attitudes toward adolescent substance use and efforts to increase identification and intervention by middle school staff to reach youth from high-risk families.

Citation: Kingston S, Rose M, Cohen-Serrins J, Knight E (2017) A Qualitative Study of the Context of Child and Adolescent Substance Use Initiation and Patterns of Use in the First Year for Early and Later Initiators. PLoS ONE 12(1): e0170794. https://doi.org/10.1371/journal.pone.0170794

Editor: Ruth Jepson, University of Edinburgh, UNITED KINGDOM

Received: July 1, 2016; Accepted: January 10, 2017; Published: January 25, 2017

Copyright: © 2017 Kingston et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: The data consist of full transcripts of qualitative interviews that contain descriptions of alcohol and other drug use and other potentially embarrassing or stigmatizing behaviors. The transcripts do not contain participants' names but do contain detailed information about individuals' lives that might lead readers to identify individual participants. Supporting quotes that do not contain potentially identifying details will be provided upon request. Participants did not consent to having full transcripts made available to individuals outside of the study team. Individuals interested in obtaining data from the Substance Use Initiation study can contact Sharon Kingston at [email protected] .

Funding: The authors received funding from the Dickinson College Research and Development Committee. The funders had no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: The authors have declared that no competing interests exist.

Introduction

Individuals who begin using psychoactive substances at an early age, typically defined as prior to age 13 or 14 [ 1 , 2 ] are at greater risk of negative psychosocial, educational and mental health outcomes than individuals who initiate substance use at a later age. These early initiators typically begin their substance use with alcohol, tobacco and marijuana and experience more pronounced individual and family risk factors for substance abuse and dependence than later initiators [ 3 – 8 ]. Despite a relatively robust literature on the negative outcomes related to early substance use initiation and the risk factors associated with early initiation there is a paucity of research on whether the context of initiation and the early trajectory of use differs between early versus later initiators.

Early initiation of alcohol, tobacco and marijuana use has been associated with an increased risk of substance misuse and negative outcomes associated with intoxication. Early initiators are more likely to report polysubstance use, more frequent use of substances, more frequent episodes of intoxication and are more likely to develop substance use disorders than later initiators [ 2 , 9 – 16 ]. Early initiators are also more likely to participate in risky behaviors while under the influence such as unsafe driving, becoming involved in a physical fight, and risky sexual behavior [ 2 , 9 – 11 , 17 – 20 ].

In addition to experiencing negative outcomes directly resulting from substance use, early initiators are more likely to exhibit poor mental health and social functioning. Early initiators exhibit increased rates of depressive symptoms and disorders, and are more likely to report suicidal ideation and attempts than later initiators [ 21 – 28 ]. Early initiation is associated with increased risk of perpetrating or being the victim of dating violence, delinquent behavior, decreased academic performance and missing days of school or work [ 13 , 19 , 29 , 30 ].

As might be expected, individuals who initiate substance use at an early age often experience numerous individual, family and peer risk factors associated with poor developmental outcomes. Individual characteristics related to early initiation include externalizing symptoms such as hyperactivity, impulsiveness, inattention and early aggressive behavior [ 4 , 5 ] and temperamental characteristics such as novelty seeking, sociability, activity, and for girls, increased frequency of negative emotions [ 4 , 6 , 7 ].

Early initiators report less optimal family and social environments than later initiators. Early initiators are more likely to be raised by a single mother or by couples who experience less positive marital adjustment and more marital disruptions [ 3 , 5 , 6 ]. Notably, parents of early initiators are more likely to engage in increased substance use and their children are more likely to judge that their parents approve of substance use [ 3 , 5 , 6 ]. Early initiators report higher levels of conflict with parents and less parental control than later initiators during early adolescence. These early adolescents also report that their peers exert a stronger influence on their behavior than their parents [ 6 ]. In terms of support from adults outside of their families, early initiators are less likely to have supportive relationships with teachers than later initiators [ 6 , 8 ].

While numerous individual and family factors related to early initiation of substance use have been identified, very little research has been done to identify situational factors involved in children and adolescents’ first non-medical use of psychoactive substances. Understanding early adolescents’ own perceptions of their motivations to initiate substance use, the situations in which they initiate substance use and their initial reactions to their first use can help us to better understand the risk factors mentioned above, provide additional insights into the differences between early and later initiators and assist in developing strategies to delay substance use initiation among high-risk early adolescents.

The current study investigated the social and environmental contexts of substance use initiation in order to identify the motivations that lead to substance use initiation, the interpersonal and environmental contexts involved in initiation and the pattern of substance use in the first year following substance use initiation. Particular emphasis was placed on investigating factors that encouraged or inhibited substance use in the first year following initiation. The study was designed to reveal similarities and differences in motivations and initiation contexts between early initiators, defined as individuals who initiated substance use before high school (prior to age 13 or 14), and later initiators.

Participants

Data for the current study were collected as part of a mixed methods study of substance use initiation consisting of a qualitative interview and quantitative survey of lifetime and current psychoactive substance use conducted by the first author. Purposive sampling was used to recruit young adults who had used psychoactive substances not prescribed by a medical provider. The participants for the study were recruited from three distinct populations: (1) students taking introductory psychology classes at a small undergraduate liberal arts college, as these classes fulfill a graduation requirement, these students represent a cross section of students enrolled in the college (n = 32), (2) young adults from the community surrounding the college who were not enrolled in a college or university (n = 28) and (3) young adults from the community surrounding the college specifically recruited because they attended a 12-Step Recovery program such as Alcoholics Anonymous or Narcotics Anonymous at least once in their lives (n = 26). These three populations were intentionally included to recruit participants who represented a range of substance use histories and educational backgrounds. The resulting participants reported substance use patterns that ranged from minimal use defined as infrequent use beginning after high school graduation to substance dependence. Age of initiation ranged from age 7 to age 21.

Participants were eligible to participate in the study if they were between the ages of 18 to 28 and had ever used tobacco, alcohol or another psychoactive substance not prescribed to them by a doctor. Participants recruited from the introductory level psychology courses received course credit for their participation. Participants from the surrounding community were recruited through flyers distributed at local businesses and Craig’s List advertisements and received $25.00 for participation. Eighty-six young adults, mean age 21.46, SD = 2.65 were interviewed. Fifty-five percent (n = 47) were men and 45% (n = 39) were women. The sample was predominately European American (86%, n = 73) but included individuals from urban, rural and suburban areas with diverse socioeconomic backgrounds.

All study procedures were approved by the Dickinson College Internal Review Board. All participants provided informed consent for the study prior to being interviewed. Participants were given a written copy of the consent form and the consent form was read to participants by their interviewer. The reading of the consent form and the participants’ verbal consent were recorded on audiotape. No written consent was collected in order to protect participants' confidentiality. The Dickinson College IRB approved this consent procedure. Records of each participant’s identifying information were destroyed after the participant completed the study.

Interviews were conducted by the first author or trained research assistants. The first author and principal investigator of the study is a European American woman with doctorate in in clinical psychology. She is a faculty member at a college in the Northeastern United States with a specific interest and expertise in substance abuse prevention. The research assistants were male and female European American undergraduate students at the college. The research assistants interviewed all of the participants from group 1: students in introductory psychology classes because it was believed that college students might be uncomfortable discussing their substance use histories with a professor. Both the first author and the research assistants interviewed participants from group 2: the young adults not enrolled in a college or university. The first author interviewed all of the participants from group 3: participants who had attended 12-Step recovery programs because group 3 participants completed a supplemental interview describing their responses to 12-Step programs that the research assistants were not trained to conduct [ 31 ]. Data from this supplemental interview was not included in the current analysis. The principal investigator and research assistants did not have any prior relationship with study participants before the interviews and did not have additional contact with participants upon completion of the interview.

Interviews were conducted in a private room at the college using a semi-structured interview guide. Participants were asked to describe their first and second use of psychoactive substances and their typical pattern of use of psychoactive substances in the year following their first use. The guide included questions about factors that encouraged or inhibited substance use during the first year following initiation and focused heavily on the interpersonal context surrounding participants’ substance use during their first year of use. The interview protocols were developed by the first author and refined several times as the first 10 participants were interviewed to improve the clarity of the interview questions. Copies of the interview guide can be found in Appendix A.

The interviews lasted between 20 and 40 minutes. Upon completion of the interview portion of the study, participants completed the survey of lifetime and current psychoactive substance use. Data from this survey was not included in the current analysis. Participants were then given a list of resources for more information about substance abuse and local substance abuse treatment providers. All study procedures were approved by the Dickinson College Internal Review Board.

Content analysis was performed using a thematic analysis framework. This qualitative analytic method was chosen because it allows researchers to highlight similarities and differences across groups of participants. The researchers worked from an essentialist/realist perspective that assumes that the language used by participants reflects their experiences, meanings and realities [ 32 ].

The interviews were transcribed and then coded by the first author and two research assistants using MAXQDA 10 a qualitative research program. Codes were developed inductively by reading the transcripts multiple times and noting patterns of reported motivations, reactions and behavior described by participants. The codes were revised multiple times during test coding of three randomly selected interviews and throughout the data coding process. Thirty percent of the interviews were double coded. The interrater reliability for the presence of specific codes in each interview was measured. The average interrater reliability for the double coded interviews was 92% and ranged from 87% to 95%. The first author and at least one other member of the coding team reviewed discrepancies in the double coded interviews and revised discrepancies through consensus. Themes were identified by the first author and reviewed by the rest of the authors. Themes were identified at a semantic level in order to organize and summarize participants’ experiences and relate the themes to previous research on substance use initiation for the purpose of understanding their implications for substance abuse prevention efforts [ 32 ].

Themes identified in the interviews of early initiators, defined as individuals who initiated substance use prior to attending high school were compared to themes identified in the interviews of participants who initiated substance use in high school or later. The authors chose this definition for early use because participants more readily remembered their first use of psychoactive substances in the context of their grade in school rather than their age.

Forty-two percent (n = 36) were coded as early initiators, 31% (n = 11) of these initiated substance use as elementary school students (11 years old or younger) and 69% (n = 25) initiated as middle school students (age 12 to 14). Fifty-eight percent (n = 50) initiated in high school or later with 14% (n = 7) of later initiators initiating after high school graduation (age 18 and older) and the remainder initiating as high school students (age 14 to 18).

Common Patterns of Initiation and Use for Both Early and Later Initiators

Two themes related to substance use initiation and use during the year following initiation for both early and later initiators were detected. The first theme was that substance use was viewed as a normal, pleasurable activity for adolescents. The second theme was that minimal efforts were made by parents or other adults in the community to curtail adolescent substance use and in fact, some parents and adults facilitated adolescent substance use.

Substance use as a normal adolescent behavior.

The common initiation situations described by both early and later initiators indicate that substance initiation is viewed as a normal adolescent behavior that is expected to produce pleasurable physical and psychoactive effects. Participants were most likely to initiate substance use with alcohol although some participants initiated with tobacco or marijuana or a combination of alcohol and tobacco or alcohol and marijuana. None of the participants reported initiating with a substance other than alcohol, tobacco or marijuana. When asked about the activities they engaged in during and following their use of substances, participants most often reported that they “hung out” and talked to peers. Substance use appears to have been the primary activity during initiation instances and participants described it as the central focus of their activities rather than as substances being used to enhance other activities. One participant described his initiation experience as, “Just having fun and acting goofy , nothing sexual , nothing violent just acting goofy I guess . ” (ID204, male, initiated after high school)

Many participants reported that their decision to use substances occurred spontaneously when the substance was offered to them. Although some of participants did experience some degree of encouragement or coercion by peers, the decision to use substances was rarely the result of strong persuasion or coercion by peers. Rather, participants reported that they simply wanted to fit in with the individuals who were offering them substances.

“ Participant: I didn’t say no because I wanted to fit in like I said before. I wanted to fit in and I didn’t want to seem like a party pooper .

Interviewer: Okay, what did you think the other people would think of you if you said no ?

Participant: He’s boring, he’s not the party type, he shouldn’t be allowed back to no more frat parties if he wasn’t going to get high, drunk, you know. Things like that. ” (ID215, male, initiated in high school)

The perception that substance use was necessary to fit in with peers was bolstered by participants’ beliefs that substance use was a normal activity or a rite of passage for their age with one participant saying: “It seemed like the logical next step in high school . ” (ID29, male, initiated in high school). Participants also reported curiosity as a reason to try substances with one participant stating that he wanted to see for himself if substance use was harmful: “Just wanted to know what it felt like , see what the big deal is , you know , see if it’s actually bad for you or whatever . ” (ID202, male, initiated in high school).

The common belief that substance use is a normal adolescent activity was supported by the fact that participants typically expressed neutral or positive opinions about initiating substance use. It was rare for participants to express feelings of nervousness, guilt or even ambivalence related to use. When describing the psychoactive effects of substances during their first use, participants usually reported pleasurable emotional and perceptual effects.

“ I mean it made me happy, any kind of stressful thing that I had on my mind was completely gone, and I wasn’t even thinking about it, I was just laughing and telling stories, and not worrying about you know, oh well this happened today at school and I know when I go home, I’m gonna be getting yelled at or something like that. ” (ID221, male, initiated in middle school)

“ I was making a lot of connections with stuff. And I like to write music and stuff like that and I was hearing stuff. And I hear that anyway, I was just hearing it differently and it was more intense. ” (ID303, male, initiated in middle school)

When participants did report negative effects of substance use these effects usually focused on unpleasant physical effects such as nausea or dizziness.

Participants were most likely to report using substances for a second time within three months after initiation with some using within one to two weeks. The most common reason for using substances in the first year following initiation was that participants enjoyed the effects of the substance, felt that substance use was a normal activity for people their age and to fit in with peers. The common perception among participants was that substance use was a normative expected behavior that also provided pleasant emotional and perceptual experiences.

Minimal efforts by parents and other community adults to curtail use.

When parents became aware of participants’ substance use their responses varied from active facilitation of use, to expressing disapproval or punishing participants for use. Most commonly however, parents and guardians remained unaware of participants’ use in the first year. The most common strategies participants used to avoid getting caught were to avoid or minimize contact with parents and guardians while intoxicated. This was sometimes accomplished by sleeping over at a friend’s house. Participants who used this strategy reported that the parents of one or more of their friends allowed them to use substances or did not monitor their activities closely enough to detect use, implying that a lack of monitoring or approval of youth substance use by adults within communities can facilitate use independently of the effects of parental monitoring and parental attitudes towards substance use.

“ A lot of times I would sleep over at Bill’s place, cuz that was kinda like the place, like his parents didn’t care so we’d always have a bunch of people over there, a lot of times I just wouldn’t go home at night. ” (ID218, male, initiated in middle school)

While many participants reported making some effort to conceal their substance use, some participants reported that they did not need to use a strategy to conceal their use. A number of participants reported that their parents and guardians approved of their use. One participant reported that his mother allowed him to smoke marijuana.

“ Participant: My mom just called me actually, she asked me was I smoking weed. I said yeah, but she said she already knew because my eyes were always red. I said I don’t smoke all the time though. She said I know you don’t smoke all the time but your eyes is red now, do you smoke? I told her yes she said why didn’t you tell me? I was scared because I didn’t want to get in trouble. She said well you can be open to me like that, because I just moved with her and we had a lot of privacy with each other .

Interviewer: So other than talking to you and telling you to be honest with her did she do anything else or have any other reaction ?

Participant: Nah, she just, the only thing she really said was don’t do it in the house. ” (ID215, male, initiated in high school)

Other participants reported that although their parents or guardians disapproved of substance use they were unable to recognize signs that their children were intoxicated or were not home often enough to detect even regular use. One participant who was living with a guardian reported; “Well she’s my great-great aunt , so she’s an older woman , so she didn’t really know what was going on . ” (ID322, male, initiated in middle school).

Differences Between Early and Later Initiators

While the common initiation contexts and pattern of use in the first year following initiation of early and later initiators displayed some similarities, three differences between the groups were detected: (1) Differences in social and environmental context; (2) Parental substance use facilitated substance use by early initiators; and (3) Early initiators were more likely to describe patterns of use associated with increased risk of poor outcomes such as daily use.

Social and environmental contexts of early versus later initiators.

The situations commonly reported by early initiators could be described as more childlike than those described by later initiators. Early initiators were most likely to initiate substance use in the afternoon or evening after school rather than at night, the most common time for later initiators to use substances for the first time. Some early initiators reported playing with their friends after use. One participant who initiated in elementary school described what he and his friends did after he smoked marijuana for the first time: “I think we went out and rode bikes and played , did kids’ stuff . ” (ID114, male, initiated use in elementary school).

Early initiators often reported initiating substances in small single sex groups or with one friend of the same sex. Later initiators more commonly reported that their first use occurred at large parties with peers of both sexes than early initiators. Early initiators more often initiated substance use in their own home or backyard than later initiators who were most often initiated substance use at a friend’s home or backyard. This pattern continued throughout the first year of use with early initiators using most commonly in their own home and later initiators using most commonly at a friend’s home. It appears that both the activities and the social and physical settings of substance initiation differ for early initiators compared to later initiators with early initiators incorporating substance use into a typical elementary or middle school social and environmental settings.

Parental use as a facilitator of early initiator use.

Perhaps the most striking differences between early and later initiators are the differences in family influence on substance use initiation and use in the first year. While later initiators most commonly initiated use and continued use with same age or older peers, early initiators reported much more variety in their substance use partners. Early users also often initiated and used with same age and older peers but also reported initiation and use with older siblings and parents or guardians more often than later users. One early initiator describes using substances with his mother: “She had a party and I was hanging out with her and drinking , smoking pot…with her . ” (ID322, male, initiated in middle school)

Early initiators like later initiators often obtained substances from friends but more frequently reported that they stole substances from parents or guardians than later initiators. In some cases, participants were able to steal substances on a regular basis because their parent was frequently intoxicated and unable to monitor their own supply of alcohol, tobacco or other drugs. One participant initiated substance use with his mother’s supply and escalated immediately to daily use by continuing to steal his mother’s alcohol and prescription drugs.

“ So I would just take it, put it in a water bottle, you know, take a whole fifth if I wanted to, she wouldn’t notice. So I would often go get drunk, not only that she was on a bunch of medicines, and I used to pop her oxycontins from her surgeries. And she was on some weight loss pills too, and I found a way to mix the weight loss pills by crushing them up, crushing up xanax and half of a klonopin, throwing it in orange juice. ” (ID302, male, initiated in middle school)

Other participants reported that substances were supplied directly by parents or guardians. Early initiators more frequently reported that parents or guardians facilitated their substance use and more often named parents or guardians as influences that encouraged them to use substances in their first year of use than later initiators. One participant referred to her parents’ desire to maintain a relationship with her by supplying her with cigarettes: “It was , oh yea I’ll buy ya cigarettes , you know the parent-friend , uh , they constantly like either had liquor or beer in there , um , they said they’re recovering but they’re not , they just self-medicate . ” (ID305, female, initiated in middle school)

Problematic substance use patterns.

Early initiators more frequently reported problematic patterns of use including using substances alone, escalating to daily use and appearing to have less interest in activities such as getting good grades or participating in organized extracurricular activities that might inhibit substance use escalation than later initiators. Early initiators much more frequently reported that they initiated substance use alone rather than in social situations than later initiators. One early initiator described his pattern of marijuana use:

“ I started smoking alone but it was still, it, the social aspect of it was still there and it didn’t change but then I basically added on you know, smoking alone. Cause a lot of the times I would be kinda like depressed or feel bad or you know any kind of emotional thing that I had going on and ya know, when I’m not at my best I tend to not be around people. Just kinda wall myself off so I don’t, can’t think of a good term for it, so I don’t change people’s impressions of me. Cause I’m like frustrated or not in the best mood. I would basically go and smoke alone and that would mellow me out or get me back to that kind of baseline personality and I would go out and meet people and be social. ” (ID228, male, initiated in middle school)

When describing their pattern of substance use in the first year of use early initiators more frequently reported that they escalated to daily use within the first year than later initiators.

“ I’d wake up, I’d get ready, you know, smoke cigarettes and then I’d smoke a bowl or whatever you know, get ready, end up going to school, and you know I’d be at school all day, sometimes I’d sneak out at lunch time, and I’d smoke a bowl and come back in and you know, and school would be over and I mean I functioned fine. ” (ID305, female, initiated in middle school)

Inhibitors of use also varied across early and later initiators. Early initiators more frequently reported that the main inhibitor of use in the first year was lack of opportunity to use substances than later users. Later users often reported that other goals such as performing well academically or athletically and a fear of being caught were the main inhibitors of substance use in their first year of use. Therefore, later users may have been more likely to have formed attachments to prosocial groups and adopted conventional norms that served to lessen their use of substances.

The interviews with young adults revealed differences between early and later initiators in initiation contexts and the pattern of use in the first year. Early users, as expected, describe much more problematic attitudes toward substance use, more negative patterns of use in the first year and less attachment to prosocial goals [ 6 ]. The interviews with early initiators indicate that they are often initiating substance use in home environments where they are not being closely monitored by adults. This lack of monitoring allows them to use substances in their own home or backyard and to steal substances from their homes. In some cases, adults are actively facilitating use. These results help explain why substance use by parents is correlated with early initiation [ 5 , 6 , 33 ]. Further, the presence of substances in the home increases availability, parental intoxication interferes with the ability to recognize use in their children or monitor their activities and positive attitudes towards substance use leads some parents to actively facilitate their child’s use.

These results indicate that prevention and early intervention programs aimed at children who are at risk for early initiation or children and early adolescents who have already initiated substance use would benefit from a strong family component [ 34 , 35 ]. Parents who use substances need interventions that will allow them to develop skills to deliver strong anti-use messages to their children despite their own use, to secure and closely monitor the substances in their homes and to monitor the behavior of their children.

Although family-based prevention appears to be a promising strategy, the family contexts of some of the respondents indicate that not all families would be able to respond to such interventions. Parents who are dependent on substances other than tobacco likely face significant challenges in preventing use by their children. Parents who actively facilitate use by their children and adolescents clearly are unable or unwilling to prevent substance use in their children. Stronger efforts by middle school personnel to deliver effective prevention programs, to recognize the signs of intoxication and to support and intervene with children and adolescents who are at high risk for substance use or actively using substances appear to be needed to reach youth in these families [ 8 ].

The widely held view among both early and later initiators that substance use was a normal adolescent activity supports the theory that the social norms about adolescent substance use held by most participants and by some adults in their communities encourage substance use initiation during adolescence [ 36 , 37 ]. The extent to which both early and later initiators reported that their first use was unplanned and in response to the belief that substance use was normal adolescent behavior fits very closely with the Social Reaction Model of Health Risk [ 38 , 39 ]. This model, developed specifically to describe adolescents’ decisions to participate in risky behavior posits that many instances of adolescent risky behavior occur due to a willingness to participate in the behavior in social settings rather than a planned intention to seek out opportunities to engage in the behavior. Furthermore, the model posits that this willingness to engage in the behavior arises out of positive images of people who engage in such behaviors and feelings of being similar to people who engage in the behavior. The predominant pattern of initiation described by participants in the current study involved spontaneous decisions to use substances when they were offered in social settings and participants rarely described feelings of ambivalence, nervousness or guilt regarding using substances because they perceived that using substances was congruent with their image of typical adolescent behavior.

Prevention programs that include social norming interventions to decrease the perception that substance use is a normative behavior and teach adolescents how to refuse offers to use substances are strongly supported by the current study [ 40 , 41 ]. In addition, the study suggests that children and adolescents should be encouraged to engage in goal directed prosocial activities such as striving to succeed academically or in extracurricular activities in order to decrease motivation to use substances [ 42 ]. Later initiators often reported that they inhibited their first year use because they feared that use would interfere with important academic or extra-curricular goals.

Finally, the inability of many parents of both early and later users to detect substance use in the first year and the substantial proportion of parents who did not intervene firmly to curtail use when they did detect it, suggests the need for increased efforts to educate parents about the dangers of adolescent substance use and support parents in developing skills to set strong anti-use expectations, effectively monitor their children and enforce appropriate consequences for adolescent substance use. In addition, many participants reported that they were able to use substances as adolescents despite prohibitions by their own parents because other adults in the community tolerated or facilitated use. Prevention interventions aimed at decreasing support for adolescent substance use among adults and increasing effective monitoring among community adults may decrease opportunities for use in this population of adolescents [ 43 ].

The study had a number of limitations. One of the most prominent was the lack of racial and ethnic diversity in the sample. The study was conducted in an area of the United States with a predominately European American population and the participants recruited for the study reflected that demographic. Only 14% of participants identified as a race/ethnicity other than European American. Future studies should investigate the initiation contexts of adolescents from diverse racial and ethnic backgrounds. It is possible that there are racial and ethnic differences in the typical initiation scenarios among children and adolescents or in the reactions of parents who detect substance use by their children.

Another limitation to the study was the reliance on participants’ reports of their parents’ attitudes and behaviors. The participants’ descriptions of their parents’ reactions to their substance use paints a fairly strong picture of families and communities in which adolescent substance use is often expected, tolerated and in some cases facilitated by adults. It is important to remember however, that these descriptions are the perceptions of the participants and not direct reports from parents and other community adults. While participants’ perceptions of their parents’ attitudes quite likely had a strong impact on their own attitudes towards substance use and their subsequent behavior, their parents may have described their attitudes and behaviors very differently. Future studies should include parents to better understand their attitudes towards substance use by their children and their strategies for dealing with this issue.

Finally, all of the data were retrospective reports of participants’ past experiences. Although participants were being asked to describe fairly salient experiences it is likely that they may not have accurately remembered all of the details of their first use and subsequent pattern of use.

Despite these limitations, the study provides a unique look at the situations of substance use initiation, helps explain the strong relationships between family risk factors and substance use among adolescents, supports prevention efforts based on social norms and suggests that greater efforts to support and protect children and adolescents at risk for early use are needed in schools and communities. The most striking finding of the study is the extent to which substance use is accepted or even facilitated by parents of some adolescents, particularly, early initiators. Initiatives to curtail these behaviors by parents should be incorporated into prevention programs.

Substance Use Initiation Interview

• If yes , continue to item 2.
• If the respondent replies that this is true, skip the interview portion of the study and begin the computer survey.
• If the respondent replies that he or she has used a drug in the past continue to item 2.
• What was the first drug you ever used ? (alcohol, tobacco, marijuana, another drug like cocaine, ecstasy, or a prescription drug like Ritalin that wasn’t prescribed for you)
• If yes , What other drugs did you use?
• If not skip to item 4.
• How old were you? What grade were you in? Where were you? Who were you with? Were they boys or girls? Were they the same age as you? Older? Younger? What was the time of day? What was the time of year? How did you get the __________________? Were you planning on using ____________ or did it happen spontaneously? How much ________________ did you use/drink/smoke?
• Ask any prompt questions not covered in participant’s account. Summarize what the participant has just told you and ask if he or she has anything to add.
• If the participant has trouble, prompt (nervous, excited, happy, scared, you did not feel very much—it was no big deal)
• Why did you use the ________________ ? If the participant answered this question clearly in their description of the event, summarize what they said and ask if they had any other reasons for using. If the participant gives more than one reason, repeat the reasons and ask if one reason was primary or stronger than the others.
• If the participant has trouble, prompt (did you get drunk or high, did you feel anything)
• Did you enjoy the effect of the ____________________ ?
• If the participant has trouble, prompt (hang out with friends, dance, romantic activity)
• After you first used _____________ , when did you use _______________ or another drug again ? How long did you wait before your second use ?
• What drug did you use the second time you used drugs ?
• On average, how often did you use drugs? Where did you use them? How did you usually get them? Who did you use them with? Why did you usually use them?
• If participant stopped using drugs in the year following their first use: What factors led you to abstain from using drugs during that first year ?
• Were there instances when you wanted to use drugs but didn’t ? What stopped you from using ?
• What encouraged you to use drugs during that first year ?
• If person got caught:
• What happened ? Did getting caught effect your drug use in any way ?
• What happened ? Did this experience affect your drug use in anyway ? How ?
• Is there anything else about your drug use that you would like to share or think would be important for us to know about ?

We are done with the interview portion of the study . Now I am going to ask you to answer some survey questions . The questions will ask for a more detailed drug use history and some questions about your risk perceptions regarding use of certain drugs . Remember everything you tell us is anonymous .

Author Contributions

• Conceptualization: SK.
• Formal analysis: SK EK.
• Investigation: SK MR JCS EK.
• Methodology: SK MR JCS EK.
• Project administration: SK EK.
• Supervision: SK EK.
• Validation: SK EK.
• Writing – original draft: SK.
• Writing – review & editing: SK MR JCS EK.
• View Article
• Google Scholar
• PubMed/NCBI
• 38. Gibbons FX, Gerrard M, Lane DJ. A social reaction model of adolescent health risk. In: Suls J, Wallston KA, editors. Malden: Blackwell Publishing; 2003. p. 107–136.
• 39. Gibbons FX, Gerrard M. Health images and their effects on health behavior. In: Buunk BP, Gibbons FX, editors. Mahwah, NJ, US: Lawrence Erlbaum Associates Publishers; 1997. p. 63–94.

• Open access
• Published: 12 April 2024

Healthcare team resilience during COVID-19: a qualitative study

• John W. Ambrose 1 ,
• Ken Catchpole 2 ,
• Heather L. Evans 3 ,
• Lynne S. Nemeth 1 ,
• Diana M. Layne 1 &
• Michelle Nichols 1  

BMC Health Services Research volume  24 , Article number:  459 ( 2024 ) Cite this article

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Resilience, in the field of Resilience Engineering, has been identified as the ability to maintain the safety and the performance of healthcare systems and is aligned with the resilience potentials of anticipation, monitoring, adaptation, and learning. In early 2020, the COVID-19 pandemic challenged the resilience of US healthcare systems due to the lack of equipment, supply interruptions, and a shortage of personnel. The purpose of this qualitative research was to describe resilience in the healthcare team during the COVID-19 pandemic with the healthcare team situated as a cognizant, singular source of knowledge and defined by its collective identity, purpose, competence, and actions, versus the resilience of an individual or an organization.

We developed a descriptive model which considered the healthcare team as a unified cognizant entity within a system designed for safe patient care. This model combined elements from the Patient Systems Engineering Initiative for Patient Safety (SEIPS) and the Advanced Team Decision Making (ADTM) models. Using a qualitative descriptive design and guided by our adapted model, we conducted individual interviews with healthcare team members across the United States. Data were analyzed using thematic analysis and extracted codes were organized within the adapted model framework.

Five themes were identified from the interviews with acute care professionals across the US ( N  = 22): teamwork in a pressure cooker , consistent with working in a high stress environment; healthcare team cohesion , applying past lessons to present challenges , congruent with transferring past skills to current situations; knowledge gaps , and altruistic behaviors , aligned with sense of duty and personal responsibility to the team. Participants’ described how their ability to adapt to their environment was negatively impacted by uncertainty, inconsistent communication of information, and emotions of anxiety, fear, frustration, and stress. Cohesion with co-workers, transferability of skills, and altruistic behavior enhanced healthcare team performance.

Working within the extreme unprecedented circumstances of COVID-19 affected the ability of the healthcare team to anticipate and adapt to the rapidly changing environment. Both team cohesion and altruistic behavior promoted resilience. Our research contributes to a growing understanding of the importance of resilience in the healthcare team. And provides a bridge between individual and organizational resilience.

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Introduction

The COVID-19 pandemic highlighted the complexity and dynamic nature of healthcare systems. It also created a unique opportunity to look at the concept of resilience through the lens of the healthcare team versus the more common approach of situating the concept within the individual or the organization. The early phase of the pandemic was marked by challenges, such as limited access to personal protective equipment, personnel shortages, drug shortages, and increased risks of infection [ 1 , 2 ]. Ensuring patient safety and proper functioning requires coordination and adaptation of the healthcare team and various processes across the health system infrastructure [ 3 , 4 ]. Resilience results from adaptive coordination which enables healthcare systems to maintain routine function in the face of all conditions [ 5 , 6 ].

Resilience in healthcare has been operationalized through resilience engineering, an interdisciplinary aspect of systems engineering focused on promotingpatient safety through the design, implementation, and management of healthcare systems [ 7 , 8 , 9 ] (e.g., how healthcare systems adapt and adjust to maneuver through the daily complexities and challenges to identify effective practices, prevent errors and maintain resilient performance) [ 6 , 8 , 9 , 10 , 11 ]. Resilient performance in healthcare is proposed to be the net result of reaching the threshold of four resilience capabilities within the system: anticipation, the ability to expect and prepare for the unexpected; monitoring, the ability to observe threats to daily system performance; responding, the ability to adapt how the performance is enacted; and learning, the ability to learn from present and past accomplishments within the system [ 12 ]. At present, there is a paucity of research on the resilience of the healthcare team as a cohesive, singular conscious source of knowledge in a highly complex healthcare system. While the resilience of both healthcare systems [ 11 , 13 ] and healthcare workers [ 14 ] has been investigated, there is a gap in knowledge specific to the resilience of the healthcare team as a unified singular consciousness. The circumstances surrounding the COVID-19 pandemic presented a unique opportunity to understand the resilience of the healthcare team in a highly complex system as a singular aware entity within the system; how it acknowledges itself, defines its purpose, and performs under extenuating circumstances. This shifts the emphasis of individual and organization resilience to the resilience in the interconnected healthcare team that extends beyond the boundary of any single person.

The adapted model situates the healthcare team as a cohesive singlular conscious source of knowledge within an intricate and highly complex system [ 15 ]. This model was designed as a bridge between resilience found in individuals within the healthcare system and the organization to emphasize the healthcare team as an aware, unified whole. Our model [ 15 ] combines the existing Systems Engineering Initiative for Patient Safety (SEIPS) model [ 16 ] (version 1), which is based on five domains (organization, person, tasks, technologies, and tools), and environment and the Advanced Team Decision Making Model [ 17 ], which includes components for team performance [ 17 , 18 , 19 ]. Team performance is comprised of team identity, team cognition, team competency, and team metacognition [ 17 , 18 , 19 ]. Team identity describes how the team identifies their purpose to help one another [ 17 ]. Team cognition describes the state of mind of the team, their focus, and common goals [ 17 ]. Team competency describes how well the team accomplishes tasks, and team metacognition describes problem solving and responsibility [ 17 , 19 ], Fig.  1 .

Healthcare Team as a cohesive, singular conscious source of knowledge in a highly complex system. The continuous variegated border represents the singularity and connectedness of the healthcare team within the system. The gears represent the processes, people, technology, and tasks within this highly dynamic healthcare system

The purpose of this qualitative research was to describe resilience in the healthcare team during the COVID-19 pandemic with the healthcare team situated as a singular conscious source of knowledge defined by its collective identity, purpose, competence, and actions. Additionally, we sought to identify factors that may facilitate or hinder the healthcare team from achieving the necessary capabilities to monitor, anticipate, adapt, and learn to meet the standard for resilient performance.

Methodology

A qualitative descriptive design [ 20 , 21 ] was employed. The interview guide was framed using the adapted model to explore various aspects of healthcare team performance (identity, purpose, competence, and cognition). These questions were pilot tested on the first 3 participants and no further changes were needed. Specifically, we aimed to investigate resilience capabilities, decision-making processes, and overall healthcare team performance.

Sampling strategy

A purposive snowball sample was used to identify healthcare team members who worked in U.S. acute care settings between January 2020–December 2020. This sampling method was used to ensure recruitment of participants most likely to have insight into the phenomenon of resilience in the acute care setting.

Inclusion criteria

To explore a wide range of interprofessional experience, participants were recruited across geographic regions and professional roles through personal contacts and social media [ 22 , 23 , 24 , 25 ]. Eligible participants included English-speaking individuals ages 20 and older with a valid personal email address, internet access, and the ability to participate in an online video interview. Potential participants had to be employed full or part-time for any period from January 2020–December 2020 in any of the following acute healthcare environments: emergency room (ER), intensive care unit (ICU), COVID- 19 ICU, COVID-19 floor, gastroenterology inpatient unit, endoscopy suite, operating room (OR), post anesthesia recovery room (PACU), pre-operative holding area, hospital administration, or inpatient medical and/or surgical patient care unit.

Exclusion criteria

Healthcare team members who did not complete the pre-screening survey or failed to schedule an interview were not enrolled.

National recruitment in the U.S

Upon approval by MUSC Institutional Review Board (IRB), registered under Pro00100917, fliers, social media posts on Twitter TM (version 9.34 IOS, San Francisco, California) and Facebook TM (version 390.1 IOS, Menlo Park, CA), and word of mouth were used to initiate recruitment efforts. Interested participants were sent a link to an electronic screening survey explaining the purpose of the study and verifying the respondents’ eligibility to participate. Informed consent was obtained from all subjects.

Data collection

Data were collected via an initial screening questionnaire to determine eligibility. Data were managed using REDCap™ (version 11.2.2) electronic data capture tools hosted at MUSC. Demographic data included age, sex, race, professional role, years of experience, geographic region, patient population served, practice specialty area, and deployment status during the pandemic. Deployment refers to the reassignment of personnel from their primary clinical area to another area to meet the demands of another clinical area without regard for the participant’s clinical expertise. Qualitative data were collected through semi-structured audio video recorded interviews to understand the healthcare team in their natural environment. Recorded interviews were conducted via Microsoft® Teams (version 1.5.00.17261, Microsoft Corporation) from the PIs private office to mitigate the risk of COVID-19 transmission and promote participation across the U.S.

Data monitoring and safety

The quality of the demographic data was monitored to ensure completeness. Potential participants who submitted incomplete responses on the questionnaire were excluded. Interviews were transcribed using software, transcriptions were reviewed and verified for accuracy, and then uploaded to MAXQDA Analytics Pro, Version 2022 (VERBI software) to facilitate data analysis. Transcripts were not returned to the participants. Qualitative codebooks, institutional review board (IRB) logs, and other study records were stored on a secure university server, with access limited to authorized study personnel. Adherence to Consolidated Criteria for Reporting Qualitative Research (COREQ) standards were maintained throughout the study and analysis [ 26 ].

Data analysis

Quantitative analysis.

Demographic data were analyzed using SPSS Statistics for MAC, version 28 (IBM). Both descriptive statistics for the continuous variables of age and years of experience (mean, standard deviation) and frequency tables (age, sex, race, role, geographic region, population served, deployment status) were analyzed.

Qualitative analysis

The Principal Investigator (PI) (JA) and senior mentor (MN) independently coded the interview transcripts. Open coding method was used to identify the categories of data [ 22 , 27 ]. Both a reflexive journal and audit trail were maintained. Codes were identified through induction from participant experiences and verified through weekly consensus meetings, while theoretical deductive analysis was guided by the adapted model and the four resilience capabilities (anticipation, monitoring, responding, learning [ 12 ]. Reflexive thematic analysis (TA) [ 28 , 29 , 30 , 31 ] was used to analyze the coded data and generate themes. Data were collected and categorized into the codebook until no further codes were identified by the PI and research mentor [ 22 , 27 ]. Participant checking was not employed.

Demographics

The eligibility pool was established based on survey completion. Eighty-nine healthcare team members opened the online screening survey; 21 were incomplete and eliminated from the dataset, which left a pool of 68 potential eligible participants. Eligible participants (100%) were contacted by email and phone to determine their interest in completing the study interview. Twenty-two participants completed screening surveys and study interviews between May–September 2021, equating to a 32.5% enrollment rate. Participant interviews lasted between 21 and 91 min with an average of 43 min. None of the interviews were repeated. Participant demographics, including descriptive statistic and role key, are noted in Tables  1 and 2 , respectively.

Five themes were identified: team work in a pressure cooker , healthcare team cohesion , applying past lessons to present challenges , knowledge gaps , and altruistic behaviors .

Teamwork in a pressure cooker

The theme teamwork in a pressure cooker describes the relentless pressures and emotional stressors (e.g., fear, anxiety, frustration, and stress) experienced by the healthcare team from the risks and potential threats associated with COVID-19 contamination and infection. Factors associated with these pressures included risk of COVID-19 exposure, lack of COVID-19 testing, rapid changes to policies and procedures from the standard, personnel shortages, limited physical space, and limited supplies. Exemplary quotes highlighting participant descriptions of these pressures or subthemes are noted in Table  3 .

The healthcare team described an unprecedented level of stress in the workplace as the healthcare team had to adjust to rapidly changing protocols. The lack of protective equipment, shortage of providers to perform patient care and a lack of a familiar clinical routine saturated them in overwhelming pressure and emotions that stuck to them as they navigated uncharted territory. Exemplary quotes highlighting the healthcare team’s descriptions of these emotions are noted in Table  4 .

“It was…uncharted territory for me.” (P1, DIR) “You were stuck in a situation you never— you didn’t know when it was going to end.” (P4, RN PACU) “They have not enough staff—they can’t do it—they—I don’t know what we’re going to do.” (P6, DIR). “When we deployed—trying to get re-accustomed to the changes—with the needs that had to be met was very difficult.” (P10, RN ENDO) “I wasn’t about to sign up for extra time working in under those stressful conditions.” (P17, RN PACU)

The fear of the unknown, combined with the constant need to adapt to rapidly changing circumstances, led to widespread stress, frustration, anxiety, and exhaustion within the healthcare team. This theme was characterized by the constant pressure both inside and outside of work experienced by the healthcare team.

“Driving to the hospital, crying, driving back from the hospital, crying, still doesn’t sum it up— surrounded by people who were just dying. And what could you do?” (P6, DIR) “It was constant. It was terrible. I couldn’t sleep at night. I’d wake up worried.” (P8, ER MD) “It was kind of like just keep sending the Calvary forward—and when one drops, you just walk over them.” (P17, RN PACU) “It was always there—COVID here, COVID there—you never could just completely get away from it. It was basically the center of everybody’s conversation everywhere you went or if you were on the phone with somebody.” (P18, RN COVID ICU) “I was having to call my parents before I’d leave my apartment to go into work— to vent to them and cry— to let out my frustration and my anxiety—and have them essentially convince me to go into work.” (P19, RN ICU). “Working so much— COVID was all that was on my brain—and it was a lot of pressure.” (P22, MGR)

Working during COVID-19 challenged the resilience of the healthcare team in the face of constant fear and uncertainty. The pressure to maintain team performance, while dealing with constant fear associated with the pandemic effected the healthcare team’s resilience.

“I have to tell you that after being in hospital—I don’t feel resilient right now— doing all the things I’ve done—I just want to be out of the hospital— [crying] I can tell you that it will stay with me the rest of my life— It will always stay with me.” (P6, DIR) “I feel like my team has used up all of their resilience. I don’t think there’s much left.” (P8, ER MD)

However, one team member stood out as an exception. They reported the pressures from the environment helped them to make decisions. This demonstrates that environmental pressures affect members of the healthcare team differently. They reported that the pressure and intensity of the situation sharpened their focus and allowed them to make choices more quickly and effectively.

“I make better decisions when I’m under pressure.” (P22, MGR)

Healthcare team cohesion

The theme healthcare team cohesion describes the unique experience of working together during the pandemic that created a means among the healthcare team to form close relationships and unite. This bond was characterized by the emergence of strong interpersonal connections among healthcare professionals during the COVID-19 pandemic. These connections shaped healthcare team relationships and were a factor in the collaborative decision-making processes within healthcare team for their day-to day functions. This cohesive bonding was fueled by the stress and uncertainty of the situation, which brought the healthcare team together illustrated by their solidarity, camaraderie, trust, and empowerment.

“All those decisions, important decisions were made together.” (P7, CRNA) “Everyone felt like they were they were, you know, in a in a battle zone and on the same side—and so that kind of brought people together.” (P8, ER MD) “I think our team worked as one.” (P11, CEO)

Solidarity described the sense of unity evident among the members of the healthcare team. This was characterized by connectedness and a sense of reliance on one another that promoted teamwork and resilience within the team from support both given and received. The sub-theme camaraderie described the close personal connection and support between the healthcare team that went beyond normal social interactions prior to the pandemic. These connections were filled with trust and respect for other healthcare team members.

“I think we were all trying to do the best we could do and help each other do the best they could do—I think early on just camaraderie helped a lot within the department and, you know, just relying on each other for support.” (P8, ER MD) “We knew that we can depend on each other and we all had different skill sets— I think that that was very important—that made us feel secure— rather than going alone.” (P10, RN ENDO) “We [The ICU Nurses] developed a sense of camaraderie that I mean, it’s nothing I’ve ever felt before, like we had to trust each other with our licenses, with our own health—my resiliency came from my coworkers.” (P14, CHG RN) “One of the things that I think the pandemic did in a positive—was—I believe that the teams that I worked for really started to solidify. We leaned on each other. I felt more of a team environment than I had had pre-pandemic—I felt that people were a bit better together. We all needed each other, and we all leaned on each other, and we gave each other support—more so than before COVID- 19.” (P15, CRNA) ”The nurses on the unit were always there for me—they became my friends— my family.” (P19, RN ICU)

The sub theme of empowerment referred to the ability of the healthcare team to confidently make decisions and assume responsibility for their actions within the healthcare setting. This process involved a sense of authority and the ability to exercise agency in decision-making together to respond and adapt to the demands the healthcare team experienced. The combination of solidarity, camaraderie, trust, and empowerment resulted in a strong sense of cohesion within the healthcare team which led to improved relationships and enhanced resilience in their performance.

“I felt that I felt that the team—we all needed each other and we all leaned on each other and we gave each other support—more so than before COVID.” (P15, CRNA) “How do you want to handle this? What’s the plan?—and we collaborated in the true sense of collaboration.” (P15, CRNA) “We just knew that we could count on each other—we knew that we could count on each other at any time if we had questions, because we all worked so closely together during this. We really became a really tight knit group, and it was great.” (P22, MGR)

The benefits of the cohesion found in the healthcare team were significant and apparent during the COVID-19 pandemic. The strengthened relationships and increased resilience allowed for improved communication and collaboration, leading to better patient care and outcomes. Despite these advantages, it was noted by one participant that the relationships developed were not sustained beyond the peak of the pandemic.

“Now that COVID is kind of at bay in our area, it’s kind of gone back to the same way it was— it has not stuck.” (P15, CRNA)

Applying past lessons to present challenges

The theme applying past lessons to present challenges describes how the knowledge and understanding gained from prior participant experiences was used to adapt to the novel clinical and infrastructural challenges faced during the pandemic. Past experiences facilitated the healthcare team to strategize ways to meet the demands of the healthcare system during this time.

Participants described two strategies the healthcare team used to improve the system’s ability to adapt and function effectively: changing roles and deploying personnel. The process of changing roles involved assigning new responsibilities to individuals based on priority-based initiatives, while deployment involved transferring clinical staff from areas with lower patient care needs to those with higher needs to optimize their utilization. Eleven participants (50%) were affected by these strategies. Of these, 73% were assigned to clinical areas for direct patient care, while the remaining 27% underwent a role change to support the operational needs of the system. The participants’ preexisting work relationships, specialized clinical expertise, and leadership abilities helped them adapt to their new clinical and non-clinical roles, which in turn enhanced the resilience of the healthcare team.

“We wanted to make sure that we were putting people into the right area where their skill set could be used the best.” (P1, DIR) “I’m known for moving people forward—I’m also well known for speaking up when I don’t think it is right and there was a lot of stuff that I didn’t think was right— and not only speaking up, I’m also going to come with the solution.” (P6, DIR)

Participants indicated the lessons learned from prior experience positively impacted team performance and improved patient care outcomes. There were two significant examples in the data: the perspective of a nurse who was redeployed to work in an obstetrics unit (P5, ENDO RN) and the perspective of a nursing director (P6, DIR) whose role was changed to develop a program to ensure adequate staffing.

“Because we [the team of interprofessionals] were all very familiar with what we had to do at the task, at handit [the experience of the provision of care] was very fluid—I think it’s because of our years of experience and working with each other for so long that it just worked out very well ”. (P5, ENDO RN) “Staff believed in me when I said I would do something— I could galvanize people because of my reputation of caring for staff, so I was chosen specifically because of my ability to move people forward in spite of things.” (P6, DIR)

Participants identified being assigned to unfamiliar clinical areas or working with unfamiliar patient populations as a barrier that hindered their ability to adapt to clinical situations. The lack of clinical competence among some personnel led to an increase in workload for other healthcare team members, who had to provide additional instruction and guidance on how to complete the task. Decision-makers who deployed nursing staff to a clinical area with higher staffing needs may have believed that the individual nurse had specific clinical skills that would be helpful in that area, and this was not the case.

“She [the patient] felt like it was that he [the new nurse]—really didn’t know what he was doing—not only were we kind of reintroduced to that role of caring for patients where we haven’t been recently, but we’re also in a teaching mode, too, for the new nurses—we had to prioritize how sick the patients were, from basic vital signs to wound dressings to respiratory, and help those new nurses know which to attend to first.” (P10, RN ENDO) “Nurses weren’t really put in a place with enough support and enough resources to be able to do a job, and to do a job that maybe they haven’t done for a few years.” (P10, RN ENDO)

The participants indicated that clinical competencies of a healthcare provider in one patient population may not necessarily be applicable to another patient group. For instance, a neonatal intensive care unit (NICU) nurse who has experience in managing Extra Corporeal Membranous Oxygen (ECMO) in newborns may not have the necessary skills to care for adult ECMO patients in an adult COVID-19 intensive care unit.

“The ECMO nurse was a NICU nurse, so she really could not help me.” (P14, CHG RN)

Knowledge gaps

The theme knowledge gaps refers to the disparity between the existing knowledge of the healthcare team and the knowledge required for the team to effectively respond and adapt to the needs of the healthcare system. The lack of COVID-19 specific knowledge led to gaps in the healthcare team’s understanding, while the lack of communication made it difficult for necessary information to be effectively conveyed and received (e.g., medical logistics, human resources, and other operational policies and procedures). This knowledge gap created a barrier to healthcare team resilience as their capacities to surveil, anticipate, and respond were diminished from the lack of knowledge.

“That [information] is pretty fundamental to how you [the healthcare team] function.” (P17, RN PACU) “I don’t think any amount of preparation could have actually prepared us for how bad COVID was—but we were very, very, very unprepared.” (P18, RN COVID ICU) “It was confusing, it was disruptive to the patients that we had there. They sensed that. And that’s— OK—screw with me, screw with my colleagues, but don’t screw with the patient.” (P21, RN ENDO)

All the participants in leadership roles during the COVID-19 pandemic emphasized the importance of having a thorough understanding of the information and effectively communicating it to the frontline healthcare team members most involved in providing patient care.

“There’s nothing worse than having to learn something in the moment and not being prepared for it.” (P1, DIR) “That made us communicate in multiple ways throughout a day because we all know people learn and adapt it could be in print. It could be in person; it could be a video. We tried to have multiple ways of getting messages out and knowing we needed to repeat messages because this was so unknown, and people were so stressed.” (P11, CEO)

One team member (P13, CRNA), highlighted areas where there were gaps in knowledge in greater detail.

“It was as if the unit was being run by all these sort of substitute teachers that were called in at the last minute. Nobody knew where stuff was—nobody knew what the protocol was—the communication was terrible.” (P13, CRNA)

The cumulative effect from the knowledge gaps contributed to the lack of a practical working knowledge for the healthcare team and affected the healthcare team’s ability to anticipate what needed to be done and adapt their performance to accomplish it. Despite knowledge gaps, healthcare team members reported their capability to learn was facilitated by incremental gains in practical knowledge through their experience over time.

“—people got to be experts at protecting patients and keeping themselves safe.” (P8, ER MD) “I think it kind of was like on the job training at that point, I felt like we were all just trying to survive—learning was like—you went out —then you came back, and you would share how things went.” (P15, CRNA) “You tried to educate yourself so you could be safe.” (P17, RN PACU)

The participant responses received from the leadership (CNO, Directors, and Manager) and front-line personnel (administrative staff, nurses, and physicians) regarding the importance of communication highlighted a difference in perspective. Leadership exhibited a strong commitment toward effective communication and made efforts to ensure all healthcare team members were well informed. On the other hand, the frontline participants indicated instances where communication strategies were not perceived as effective.

“I wasn’t contacted by a manager from the unit or anything to be able to reassure, reassure me that things were being followed through and it should be okay, so that was tough.” (P10, RN ENDO) “It really seemed like there was no communication between—like staffing and the floor—we would get up to the floor and they would say, who are you? What are you doing here? What are we supposed to do with you?” (P20, RN OR)

Altruistic behaviors

The theme altruistic behaviors , encompasses the participants’ perception of their obligation and accountability to their patients and healthcare team, and their steadfastness in supporting the healthcare team even if it meant facing personal or professional repercussions. This readiness to aid the healthcare team and accept consequences showcased their altruism and commitment to the healthcare team. The team’s dedication to both their patients and each other was a primary focus driven by a strong sense of responsibility and obligation.

“I want to be able to look myself in the mirror and feel like I did the right thing—.” (P6, DIR) “My resiliency came from my coworkers. I wanted to come back to work to help them.” (P14, RN COVID ICU) “People really looked out for each other—and people were really kind and compassionate to each other—we all were in this together.” (P15, CRNA) “I’m grateful for the experience that I had and all of the different patients that I was able to help in my time there definitely solidified that being a nurse is what I needed to do—and why I chose the profession is exactly what I should have been doing.” (P19, RN ICU) “You just have to go with what seems right—.” (P22, MGR)

A defining characteristic of this theme was a willingness to endure consequences for the benefit of the healthcare team. These consequences varied from contracting the virus, facing criticism from the healthcare team, to foregoing financial incentives, and even job loss.

“I felt like I was punished for speaking up and I was punished for doing the right thing for patients.” (P6, DIR) “I mean, I literally broke the law so many times. Do you know how many times I started pressors [vasoactive drugs to increase blood pressure] on patients that I had no orders for [because a physician would not enter the ICU]?” (P14, CHG RN)

We identified five key themes based on the coded data; namely teamwork in a pressure cooker , healthcare team cohesion , applying past lessons to present challenges , knowledge gaps , and altruistic behaviors . The researchers propose that stressors arising from the COVID-19 pandemic had an impact on the healthcare team’s resilience. In addition, strong healthcare team cohesion, selfless behaviors among the healthcare team, shared knowledge, and job competence within the healthcare team, enhanced resilient performance.

The healthcare team experienced significant stress and uncertainty, due to the COVID-19 pandemic. This is consistent with previous research that has shown that the unprecedented nature of the pandemic led to challenging working conditions, limited resources, lack of information, and concerns about infecting loved ones [ 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 ]. The collective global impact of COVID-19 on healthcare systems is likely a contributing factor to these stressors [ 45 , 46 , 47 , 48 ].

Our study, along with those conducted by Anjara et al. (2021)[ 49 ] and Kaye-Kauderer et al. (2022) [ 50 ], found that solidarity and camaraderie among healthcare professionals improve resilience. Specifically, Anjara et al. observed increased collaboration among the healthcare professionals they studied in Ireland during the COVID-19 pandemic, while Kaye-Kauderer et al. identified team camaraderie among their sample of front-line healthcare workers from New York. Kinsella et al. (2023) [ 51 ] reported that COVID − 19 offered frontline workers in the UK the opportunity to work together toward a common goal. Potential explanations for these findings align with the concepts of social capital proposed by Coleman [ 52 ] and social identification with other as proposed by Drury [ 54 ]. Coleman suggests an individual’s skills and capabilities are enhanced through their interdependent relationships with others [ 52 ]. Drury found in communities affected by disasters, mutual aid and support emerged from a shared social identity, which serves to strengthen the community [ 53 ]. Brooks et al. (2021) [ 54 ] conducted a study with healthcare, police, and commercial sectors in England. They found it was important for these individuals to receive support from and provide support to their colleagues to mitigate the psychological impact of disaster exposure [ 54 ]. In addition, like our findings, Aufegger and colleague’s 2019 systematic review [ 55 ] found that social support in acute care healthcare teams creates a supportive atmosphere where team members help each other communicate problems, fulfill needs, and deal with stress.

Our results are consistent with those of Liu et al. (2020) [ 32 ] and Banerjee et al. (2021) [ 44 ] who each found that healthcare professionals frequently feel a sense of personal responsibility to overcome challenges. One potential explanation for this may be the influence of collectivism in their cultures. Similarly, our study suggests the sense of camaraderie among healthcare professionals may also contribute to a sense of responsibility and increased altruistic behavior. However, other studies have highlighted different perspectives on healthcare professionals’ sense of responsibility and duty. Godkin and Markwell’s (2003) [ 56 ] revealed that healthcare professionals’ sense of responsibility during the Severe Acute Respiratory Syndrome (SARS) outbreak was dependent on the protective measures and support offered by the healthcare system where most SARS infected patients were hospitalized. More recently, Gray et al. (2021) reported that nurses’ sense of responsibility stems from their ethical obligations, regardless of potential personal or familial risks [ 57 ].

The altruistic behaviors described by our participants helped maintain the performance of the healthcare team. It is too soon to see the long-term impact from working in this high-pressure environment; however, past research by Liu et al. (2012) [ 58 ] and Wu (2009) [ 59 ] demonstrated that “altruistic-risk acceptance” during the SARS outbreak was shown to decrease depressive symptoms among hospital employees in China.

Our research on resilience has important implications for healthcare organizations and professionals. In order to ready themselves for forthcoming events, healthcare systems must emphasize the significance of shared knowledge and its influence on the healthcare team’s ability to foresee and monitor effectively. This knowledge can help the healthcare organization function as a unified entity, rather than as individuals in separate roles or clusters within the organization to improve healthcare team preparedness. Establishing a cohesive, clinically competent healthcare team benefits the organization and the patients served. Measures to enhance social support, improve communication and ensure clinical competence maintain healthcare team resilience.

There are several limitations to consider when interpreting the results of this study. First, the sample was obtained using purposive snowball sampling, which may have introduced sampling bias and may not accurately represent the larger population of healthcare team members who worked during the COVID-19, as 95% of the sample were white. Second, our study did not have equal representation of all interprofessional team members. It is possible that a more heterogenous sample regarding role, race and gender may have introduced additional codes. Additionally, the PI (JA) worked as a Certified Registered Nurse Anesthesiologist (CRNA) in acute care during the pandemic and personal experience may have introduced confirmation bias. Also, the focus of our research was to fill a gap in the existing knowledge of what is known about healthcare team resilience in pandemic disasters, and help to answer if and how it intersects with individual and organizational resilience. It is possible this novel conceptualization of healthcare team as a cohesive singular conscious source of knowledge did not adequately address this.

Steps to ensure rigor and mitigate any potential shortcomings of qualitative data analysis were the maintenance of a reflexive journal, a willingness of the PI to let go of unsupported ideas and constant verification of codes and themes with the research mentor (MN) for coherence and consistency within the coded data, selected methodology and research questions.

Overall, the extracted themes of teamwork in a pressure cooker; healthcare team cohesion; applying past lessons to present challenges; knowledge gaps; and altruistic behaviors illustrate comparable experiences within the healthcare team. As healthcare professionals and organizations continue to navigate the challenges of the COVID-19 pandemic and other crises, our findings provide valuable insights into how team cohesion, along with altruistic behaviors, may enhance resilience capabilities to create and maintain a unified resilient healthcare team.

Data availability

The data for this study are confidential as required by the IRB approval. To protect the anonymity of the participants, the data are not publicly available. Additional information about the research method, Interview questions, informant data, and the study in general can be requested from the corresponding author, J.A.

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Acknowledgements

The authors want to thank all the interviewed healthcare team participants for their time and sharing their personal stories and for their continued service during the COVID-19 pandemic. We would also like to acknowledge Ayaba Logan, the Research and Education Informationist, Mohan Madisetti, the MUSC College of Nursing Director of Research, the staff of the MUSC Center for Academic Excellence and the reviewers of this journal for their constructive criticism.

This research (software, transcription services, etc.) was solely funded by the Principal Investigator, J.A.

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Conceptualization J.A., K.C., L.N., D.L., H.E., and M.N.; methodology J.A. and M.N.; J.A. led the study, recruited the interviewees, conducted interviews, led the data analysis, and drafted the manuscript. J.A., and M.N. conducted the data analyses; review and editing K.C., H.E., D.L., and M.N.; supervision M.N.; research project administration J.A. and M.N.; funding acquisition J.A. All authors reviewed the manuscript.

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This study presented no greater than minimal risk to participants and met exempt status per regulatory criteria established by 45 CFR 46.104 and 21 CFR 56.104. The study protocol and all materials were approved by the MUSC Institutional Review Board (IRB), [Pro00100917 ]. All study procedures were followed in accordance with these standards.

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Ambrose, J.W., Catchpole, K., Evans, H.L. et al. Healthcare team resilience during COVID-19: a qualitative study. BMC Health Serv Res 24 , 459 (2024). https://doi.org/10.1186/s12913-024-10895-3

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Building public engagement and access to palliative care and advance care planning: a qualitative study

• Rachel Black   ORCID: orcid.org/0000-0001-8952-0501 1 ,
• Felicity Hasson   ORCID: orcid.org/0000-0002-8200-9732 2 ,
• Paul Slater   ORCID: orcid.org/0000-0003-2318-0705 3 ,
• Esther Beck   ORCID: orcid.org/0000-0002-8783-7625 4 &
• Sonja McIlfatrick   ORCID: orcid.org/0000-0002-1010-4300 5  

BMC Palliative Care volume  23 , Article number:  98 ( 2024 ) Cite this article

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Research evidence suggests that a lack of engagement with palliative care and advance care planning could be attributed to a lack of knowledge, presence of misconceptions and stigma within the general public. However, the importance of how death, dying and bereavement are viewed and experienced has been highlighted as an important aspect in enabling public health approaches to palliative care. Therefore, research which explores the public views on strategies to facilitate engagement with palliative care and advance care planning is required.

Exploratory, qualitative design, utilising purposive random sampling from a database of participants involved in a larger mixed methods study. Online semi-structured interviews were conducted ( n  = 28) and analysed using reflexive thematic analysis. Thematic findings were mapped to the social-ecological model framework to provide a holistic understanding of public behaviours in relation to palliative care and advance care planning engagement.

Three themes were generated from the data: “Visibility and relatability”; “Embedding opportunities for engagement into everyday life”; “Societal and cultural barriers to open discussion”. Evidence of interaction across all five social ecological model levels was identified across the themes, suggesting a multi-level public health approach incorporating individual, social, structural and cultural aspects is required for effective public engagement.

Conclusions

Public views around potential strategies for effective engagement in palliative care and advance care planning services were found to be multifaceted. Participants suggested an increase in visibility within the public domain to be a significant area of consideration. Additionally, enhancing opportunities for the public to engage in palliative care and advance care planning within everyday life, such as education within schools, is suggested to improve death literacy and reduce stigma. For effective communication, socio-cultural aspects need to be explored when developing strategies for engagement with all members of society.

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It is estimated that globally only 14% of patients who require palliative support receive it [ 1 ]. The World Health Organisation (WHO) advocates for palliative care (PC) to be considered a public health issue and suggests earlier integration of PC services within the wider healthcare system is required [ 2 ]. However, research has shown that a lack of public knowledge and misconceptions about PC may deter people from accessing integrative PC services early in a disease trajectory [ 3 ]. Integral to good PC is the facilitation of choice and decision-making, which can be facilitated via advance care planning (ACP). Evidence suggests that ACP can positively impact the quality of end of life care and increase the uptake of palliative care services [ 4 ]. While ACP is commonly associated with end of life (EOL) care, it provides the opportunity for adults of any age to consider their wishes for future care and other financial and personal planning. However, there is evidence of a lack of active engagement in advance care planning (ACP) [ 5 ]. Recent research exploring knowledge and public attitudes towards ACP found just 28.5% of participants had heard the term and only 7% had engaged in ACP [ 6 ]. Barriers to engagement in ACP discussions have been found to include topics such as death and dying are considered a social taboo, posing an increased risk of distress for loved ones; and [ 6 ] a misconception that ACP is only for those at the end of life rather than future planning [ 7 ]. Therefore, there is a need for a public health approach to ACP, to enable and support individuals to engage in conversations about their wishes and make decisions surrounding their future care.

The need for a public health approach to PC, to tackle the challenges of equity and access for diverse populations, was noted in a recent Lancet paper [ 8 ]. This is further supported in a recent review, exploring inequalities in hospice care in the UK, Australia, New Zealand, and Canada which reported that disadvantaged groups such as those with non-cancer illnesses, people living in rural locations and homeless individuals had unequal access to palliative care [ 9 ]. They postulated that differing levels of public awareness in what hospice care provides, and to whom, was an influencing factor with variations in health literacy and knowledge of health services being present in both minority and socioeconomic groups [ 9 ].

Changes in how we experience death and dying have resulted in a shift away from family and community settings into healthcare settings. The Lancet commission exploring the ‘Value of Death’, suggests it has created an imbalance where the value of death is no longer recognised [ 10 ]. The commission’s report posits the need to rebalance death, dying and grieving, where changes across all death systems are required. This needs to consider how the social, cultural, economic, religious, and political factors that determine how death, dying, and bereavement are understood, experienced, and managed [ 10 ].

New public health approaches that aim to strengthen community action and improve death literacy, through increased community responsibility are reflected in initiatives, such as ‘Compassionate Communities’ and ‘Last Aid’ [ 11 , 12 ]. However, a suggested challenge is the management of potential tensions that are present when attempting to conceptualise death in a way that mobilises a whole community [ 13 ]. Whilst palliative care education (PCE) can be effective in improving knowledge and reducing misconceptions, many PCE intervention studies, have focused on carers and healthcare professionals [ 14 ]. Initiatives such as ‘Last Aid’ attempt to bridge this gap by focusing on delivering PCE to the public, however, they are not embedded into the wider social networks of communities. It can be argued that public health campaigns, such as these are falling short by neglecting to use the full range of mass media to suit different ages, cultures, genders and religious beliefs [ 15 ]. Consequently, to understand what is required to engage the public successfully, the voice of the public must lead this conversation. Therefore, this study sought to explore public views on strategies and approaches to enable engagement with palliative care and advance care planning to help share future debate and decision making.

Within the last decades the delivery of PC and ACP have been increasingly medicalised and viewed as a specialist territory, however in reality, the care of those with life-limiting conditions occurs not only within clinical settings but within a social structure that affects the family and an entire community [ 16 ]. Therefore, death, dying and bereavement involve a combination of social, physical, psychological and spiritual events, therefore, to frame PC and ACP within a public health approach the response requires a shift from the individual to understanding the systems and culture within which we live. The Social Ecological Model (SEM) recognises the complex interplay between individual behaviours, and organisational, community, and societal factors that shape our acceptance and engagement. SEM provides a framework to understand the influences affecting engagement with PC and ACP and has been utilised as a lens through which the data in this study is explored.

Qualitative research, using semi-structured interviews were adopted as this enabled an in-depth understanding of public views on strategies to enable engagement with PC. This research was part of a larger mixed-methods study [ 17 ]. Comprehensive Consolidated Criteria for Reporting Qualitative research (COREQ) were used [ 18 ](See Supplementary file 1 ).

A purposive random sampling method, using a random number generator, was adopted to recruit participants who consented to be contacted during data collection of a larger mixed methods study. Selected individuals were contacted by telephone and email to invite them to participate. Inclusion and exclusion criteria are outlined in Table  1 . Interested individuals were provided with a participant information sheet detailing the aims of the study and asked to complete a consent form and demographic questionnaire.

A total of 159 participants were contacted, 105 did not respond, 21 declined and three were ineligible to participate. A total of thirty participants consented, however, two subsequently opted to withdraw prior to the interview.

Data collection

Data was collected from December 2022 to March 2023 by RB. The qualitative interview schedule comprised four broad topic areas: (1) participants’ knowledge of PC and ACP; (2) sources of information on PC and ACP and current awareness of local initiatives for public awareness; (3) knowledge of accessibility to PC and ACP and (4) future strategies for promoting public awareness of PC and ACP, with a consideration of supporting and inhibiting factors. The interview schedule was adapted from a previous study on palliative care to incorporate the topic of ACP [ 3 ] (See Supplementary file 2 ). This paper reports on future strategies.

Participants were asked to complete a short demographic questionnaire prior to the interview to enable the research team to describe the characteristics of those who participated. These questions included variables such as age, gender, religion, marital status, behaviour relating to ACP and experience of PC.

Data was collected via online interviews conducted using the videoconferencing platform Microsoft Teams. Interviews lasted between 20 and 60 min and were recorded with participant consent. Data were stored on a secure server and managed through NVivo 12 Software.

Data analysis

Qualitative data were transcribed verbatim automatically by Microsoft Teams and the transcripts were reviewed and mistakes corrected by the interviewer. All identifying information was removed. Transcripts were analysed using reflexive thematic analysis which involved a six-step process: familiarisation, coding, generating initial themes, developing and reviewing themes, refining, defining and naming themes, and writing up [ 19 ]. Themes were derived by exploring patterns, similarities and differences within and across the data in relation to participant’s views on the promotion of PC and ACP and the best ways to engage the public in open discussions.

The study explored the data through a SEM lens to provide a holistic framework for understanding the influences surrounding health behaviour change in relation to palliative care and advance care planning by mapping the findings to each of the SEM constructs.

The SEM for public health was conceptualised by McLeroy et al. [ 20 ]., and was based on previous work by Bronfenbrenner’s ecological systems theory [ 21 ]. The SEM looks to identify social-level determinants of health behaviours [ 22 ]. Five factor levels have been identified within the SEM; (1) Intrapersonal factors (2) Interpersonal processes (3) Institutional factors (4) Community factors and (5) Public policy [ 20 ]. In short, the SEM suggests that the social factors that influence health behaviours on an individual level are nestled within a wider complex system of higher levels. Current research literature has explored SEM as a model for understanding barriers and facilitators to the delivery of PC, adults’ preferences for EOL care and older adults’ knowledge and attitudes of ACP within differing socioeconomic backgrounds [ 23 , 24 , 25 ]. It has demonstrated the importance of a multilevel approach within these populations. However, there is a scarcity of research exploring strategies for public engagement with PC and/or ACP which are underpinned by SEM theory.

To ensure rigour in the analysis four members of the research team (RB, SM, FH, EB) independently reviewed the transcripts and were involved in the analysis and development of themes as a method of confirmability [ 26 ].

Ethical approval was gained from the University Research Ethics Filter Committee prior to commencing data collection. Participants provided written informed consent prior to the commencement of the interviews. They were advised of their right to withdraw, and the confidentiality and anonymity of all data were confirmed. All data was kept in accordance with the Data Protection Act (2018) [ 27 ].

All participants were white; 70% were female (n-19) and 70% were either married or cohabiting (n-19). The largest proportion of the sample 44% was aged under 50 years (n-12), with 22% aged between 50 and 59 (n-6) and 33% (n-9) aged between 60 and 84. Over half of the sample was employed (n-15), 15% were self-employed [ 4 ] whilst 26% were retired (n-7). Demographic data were missing for one of the included participants (see Table  2 ).

Responses to questions relating to ACP knowledge and behaviours found just 12 participants had heard of the term ACP prior to completing the Northern Ireland Life and Times Survey. Furthermore, none of the participants had been offered the opportunity to discuss ACP and none had prepared a plan of their wishes and preferences.

Main findings

Three overarching themes were generated from the data: ‘Visibility and relatability’; ‘Embedding opportunities for engagement into everyday life’; ‘Societal and cultural barriers. These findings were then mapped to the five social ecological model (SEM) levels ( individual; interpersonal; institutional; community; and policy ) to demonstrate the importance of a multilevel approach when seeking to engage the public around PC and ACP. See Fig.  1 for SEM construct mapping.

Theme 1: visibility and relatability

This theme relates to the suggestion that social taboo was a barrier to awareness and the mechanism to ameliorate this was visibility – in turn promoting reduction of stereotypes and promoting understanding and engagement. This posits the idea that the lack of understanding of PC is the root cause of much of the stigma surrounding it. The SEM construct mapping suggests a multilevel approach is required with intrapersonal (increased individual understanding), interpersonal (openness in discussion with friends and family through media normalisation) and institutional (health service policies for promotion and support) levels being identified.

Participants discussed how there is a lack of knowledge on what PC is, with many assuming that it was for people in the latter stages of life or facing end of life care. This highlighted the lack of individual education with participants suggesting that there should be more visibility and promotion on PC and ACP so that individuals are better informed.

“So, it’s really um there needs to be more education, maybe, I think around it. So that people can view it maybe differently or you know talk about it a bit more. Yeah, probably demystifying what it is. This is this is what it is. This isn’t what it is. You know, this isn’t about um, ending your life for you, you know. And this is about giving you choices and ensuring that you know, you know people are here looking after you”(P37538F45) .

However, there was a recognition that individual differences play a part in whether people engage in discussions. A number of participants explored the idea that some people just don’t want to talk about death and that for some it was not a subject that they want to approach. Despite this, there was a sense that increasing visibility was considered important as there will still be many people who are willing to increase their knowledge and understanding of PC and ACP.

“I can talk about it, for example, with one of my sisters, but not with my mom and not with my other sister or my brothers. They just refuse point blank to talk about it…. some of them have done and the others have started crying and just shut me. Shut me off. And just. No, we don’t want to talk about that. So, it just depends on the personality, I suppose” (P14876F59) .

The lack of knowledge and awareness of PC and ACP was suggested to be the attributed to the scarcity of information being made available at a more institutional level. For some participant’s, this was felt to be the responsibility of the health service to ensure the knowledge is out there and being promoted.

“I think people are naive and they know they’re not at that stage and they don’t know what palliative care is, you know. It’s all like it’s ignorance. But our health service is not promoting this. Well in my eyes, they’re not promoting it whatsoever. And they should, they should, because it would help a hell of a lot of people ” (P37172M61). “I and I think it needs to be promoted by the point of contact, whether it’s a GP, National Health, whatever it might be, I think when they’re there, there needs to be a bit more encouragement to have that conversation” (P26495M43) .

The lack of visibility within the general practice was discussed by several participants who said that leaflets and posters would be helpful in increasing visibility. One participant went as far as to say that a member of staff within a GP surgery would be beneficial.

“I suppose the palliative care because it is a bit more personal. There should be even maybe a professional that you could talk to in your GP practice, or you know, like they have mental health practitioners now in GP practices. Maybe there are I don’t know if there is or not, but there should be maybe a palliative health practitioner that talks to people when they are at that stage of their life” (P21647F29).

Participants also noted how there were generational differences in how people accessed health information. Many of the participants suggested that they would turn to the internet and ‘google’ for information, however, the suggestion was made that care should be taken to target awareness campaigns to different age groups via different methods to reduce disparities in technology skills such as those with less computer literacy.

“ I think a certain proportion of society need the visibility because they’re not always going to be self-sufficient enough to jump on the Internet even though you know we’re getting to the point now where the generational thing is. The generation have been brought up with the Internet and they’re obviously they go to it as the first point of call. But we still got the generation at the moment that don’t”. (P25046F-)

One of the participants talked about ways to increase visibility via the use of the media, including social media, and the utilisation of famous faces.

“Yeah, I think you know, they need to discuss it on Loose Women. You know, morning TV need to get on the bandwagon….But you know. It only takes like that one celebrity to mention it and then the whole media is jumping on the bandwagon.” (P19874F-) .

The UK media coverage of other successful campaigns such as those highlighting mental health and bowel cancer were noted to have been particularly helpful in raising awareness.

“if I think myself about the whole exposure that we have and as a society at the minute about mental health in general, you know a lot of the work on that has been done via social media. You know, celebrities hash tagging and talked about their experience. It’s OK to not be OK etcetera. And I feel like that is responsible for a lot of people who are now discussing their mental health” (P21647F29) .

The sentiment expressed in the above quotes regarding increased visibility in the media also suggests that unless a topic seems relevant to an individual then they won’t engage with health promotion. This concept of relatability pertains to those aspects of human empathy where they can place themselves within a situation leading it to become more relevant to them.

Many participants discussed that using real-life stories on television and in campaigns would be an effective way to connect with the public and it would make PC and ACP more relatable and highlight the importance of thinking about it.

“I think always what tends to be most effective is when it’s somebody that we could all relate to telling their own story (…)……I’m not too sure I know enough about what it involves, but really, like the consequences, that the consequences that people have suffered from not having done that. Not knowing what the wishes were, not having planned for it”. (P32288F62)

Several participants discussed how the topics of PC and ACP were not something they would identify with as being relevant to them. The suggestion was that without it being an immediate concern, for example, if they were not approaching a certain age, then they would assume that they did not need to increase their knowledge about what PC or ACP involves.

“You have to be able to relate to it in order to think, oh, yeah, that applies to me. You need to have something in which you identify with”. (P13697F51)

Theme 2: embedding opportunities for engagement into everyday life

Throughout the discussions, there was evidence that participants felt that death literacy could be increased by providing more opportunities to gain knowledge about planning for future care and what PC involves. Education was highlighted as a potential pathway to engaging the public by targeting appropriate age groups and professions with relevant knowledge and skills. For some, this was thought to be best achieved through educating the youth and for others, the importance of educating those who are working in the healthcare profession was particularly salient. In addition, almost half of the participants suggested they would approach charity organisations for information, with participants advocating for education within secondary and tertiary levels and within community organisations. This data reflects an institutional-level construct within the SEM framework.

Educating younger generations on the topics of PC and ACP through open discussions in schools, and providing skills on how to have difficult conversations with loved ones were seen to be a valuable strategies.

“ young people don’t have that ability to accept and admit and bring it out into the open and I think they need to be perhaps encouraged more to do that through some kind of teaching in the school environment when they’re at a young and impressionable age ”. (P25046F-)

Due to the difficulties around having conversations about death, it was suggested that different healthcare professionals should be trained to have conversations with their patients.

“Yeah, it’s like you think the discussions are difficult to broach for maybe health care professionals that you know, a difficult topic even for them to bring up. Well, if you’re working with someone who’s you know with a family and where things are quite distressed and very often it can be either, it can be the stress can cause a lot of friction and you know, decision making can be very difficult for people…., but just at every level, there’s, you know, possibility to be having conversations like that with people.”(P37538F45) . “I suppose you could think about training some care professionals (…) there may be some way that as a second part of the person’s job or whatever that they’re trained so that people could go along and discuss ” (P19265F76) .

Further to education for young people and healthcare professionals, there was the recognition that community organisations are perfectly positioned to educate the public in PC and ACP. One participant highlighted the missed opportunity to educate family members and carers through an existing programme on dementia. This is particularly pertinent to ACP due to the impact of cognitive decline on decision-making.

“I went to zoom meetings for four weeks in a row with the Alzheimer’s Society. Umm regarding things to do with dementia. And you know, there was a week about your finances and things like that. I suppose. They never really talked about end of life care you know that sort of thing. Um I suppose it would have been useful had they you know, broached that subject as well. But it wasn’t, you know, there was more about looking after yourself, looking after the person. The symptoms of dementia and all this sort of thing, Alzheimer’s and then you know, um the financial and the help available to you. You know, but they didn’t mention about the end-of-life care and like the end result of dementia, I guess, is death. So, you know that that subject, you know, I was, I suppose to just those organizations that deal with um the issues of, like dementia or, as you say, all the rest for, you know, the rest of the diseases and that. You know to be up front and honest and say you know where this can lead and to make people you know, make people aware that there is a palliative care process that can be gone through.” (P19874F-) .

Furthermore, the option of a helpline was suggested with reference made to other successful charity helplines such as the National Society for the Prevention of Cruelty to Children (NSPCC) and The Samaritans. Whilst it was acknowledged there were specialist support services available for people living with a terminal diagnosis, there was a sense that a generic information support helpline would be helpful.

“You know, people need to be (aware)… they’re not alone. There is help out there. You know, you see your helpline, your children, NSPCC, your Samaritans. All on all these helplines, I have to think, I’ve never seen a helpline for palliative care or who you can contact. You don’t see things like that.” (P22964F52) .

In addition to education, the suggestion that embedding ACP discussions into other more common aspects of future planning such as will making, and organ donation was postulated as a potential way to engage the public. This demonstrated clear links to the policy and institutional level constructs within SEM. Changes within organisational policies and public law to support individuals to consider future planning would promote better engagement on a wider societal level.

Participants suggested that they would like to see some of the conversations surrounding ACP introduced into workplace policies and guidelines, as well as through other legal discussions. They noted that conversations surrounding future planning already occur when discussing legal wills and workplace pensions. The potential to expand these discussions to include ACP with solicitors and in workplaces was seen to be a missed opportunity.

“So maybe um around people who are making their wills and you know, you get will making services advertised and things like that. And I think once you get into your 30s and 40s, people start thinking about a will and things like that. So maybe aligned to something like that, you know would get younger people.” (P13790F67) . “when people talk about the pension, you know so retirement, you know, to make people aware about this as well. You know, I would say that’s probably good ways to reach people” (P21263M54) .

Current legislation and promotion regarding organ donation were discussed as being successful in engaging the public and therefore implied that the government should take a more active role in the promotion of ACP.

“If you look at the way, sort of, government have been promoting like organ donation and that. You know that sort of thing. And then people have really bought into it and you know, and there’s a lot of positivity around it. So, I think that’s sort of similar approach would be good”. (P29453F40) “You know, people talking about pension, pension plans and so on and it’s part of the natural life circle, you know. So, if it’s in connection with this, you know, so think about your future, make your plans …so probably in connection with organ donation and so on, you know, so I think they could be trigger points, you know,, people talking about this.” (P21263M54) .

Theme 3: societal and cultural barriers to open discussion

In conversations surrounding why there was a lack of openness in discussion, participants postulated that a potential factor was the influence of cultural and societal norms. This was found to overlap in the SEM levels of intrapersonal, interpersonal and community.

Rural farming communities were highlighted as potentially being more isolated and traditional in their views around death and dying, whilst those with strong religious beliefs were seen to be less likely to engage in discussions.

“You know, and there is a, I’m out in the countryside. Well, it’s (place name). So it’s a relatively rural sort of conservative place and it and it’s that… you know you’re tied to the land, you’re tied to the farm. This is your home and sending you away from it early it is seen as a bit of a shameful thing. So yeah, to try and educate folk and to try and speak into that I think would be really helpful because again, I’ve seen situations where probably the individual’s life, the end of life, has been made tougher because the family have fought to keep that person at home.…. We’re going to try and do it ourselves” (P26495M43) . “I think it’s probably a lot to do with religion more than likely because people just like to hear, because we still are very much, you know, a lot is dictated by religion. So, people just want to leave stuff in God’s hands so they don’t want to have like…that would be the kind of where my mom and dad are coming from, you know, don’t interfere with it, blah blah blah. So, it’s a very gentle like kind of reminding them, you know, well, I think we do need to think about it. And I think people are afraid that they’ll make again that um it’s kind of euthanasia you know what I mean” (P37538F45) .

Cultural differences between countries were also considered with some seeing other global communities approaching death as a celebration rather than something to shy away from.

“I think in Northern Ireland we are, and the UK and probably the world in general. We are really poor at talking about, about death, and it has to be a positive thing to be able to talk more about death. You look at other cultures where you know. Death is treated differently, you know, even in Africa things where, you know, it’s a real celebration, whereas it’s seen so differently in in Northern Ireland” (P31154F35) .

Furthermore, regions and countries that have experienced war and conflict were perceived by one participant as a potential barrier to engaging in subject matters which involve death.

“I don’t I don’t know about other countries, but those that grew up maybe during the conflict here, maybe it’s just something that, you know it’s it’s a completely different mindset to them” (P23609M39) .

Whilst it is unclear from the data why the participant felt the conflict might inhibit engagement with the subject of dying, it could be interpreted that the participant was suggesting that death is too morbid to engage with following a conflict period which saw numerous deaths. An alternative interpretation could be that people are desensitised to death and do not see death as something that an individual has autonomy over.

It was noted that in many modern societies communities are changing. People no longer interact with their neighbours in the way they used to which results in a reduced sense of community responsibility.

“I don’t know that everyone is as neighbourly as they used to be. Northern Ireland I always perceived as being open door policy and everybody looked out for everyone else. But I think as a society has changed and it has changed in Northern Ireland, and it’s become becoming more closed (…) So I think we need to try and encourage that community um experience back again so that people are mindful of their neighbours and share that responsibility and making sure that everyone’s OK” (P25046F) .

This sense of social isolation was discussed by one participant who referred to homeless people. They reflected on how current social structures may not be providing the information and support to this minority group and therefore should be considered when developing public health approaches to engaging them in PC and ACP education.

“And if you look at homeless people on the streets, where do they get the information from? Where do they get the care, the information, the attention. I know there are Street workers that work, but I don’t know again to what extent in Northern Ireland compared with the likes of London” (P25046F) .

Mapping the findings to a social ecological model framework

Following thematic analysis each of the resulting themes were mapped to the five socioecological levels identified by McLeroy et al. (1988) for health promotion programmes. Construct mapping can be found in Fig.  1 below.

Thematic interaction within the Social Ecological Model levels

The findings from this study highlight the complexity of current public perceptions of palliative care and their views on effective engagement with PC and ACP. Within medicalised western culture there is a tendency to focus on the preservation of life, with conversations about death avoided. This has resulted in death becoming a taboo, raising fear and stigma where death is equated with failure. These social taboos that exist around death, dying and bereavement are posited to stem from the lack of awareness and understanding of PC and ACP and the resulting stigma of approaching these discussions. There was evidence of influencing factors on all SEM levels, which demonstrates the need for a multifaceted public health approach that uses not only behaviour change communication but also social change communication, social mobilisation and advocacy. It can be argued this reflects the key aspects outlined in Lancet Commission report on ‘Valuing Death’, which advocated for a ‘systems approach’ [ 10 ]. This systems approach is aligned to differing levels within the SEM and the different approaches the public have identified when seeking to build public engagement and access to palliative care. Three key aspects were noted: visibility, embedding opportunities for engagement in everyday life and societal and cultural influences.

It was clear from the analysis that a major factor associated with poor public engagement was the lack of visibility within the public domain, which was hindering both the normalisation of death and understanding that PC was more than just end of life care. The findings demonstrated different ways to address the lack of visibility, such as the use of targeted social media and wider publicity campaigns. Research to date has demonstrated that palliative care education is a useful tool in improving knowledge of, confidence in and attitudes towards palliative care amongst healthcare professionals and carers [ 14 ]. Similar results have been noted for the public when exploring the potential to promote palliative care through various media challenges such as YouTube and social media [ 28 ]. This does, however, raise questions around the quality and accuracy of information offered via the media, taking cognisance of whether some of the messaging may inadvertently be adding to misunderstanding, and thus a lack of public engagement.

Secondly, the findings indicated that experience at the individual level within a social context was noted as an important element when seeking ways to increase public engagement with PC and ACP. The experience of illness, dying and loss is often overlooked, therefore, this points to the potential value of community-based education approaches, with peers enabling experience-based exchange. Such interventions have been noted in the literature on the role of volunteers and education [ 29 ]. This reflects the need for an overall public health palliative care approach that seeks to empower individuals, families and communities to draw on their own resources and community supports to adapt and cope with death and dying [ 6 , 30 ].

Thirdly, the findings from this study indicated the need for enhancing opportunities for engagement in PC and ACP within everyday life. Research indicates there is an appetite for people to talk about death, for example, in the UK, a recent YouGov ‘daily question’ survey reported 67% of adults who responded think the subject of death and dying should be talked about in schools [ 31 ]. This speaks to the need to consider schools, workplaces and key trigger points in life as times to consider engagement with PC and ACP. This reflects the overall need for death literacy in society to improve experiences at the end of life [ 10 ].

Finally, the importance of socio-cultural aspects for the public cannot be underestimated. Therefore, effective communication strategies need to be tailored to individuals, and communities and be culturally appropriate. This has been noted as an important aspect for specific communities, such as the Chinese diaspora, for example, but nuances around this for specific ethnic, political, religious, and geographical aspects need further consideration [ 32 ]. Cultural competence, defined as an understanding of how culture affects an individual’s beliefs, values and behaviour, is an important consideration [ 33 ]. A meta-analysis of 19 review articles, concluded that interventions to increase cultural competence in healthcare were effective in enhancing the knowledge, skills and attitudes of healthcare providers, leading to clinical benefits for patients/clients through improved access and utilization of healthcare [ 34 ]. The translation of such reviews for public engagement in PC and ACP warrants further exploration. It has been advocated that elements of cultural systems should be analysed with a socio-ecological framework [ 35 ]. Such consideration and integration of salient contextual cultural factors could assist public messaging and cultural communication, which would enhance more effective and sustainable public engagement in PC and ACP.

Limitations

When considering potential limitations, it is pertinent to note that due to the sensitive nature of the topic the exclusion criteria restricted the sample to those who had not experienced a recent bereavement. This may have limited the ability to gain a wider perspective, as the views of the recently bereaved may have provided further nuanced insights into how best to engage the public. Furthermore, the participant sample was limited to those involved in a larger mixed-methods study. This may have introduced bias in relation to true knowledge and attitudes due to the participants having completed the survey questionnaire prior to the interviews.

In conclusion, this qualitative study has provided insights into how the public would like to be engaged in PC and ACP. The findings highlighted that to build public engagement and access to palliative care and advance care planning a multifaceted public health approach is required. Discussions of death and dying remain difficult for many members of society, therefore, an increase in death literacy across all systems to reduce misperceptions surrounding PC and APC is needed, by increasing visibility and providing opportunities for the public to engage with PC and ACP within everyday life. Finally, socio-cultural aspects need consideration when developing strategies to ensure effective communication and engagement with all members of the community.

Data availability

The datasets analysed are not publicly available but are available from the corresponding author upon reasonable request.

Abbreviations

Advance care plan

• Palliative care

Palliative care education

Social ecological model

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Acknowledgements

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This study was funded by HSC R&D Division of Public Health Agency in Northern Ireland.

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Teachers and educators’ experiences and perceptions of artificial-powered interventions for autism groups

• Guang Li 1 ,
• Mohammad Amin Zarei 2 ,
• Goudarz Alibakhshi 2 &
• Akram Labbafi 3  

BMC Psychology volume  12 , Article number:  199 ( 2024 ) Cite this article

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Artificial intelligence-powered interventions have emerged as promising tools to support autistic individuals. However, more research must examine how teachers and educators perceive and experience these AI systems when implemented.

The first objective was to investigate informants’ perceptions and experiences of AI-empowered interventions for children with autism. Mainly, it explores the informants’ perceived benefits and challenges of using AI-empowered interventions and their recommendations for avoiding the perceived challenges.

Methodology

A qualitative phenomenological approach was used. Twenty educators and parents with experience implementing AI interventions for autism were recruited through purposive sampling. Semi-structured and focus group interviews conducted, transcribed verbatim, and analyzed using thematic analysis.

The analysis identified four major themes: perceived benefits of AI interventions, implementation challenges, needed support, and recommendations for improvement. Benefits included increased engagement and personalized learning. Challenges included technology issues, training needs, and data privacy concerns.

Conclusions

AI-powered interventions show potential to improve autism support, but significant challenges must be addressed to ensure effective implementation from an educator’s perspective. The benefits of personalized learning and student engagement demonstrate the potential value of these technologies. However, with adequate training, technical support, and measures to ensure data privacy, many educators will likely find integrating AI systems into their daily practices easier.

Implications

To realize the full benefits of AI for autism, developers must work closely with educators to understand their needs, optimize implementation, and build trust through transparent privacy policies and procedures. With proper support, AI interventions can transform how autistic individuals are educated by tailoring instruction to each student’s unique profile and needs.

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Introduction

Autism education has become an increasingly important area of focus in recent years due to the rising prevalence of autism spectrum conditions (ASC) among children. The estimated prevalence of ASC has increased from 1 in 10,000 in the 1960s to at least 1 in 100 today [ 1 , 2 , 3 ]. ASC is a neurodevelopmental condition characterized by impaired social interaction and communication abilities and stereotypical or obsessive behavior patterns. These impairments can significantly impact an individual’s social, educational, and employment experiences, leading to poor long-term outcomes and difficulties in social transactions, independent work, and job fulfillment [ 4 , 5 , 6 , 7 , 8 , 9 , 10 ].

The reported prevalence of autism spectrum disorders (ASDs) in developed countries is around 2% [ 11 ]. ASDs typically manifest within the first three years of life. They are characterized by challenges in social interaction, speech and language delays, avoidance of eye contact, difficulty adapting to changes in the environment, display of repetitive behaviors, and differences in learning profiles [ 11 , 12 , 13 ]. Those with ASDs, including children and adults, have a high frequency of anxiety and depression. Neurobiological research has revealed differences in brain development between children with ASDs and neurotypical children [ 14 ]. These excessive connections are thought to be due to reduced pruning of damaged neuronal connections during brain development, resulting in disordered neural patterning across the brain and dysregulation in cognitive function coordination between different brain regions [ 14 , 15 ].

The dominant perspective regarding AI technologies has revolved mainly around understanding these systems as a collection of processes and their corresponding responses, emphasizing autonomy, adaptability, and interactivity [ 16 , 17 , 18 , 19 , 20 , 21 ]. These characteristics are considered fundamental technological focuses that researchers argue should be integral to AI systems. Although autonomy, adaptability, and interactivity are significant, they may only cover some essential criteria for an adequate K-12 education. Specifically, these criteria are about skills taught by human educators, such as B. Self-efficacy, technical skills, and socialization skills. Samuel [ 22 ] emphasizes that AI technologies should replicate human actions and mimic expressions of “human intelligence, cognition, and logic.” This highlights the need to refine features that determine effective AI in education. The recent challenges in education due to the pandemic provide a unique opportunity to examine the demands on stakeholders, including educators, students, and parents [ 23 , 24 , 25 , 26 , 27 ].

The potential of artificial intelligence (AI) to drive developments in education is well-recognized [ 6 , 7 ]. Artificial intelligence is one of the technological advancements which can be used in education. AI encompasses a range of technologies that aim to simulate human intelligence, including machine learning, natural language processing, and computer vision [ 8 ]. These technologies have already been used in various applications, from speech recognition to image classification, and can potentially revolutionize how we think about education. In the context of autism, AI has the potential to provide personalized learning experiences that are tailored to the specific needs of each child [ 8 ]. For example, AI-powered systems can analyze a child’s behavior and responses to stimuli and use this information to adapt the learning materials and activities to suit their needs. Furthermore, AI can also be utilized to support communication and social interaction, which are areas of difficulty for many children with autism [ 9 ].

AI-powered interventions in the context of autism education refer to the utilization of artificial intelligence technologies to create tailored and interactive experiences for individuals on the autism spectrum. These interventions encompass a spectrum of applications, including educational tools, therapeutic programs, and support systems designed to address the unique learning and social communication needs of individuals with autism. AI technologies such as machine learning, natural language processing, and computer vision are employed to analyze and respond to the specific behaviors, preferences, and challenges exhibited by each individual [ 1 , 2 , 3 , 4 , 5 , 6 ]. The goal is to provide personalized and adaptive learning experiences, enhance social interaction skills, and offer targeted support for cognitive and emotional development. Examples of AI-powered interventions include virtual reality scenarios, interactive games, and educational software that can dynamically adjust content based on real-time feedback, creating a more individualized and effective educational approach for children with autism [ 2 , 3 , 4 , 5 ].

Moreover, there is a risk of bias and discrimination in AI-powered interventions for children with autism. For example, if the AI system is trained on data that is not representative of the diverse population of children with autism, it may not be effective for all individuals [ 10 ]. Moreover, there is a risk of perpetuating harmful stereotypes or reinforcing inappropriate behaviors if the AI system is not designed and programmed with ethical considerations (10). Third, there are concerns about data privacy and security when using AI in education for children with autism. For instance, if sensitive personal information is collected and stored by the AI system, there is a risk that it could be misused or accessed by unauthorized parties [ 16 ]. Therefore, it is essential to address these challenges and concerns to fully realize the potential of AI in education for children with autism. By doing so, we can create evidence-based and ethically sound interventions that support personalized learning and social communication skills while mitigating the risks associated with AI-powered education.

The potential of AI in autism education lies in its ability to offer personalized learning experiences, tailoring interventions to the unique needs of each child [ 8 ]. By analyzing a child’s behavior and responses, AI can adapt learning materials, potentially revolutionizing education for children with autism. However, this transformative potential is not without challenges. The risk of bias and discrimination looms large, as AI systems may not be effective if trained on non-representative data, perpetuating harmful stereotypes [ 10 ]. Ethical considerations become paramount, addressing concerns about data privacy and security, which, if overlooked, pose potential risks associated with unauthorized access and misuse of sensitive information [ 16 ]. Bridging the gap between the promise of AI in education and its responsible application is crucial. Therefore, this study aims to explore educators’ experiences and perceptions of AI-powered interventions for autism, shedding light on the nuanced landscape where technological advancements intersect with the delicate realm of autism education.

Research questions

In line with the research gap mentioned in the previous section, the following research questions are raised:

What are the benefits and challenges of using AI-powered interventions to support the learning and social communication skills of children with autism from teachers’ and educators’ perceptions?

How can AI-powered interventions be designed and implemented to ensure that they are culturally and linguistically appropriate for a diverse population of children with autism while also avoiding bias and discrimination in the learning materials and activities?

Review of literature

Theoretical background.

Machine learning is a component of artificial intelligence (AI) wherein models perform tasks autonomously without human intervention. Traditional machine learning models are trained using input data, enabling accurate outcome predictions. Deep learning, a subset of machine learning, employs extensive data to prepare models, achieving similarly high prediction accuracies. Both models are frequently utilized in diagnosing neurological disorders such as autism [ 28 , 29 ], ADHD [ 30 , 31 ], and depression [ 32 , 33 ]. Diagnostic inputs encompass images from computerized tomography (CT), magnetic resonance imaging (MRI), positron emission tomography (PET) scans, or electroencephalogram (EEG) signals.

AI has been instrumental in social skills training for children with autism spectrum disorders (ASDs), aiding in recognizing and responding to social cues. Belpaeme et al. [ 34 ] utilized sensory features (facial expressions, body movements, and voice recordings) as inputs to a machine-learning model implemented in a robot for analyzing autistic children’s behavior and engagement levels during therapy. This study demonstrated the robot’s potential to adapt to interactants, influencing engagement. Another survey by Sanghvi et al. [ 35 ] employed postural expressions, specifically silhouette images of the upper body during chess playing, to analyze the engagement levels of autistic children. The integration of representative data with an affect recognition model suggested the potential for the robot to serve as a game-mate for autistic children in real-world scenarios. Kim et al. [ 36 ] employed audio recordings to assess the emotional states of autistic children, enhancing the robot’s ability to evaluate engagement and modify responses for a more interactive learning environment.

Various studies explored diverse input features such as facial expressions [ 37 ], body movements [ 38 ], and biosignals [ 39 ]. Esteban et al. [ 40 ] investigated facial expressions, direction of look, body posture, and voice tones as input features to a model within the NAO robot for assessing the social engagement of autistic children, showcasing the capability of robots to possess increased autonomy. Rudovic et al. [ 41 ] developed a personalized deep model using coordinated video recordings, audio recordings, and biosignals to assess engagement in autistic children, outperforming non-personalized machine learning solutions. Another study created a hybrid physical education teaching tool using speech recognition and artificial intelligence, achieving a recognition accuracy of over 90% for a voice interactive educational robot. Collectively, these studies affirm that AI holds promise in enhancing social interaction and supportive education for children with mental disorders.

Artificial intelligence and education

The use of AI technology in education has led to increased published studies on the subject, with a reported growing interest and impact of research on AI in education [ 42 ]. AI literacy, which refers to the capacity to comprehend the essential processes and concepts underpinning AI in various products and services, has been discussed in several studies [ 43 , 44 , 45 , 46 , 47 ]. Ng et al. [ 48 ] proposed a four-dimensional AI literacy framework covering knowing and understanding AI, using and applying AI, evaluating and creating AI, and AI ethics.

Recent review papers on AI in education have highlighted several major AI applications, such as intelligent tutoring systems, natural language processing, educational robots, educational data mining, discourse analysis, neural networks, affective computing, and recommender systems [ 22 , 23 , 33 – 34 ]. However, Chen et al. [ 49 ] identified some critical issues in their review paper on AI in education, including a lack of effort in integrating deep learning technologies into educational settings, insufficient use of advanced techniques, and a scarcity of studies that simultaneously employed AI technologies and delved extensively into educational theories. Furthermore, there needs to be more knowledge and discussion on the role of AI in early childhood education (ECE), an area often ignored in cutting-edge research.

Using AI to teach children with ASD

Autism Spectrum Disorder (ASD) is a complex neurodevelopmental disorder that affects communication, social interaction, and behavior (1). The disorder is characterized by various symptoms and severity levels, making it challenging to provide effective interventions for affected individuals [12]. Children with ASD often experience difficulties in learning and require specialized educational interventions to help them achieve their full potential [1]. In recent years, there has been growing interest in the potential of AI to improve the learning outcomes of children with autism [8). AI has the potential to provide personalized learning experiences that are tailored to the specific needs of each child with autism [ 9 ]. For example, AI-powered systems can analyze a child’s behavior and responses to stimuli and use this information to adapt the learning materials and activities to suit their needs [8].

AI can also be used to support communication and social interaction, which are areas of difficulty for many children with autism [10]. Chatbots and virtual assistants can provide a non-judgmental and non-threatening environment for children to practice their social skills while providing feedback and guidance [ 23 ]. These interventions can be particularly valuable for children who struggle with face-to-face interactions or feel uncomfortable in social situations [ 24 ]. Despite the potential benefits of using AI in education for children with autism, several challenges and concerns need to be addressed:

First, there is a lack of consensus on the most effective ways to use AI to support learning for autistic children [ 8 ]. While there have been some promising results from initial studies, more research is needed to determine the most effective methods for using AI to personalize learning and support social communication skills in this population [10]. Second, there is a risk of bias and discrimination in AI-powered interventions for children with autism. For example, if the AI system is trained on data that is not representative of the diverse population of children with autism, it may not be effective for all individuals [ 9 ]. Moreover, there is a risk of perpetuating harmful stereotypes or reinforcing inappropriate behaviors if the AI system is not designed and programmed with ethical considerations [ 23 ]. And, third, there are concerns about data privacy and security when using AI in education for children with autism. For instance, if sensitive personal information is collected and stored by the AI system, there is a risk that it could be misused or accessed by unauthorized parties [10].

Several research studies have investigated the use of AI in education for children with autism. For example, Goodwin and Stone [8] developed an AI-powered system called Maki, which uses natural language processing to provide personalized feedback on social communication skills. The system was effective in improving social communication skills in children with autism. Similarly, Alzoubi et al. [ 50 ] developed an AI-powered system that uses virtual reality to provide social skills training for children with autism. The system was found to be effective in improving social skills and reducing anxiety in children with autism.

Other research studies have explored the potential of AI to improve different aspects of learning for children with autism. For example, Zhang et al. [ 10 ] developed an AI-assisted system that uses computer vision and machine learning to provide personalized feedback on handwriting skills. The system was effective in improving handwriting skills in children with autism. Similarly, Wang et al. [ 51 ] developed an AI-powered system that uses game-based learning to enhance math skills in children with autism.

There have also been efforts to develop AI-powered systems that can assist teachers and parents in providing effective interventions for children with autism. The system effectively improved the quality of interventions offered by teachers and parents. However, there are also concerns about the potential negative impacts of AI on children with autism. For example, some studies have suggested that excessive use of AI-powered interventions could reduce face-to-face interactions and social skills development [9]. Additionally, there are concerns about the potential for AI-powered interventions to replace human teachers and therapists, which could have negative implications for the quality of care provided to children with autism [8].

To address these concerns and maximize the potential benefits of AI for children with autism, it is essential to prioritize ethical considerations and involve stakeholders in designing and implementing AI-powered interventions [ 23 ]. This includes ensuring that AI systems are developed and programmed to avoid bias and discrimination, protecting the privacy and security of personal data, and promoting transparency and accountability in using AI in education for children with autism [ 10 ].

Other studies have investigated using chatbots and virtual assistants to support social communication skills in children with autism. For example, Kocaballi et al. [ 52 ] developed a chatbot called Tess that provides social skills training and support for children with autism. The chatbot was effective in improving social communication skills in children with autism. Similarly, Tanaka et al. [ 53 ] developed a virtual assistant called Miko that uses artificial empathy to support social communication skills in children with autism.

Further studies highlighted the importance of ethical consideration while using AL in education for children with autism. For example, there is a risk of perpetuating harmful stereotypes or reinforcing inappropriate behaviors if the AI system is not designed and programmed with ethical considerations [ 23 ]. Moreover, there is a risk of bias and discrimination if the AI system is trained on data that is not representative of the diverse population of children with autism [9]. Therefore, it is essential to carefully consider the ethical implications of using AI in education for children with autism. In conclusion, utilizing AI in education can transform how we think about learning and support children with autism to achieve their full potential.

Research Methodology

The study used purposive sampling to select 20 informants who met specific criteria. These individuals were parents or educators of autistic children and had valuable experience using AI-powered interventions to improve their children’s learning and social communication skills. They were all Iranian living in Tehran, Iran. 30% ( n  = 6) were female and 70% ( n  = 14) were male.

The participants in the study encompassed an age range spanning from 29 to 58 years old. Educators teaching experience was above 8 years. Recruitment efforts were conducted through various channels and social media platforms to ensure a diverse and representative sample. Potential participants were fully informed about the study’s purpose, procedures, and possible benefits throughout the recruitment process. They were also told of their rights as participants and the assurance of confidentiality. To confirm their willingness to participate, informants were asked for written consent before formal inclusion in the study.

Data collection

The study used semi-structured interviews and focus groups to collect data from the informants. The researcher developed the interview questions (Appendix), and a panel of three qualitative researchers reviewed their relevance. Interviews were conducted individually, either in person or virtually, and lasted approximately 45–60 min each. Focus groups with 3–5 participants conducted almost or in person were also organized. The duration of the focus group discussions was between 60 and 90 min. During the data collection process, the interviews and focus group sessions were audio-recorded to capture participants’ responses and insights accurately. These recordings were later transcribed verbatim, allowing a comprehensive analysis of the data collected. Through semi-structured interviews and focus groups, the study aimed to obtain complete and detailed information about participants’ experiences and perspectives regarding using AI-assisted interventions to support the learning and social communication skills of children with autism. The semi-structured nature of the interviews allowed for flexibility in exploring different topics while ensuring a consistent data collection framework for all participants. Additionally, the dynamic and interactive nature of the focus groups encouraged group discussions and allowed participants to share and build on one another.

Data analysis

Following the data collection phase, the study thoroughly analyzed the information collected. The audio recordings of the interviews and focus group sessions were transcribed verbatim, resulting in a comprehensive text dataset that captured participants’ responses and insights. The analysis began with a thorough familiarization process in which researchers immersed themselves in the transcribed data to understand participants’ accounts deeply. This immersion allowed researchers to identify recurring themes, patterns, and noteworthy information in the data set. A systematic analysis approach was used to ensure reliability and validity. Data were coded using a combination of inductive and deductive methods. First, an open coding process was conducted in which researchers generated initial codes by closely examining the data and labeling meaningful segments. As the analysis progressed, these codes were refined, grouped, and organized into categories and subcategories, creating a coding framework. After coding, researchers conducted a thematic analysis by identifying overarching themes from the data. The topics represented vital concepts, ideas, and perspectives shared by participants regarding the use of AI-assisted interventions to support the learning and social communication skills of children with autism. Throughout the analysis, the researchers ensured the accuracy and trustworthiness of the findings by employing techniques such as member checking, where participants were allowed to review and validate the interpretations made from their data.

Ethical considerations

The study adhered to ethical guidelines for conducting research with human subjects. Informed consent was obtained from all participants. Participants’ privacy and confidentiality were protected throughout the research process. The study also obtained ethical clearance from a relevant research ethics committee.

The study’s findings were presented in a report summarizing the themes and sub-themes that emerged from the data analysis. The report also provides recommendations for designing and implementing culturally and linguistically appropriate AI-powered interventions for children with autism while avoiding bias and discrimination in the learning materials and activities. The report also includes direct participant quotes to illustrate their experiences and perceptions. The findings are presented based on the order of research questions,

Benefits and challenges of AI-powered interventions

Informants of the study mentioned three benefits and some challenges of AI-empowered intervention for children with autism. Each is explained and exemplified as follows.

Increased engagement and motivation among children with autism

AI-powered interventions can use technologies like robots, virtual reality, and interactive games to provide personalized and engaging experiences for children with autism. Informants believed that AI-powered interventions can effectively increase engagement and motivation among children with autism. For example, educator 1 stated, “Children with autism who interacted with a humanoid robot showed increased engagement and motivation compared to those who received traditional therapy.” Educator 5 said, “By leveraging AI technologies, interventions for children with autism can be tailored to their needs and preferences, providing a more personalized and engaging learning experience. This can lead to improved outcomes and better quality of life for children with autism and their families. This finding is also supported by parent one, who stated, “My son used to struggle with traditional teaching methods, but with AI-powered interventions, he is more engaged and motivated to learn. The technology provides him with immediate feedback, which helps him understand his mistakes and learn from them.”

Customized and individualized interventions that cater to the unique needs of each child

Informants argued that every child with autism is unique, with their own set of strengths and challenges. Therefore, interventions tailored to each child’s specific needs and preferences can be more effective in promoting their development and well-being. This finding echoes the direct quotation by educator 6 who stated, “One size does not fit all when it comes to autism interventions. Each child is unique and requires a personalized approach that takes into account their individual strengths, challenges, and interests.” (Educator 6). Similarly, parent 6 stated, “As a parent, I have learned that the key to helping my child with autism is to focus on his individual needs. By working with his teachers and therapists to develop a personalized intervention plan, we have seen significant progress in his development and well-being.”

Real-time feedback to both children and educators about progress and areas for improvement

Real-time feedback involves providing immediate and ongoing information about a child’s performance and progress in a given activity or intervention. This feedback can reinforce positive behaviors, correct errors, and identify areas where additional support or instruction may be needed. Real-time feedback can be especially beneficial for children with autism, who may benefit from more frequent and targeted feedback to support their learning and development. By providing timely and specific feedback, children with autism can better understand their strengths and areas for improvement, and educators can adjust their interventions and supports accordingly. As an example, one of the educators stated, “Real-time feedback is crucial in helping children with autism learn and grow. By providing immediate and targeted feedback, we can reinforce positive behaviors and help children build new skills.” (Educator 4). Another educator stated, “Real-time feedback is not just important for children but for educators as well. By receiving ongoing feedback about a child’s progress, we can make more informed decisions about the interventions and supports that are most effective for them.“(Educator 8).

The potential for AI-powered interventions to enhance the work of educators and provide them with additional tools and resources

AI-powered interventions have the potential to enhance the work of educators and provide them with additional tools and resources to support the learning and development of children with autism. AI technologies like machine learning algorithms and natural language processing can analyze and interpret data from various sources, including assessment results, behavioral observations, and social communication interactions. This can provide educators with valuable insights and information about each child’s strengths, challenges, and learning needs. Educator 10 stated, “AI-powered interventions can provide educators with powerful tools and resources for supporting autistic children. By analyzing data and providing real-time feedback, these interventions can help educators tailor their teaching strategies and supports to the unique needs of each child.” Educator 3 also stated,” AI-powered interventions have the potential to transform the way we support children with autism in the classroom. By providing educators with insights and information about each child’s learning needs, these interventions can help us deliver more effective and personalized instruction.”

Challenges of AI-powered interventions

The content of interviews with informants was analyzed, and five main themes were extracted. Each is explained and exemplified as follows.

Lack of personalization

Informants stated that while AI-powered interventions have the potential to be personalized, there is a risk that they may not account for the unique needs and preferences of each child. For example, educator 3 stated, “We need to remember that technology is a tool, not a replacement for human interaction.”

Limited access to technology

Not all families and schools can access the necessary technologies for AI-powered interventions. As a parent of a child with autism notes, “Technology can be expensive, and not all families can afford it.”

Difficulty in interpreting and responding to social cues

Children with autism may have trouble analyzing and reacting to social cues, making it challenging to interact with AI technologies. A clinical psychologist notes: “Children with autism may struggle to understand that a robot or virtual character is not a real person, which can limit the effectiveness of AI-powered interventions.”

Ethical concerns

Ethical concerns surrounding using AI technologies with children include privacy, data security, and the potential for misuse or unintended consequences. The Director of Education at one School for Children with Autism notes: “We need to be mindful of the potential risks and unintended consequences of using AI technologies with children with autism.”

Lack of human interaction

While AI-powered interventions can be engaging and interactive, they cannot replace the importance of human interaction in promoting social and emotional development in children with autism. As a parent of a child with autism notes: “Technology can be helpful, but it is important to balance it with real-life experiences and interactions.”

Concerns about the cost and affordability of these interventions

One concern related to using interventions for children with autism is their cost and affordability. Many interventions, such as behavioral and developmental therapies, assistive technologies, and specialized education programs, can be expensive and may not be covered by insurance or other funding sources. This can create barriers for families, particularly those with limited financial resources, in accessing the interventions their child needs to thrive. As Educator 9 stated, “The cost of interventions for children with autism can be a significant burden for families, particularly those with limited financial resources. We must ensure these interventions are accessible and affordable for all families.” Similarly, parent 5 stated, “As a parent of a child with autism, the cost of interventions has been a major concern for our family. Based on our financial limitations, we have had to decide which interventions to prioritize.”

Suggestions for improving the quality of AL-empowered interventions

Interviews with informants were thematically analyzed, and different themes were extracted. Each theme is explained and exemplified as follows.

Using culturally and linguistically appropriate interventions

Participants emphasized the importance of designing and implementing AI-powered interventions that are culturally and linguistically appropriate for a diverse population of children with autism. Some of the suggestions made by participants include:

Ensuring that the language and content of the interventions are culturally sensitive and relevant to the target population.

Incorporating diverse perspectives and experiences into the design and development process.

Providing interventions in multiple languages to accommodate diverse linguistic backgrounds.

Quotations from educators and parents support these suggestions. For instance, educator 1 stated, “Cultural sensitivity is important when designing interventions for children with autism, particularly for those from diverse backgrounds. We need to ensure that the interventions are culturally relevant and take into account the unique needs and experiences of each child.” Similarly, parent 6 stated, “As a parent of a child with autism who comes from a different cultural background, I appreciate interventions that take into account my child’s unique needs and experiences. It’s important to have interventions that are culturally sensitive and relevant.”

Avoiding bias and discrimination

Participants also emphasized the importance of avoiding bias and discrimination in AI-powered interventions’ learning materials and activities. Some of the suggestions made by participants include:

Conducting regular audits of the interventions to identify and address any potential biases or discriminatory content.

Incorporating diverse perspectives and experiences into the design and development process to avoid perpetuating stereotypes.

Providing training and education to educators and developers to ensure that they are aware of and can address potential biases and discrimination.

Quotations from informants support these strategies. As an example, educator 8 stated,

“We need to be careful to avoid stereotypes and biases in the interventions we design and implement. It’s important to be aware of potential biases and to work to address them.” Similarly, parent 7 stated, “To ensure that AI-powered interventions are effective and inclusive, we need to make sure that they are designed with diversity and inclusivity in mind. This means avoiding discrimination and bias in the materials and activities.”

Training educators

Participants discussed the role of educators in implementing AI-powered interventions to support the learning and social communication skills of children with autism. Some of the key findings include:

The importance of providing training and education to educators to ensure that they can effectively implement these interventions.

The need for educators to work collaboratively with parents and other professionals to ensure that the interventions are tailored to the unique needs of each child.

“Educators play a critical role in implementing AI-powered interventions. They need to be trained and educated on how to use these interventions effectively and how to tailor them to the unique needs of each child.” [Educator 3).

We regularly audit the interventions to identify and address potential biases or discriminatory content

Conducting regular audits of interventions for children with autism is an essential step in ensuring that these interventions are effective, evidence-based, and free from biases or discriminatory content. Regular audits help identify areas for improvement, ensure that interventions are aligned with current best practices and ethical guidelines, and promote accountability and transparency in developing and implementing these interventions. Here are two quotations that address the importance of conducting regular audits of interventions for children with autism. To exemplify this finding, the following quotations are presented:

“As educators and researchers, it is our responsibility to ensure that interventions for children with autism are evidence-based, effective, and free from biases or discriminatory content. Regular audits can help us identify and address any areas of concern and promote the highest standards of quality and ethical practice.” (Educator 4). “Regular audits are essential to ensuring that interventions for children with autism are meeting the needs of all children, regardless of their race, ethnicity, gender, or other factors. We must be vigilant in identifying and addressing any biases or discriminatory content that may be present, and work to create interventions that are inclusive and equitable for all children.” (Educator 9).

Involving families and communities in the design and implementation process ensures their voices and perspectives are heard and valued

Involving families and communities in the design and implementation process of interventions for children with autism is crucial to ensuring that their voices and perspectives are heard and valued. Families and communities can provide valuable insights and feedback on the needs and preferences of children with autism and the effectiveness and cultural relevance of interventions. Here are two quotations that address the importance of involving families and communities in the design and implementation process:

“Families and communities are essential partners in the design and implementation of interventions for children with autism. Their insights and feedback can help us create interventions that are effective, culturally relevant, and responsive to the needs of all children.” (Educator 10). “As a parent of a child with autism, I know firsthand the importance of involving families and communities in the design and implementation of interventions. By listening to our voices and perspectives, researchers and educators can create interventions that are more meaningful and effective for our children.” (Parent 8).

Discussion and implications

The present study aimed at exploring the teachers and educators’ experiences and perceptions of artificial intelligence powered interventions for Autism groups. A qualitative research study was employed and interviews were analyzed thematically and different themes were extracted. Participant believed that AI-powered interventions represent a groundbreaking frontier in reshaping the support systems for the learning and social communication skills of children with autism [ 54 ]. Participants also highlighted several noteworthy benefits, with a critical emphasis on the heightened engagement and motivation witnessed among children with autism when exposed to AI-powered interventions [ 1 , 2 , 54 ]. Recognizing the limitations of traditional teaching methods in meeting the distinctive learning needs of these children, AI interventions emerge as a promising avenue [ 1 , 2 ].

The first advantage underscored by participants is the adaptability of AI-powered interventions to provide personalized and individualized support, furnishing real-time feedback to children and educators regarding progress and areas for improvement [ 3 , 4 , 5 ]. This tailored approach aligns seamlessly with the diverse and unique challenges presented by children with autism. However, embracing AI-powered interventions is full of challenges, and participants articulated various concerns [ 55 , 56 ]. Technical glitches and difficulties were identified as potential disruptors of the learning process, prompting apprehensions about an overreliance on technology [ 55 , 56 ]. Moreover, the limited access to technology and resources in specific communities and regions raises concerns about the equitable distribution of intervention benefits [ 55 , 56 ]. Addressing these challenges is imperative to ensure that all children with autism, irrespective of geographical location or socioeconomic status, have equitable access to effective interventions.

The second theme, cultural and linguistic appropriateness, emerged as a primary consideration, with participants highlighting the importance of interventions tailored to the diverse backgrounds of children with autism [ 55 , 56 ]. This includes ensuring that the language and content of interventions are culturally sensitive and relevant, integrating diverse perspectives into the design process, and providing interventions in multiple languages ​​to accommodate linguistic diversity [ 7 , 8 , 9 ]. This finding is consistent with the findings of the previous research which highlighted that language differences can pose significant barriers to accessing autism interventions, highlighting the urgent need for interventions in the child’s native language [ 66 ].

As the third extracted theme “mitigating bias and discrimination in AI-powered interventions” extracted as another critical aspect, necessitating regular audits to identify and rectify potential biases [ 57 ]. The imperative of incorporating diverse perspectives into the design process and providing training to educators and developers to address biases and discrimination was highlighted as crucial [ 10 , 11 ]. This finding confirms the findings of the study that emphasizes the pivotal role of involving families and communities in designing and developing autism interventions to ensure cultural sensitivity and effectiveness [ 67 ].

Despite the above-mentioned potential of AI-powered interventions, the participants concurrently acknowledged the need for further research to evaluate the effectiveness of remote interventions and ensure their cultural and linguistic appropriateness [ 12 , 13 ]. Simultaneously, there are apprehensions and concerns with the potential for these interventions to exacerbate existing disparities in access to care if not implemented equitably. Moreover, challenges have been discerned alongside these benefits, prompting a comprehensive approach to ensure effectiveness, inclusivity, and accessibility [ 55 , 56 ]. Technical glitches, concerns about overreliance on technology, and limited access to resources pose hurdles that need addressing [ 55 , 56 ]. Policymakers must prioritize equitable access, focusing on both technological infrastructure and training programs for educators [ 55 , 56 ].

In addition, ensuring cultural and linguistic appropriateness emerges as a critical consideration in designing and implementing AI-powered interventions [ 55 , 56 ]. Culturally sensitive content, diverse perspectives in development, and multilingual offerings are underscored as essential [ 7 , 8 , 9 ]. Recognizing potential biases and discrimination, participants advocate for regular audits, diversity in development teams, and education on bias mitigation as integral components of ethical AI intervention deployment [ 10 , 11 , 57 ].

AI-powered interventions have emerged as a promising avenue to revolutionize the support for children with autism, offering transformative benefits while presenting challenges that demand careful consideration [ 54 ]. One pivotal advantage emphasized by participants is the heightened engagement and motivation observed among children with autism undergoing AI-powered interventions [ 54 ]. This is particularly noteworthy as traditional teaching methods often need to catch up in meeting the unique learning needs of these children. AI interventions, utilizing technologies such as robots, virtual reality, and interactive games, create personalized and engaging experiences, as reported by educators and parents.

It can also be concluded that transformative potential of AI-powered interventions underscores the need for collaborative efforts among educators, parents, and developers, ensuring effectiveness, inclusivity, and accessibility for all children [ 60 , 61 , 62 , 63 , 64 , 65 ]. The imperative of providing interventions in multiple languages and incorporating diverse perspectives into the design and development process is underscored [ 63 ]. Additionally, including culturally responsive teaching practices alongside AI interventions emerges as a strategy to enhance engagement and outcomes, particularly for children from diverse cultural backgrounds [ 68 ]. Ongoing research, collaborative endeavors, and an unwavering commitment to addressing challenges are imperative to maximize the benefits of AI-powered interventions for children with autism.

It can also be inferred that the collaborative involvement of families and communities is championed to enhance interventions’ impact and cultural sensitivity [ 12 , 13 , 67 ]. Balancing technology with human interaction is deemed crucial, emphasizing the irreplaceable role of personal connections in social and emotional development [ 39 , 41 ]. Moreover, the potential for AI-powered interventions to address access disparities, especially in remote or underserved areas, highlights the importance of further research and evaluation [ 58 , 59 ]. However, concerns persist about exacerbating existing disparities, demanding meticulous attention to cultural, linguistic, and regional nuances.

As another concluding remark, it can be inferred that AI-powered interventions have the potential to revolutionize the way we support the learning and social communication skills of children with autism. These interventions can provide customized and individualized interventions that cater to the unique needs of each child, providing real-time feedback to both children and educators about progress and areas for improvement. AI-powered interventions can also improve access to care for children with autism, particularly for those in remote or underserved areas. The findings suggest that to ensure that AI-powered interventions are culturally and linguistically appropriate for a diverse population of children with autism while also avoiding bias and discrimination in the learning materials and activities, it is essential to incorporate various perspectives and experiences into the design and development process, provide interventions in multiple languages, ensure that the language and content of the interventions are culturally sensitive and relevant, deliver training and education to educators and developers, conduct regular audits of the interventions, involve families and community members in the design and implementation process, and use culturally responsive teaching practices. These efforts can help to address the challenges and considerations of using AI-powered interventions and ensure that all children with autism have access to practical, inclusive, and culturally appropriate interventions.

However, several challenges and considerations need to be taken into account to ensure that these interventions are effective, inclusive, and accessible to all children with autism. These challenges include technical difficulties, overreliance on technology, limited access to technology and resources in specific communities and regions, and the need to design and implement culturally and linguistically appropriate interventions to avoid bias and discrimination.

Finally, one recurring theme is the importance of professional development for educators, which recognizes their critical role in successfully applying AI-powered interventions. Providing educators with technological expertise, cultural sensitivity, and ethical awareness is essential. Furthermore, legislators, educators, and parents must work together to prioritize the financial accessibility of interventions. The ramifications in this complex environment suggest a comprehensive and collaborative strategy. The key to success is overcoming obstacles, adopting technology responsibly, and giving accessibility and inclusivity top priority in intervention and education initiatives. Because technology constantly changes, we must remain committed to ongoing iteration and improvement. Community, parent, and educator feedback loops help us refine AI-powered interventions.

Limitations and suggestions for further studies

The current body of research on AI-powered interventions for children with autism, while promising, grapples with several limitations that warrant careful consideration. Firstly, the generalization of findings remains a challenge, as many studies tend to focus on specific demographic groups or particular manifestations of autism spectrum disorder (ASD). This limits the broader applicability of the insights gained, as the diversity within the autism spectrum may not be comprehensively represented. Additionally, a notable gap exists in understanding the long-term efficacy of AI interventions. While short-term outcomes are frequently explored, there is a scarcity of research delving into the sustained impact of these interventions on the developmental trajectories of children with autism. Longitudinal studies are crucial to elucidating AI-powered approaches’ durability and lasting benefits.

Moreover, the current literature may lack ethnic and cultural diversity, raising concerns about AI interventions’ universal applicability and artistic sensitivity. This underrepresentation hinders our understanding of how these technologies might function across diverse populations. Ethical considerations, although acknowledged, need to be thoroughly examined. Privacy, data security, and potential biases in algorithmic decision-making demand a more in-depth investigation to ensure responsible and equitable use of AI technologies in educational settings.

To address these limitations, future research should prioritize several vital areas. Long-term impact assessments are imperative to ascertain the sustained efficacy of AI interventions over time. Diverse and inclusive studies encompassing a range of ethnicities and cultural backgrounds are essential to validate the universal applicability of these technologies. Robust ethical frameworks should be developed to guide the implementation of AI interventions, addressing privacy, security, and bias concerns. Comparative studies, pitting AI interventions against traditional methods, will offer nuanced insights into their relative advantages and limitations. Family and community involvement in designing and implementing AI interventions should be explored further, recognizing the unique insights these stakeholders bring. Finally, comprehensive cost-benefit analyses are necessary to evaluate the economic aspects of AI interventions, ensuring their affordability and long-term viability in diverse educational settings. In navigating these avenues, researchers can contribute substantively to the responsible and inclusive integration of AI-powered interventions for children with autism.

Data availability

The data will be made available upon request from the corresponding author (Corresponding author: email: [email protected].

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Acknowledgements

The authors would like to thank all participants who contributed to the study.

This work was supported by The General Project of Beijing Postdoctoral Research Foundation in 2023, “Research on the Representation of the Tacit Knowledge of High School History Teachers Based on Natural language processing”. (Project No.2023-zz-182)

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Li, G., Zarei, M.A., Alibakhshi, G. et al. Teachers and educators’ experiences and perceptions of artificial-powered interventions for autism groups. BMC Psychol 12 , 199 (2024). https://doi.org/10.1186/s40359-024-01664-2

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Active involvement in scientific research of persons living with dementia and long-term care users: a systematic review of existing methods with a specific focus on good practices, facilitators and barriers of involvement

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Active involvement of persons living with dementia (PLWD) and long-term care (LTC) users in research is essential but less developed compared to other patient groups. However, their involvement in research is not only important but also feasible. This study aims to provide an overview of methods, facilitators, and barriers for involving PLWD and LTC users in scientific research.

A systematic literature search across 12 databases in December 2020 identified studies involving PLWD, LTC users, or their carers beyond research subjects and describing methods or models for involvement. Qualitative descriptions of involvement methods underwent a risk of bias assessment using the Critical Appraisal Skills Programme (CASP) Qualitative Checklist 2018. A data collection sheet in Microsoft Excel and thematic analysis were used to synthesize the results.

The eighteen included studies delineated five core involvement methods spanning all research phases: advisory groups, formal and informal research team meetings, action groups, workshops, and co-conducting interviews. Additionally, two co-research models with PLWD and carers were found, while only two studies detailed LTC user involvement methods. Four distinct involvement roles were identified: consulting and advisory roles, co-analysts, co-researchers, and partners. The review also addressed barriers, facilitators, and good practices in the preparation, execution, and translation phases of research, emphasizing the importance of diversity, bias reduction, and resource allocation. Trust-building, clear roles, ongoing training, and inclusive support were highlighted.

Conclusions

Planning enough time for active involvement is important to ensure that researchers have time to build a trusting relationship and meet personal needs and preferences of PLWD, LTC users and carers. Researchers are advised not to presume the meaning of burden and to avoid a deficit perspective. A flexible or emergent design could aid involved persons’ ownership of the research process.

Trial registration

Prospero 2021: CRD42021253736.

Peer Review reports

In research characterized by active involvement, the target group plays a pivotal role in shaping research decisions and outcomes, directly impacting them. Involving patients in health research offers significant benefits [ 1 , 2 ]: it enhances participant recruitment [ 2 ], refines research questions [ 2 ], aligns study results with the target population [ 1 , 2 ], and promotes effective implementation of findings [ 1 ]. Active involvement of patients has also benefits for themselves, namely an enhanced understanding of research, building relationships, personal development, improved health and wellbeing, and enjoyment and satisfaction [ 3 , 4 ]. It gives them a sense of purpose and satisfaction through their tangible impact.

However, for long-term care (LTC) users and persons living with dementia (PLWD) active involvement in research is less developed than for other patient groups [ 5 , 6 ]. PLWD and LTC users share similar care needs, encompassing assistance with activities of daily living (ADLs), medication management, medical condition monitoring, and emotional support. Furthermore, a substantial portion of LTC users comprises individuals living with dementia [ 7 ]. Additionally, statistical data from the United States reveals that one in four older individuals is likely to reside in long-term care (LTC) facilities [ 8 ], and approximately forty to eighty percent of LTC residents in the United States, Japan, Australia, and England experience dementia or severe memory problems [ 7 , 9 ].

Due to these considerations, we have chosen to combine the target audiences of PLWD and LTC users in our systematic review. However, it's important to note that while there are potential advantages to combining these target groups, there may also be challenges. PLWD and LTC users may have varying needs, preferences, and experiences, including differences in care requirements driven by individual factors like the stage of dementia, coexisting conditions, and personal preferences. Therefore, it's imperative to conduct comprehensive research and involve these communities to ensure that involvement approaches are not only inclusive but also tailored to meet their specific requirements.

Given our ageing population and the intricate health challenges faced by PLWD and LTC users, including their vulnerability and shorter life expectancy in old age, it's crucial to establish effective research involvement methods. These individuals have unique needs and preferences that require attention. They possess a voice, and as researchers, it is our responsibility to not only listen to them but also actively involve them in the research process. Consequently, it is essential to identify means through which the voices of PLWD and LTC users can be effectively heard and ensure that their input is incorporated into research.

Fortunately, publication of studies on involvement of PLWD and LTC users in scientific research is slowly increasing [ 5 , 9 , 10 , 11 ]. A few reviews have described how PLWD and LTC users were involved [ 5 , 9 , 10 ]. However, with the increasing attention for involvement, the understanding of when involvement is meaningful grows and stricter requirements can be imposed to increase the quality of active involvement [ 12 , 13 ]. To our knowledge there is no up to date overview of involvement methods used with either or both PLWD and LTC users. Such an overview of involvement methods for PWLD and LTC users would provide a valuable, comprehensive resource encompassing various stages of the research cycle and different aspects of involvement. It would equip researchers with the necessary guidance to navigate the complexities of involving PLWD and LTC users in their research projects.

Recognizing the need to enhance the involvement of PLWD and LTC users in scientific research, this systematic review aims to construct a comprehensive overview of the multiple methodologies employed in previous studies, along with an examination of the facilitators and barriers of involvement. Our overarching goal is to promote inclusive and effective involvement practices within the research community. To achieve this objective, this review will address the following questions: (1) What kind of methods are used and how are these methods implemented to facilitate involvement of PLWD and LTC users in scientific research? (2) What are the facilitators and barriers encountered in previous research projects involving PLWD and LTC users?

Protocol and registration

The search and analysis methods were specified in advance in a protocol. The protocol is registered and published in the PROSPERO database with registration number CRD42021253736. The search and analysis methods are also described below more briefly.

Information sources, search strategy, and eligibility criteria

In preparation of the systematic literature search, key articles and reviews about involvement of PLWD and LTC users in research were screened to identify search terms. In addition, Thesaurus and MeSH terms were used to broaden the search. The search was conducted on December 10, 2020, across multiple databases: PubMed, Medline, Embase, Emcare, Web of Science, Cochrane Library, PsycINFO, Academic Search Premier, JSTOR, Social Services Abstracts, Sociological Abstracts, Psychology and Behavioral Sciences Collection. The search terms were entered in "phrases". The search strategy included synonymous and related terms for dementia, LTC user, involvement, research, method, and long-term care. The full search strategy is provided in supplement 1 .

After conducting the search, records underwent initial screening based on titles and abstracts. Selected reports were retrieved for full-text assessment, and studies were evaluated for eligibility based on several criteria. However, no restriction was made regarding publication date. First, to be included studies had to be written in English, German, French, or Dutch. Second, we only included original research studies. Third, studies were excluded when the target group or their representatives were not involved in research, but only participated as research subjects. Fourth, studies were excluded when not describing involvement in research. Therefore, studies concerning involvement in care, policy, or self-help groups were excluded. Fifth, the focus of this systematic review is on methods. Therefore, studies with a main focus on the results, evaluation, ethical issues, and impact of involvement in research were excluded. Additionally, we have not set specific inclusion or exclusion criteria based on study design since our primary focus is on involvement methodologies, regardless of the chosen research design. Sixth, the included studies had to concern the involvement in research of PLWD or adult LTC users, whether living in the community or in institutional settings, as well as informal caregivers or other representatives of these groups who may represent PLWD and LTC users facing limitations. Studies that involved LTC users that were children or ‘young adults’, or their representatives, were excluded. Studies were also excluded if they involved mental healthcare users if it remained unclear if the care that they received entailed more than only treatment from mental healthcare providers, but for example also assistance with ADL.

Terminology

For readability purposes, we use the abbreviation PLWD to refer to persons diagnosed with dementia, and we use the abbreviation LTC users to refer to persons receiving long-term care, at home or as residents living in nursing homes or other residential facilities. We use the term carers to refer to informal caregivers and other representatives of either PLWD or LTC users. As clear and consistent definitions regarding participatory research remains elusive [ 14 , 15 ], we formulated a broad working definition of involvement in research so as not to exclude any approach to participatory research. We defined involvement in research as “research carried out ‘with’ or ‘by’ the target group” [ 16 ], where the target group or their representatives take part in the governance or conduct of research and have some degree of ownership of the research [ 12 ]. It concerns involvement in research in which lived experienced experts work alongside research teams. We use the terms participation and participants, to refer to people being part of the research as study subjects.

Selection process, data-collection process, and data items

Titles and abstracts were independently screened by the first and second author (JG and LT). Only the studies that both reviewers agreed and met the inclusion criteria were included in the full-text screening process. Any uncertainty about whether the studies truly described a model or approach for involvement, was resolved by a quick screening of the full-text paper. The full-text screening process was then conducted according to the same procedure by JG and LT. Any disagreement was resolved by discussion until consensus was reached. If no agreement could be reached, a third researcher (MC) was consulted. References of the included studies were screened for any missing papers.

The following information was collected on a data collection sheet in Microsoft Excel: year and country of publication, topic, research aim, study design, living situation of involved persons (at home or institutionalized), description of involved persons, study participants (study subjects), theories and methods used, type/role(s) of involvement, research phase(s), recruitment, consent approach, study setting, structure of participatory activities, training, resources, facilitators, barriers, ethics, benefits, impact, and definition of involvement used.

JG independently extracted data from all included studies, the involved co-researcher (THL) independently extracted data from two studies, the second author (LT) from five. Differences in the analysis were discussed with the co-researcher (THL) and second author (LT) until consensus was reached. As only minor differences emerged, limited to the facilitator and barrier categories, data from the remaining studies was extracted by JG.

Risk of bias assessment

Every research article identified through the systematic review exclusively comprised qualitative descriptions of the involvement method(s) employed. Consequently, all articles underwent evaluation using the Critical Appraisal Skills Programme (CASP) Qualitative Checklist 2018 [ 17 ], as opposed to the checklists intended for quantitative or mixed methods research. All included studies were independently assessed on quality by two reviewers (JG,LT) and any disagreement was resolved by discussion until consensus was reached. The CASP Qualitative Checklist consists of ten questions. The checklist does not provide suggestions on scoring, the first author designed a scoring system: zero points if no description was provided (‘no’), one point if a minimal description was provided (‘can’t tell’) and two points when the question was answered sufficiently (‘yes’). The second question of the checklist, “is a qualitative methodology appropriate”, was not applicable to the aims (i.e., to describe involvement) of the included studies and was therefore excluded. The tenth question was translated into a ‘yes’, ‘can’t tell’, or ‘no’ score to fit the scoring system. A maximum of eighteen points could be assigned.

Synthesis methods

Tables were used to summarize the findings and to acquire an overview of (1) the kinds of methods used to enable involvement of PLWD, LTC users, or carers in scientific research, and (2) the facilitators and barriers for involving this target group in scientific research. As to the first research aim, the headings of the first two tables are based on the Guidance for Reporting Involvement of Patients and the Public, long form version 2 (GRIPP2-LF) [ 18 ]. Because our systematic review focusses on methods, only the topics belonging to sections two, three, and four were included. Following Shippee et al., three main research phases were distinguished: preparation, execution, and translation [ 19 ]. Furthermore, the following fields were added to the GRIPP2-LF: First author, year of publication, country of study, setting of involvement, frequency of meetings, and a summary description of activities.

Concerning the second research aim, the extracted facilitators, barriers, and good practices were imported per study in ATLAS.ti for qualitative data analysis. Following the method for thematic synthesis of qualitative studies in systematic reviews [ 20 ], all imported barriers, facilitators and good practices were inductively coded staying 'close' to the results of the original studies, which resulted in 50 initial codes. After multiple rounds of pile sorting [ 21 ], based on similarities and differences and discussions in the research team, this long code list was grouped into a total of 27 categories, which were thereafter subsequently organized into 14 descriptive themes within the three research phases (preparation, execution, translation).

Study selection and characteristics

The Prisma Flow Diagram was used to summarize the study selection process [ 22 ]. In the full text screening, 72 of the 93 remaining studies were excluded because they were not original research articles (n = 5), not about involvement (n = 8), not about involvement in a research project (n = 1), they did not describe a model or method for involvement (n = 34), or they were not about PLWD or LTC users (n = 24). The search resulted in 18 publications eligible for analysis (Fig.  1 ).

Preferred Reporting items for Systematic Reviews and Meta-analyses (PRISMA) flow diagram

Table 1 presents the general study characteristics. Two studies explicitly aimed to develop a model for involvement or good practice, and both focus on co-research either with PLWD [ 23 ] or their carers [ 13 ]. The other sixteen provide a description of the involvement of PLWD [ 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 ] or LTC users in their research projects [ 35 , 36 , 37 , 38 , 39 ].

Quality assessment

Table 1 presents the CASP-score per study [ 17 ]. Five scored 16 to 18 points [ 13 , 28 , 29 , 32 , 35 ], indicating high quality with robust methods, clear aims, and strong data analysis. Eleven scored 12 to 15 [ 23 , 24 , 26 , 30 , 32 , 33 , 34 , 36 , 37 , 38 , 39 ], showing generally strong methodologies but with some limitations. Two scored 9 or lower [ 25 , 27 ], signifying significant methodological and analytical shortcomings. Notably, these low-scoring studies were short articles lacking clear recommendations for involvement in research.

Design and implementation of involvement

Phases and methods of involvement.

Table 2 describes the involvement methods used for and the implementation of involvement in research. The included studies jointly presented methods for involvement in the three main research phases [ 19 ]. Regarding the preparation phase, which involves the preparatory work for the study, only three studies provided detailed descriptions of the methods employed [ 26 , 30 , 32 ]. The execution phase, encompassing the actual conduct of the research, was most frequently discussed [ 23 , 24 , 25 , 26 , 27 , 28 , 29 ]. Five studies addressed the translation phase [ 13 , 25 , 31 , 36 , 37 ], where the focus shifts to translating research findings into actionable outcomes.

The eighteen studies introduced a variety of involvement methods, categorizable into five groups: 1) advisory groups, 2) research team meetings (both formal and informal), 3) action groups, 4) workshops, and 5) co-research in interviews. In five studies, individuals including PLWD, LTCF residents, carers, and health professionals participated in advisory/reference groups [ 25 , 26 , 27 , 32 ], working groups [ 27 ], and panels [ 28 ]. These groups offered valuable feedback on research aspects, spanning protocols, design, questionnaires, and implementation of research. Meetings occurred at varying frequencies - monthly, quarterly, or biannually.

Two studies exemplify diverse research collaboration settings. One involving older individuals within an academic research team of five [ 37 ], and another featuring a doctoral student and a co-researcher conducting informal monthly discussions at a local coffee shop [ 31 ]. Brown et al. sought to minimize power differentials and enhance inclusivity [ 37 ], while Mann and Hung focused on benefiting people with dementia and challenging negative discourse on dementia [ 31 ].

An additional five studies employed methods involving frequent meetings, including action [ 35 , 39 ], inquiry [ 23 ], and discussion groups [ 29 , 36 ] In these groups, involved persons with lived experience contributed to developing a shared vision and community improvements, such as enhancing the mealtime experience in care facilities [ 35 ].

Seven studies involved individuals through workshops, often conducted over one or two sessions. These workshops contributed to generating recommendations [ 37 ], informing future e-health designs [ 29 , 30 ], and ensuring diverse perspectives and lived experiences were included in data analysis [ 13 , 24 , 32 , 33 ]. In three studies, representatives worked as co-researchers in interviews, drawing on personal experiences to enhance the interview process, making it more dementia-appropriate and enriching data collection [ 13 , 32 , 34 ]. Finally, one study involved representatives in the recruitment and conduct of interviews [ 38 ].

People involved

The number of persons involved varied from a single co-researcher [ 31 ] to 34 panel individuals providing feedback on their experiences in a clinical trial [ 28 ]. Thirteen studies focussed on PLWD: eleven involved PLWD themselves [ 23 , 24 , 25 , 26 , 27 , 29 , 30 , 31 , 32 , 33 , 34 ], one exclusively focused on caregivers [ 13 ], and another one involved people without or with mild cognitive impairment, who participated in a study examining the risks of developing Alzheimer's disease [ 28 ]. Although not all articles provided descriptions of the dementia stage, available information indicated that individuals involved typically fell within the early to mid-stages of dementia [ 29 , 30 , 32 , 33 , 34 ]. Next to PLWD and carers, two studies additionally involved organizational or advocacy representatives [ 25 , 27 ]. The other five studies concerned older adults living in a LTC facility. Two of them involved older residents themselves [ 35 , 39 ], the other three carers, older community/client representatives or health care practitioners [ 36 , 37 , 38 ].

Roles and level of involvement

Four general roles could be identified. First, consultation and advisory roles were held by PLWD and carers [ 25 , 26 , 27 , 28 , 29 , 30 , 32 ], where involved persons share knowledge and experiences to make suggestions [ 32 ], but the research team retained formal decision-making power [ 25 ]. Second, PLWD were involved as co-analysts in data analysis [ 24 , 32 , 33 ]. Co-analysts influence data analysis, but the decision-making power remained with academic researchers [ 24 ]. Third, in six studies the co-researcher role was part of the research design in which involved persons and researchers steer and conduct research together [ 13 , 23 , 31 , 32 , 34 , 36 ]. Finally, two studies partnered with LTC residents [ 35 , 39 ], with residents at the core of the group, and positioned as experts by experience [ 39 ]. Residents had the decision-making authority regarding how to improve life in LTC facilities [ 35 ].

Models for involvement in research

Only two studies designed a model for co-research with PLWD [ 23 ] or their carers [ 13 ] across all research phases. These models underscored the importance of iterative training for co-researchers [ 13 , 23 ] and academic researchers [ 23 ]. Furthermore, these studies advocate involving co-researchers early on in the research process [ 13 ] and in steering committees [ 23 ]. Co-researchers can be involved in designing research materials [ 23 ], conducting interviews [ 13 , 23 ], analysing data [ 13 ], and co-disseminating findings [ 13 , 23 ]. Additionally, one study stressed involving PLWD in identifying (future) research priorities [ 23 ].

Barriers, facilitators, and good practices in research phases

Preparation phase.

Table 3 describes the barriers, facilitators, and good practices per main research phase. Lack of diversity in ethnicity and stages of dementia in the recruitment of involved persons is mentioned as a recurring barrier [ 26 , 28 , 32 , 33 ]. The exclusion of people with cognitive impairments is partly due to gatekeepers’ and recruiters’ bias towards cognitively healthy people [ 28 , 32 ]. It is stressed that researchers should refrain from making assumptions about the abilities of PLWD and ask the person what he/she is willing to do [ 31 ]. It is considered good practice to involve people regardless of cognitive abilities [ 23 ], based on skills, various personal characteristics [ 13 ] and, if possible, relevant prior experience [ 38 ].

Many studies stress the importance of building a mutual trusting relationship between involved persons and academic researchers [ 13 , 23 , 31 , 33 , 34 , 37 ]. A good relationship is believed to break down social barriers [ 37 ], foster freedom of expression [ 33 ], and thereby avoiding tokenistic involvement [ 13 ]. In addition, spending time with these persons is important to become familiar with an individual’s strengths and limitations [ 31 ].

Opting for naturally evolving involvement roles was mentioned as a barrier, as this may result in conflicting expectations and irrelevant tasks [ 37 ]. A clear role description and clarification of tasks is key to balancing potentially different expectations of the involved persons and researchers [ 26 , 28 , 29 , 32 , 38 ]. When designing a role for involvement in research, good practices dictate taking into account personal skills, preferences, development goals, and motivation for involvement [ 13 , 32 ]. This role should ideally be designed in collaboration with involved persons [ 13 , 32 ].

The perception of providing training to involved persons is ambivalent. Studies cited that training should not aim to transform them into “pseudo-scientist” [ 32 , 37 ] and that it raises the costs for involvement [ 28 ]. However, multiple scholars emphasize the importance of providing iterative training to facilitate meaningful involvement and development opportunities [ 13 , 23 , 28 , 31 , 32 , 33 , 36 , 37 ]. Training can empower involved persons to engage in the research process equally and with confidence, with the skills to fulfil their role [ 13 , 33 , 38 ]. However, the implementation of training may present a potential conflict with the fundamental principle of valuing experiential knowledge [ 37 ] and should avoid the objective of transforming co-researchers into 'expert' researchers [ 32 ]. Academic researchers should also be offered training on how to facilitate meaningful involvement [ 13 , 23 , 28 , 31 ].

Limited time and resources were mentioned as barriers to involvement that can delay the research process [ 13 , 33 , 36 , 39 ], restrict the involvement [ 28 ] and hinder the implementation of developed ideas [ 39 ]. Financial compensation for involvement is encouraged [ 25 , 26 , 27 , 32 ], as it acknowledges the contribution of involved persons [ 13 ]. Thus, meaningful involvement in research requires adequate funding and infrastructure to support the involvement activities [ 13 , 28 , 33 , 37 ].

Execution phase

The use of academic jargon and rapid paced discussions [ 13 , 37 ], power differentials, and the dominant discourse in biomedical research on what is considered “good science” can limit the impact of involvement [ 13 , 24 , 32 , 36 , 37 ]. Facilitating researchers should reflect on power differentials [ 35 ] and how decision-making power is shared [ 31 ]. Other facilitating factors are making a glossary of terms used and planning separate meetings for “technical topics” [ 37 ]. In addition, an emergent research design [ 35 ] or a design with flexible elements [ 28 ] can increase ownership in the research project and provide space for involvement to inform the research agenda [ 28 , 35 ]. This requires academic researchers to value experiential knowledge and to have an open mind towards the evolving research process [ 13 , 23 , 31 ].

Furthermore, managing the involvement process and ensuring equity in the collaboration [ 13 , 32 , 33 ], facilitating researchers must encourage involved persons to voice their perspectives. This means that they sometimes need to be convinced that they are experts of lived experience [ 32 , 33 , 36 , 37 , 39 ]. To enable involvement of PLWD, the use of visual and creative tools to prompt memories can be considered [ 24 , 30 , 33 , 34 ], as well as flexibility in relation to time frames and planning regular breaks to avoid too fast a pace for people who may tire easily [ 24 , 25 , 29 , 30 ].

Involvement can be experienced as stressful [ 13 , 32 , 38 ] and caring responsibilities may interfere [ 26 ]. Tailored [ 29 ] physical and emotional support should therefore be offered [ 13 , 23 , 38 ] without making assumptions about the meaning of burden [ 30 , 31 ]. Moreover, being the only PLWD involved in an advisory group was experienced as intimidating [ 25 ] and, ideally, a larger team of PLWD is involved to mitigate responsibilities [ 37 ]. PLWD having a focal point of contact [ 28 , 37 ] and involving nurses or other staff with experience working with PLWD and their carers [ 29 , 30 ] are mentioned as being beneficial. Some stress the importance of involving carers when engaging with PLWD in research [ 25 , 29 , 30 ].

To avoid an overload of information that is shared with the involved persons, tailoring information-sharing formats to individual preferences and abilities is essential to make communication effective [ 27 , 37 ].

Translation

Two studies indicated a need for more robust evaluation measures to assess the effect of involvement [ 28 , 33 ]. Reflection and evaluation of the involvement serves to improve the collaboration and to foster introspective learning [ 13 , 23 , 26 , 31 ]. The included studies evaluated involvement through the use of reflective diaries [ 13 ] or a template [ 38 ] with open-ended questions [ 33 ].

Two studies postulate that findings should benefit and be accessible to PLWD [ 23 , 31 ]. The use of creative tools not only enables involvement of PLWD, but can also increase accessibility of research findings and expand the present representation of PLWD [ 23 ].

The 18 included studies presented multiple methods for involvement in all three research phases. We found five types of involvement: advisory groups, (formal and informal) research team meetings, action groups, workshops, and co-conducting interviews. Only two studies described methods for involvement of LTC users in research. Involved persons were most often involved in consulting and advisory roles, but also as co-analysts, co-researchers, and partners. Involved persons’ roles can evolve and change over time. Especially as involved persons grow into their role, and gain confidence and knowledge of the specific research project, a more active role with shared responsibilities can become part of the research project. In addition, multiple involvement roles can be used throughout the research depending on the research phase.

Compared to the five types of involvement that we identified, other literature reviews about involvement methods for LTC users and PLWD in research also described advisory groups [ 10 ] and workshops [ 5 , 11 ], and methods that were similar to research team meetings (drop-in sessions and meetings [ 11 ]). Methods for action research (action groups) and co-conducting research (interviews) were not included by these other review studies. In addition to our findings, these other reviews also described as involvement methods interviews and focus groups [ 5 , 10 ] surveys [ 10 ], reader consultation [ 11 ]. Those types of methods were excluded from our study, because our definition of involvement is more strict; collecting opinions is not involvement per se, but sometimes only study participation. Moreover, compared to these previous reviews we set a high standard for transparency about the participation methods and the level of detail at which they are described.

Engaging the target group in research, particularly when collaborating with PLWD, LTC users, and carers, involves navigating unforeseen challenges [ 40 ]. This requires academic researchers to carefully balance academic research goals and expectations, and the expectations, personal circumstances and development goals related to the involved person. The aim is to maximize involvement while being attentive to the individual’s needs and avoiding a deficit perspective. Effective communication should be established, promoting respect, equality, and regular feedback between all stakeholders, including individuals living with dementia and LTCF staff. Building a mutual trusting relationship between involved persons and academic researchers through social interaction and clear communication is key to overcome barriers and ensure meaningful involvement. Inclusivity and empowerment, along with fostering an environment where diverse voices are heard, are crucial for the success of involvement in research. Our results are in line with a recent study concerning the experiences of frail older persons with involvement in research, confirming the importance of avoiding stereotypic views of ageing and frailty, building a trusting relationship, and being sensitive to older persons’ preferences and needs [ 41 ].

Furthermore, our results show that training academic researchers and involved persons is essential to develop the skills to facilitate involvement and to fulfil their role with confidence, respectively. Whilst the need for training is acknowledged by others [ 41 , 42 ], there are legitimate objections to the idea of training involved persons, as the professionalization underpinning the concept of training is at odds with voicing a lay perspective [ 43 , 44 ]. Furthermore, it is argued that experiential knowledge is compromised when training is structured according to the dominant professional epistemology of objectivity [ 45 ]. Therefore, training of involved persons should not focus on what researchers think they ought to know, but on what they want to learn [ 41 ].

Academic culture was frequently mentioned as a barrier to meaningful involvement. This result resonates with the wider debate related to involvement in health research which is concerned about active or “authentic involvement” being replaced with the appropriation of the patient voice as an add-on to conventional research designs [ 12 , 46 ]. It is argued that such tokenistic involvement limits the involved persons’ ability to shape research outcomes [ 46 ]. To reduce tokenism requires a culture shift [ 13 ]. We believe that due to the strict definition of involvement and high transparency standard used in this review, tokenistic approaches were excluded. This may set an example for how to stimulate making this culture shift.

Furthermore, the importance of practical aspects such as funding and, by extension, the availability of time should not be underestimated. Adequate funding is necessary for compensation of involvement, but also to ensure that researchers have ample time to plan involvement activities and provide personalized support for PLWD, LTC residents and their carers. Funding bodies increasingly require involvement of the public to be part of research proposals. Yet, support in terms of financial compensation and time for the implementation of involvement in research is rarely part of funding grants [ 42 ]. In addition, whereas an emergent design could aid the impact of involvement, funders often require a pre-set research proposal in which individual components are already fixed [ 5 , 47 ]. This indicates that not only do academic researchers and culture need to change, academic systems also need to be modified in order to facilitate and nurture meaningful involvement [ 47 ].

Strengths and limitations

A key strength of this review is the inclusion of over ten scientific databases, with a reach beyond the conventional biomedical science databases often consulted in systematic reviews. Besides, we believe that we have overcome the inconsistent use of terminology of involvement in research by including also other terms used, such as participation and engagement, in our search strategy. However, there was also inconsistency in length of publications and precision of the explanation of the process of involvement. E.g., involvement in the execution phase was often elaborated on, contributions to the research proposal and co-authoring research findings were only stated and not described. This presented challenges for data extraction and analysis, as it was not always possible to identify how the target group was involved. Involvement in these research phases is therefore not fully represented in this review.

The included studies in this review, the majority of which are of high quality, provide methods for involvement of PLWD and LTC users in research and they do not explicitly attend to the effectiveness or impact of the method for involvement used. Therefore, a limitation of this review is that it cannot make any statements regarding the effectiveness of the involvement methods included. Moreover, our target population was broad, although PLWD and LTC users are largely overlapping in their care needs and share important features, this may have led to heterogeneous results. In future research, it would be interesting to interpret potential differences between involvement of PLWD, LTC users, and their carers. However, as we expected, the amount of literature included in our analyses was too limited to do so. Furthermore, whereas the broad target group is a limitation it is also a strength of our review. Limiting our search to specifically persons living in LTC facilities would have provided limited methods for involvement of persons living with dementia. Our broad target groups enabled us to learn from research projects in which people living with early staged dementia are directly involved from which we can draw lessons on the involvement of people with more advanced stages of dementia and persons living with cognitive problems who live within LTC facilities.

Since January 2021 quite some research has been published about the importance of involvement in research. Although we had quickly screened for new methods, we realise that we may have missed some involvement methods in the past years. There will be a need for a search update in the future.

Implications for future research

Our review shows that a flexible and emergent design may help to increase involved persons' influence on and ownership in the research process. However, not all research objectives may be suitable for the implementation of an emergent design. Future research should therefore examine how aspects of a flexible emergent design can be integrated in, e.g., clinical research without compromising the validity of research outcomes.

Alzheimer Europe has called for the direct involvement of persons living with dementia in research [ 48 ]. In addition, Swarbrick et al. (this review) advise to involve persons regardless of their cognitive abilities [ 23 ]. These statements question the involvement of proxies, such as carers, professional caregivers and others involved in the care of PLWD. While PLWD and persons with other cognitive problems constitute a significant group within residential and nursing homes [ 7 ], none of the studies included in this review have provided methods to directly involve persons with more advanced stages of dementia. This raises the question if research methods should be adapted to allow those with more advanced stages of dementia to be involved themselves or if, concerning the progressive nature of the disease, it is more appropriate to involve proxies. And secondly who should these proxies be? Those that care for and live with persons with an advanced stage of dementia, or for example a person living with an early stage of dementia to represent the voices of persons with more advanced stages of dementia [ 31 ]?

Future research should adopt our example for stricter requirements for involvement and transparency about the involvement methods used. This will reduce tokenistic involvement and further promote the culture shift towards meaningful involvement. In addition, future research should assess the impact of the involvement methods that are described in this review. One of the first instruments that that may be used to do so in varying healthcare settings is the Public and Patient Engagement Evaluation Tool (PPEET) [ 49 ]. Moreover, scholars in this review stress, and we agree with this, that future research is needed on the involvement of persons with more advanced stages of dementia to ensure their voices are not excluded from research [ 33 , 34 ].

This review provides an overview of the existing methods used to actively involve PLWD, LTC users, and carers in scientific research. Our findings show that their involvement is feasible throughout all research phases. We have identified five different methods for involvement, four different roles, and two models for co-research. Our results suggest that planning enough time for involving PLWD, LTC users, and carers in research, is important to ensure that researchers have time to build a trusting relationship and meet their personal needs and preferences. In addition, researchers are advised not to presume the meaning of burden and to avoid a deficit perspective. A flexible or emergent design could aid involved persons’ ownership in the research process.

Availability of data and materials

The full search strategy is provided in supplement 1 . The data extraction form can be provided by the corresponding author on reasonable request.

Abbreviations

Critical Appraisal Skills Programme

Guidance for Reporting Involvement of Patients and the Public, long form version 2

• Long-term care

Persons living with dementia

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Acknowledgements

We thank Jan W. Schoones, information specialist Directorate of Research Policy (formerly: Walaeus Library, Leiden University Medical Centre, Leiden, the Netherlands), for helping with the search.

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Groothuijse, J.M., van Tol, L.S., Leeuwen, C.C.M.(.Hv. et al. Active involvement in scientific research of persons living with dementia and long-term care users: a systematic review of existing methods with a specific focus on good practices, facilitators and barriers of involvement. BMC Geriatr 24 , 324 (2024). https://doi.org/10.1186/s12877-024-04877-7

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• Introduction

Qualitative research is a type of research that explores and provides deeper insights into real-world problems. [1] Instead of collecting numerical data points or intervene or introduce treatments just like in quantitative research, qualitative research helps generate hypotheses as well as further investigate and understand quantitative data. Qualitative research gathers participants' experiences, perceptions, and behavior. It answers the hows and whys instead of how many or how much. It could be structured as a stand-alone study, purely relying on qualitative data or it could be part of mixed-methods research that combines qualitative and quantitative data. This review introduces the readers to some basic concepts, definitions, terminology, and application of qualitative research.

Qualitative research at its core, ask open-ended questions whose answers are not easily put into numbers such as ‘how’ and ‘why’. [2] Due to the open-ended nature of the research questions at hand, qualitative research design is often not linear in the same way quantitative design is. [2] One of the strengths of qualitative research is its ability to explain processes and patterns of human behavior that can be difficult to quantify. [3] Phenomena such as experiences, attitudes, and behaviors can be difficult to accurately capture quantitatively, whereas a qualitative approach allows participants themselves to explain how, why, or what they were thinking, feeling, and experiencing at a certain time or during an event of interest. Quantifying qualitative data certainly is possible, but at its core, qualitative data is looking for themes and patterns that can be difficult to quantify and it is important to ensure that the context and narrative of qualitative work are not lost by trying to quantify something that is not meant to be quantified.

However, while qualitative research is sometimes placed in opposition to quantitative research, where they are necessarily opposites and therefore ‘compete’ against each other and the philosophical paradigms associated with each, qualitative and quantitative work are not necessarily opposites nor are they incompatible. [4] While qualitative and quantitative approaches are different, they are not necessarily opposites, and they are certainly not mutually exclusive. For instance, qualitative research can help expand and deepen understanding of data or results obtained from quantitative analysis. For example, say a quantitative analysis has determined that there is a correlation between length of stay and level of patient satisfaction, but why does this correlation exist? This dual-focus scenario shows one way in which qualitative and quantitative research could be integrated together.

Examples of Qualitative Research Approaches

Ethnography

Ethnography as a research design has its origins in social and cultural anthropology, and involves the researcher being directly immersed in the participant’s environment. [2] Through this immersion, the ethnographer can use a variety of data collection techniques with the aim of being able to produce a comprehensive account of the social phenomena that occurred during the research period. [2] That is to say, the researcher’s aim with ethnography is to immerse themselves into the research population and come out of it with accounts of actions, behaviors, events, etc. through the eyes of someone involved in the population. Direct involvement of the researcher with the target population is one benefit of ethnographic research because it can then be possible to find data that is otherwise very difficult to extract and record.

Grounded Theory

Grounded Theory is the “generation of a theoretical model through the experience of observing a study population and developing a comparative analysis of their speech and behavior.” [5] As opposed to quantitative research which is deductive and tests or verifies an existing theory, grounded theory research is inductive and therefore lends itself to research that is aiming to study social interactions or experiences. [3] [2] In essence, Grounded Theory’s goal is to explain for example how and why an event occurs or how and why people might behave a certain way. Through observing the population, a researcher using the Grounded Theory approach can then develop a theory to explain the phenomena of interest.

Phenomenology

Phenomenology is defined as the “study of the meaning of phenomena or the study of the particular”. [5] At first glance, it might seem that Grounded Theory and Phenomenology are quite similar, but upon careful examination, the differences can be seen. At its core, phenomenology looks to investigate experiences from the perspective of the individual. [2] Phenomenology is essentially looking into the ‘lived experiences’ of the participants and aims to examine how and why participants behaved a certain way, from their perspective . Herein lies one of the main differences between Grounded Theory and Phenomenology. Grounded Theory aims to develop a theory for social phenomena through an examination of various data sources whereas Phenomenology focuses on describing and explaining an event or phenomena from the perspective of those who have experienced it.

Narrative Research

One of qualitative research’s strengths lies in its ability to tell a story, often from the perspective of those directly involved in it. Reporting on qualitative research involves including details and descriptions of the setting involved and quotes from participants. This detail is called ‘thick’ or ‘rich’ description and is a strength of qualitative research. Narrative research is rife with the possibilities of ‘thick’ description as this approach weaves together a sequence of events, usually from just one or two individuals, in the hopes of creating a cohesive story, or narrative. [2] While it might seem like a waste of time to focus on such a specific, individual level, understanding one or two people’s narratives for an event or phenomenon can help to inform researchers about the influences that helped shape that narrative. The tension or conflict of differing narratives can be “opportunities for innovation”. [2]

Research Paradigm

Research paradigms are the assumptions, norms, and standards that underpin different approaches to research. Essentially, research paradigms are the ‘worldview’ that inform research. [4] It is valuable for researchers, both qualitative and quantitative, to understand what paradigm they are working within because understanding the theoretical basis of research paradigms allows researchers to understand the strengths and weaknesses of the approach being used and adjust accordingly. Different paradigms have different ontology and epistemologies . Ontology is defined as the "assumptions about the nature of reality” whereas epistemology is defined as the “assumptions about the nature of knowledge” that inform the work researchers do. [2] It is important to understand the ontological and epistemological foundations of the research paradigm researchers are working within to allow for a full understanding of the approach being used and the assumptions that underpin the approach as a whole. Further, it is crucial that researchers understand their own ontological and epistemological assumptions about the world in general because their assumptions about the world will necessarily impact how they interact with research. A discussion of the research paradigm is not complete without describing positivist, postpositivist, and constructivist philosophies.

Positivist vs Postpositivist

To further understand qualitative research, we need to discuss positivist and postpositivist frameworks. Positivism is a philosophy that the scientific method can and should be applied to social as well as natural sciences. [4] Essentially, positivist thinking insists that the social sciences should use natural science methods in its research which stems from positivist ontology that there is an objective reality that exists that is fully independent of our perception of the world as individuals. Quantitative research is rooted in positivist philosophy, which can be seen in the value it places on concepts such as causality, generalizability, and replicability.

Conversely, postpositivists argue that social reality can never be one hundred percent explained but it could be approximated. [4] Indeed, qualitative researchers have been insisting that there are “fundamental limits to the extent to which the methods and procedures of the natural sciences could be applied to the social world” and therefore postpositivist philosophy is often associated with qualitative research. [4] An example of positivist versus postpositivist values in research might be that positivist philosophies value hypothesis-testing, whereas postpositivist philosophies value the ability to formulate a substantive theory.

Constructivist

Constructivism is a subcategory of postpositivism. Most researchers invested in postpositivist research are constructivist as well, meaning they think there is no objective external reality that exists but rather that reality is constructed. Constructivism is a theoretical lens that emphasizes the dynamic nature of our world. “Constructivism contends that individuals’ views are directly influenced by their experiences, and it is these individual experiences and views that shape their perspective of reality”. [6] Essentially, Constructivist thought focuses on how ‘reality’ is not a fixed certainty and experiences, interactions, and backgrounds give people a unique view of the world. Constructivism contends, unlike in positivist views, that there is not necessarily an ‘objective’ reality we all experience. This is the ‘relativist’ ontological view that reality and the world we live in are dynamic and socially constructed. Therefore, qualitative scientific knowledge can be inductive as well as deductive.” [4]

So why is it important to understand the differences in assumptions that different philosophies and approaches to research have? Fundamentally, the assumptions underpinning the research tools a researcher selects provide an overall base for the assumptions the rest of the research will have and can even change the role of the researcher themselves. [2] For example, is the researcher an ‘objective’ observer such as in positivist quantitative work? Or is the researcher an active participant in the research itself, as in postpositivist qualitative work? Understanding the philosophical base of the research undertaken allows researchers to fully understand the implications of their work and their role within the research, as well as reflect on their own positionality and bias as it pertains to the research they are conducting.

Data Sampling 

The better the sample represents the intended study population, the more likely the researcher is to encompass the varying factors at play. The following are examples of participant sampling and selection: [7]

• Purposive sampling- selection based on the researcher’s rationale in terms of being the most informative.
• Criterion sampling-selection based on pre-identified factors.
• Convenience sampling- selection based on availability.
• Snowball sampling- the selection is by referral from other participants or people who know potential participants.
• Extreme case sampling- targeted selection of rare cases.
• Typical case sampling-selection based on regular or average participants. 

Data Collection and Analysis

Qualitative research uses several techniques including interviews, focus groups, and observation. [1] [2] [3] Interviews may be unstructured, with open-ended questions on a topic and the interviewer adapts to the responses. Structured interviews have a predetermined number of questions that every participant is asked. It is usually one on one and is appropriate for sensitive topics or topics needing an in-depth exploration. Focus groups are often held with 8-12 target participants and are used when group dynamics and collective views on a topic are desired. Researchers can be a participant-observer to share the experiences of the subject or a non-participant or detached observer.

While quantitative research design prescribes a controlled environment for data collection, qualitative data collection may be in a central location or in the environment of the participants, depending on the study goals and design. Qualitative research could amount to a large amount of data. Data is transcribed which may then be coded manually or with the use of Computer Assisted Qualitative Data Analysis Software or CAQDAS such as ATLAS.ti or NVivo. [8] [9] [10]

After the coding process, qualitative research results could be in various formats. It could be a synthesis and interpretation presented with excerpts from the data. [11] Results also could be in the form of themes and theory or model development.

Dissemination

To standardize and facilitate the dissemination of qualitative research outcomes, the healthcare team can use two reporting standards. The Consolidated Criteria for Reporting Qualitative Research or COREQ is a 32-item checklist for interviews and focus groups. [12] The Standards for Reporting Qualitative Research (SRQR) is a checklist covering a wider range of qualitative research. [13]

Examples of Application

Many times a research question will start with qualitative research. The qualitative research will help generate the research hypothesis which can be tested with quantitative methods. After the data is collected and analyzed with quantitative methods, a set of qualitative methods can be used to dive deeper into the data for a better understanding of what the numbers truly mean and their implications. The qualitative methods can then help clarify the quantitative data and also help refine the hypothesis for future research. Furthermore, with qualitative research researchers can explore subjects that are poorly studied with quantitative methods. These include opinions, individual's actions, and social science research.

A good qualitative study design starts with a goal or objective. This should be clearly defined or stated. The target population needs to be specified. A method for obtaining information from the study population must be carefully detailed to ensure there are no omissions of part of the target population. A proper collection method should be selected which will help obtain the desired information without overly limiting the collected data because many times, the information sought is not well compartmentalized or obtained. Finally, the design should ensure adequate methods for analyzing the data. An example may help better clarify some of the various aspects of qualitative research.

A researcher wants to decrease the number of teenagers who smoke in their community. The researcher could begin by asking current teen smokers why they started smoking through structured or unstructured interviews (qualitative research). The researcher can also get together a group of current teenage smokers and conduct a focus group to help brainstorm factors that may have prevented them from starting to smoke (qualitative research).

In this example, the researcher has used qualitative research methods (interviews and focus groups) to generate a list of ideas of both why teens start to smoke as well as factors that may have prevented them from starting to smoke. Next, the researcher compiles this data. The research found that, hypothetically, peer pressure, health issues, cost, being considered “cool,” and rebellious behavior all might increase or decrease the likelihood of teens starting to smoke.

The researcher creates a survey asking teen participants to rank how important each of the above factors is in either starting smoking (for current smokers) or not smoking (for current non-smokers). This survey provides specific numbers (ranked importance of each factor) and is thus a quantitative research tool.

The researcher can use the results of the survey to focus efforts on the one or two highest-ranked factors. Let us say the researcher found that health was the major factor that keeps teens from starting to smoke, and peer pressure was the major factor that contributed to teens to start smoking. The researcher can go back to qualitative research methods to dive deeper into each of these for more information. The researcher wants to focus on how to keep teens from starting to smoke, so they focus on the peer pressure aspect.

The researcher can conduct interviews and/or focus groups (qualitative research) about what types and forms of peer pressure are commonly encountered, where the peer pressure comes from, and where smoking first starts. The researcher hypothetically finds that peer pressure often occurs after school at the local teen hangouts, mostly the local park. The researcher also hypothetically finds that peer pressure comes from older, current smokers who provide the cigarettes.

The researcher could further explore this observation made at the local teen hangouts (qualitative research) and take notes regarding who is smoking, who is not, and what observable factors are at play for peer pressure of smoking. The researcher finds a local park where many local teenagers hang out and see that a shady, overgrown area of the park is where the smokers tend to hang out. The researcher notes the smoking teenagers buy their cigarettes from a local convenience store adjacent to the park where the clerk does not check identification before selling cigarettes. These observations fall under qualitative research.

If the researcher returns to the park and counts how many individuals smoke in each region of the park, this numerical data would be quantitative research. Based on the researcher's efforts thus far, they conclude that local teen smoking and teenagers who start to smoke may decrease if there are fewer overgrown areas of the park and the local convenience store does not sell cigarettes to underage individuals.

The researcher could try to have the parks department reassess the shady areas to make them less conducive to the smokers or identify how to limit the sales of cigarettes to underage individuals by the convenience store. The researcher would then cycle back to qualitative methods of asking at-risk population their perceptions of the changes, what factors are still at play, as well as quantitative research that includes teen smoking rates in the community, the incidence of new teen smokers, among others. [14] [15]

Qualitative research functions as a standalone research design or in combination with quantitative research to enhance our understanding of the world. Qualitative research uses techniques including structured and unstructured interviews, focus groups, and participant observation to not only help generate hypotheses which can be more rigorously tested with quantitative research but also to help researchers delve deeper into the quantitative research numbers, understand what they mean, and understand what the implications are.  Qualitative research provides researchers with a way to understand what is going on, especially when things are not easily categorized. [16]

• Issues of Concern

As discussed in the sections above, quantitative and qualitative work differ in many different ways, including the criteria for evaluating them. There are four well-established criteria for evaluating quantitative data: internal validity, external validity, reliability, and objectivity. The correlating concepts in qualitative research are credibility, transferability, dependability, and confirmability. [4] [11] The corresponding quantitative and qualitative concepts can be seen below, with the quantitative concept is on the left, and the qualitative concept is on the right:

• Internal validity--- Credibility
• External validity---Transferability
• Reliability---Dependability
• Objectivity---Confirmability

In conducting qualitative research, ensuring these concepts are satisfied and well thought out can mitigate potential issues from arising. For example, just as a researcher will ensure that their quantitative study is internally valid so should qualitative researchers ensure that their work has credibility.  

Indicators such as triangulation and peer examination can help evaluate the credibility of qualitative work.

• Triangulation: Triangulation involves using multiple methods of data collection to increase the likelihood of getting a reliable and accurate result. In our above magic example, the result would be more reliable by also interviewing the magician, back-stage hand, and the person who "vanished." In qualitative research, triangulation can include using telephone surveys, in-person surveys, focus groups, and interviews as well as surveying an adequate cross-section of the target demographic.
• Peer examination: Results can be reviewed by a peer to ensure the data is consistent with the findings.

‘Thick’ or ‘rich’ description can be used to evaluate the transferability of qualitative research whereas using an indicator such as an audit trail might help with evaluating the dependability and confirmability.

• Thick or rich description is a detailed and thorough description of details, the setting, and quotes from participants in the research. [5] Thick descriptions will include a detailed explanation of how the study was carried out. Thick descriptions are detailed enough to allow readers to draw conclusions and interpret the data themselves, which can help with transferability and replicability.
• Audit trail: An audit trail provides a documented set of steps of how the participants were selected and the data was collected. The original records of information should also be kept (e.g., surveys, notes, recordings).

One issue of concern that qualitative researchers should take into consideration is observation bias. Here are a few examples:

• Hawthorne effect: The Hawthorne effect is the change in participant behavior when they know they are being observed. If a researcher was wanting to identify factors that contribute to employee theft and tells the employees they are going to watch them to see what factors affect employee theft, one would suspect employee behavior would change when they know they are being watched.
• Observer-expectancy effect: Some participants change their behavior or responses to satisfy the researcher's desired effect. This happens in an unconscious manner for the participant so it is important to eliminate or limit transmitting the researcher's views.
• Artificial scenario effect: Some qualitative research occurs in artificial scenarios and/or with preset goals. In such situations, the information may not be accurate because of the artificial nature of the scenario. The preset goals may limit the qualitative information obtained.
• Clinical Significance

Qualitative research by itself or combined with quantitative research helps healthcare providers understand patients and the impact and challenges of the care they deliver. Qualitative research provides an opportunity to generate and refine hypotheses and delve deeper into the data generated by quantitative research. Qualitative research does not exist as an island apart from quantitative research, but as an integral part of research methods to be used for the understanding of the world around us. [17]

• Enhancing Healthcare Team Outcomes

Qualitative research is important for all members of the health care team as all are affected by qualitative research. Qualitative research may help develop a theory or a model for health research that can be further explored by quantitative research.  Much of the qualitative research data acquisition is completed by numerous team members including social works, scientists, nurses, etc.  Within each area of the medical field, there is copious ongoing qualitative research including physician-patient interactions, nursing-patient interactions, patient-environment interactions, health care team function, patient information delivery, etc. 

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Disclosure: Steven Tenny declares no relevant financial relationships with ineligible companies.

Disclosure: Janelle Brannan declares no relevant financial relationships with ineligible companies.

Disclosure: Grace Brannan declares no relevant financial relationships with ineligible companies.

This book is distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) ( http://creativecommons.org/licenses/by-nc-nd/4.0/ ), which permits others to distribute the work, provided that the article is not altered or used commercially. You are not required to obtain permission to distribute this article, provided that you credit the author and journal.

• Cite this Page Tenny S, Brannan JM, Brannan GD. Qualitative Study. [Updated 2022 Sep 18]. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2024 Jan-.

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