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• Inductive vs. Deductive Research Approach | Steps & Examples

Inductive vs. Deductive Research Approach | Steps & Examples

Published on April 18, 2019 by Raimo Streefkerk . Revised on June 22, 2023.

The main difference between inductive and deductive reasoning is that inductive reasoning aims at developing a theory while deductive reasoning aims at testing an existing theory .

In other words, inductive reasoning moves from specific observations to broad generalizations . Deductive reasoning works the other way around.

Both approaches are used in various types of research , and it’s not uncommon to combine them in your work.

Table of contents

Inductive research approach, deductive research approach, combining inductive and deductive research, other interesting articles, frequently asked questions about inductive vs deductive reasoning.

When there is little to no existing literature on a topic, it is common to perform inductive research , because there is no theory to test. The inductive approach consists of three stages:

• A low-cost airline flight is delayed
• Dogs A and B have fleas
• Elephants depend on water to exist
• Another 20 flights from low-cost airlines are delayed
• All observed dogs have fleas
• All observed animals depend on water to exist
• Low cost airlines always have delays
• All dogs have fleas
• All biological life depends on water to exist

Limitations of an inductive approach

A conclusion drawn on the basis of an inductive method can never be fully proven. However, it can be invalidated.

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When conducting deductive research , you always start with a theory. This is usually the result of inductive research. Reasoning deductively means testing these theories. Remember that if there is no theory yet, you cannot conduct deductive research.

The deductive research approach consists of four stages:

• If passengers fly with a low cost airline, then they will always experience delays
• All pet dogs in my apartment building have fleas
• All land mammals depend on water to exist
• Collect flight data of low-cost airlines
• Test all dogs in the building for fleas
• Study all land mammal species to see if they depend on water
• 5 out of 100 flights of low-cost airlines are not delayed
• 10 out of 20 dogs didn’t have fleas
• All land mammal species depend on water
• 5 out of 100 flights of low-cost airlines are not delayed = reject hypothesis
• 10 out of 20 dogs didn’t have fleas = reject hypothesis
• All land mammal species depend on water = support hypothesis

Limitations of a deductive approach

The conclusions of deductive reasoning can only be true if all the premises set in the inductive study are true and the terms are clear.

• All dogs have fleas (premise)
• Benno is a dog (premise)
• Benno has fleas (conclusion)

Many scientists conducting a larger research project begin with an inductive study. This helps them develop a relevant research topic and construct a strong working theory. The inductive study is followed up with deductive research to confirm or invalidate the conclusion. This can help you formulate a more structured project, and better mitigate the risk of research bias creeping into your work.

Remember that both inductive and deductive approaches are at risk for research biases, particularly confirmation bias and cognitive bias , so it’s important to be aware while you conduct your research.

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

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

Research bias

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

Inductive reasoning is a bottom-up approach, while deductive reasoning is top-down.

Inductive reasoning takes you from the specific to the general, while in deductive reasoning, you make inferences by going from general premises to specific conclusions.

Inductive reasoning is a method of drawing conclusions by going from the specific to the general. It’s usually contrasted with deductive reasoning, where you proceed from general information to specific conclusions.

Inductive reasoning is also called inductive logic or bottom-up reasoning.

Deductive reasoning is a logical approach where you progress from general ideas to specific conclusions. It’s often contrasted with inductive reasoning , where you start with specific observations and form general conclusions.

Deductive reasoning is also called deductive logic.

Exploratory research aims to explore the main aspects of an under-researched problem, while explanatory research aims to explain the causes and consequences of a well-defined problem.

Explanatory research is used to investigate how or why a phenomenon occurs. Therefore, this type of research is often one of the first stages in the research process , serving as a jumping-off point for future research.

Exploratory research is often used when the issue you’re studying is new or when the data collection process is challenging for some reason.

You can use exploratory research if you have a general idea or a specific question that you want to study but there is no preexisting knowledge or paradigm with which to study it.

A research project is an academic, scientific, or professional undertaking to answer a research question . Research projects can take many forms, such as qualitative or quantitative , descriptive , longitudinal , experimental , or correlational . What kind of research approach you choose will depend on your topic.

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What is Qualitative in Qualitative Research

Patrik aspers.

1 Department of Sociology, Uppsala University, Uppsala, Sweden

2 Seminar for Sociology, Universität St. Gallen, St. Gallen, Switzerland

3 Department of Media and Social Sciences, University of Stavanger, Stavanger, Norway

What is qualitative research? If we look for a precise definition of qualitative research, and specifically for one that addresses its distinctive feature of being “qualitative,” the literature is meager. In this article we systematically search, identify and analyze a sample of 89 sources using or attempting to define the term “qualitative.” Then, drawing on ideas we find scattered across existing work, and based on Becker’s classic study of marijuana consumption, we formulate and illustrate a definition that tries to capture its core elements. 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. This formulation is developed as a tool to help improve research designs while stressing that a qualitative dimension is present in quantitative work as well. Additionally, it can facilitate teaching, communication between researchers, diminish the gap between qualitative and quantitative researchers, help to address critiques of qualitative methods, and be used as a standard of evaluation of qualitative research.

If we assume that there is something called qualitative research, what exactly is this qualitative feature? And how could we evaluate qualitative research as good or not? Is it fundamentally different from quantitative research? In practice, most active qualitative researchers working with empirical material intuitively know what is involved in doing qualitative research, yet perhaps surprisingly, a clear definition addressing its key feature is still missing.

To address the question of what is qualitative we turn to the accounts of “qualitative research” in textbooks and also in empirical work. In his classic, explorative, interview study of deviance Howard Becker ( 1963 ) asks ‘How does one become a marijuana user?’ In contrast to pre-dispositional and psychological-individualistic theories of deviant behavior, Becker’s inherently social explanation contends that becoming a user of this substance is the result of a three-phase sequential learning process. First, potential users need to learn how to smoke it properly to produce the “correct” effects. If not, they are likely to stop experimenting with it. Second, they need to discover the effects associated with it; in other words, to get “high,” individuals not only have to experience what the drug does, but also to become aware that those sensations are related to using it. Third, they require learning to savor the feelings related to its consumption – to develop an acquired taste. Becker, who played music himself, gets close to the phenomenon by observing, taking part, and by talking to people consuming the drug: “half of the fifty interviews were conducted with musicians, the other half covered a wide range of people, including laborers, machinists, and people in the professions” (Becker 1963 :56).

Another central aspect derived through the common-to-all-research interplay between induction and deduction (Becker 2017 ), is that during the course of his research Becker adds scientifically meaningful new distinctions in the form of three phases—distinctions, or findings if you will, that strongly affect the course of his research: its focus, the material that he collects, and which eventually impact his findings. Each phase typically unfolds through social interaction, and often with input from experienced users in “a sequence of social experiences during which the person acquires a conception of the meaning of the behavior, and perceptions and judgments of objects and situations, all of which make the activity possible and desirable” (Becker 1963 :235). In this study the increased understanding of smoking dope is a result of a combination of the meaning of the actors, and the conceptual distinctions that Becker introduces based on the views expressed by his respondents. Understanding is the result of research and is due to an iterative process in which data, concepts and evidence are connected with one another (Becker 2017 ).

Indeed, there are many definitions of qualitative research, but if we look for a definition that addresses its distinctive feature of being “qualitative,” the literature across the broad field of social science is meager. The main reason behind this article lies in the paradox, which, to put it bluntly, is that researchers act as if they know what it is, but they cannot formulate a coherent definition. Sociologists and others will of course continue to conduct good studies that show the relevance and value of qualitative research addressing scientific and practical problems in society. However, our paper is grounded in the idea that providing a clear definition will help us improve the work that we do. Among researchers who practice qualitative research there is clearly much knowledge. We suggest that a definition makes this knowledge more explicit. If the first rationale for writing this paper refers to the “internal” aim of improving qualitative research, the second refers to the increased “external” pressure that especially many qualitative researchers feel; pressure that comes both from society as well as from other scientific approaches. There is a strong core in qualitative research, and leading researchers tend to agree on what it is and how it is done. Our critique is not directed at the practice of qualitative research, but we do claim that the type of systematic work we do has not yet been done, and that it is useful to improve the field and its status in relation to quantitative research.

The literature on the “internal” aim of improving, or at least clarifying qualitative research is large, and we do not claim to be the first to notice the vagueness of the term “qualitative” (Strauss and Corbin 1998 ). Also, others have noted that there is no single definition of it (Long and Godfrey 2004 :182), that there are many different views on qualitative research (Denzin and Lincoln 2003 :11; Jovanović 2011 :3), and that more generally, we need to define its meaning (Best 2004 :54). Strauss and Corbin ( 1998 ), for example, as well as Nelson et al. (1992:2 cited in Denzin and Lincoln 2003 :11), and Flick ( 2007 :ix–x), have recognized that the term is problematic: “Actually, the term ‘qualitative research’ is confusing because it can mean different things to different people” (Strauss and Corbin 1998 :10–11). Hammersley has discussed the possibility of addressing the problem, but states that “the task of providing an account of the distinctive features of qualitative research is far from straightforward” ( 2013 :2). This confusion, as he has recently further argued (Hammersley 2018 ), is also salient in relation to ethnography where different philosophical and methodological approaches lead to a lack of agreement about what it means.

Others (e.g. Hammersley 2018 ; Fine and Hancock 2017 ) have also identified the treat to qualitative research that comes from external forces, seen from the point of view of “qualitative research.” This threat can be further divided into that which comes from inside academia, such as the critique voiced by “quantitative research” and outside of academia, including, for example, New Public Management. Hammersley ( 2018 ), zooming in on one type of qualitative research, ethnography, has argued that it is under treat. Similarly to Fine ( 2003 ), and before him Gans ( 1999 ), he writes that ethnography’ has acquired a range of meanings, and comes in many different versions, these often reflecting sharply divergent epistemological orientations. And already more than twenty years ago while reviewing Denzin and Lincoln’ s Handbook of Qualitative Methods Fine argued:

While this increasing centrality [of qualitative research] might lead one to believe that consensual standards have developed, this belief would be misleading. As the methodology becomes more widely accepted, querulous challengers have raised fundamental questions that collectively have undercut the traditional models of how qualitative research is to be fashioned and presented (1995:417).

According to Hammersley, there are today “serious treats to the practice of ethnographic work, on almost any definition” ( 2018 :1). He lists five external treats: (1) that social research must be accountable and able to show its impact on society; (2) the current emphasis on “big data” and the emphasis on quantitative data and evidence; (3) the labor market pressure in academia that leaves less time for fieldwork (see also Fine and Hancock 2017 ); (4) problems of access to fields; and (5) the increased ethical scrutiny of projects, to which ethnography is particularly exposed. Hammersley discusses some more or less insufficient existing definitions of ethnography.

The current situation, as Hammersley and others note—and in relation not only to ethnography but also qualitative research in general, and as our empirical study shows—is not just unsatisfactory, it may even be harmful for the entire field of qualitative research, and does not help social science at large. We suggest that the lack of clarity of qualitative research is a real problem that must be addressed.

Towards a Definition of Qualitative Research

Seen in an historical light, what is today called qualitative, or sometimes ethnographic, interpretative research – or a number of other terms – has more or less always existed. At the time the founders of sociology – Simmel, Weber, Durkheim and, before them, Marx – were writing, and during the era of the Methodenstreit (“dispute about methods”) in which the German historical school emphasized scientific methods (cf. Swedberg 1990 ), we can at least speak of qualitative forerunners.

Perhaps the most extended discussion of what later became known as qualitative methods in a classic work is Bronisław Malinowski’s ( 1922 ) Argonauts in the Western Pacific , although even this study does not explicitly address the meaning of “qualitative.” In Weber’s ([1921–-22] 1978) work we find a tension between scientific explanations that are based on observation and quantification and interpretative research (see also Lazarsfeld and Barton 1982 ).

If we look through major sociology journals like the American Sociological Review , American Journal of Sociology , or Social Forces we will not find the term qualitative sociology before the 1970s. And certainly before then much of what we consider qualitative classics in sociology, like Becker’ study ( 1963 ), had already been produced. Indeed, the Chicago School often combined qualitative and quantitative data within the same study (Fine 1995 ). Our point being that before a disciplinary self-awareness the term quantitative preceded qualitative, and the articulation of the former was a political move to claim scientific status (Denzin and Lincoln 2005 ). In the US the World War II seem to have sparked a critique of sociological work, including “qualitative work,” that did not follow the scientific canon (Rawls 2018 ), which was underpinned by a scientifically oriented and value free philosophy of science. As a result the attempts and practice of integrating qualitative and quantitative sociology at Chicago lost ground to sociology that was more oriented to surveys and quantitative work at Columbia under Merton-Lazarsfeld. The quantitative tradition was also able to present textbooks (Lundberg 1951 ) that facilitated the use this approach and its “methods.” The practices of the qualitative tradition, by and large, remained tacit or was part of the mentoring transferred from the renowned masters to their students.

This glimpse into history leads us back to the lack of a coherent account condensed in a definition of qualitative research. Many of the attempts to define the term do not meet the requirements of a proper definition: A definition should be clear, avoid tautology, demarcate its domain in relation to the environment, and ideally only use words in its definiens that themselves are not in need of definition (Hempel 1966 ). A definition can enhance precision and thus clarity by identifying the core of the phenomenon. Preferably, a definition should be short. The typical definition we have found, however, is an ostensive definition, which indicates what qualitative research is about without informing us about what it actually is :

Qualitative research is multimethod in focus, involving an interpretative, naturalistic approach to its subject matter. This means that qualitative researchers study things in their natural settings, attempting to make sense of, or interpret, phenomena in terms of the meanings people bring to them. Qualitative research involves the studied use and collection of a variety of empirical materials – case study, personal experience, introspective, life story, interview, observational, historical, interactional, and visual texts – that describe routine and problematic moments and meanings in individuals’ lives. (Denzin and Lincoln 2005 :2)

Flick claims that the label “qualitative research” is indeed used as an umbrella for a number of approaches ( 2007 :2–4; 2002 :6), and it is not difficult to identify research fitting this designation. Moreover, whatever it is, it has grown dramatically over the past five decades. In addition, courses have been developed, methods have flourished, arguments about its future have been advanced (for example, Denzin and Lincoln 1994) and criticized (for example, Snow and Morrill 1995 ), and dedicated journals and books have mushroomed. Most social scientists have a clear idea of research and how it differs from journalism, politics and other activities. But the question of what is qualitative in qualitative research is either eluded or eschewed.

We maintain that this lacuna hinders systematic knowledge production based on qualitative research. Paul Lazarsfeld noted the lack of “codification” as early as 1955 when he reviewed 100 qualitative studies in order to offer a codification of the practices (Lazarsfeld and Barton 1982 :239). Since then many texts on “qualitative research” and its methods have been published, including recent attempts (Goertz and Mahoney 2012 ) similar to Lazarsfeld’s. These studies have tried to extract what is qualitative by looking at the large number of empirical “qualitative” studies. Our novel strategy complements these endeavors by taking another approach and looking at the attempts to codify these practices in the form of a definition, as well as to a minor extent take Becker’s study as an exemplar of what qualitative researchers actually do, and what the characteristic of being ‘qualitative’ denotes and implies. We claim that qualitative researchers, if there is such a thing as “qualitative research,” should be able to codify their practices in a condensed, yet general way expressed in language.

Lingering problems of “generalizability” and “how many cases do I need” (Small 2009 ) are blocking advancement – in this line of work qualitative approaches are said to differ considerably from quantitative ones, while some of the former unsuccessfully mimic principles related to the latter (Small 2009 ). Additionally, quantitative researchers sometimes unfairly criticize the first based on their own quality criteria. Scholars like Goertz and Mahoney ( 2012 ) have successfully focused on the different norms and practices beyond what they argue are essentially two different cultures: those working with either qualitative or quantitative methods. Instead, similarly to Becker ( 2017 ) who has recently questioned the usefulness of the distinction between qualitative and quantitative research, we focus on similarities.

The current situation also impedes both students and researchers in focusing their studies and understanding each other’s work (Lazarsfeld and Barton 1982 :239). A third consequence is providing an opening for critiques by scholars operating within different traditions (Valsiner 2000 :101). A fourth issue is that the “implicit use of methods in qualitative research makes the field far less standardized than the quantitative paradigm” (Goertz and Mahoney 2012 :9). Relatedly, the National Science Foundation in the US organized two workshops in 2004 and 2005 to address the scientific foundations of qualitative research involving strategies to improve it and to develop standards of evaluation in qualitative research. However, a specific focus on its distinguishing feature of being “qualitative” while being implicitly acknowledged, was discussed only briefly (for example, Best 2004 ).

In 2014 a theme issue was published in this journal on “Methods, Materials, and Meanings: Designing Cultural Analysis,” discussing central issues in (cultural) qualitative research (Berezin 2014 ; Biernacki 2014 ; Glaeser 2014 ; Lamont and Swidler 2014 ; Spillman 2014). We agree with many of the arguments put forward, such as the risk of methodological tribalism, and that we should not waste energy on debating methods separated from research questions. Nonetheless, a clarification of the relation to what is called “quantitative research” is of outmost importance to avoid misunderstandings and misguided debates between “qualitative” and “quantitative” researchers. Our strategy means that researchers, “qualitative” or “quantitative” they may be, in their actual practice may combine qualitative work and quantitative work.

In this article we accomplish three tasks. First, we systematically survey the literature for meanings of qualitative research by looking at how researchers have defined it. Drawing upon existing knowledge we find that the different meanings and ideas of qualitative research are not yet coherently integrated into one satisfactory definition. Next, we advance our contribution by offering a definition of qualitative research and illustrate its meaning and use partially by expanding on the brief example introduced earlier related to Becker’s work ( 1963 ). We offer a systematic analysis of central themes of what researchers consider to be the core of “qualitative,” regardless of style of work. These themes – which we summarize in terms of four keywords: distinction, process, closeness, improved understanding – constitute part of our literature review, in which each one appears, sometimes with others, but never all in the same definition. They serve as the foundation of our contribution. Our categories are overlapping. Their use is primarily to organize the large amount of definitions we have identified and analyzed, and not necessarily to draw a clear distinction between them. Finally, we continue the elaboration discussed above on the advantages of a clear definition of qualitative research.

In a hermeneutic fashion we propose that there is something meaningful that deserves to be labelled “qualitative research” (Gadamer 1990 ). To approach the question “What is qualitative in qualitative research?” we have surveyed the literature. In conducting our survey we first traced the word’s etymology in dictionaries, encyclopedias, handbooks of the social sciences and of methods and textbooks, mainly in English, which is common to methodology courses. It should be noted that we have zoomed in on sociology and its literature. This discipline has been the site of the largest debate and development of methods that can be called “qualitative,” which suggests that this field should be examined in great detail.

In an ideal situation we should expect that one good definition, or at least some common ideas, would have emerged over the years. This common core of qualitative research should be so accepted that it would appear in at least some textbooks. Since this is not what we found, we decided to pursue an inductive approach to capture maximal variation in the field of qualitative research; we searched in a selection of handbooks, textbooks, book chapters, and books, to which we added the analysis of journal articles. Our sample comprises a total of 89 references.

In practice we focused on the discipline that has had a clear discussion of methods, namely sociology. We also conducted a broad search in the JSTOR database to identify scholarly sociology articles published between 1998 and 2017 in English with a focus on defining or explaining qualitative research. We specifically zoom in on this time frame because we would have expect that this more mature period would have produced clear discussions on the meaning of qualitative research. To find these articles we combined a number of keywords to search the content and/or the title: qualitative (which was always included), definition, empirical, research, methodology, studies, fieldwork, interview and observation .

As a second phase of our research we searched within nine major sociological journals ( American Journal of Sociology , Sociological Theory , American Sociological Review , Contemporary Sociology , Sociological Forum , Sociological Theory , Qualitative Research , Qualitative Sociology and Qualitative Sociology Review ) for articles also published during the past 19 years (1998–2017) that had the term “qualitative” in the title and attempted to define qualitative research.

Lastly we picked two additional journals, Qualitative Research and Qualitative Sociology , in which we could expect to find texts addressing the notion of “qualitative.” From Qualitative Research we chose Volume 14, Issue 6, December 2014, and from Qualitative Sociology we chose Volume 36, Issue 2, June 2017. Within each of these we selected the first article; then we picked the second article of three prior issues. Again we went back another three issues and investigated article number three. Finally we went back another three issues and perused article number four. This selection criteria was used to get a manageable sample for the analysis.

The coding process of the 89 references we gathered in our selected review began soon after the first round of material was gathered, and we reduced the complexity created by our maximum variation sampling (Snow and Anderson 1993 :22) to four different categories within which questions on the nature and properties of qualitative research were discussed. We call them: Qualitative and Quantitative Research, Qualitative Research, Fieldwork, and Grounded Theory. This – which may appear as an illogical grouping – merely reflects the “context” in which the matter of “qualitative” is discussed. If the selection process of the material – books and articles – was informed by pre-knowledge, we used an inductive strategy to code the material. When studying our material, we identified four central notions related to “qualitative” that appear in various combinations in the literature which indicate what is the core of qualitative research. We have labeled them: “distinctions”, “process,” “closeness,” and “improved understanding.” During the research process the categories and notions were improved, refined, changed, and reordered. The coding ended when a sense of saturation in the material arose. In the presentation below all quotations and references come from our empirical material of texts on qualitative research.

Analysis – What is Qualitative Research?

In this section we describe the four categories we identified in the coding, how they differently discuss qualitative research, as well as their overall content. Some salient quotations are selected to represent the type of text sorted under each of the four categories. What we present are examples from the literature.

Qualitative and Quantitative

This analytic category comprises quotations comparing qualitative and quantitative research, a distinction that is frequently used (Brown 2010 :231); in effect this is a conceptual pair that structures the discussion and that may be associated with opposing interests. While the general goal of quantitative and qualitative research is the same – to understand the world better – their methodologies and focus in certain respects differ substantially (Becker 1966 :55). Quantity refers to that property of something that can be determined by measurement. In a dictionary of Statistics and Methodology we find that “(a) When referring to *variables, ‘qualitative’ is another term for *categorical or *nominal. (b) When speaking of kinds of research, ‘qualitative’ refers to studies of subjects that are hard to quantify, such as art history. Qualitative research tends to be a residual category for almost any kind of non-quantitative research” (Stiles 1998:183). But it should be obvious that one could employ a quantitative approach when studying, for example, art history.

The same dictionary states that quantitative is “said of variables or research that can be handled numerically, usually (too sharply) contrasted with *qualitative variables and research” (Stiles 1998:184). From a qualitative perspective “quantitative research” is about numbers and counting, and from a quantitative perspective qualitative research is everything that is not about numbers. But this does not say much about what is “qualitative.” If we turn to encyclopedias we find that in the 1932 edition of the Encyclopedia of the Social Sciences there is no mention of “qualitative.” In the Encyclopedia from 1968 we can read:

Qualitative Analysis. For methods of obtaining, analyzing, and describing data, see [the various entries:] CONTENT ANALYSIS; COUNTED DATA; EVALUATION RESEARCH, FIELD WORK; GRAPHIC PRESENTATION; HISTORIOGRAPHY, especially the article on THE RHETORIC OF HISTORY; INTERVIEWING; OBSERVATION; PERSONALITY MEASUREMENT; PROJECTIVE METHODS; PSYCHOANALYSIS, article on EXPERIMENTAL METHODS; SURVEY ANALYSIS, TABULAR PRESENTATION; TYPOLOGIES. (Vol. 13:225)

Some, like Alford, divide researchers into methodologists or, in his words, “quantitative and qualitative specialists” (Alford 1998 :12). Qualitative research uses a variety of methods, such as intensive interviews or in-depth analysis of historical materials, and it is concerned with a comprehensive account of some event or unit (King et al. 1994 :4). Like quantitative research it can be utilized to study a variety of issues, but it tends to focus on meanings and motivations that underlie cultural symbols, personal experiences, phenomena and detailed understanding of processes in the social world. In short, qualitative research centers on understanding processes, experiences, and the meanings people assign to things (Kalof et al. 2008 :79).

Others simply say that qualitative methods are inherently unscientific (Jovanović 2011 :19). Hood, for instance, argues that words are intrinsically less precise than numbers, and that they are therefore more prone to subjective analysis, leading to biased results (Hood 2006 :219). Qualitative methodologies have raised concerns over the limitations of quantitative templates (Brady et al. 2004 :4). Scholars such as King et al. ( 1994 ), for instance, argue that non-statistical research can produce more reliable results if researchers pay attention to the rules of scientific inference commonly stated in quantitative research. Also, researchers such as Becker ( 1966 :59; 1970 :42–43) have asserted that, if conducted properly, qualitative research and in particular ethnographic field methods, can lead to more accurate results than quantitative studies, in particular, survey research and laboratory experiments.

Some researchers, such as Kalof, Dan, and Dietz ( 2008 :79) claim that the boundaries between the two approaches are becoming blurred, and Small ( 2009 ) argues that currently much qualitative research (especially in North America) tries unsuccessfully and unnecessarily to emulate quantitative standards. For others, qualitative research tends to be more humanistic and discursive (King et al. 1994 :4). Ragin ( 1994 ), and similarly also Becker, ( 1996 :53), Marchel and Owens ( 2007 :303) think that the main distinction between the two styles is overstated and does not rest on the simple dichotomy of “numbers versus words” (Ragin 1994 :xii). Some claim that quantitative data can be utilized to discover associations, but in order to unveil cause and effect a complex research design involving the use of qualitative approaches needs to be devised (Gilbert 2009 :35). Consequently, qualitative data are useful for understanding the nuances lying beyond those processes as they unfold (Gilbert 2009 :35). Others contend that qualitative research is particularly well suited both to identify causality and to uncover fine descriptive distinctions (Fine and Hallett 2014 ; Lichterman and Isaac Reed 2014 ; Katz 2015 ).

There are other ways to separate these two traditions, including normative statements about what qualitative research should be (that is, better or worse than quantitative approaches, concerned with scientific approaches to societal change or vice versa; Snow and Morrill 1995 ; Denzin and Lincoln 2005 ), or whether it should develop falsifiable statements; Best 2004 ).

We propose that quantitative research is largely concerned with pre-determined variables (Small 2008 ); the analysis concerns the relations between variables. These categories are primarily not questioned in the study, only their frequency or degree, or the correlations between them (cf. Franzosi 2016 ). If a researcher studies wage differences between women and men, he or she works with given categories: x number of men are compared with y number of women, with a certain wage attributed to each person. The idea is not to move beyond the given categories of wage, men and women; they are the starting point as well as the end point, and undergo no “qualitative change.” Qualitative research, in contrast, investigates relations between categories that are themselves subject to change in the research process. Returning to Becker’s study ( 1963 ), we see that he questioned pre-dispositional theories of deviant behavior working with pre-determined variables such as an individual’s combination of personal qualities or emotional problems. His take, in contrast, was to understand marijuana consumption by developing “variables” as part of the investigation. Thereby he presented new variables, or as we would say today, theoretical concepts, but which are grounded in the empirical material.

Qualitative Research

This category contains quotations that refer to descriptions of qualitative research without making comparisons with quantitative research. Researchers such as Denzin and Lincoln, who have written a series of influential handbooks on qualitative methods (1994; Denzin and Lincoln 2003 ; 2005 ), citing Nelson et al. (1992:4), argue that because qualitative research is “interdisciplinary, transdisciplinary, and sometimes counterdisciplinary” it is difficult to derive one single definition of it (Jovanović 2011 :3). According to them, in fact, “the field” is “many things at the same time,” involving contradictions, tensions over its focus, methods, and how to derive interpretations and findings ( 2003 : 11). Similarly, others, such as Flick ( 2007 :ix–x) contend that agreeing on an accepted definition has increasingly become problematic, and that qualitative research has possibly matured different identities. However, Best holds that “the proliferation of many sorts of activities under the label of qualitative sociology threatens to confuse our discussions” ( 2004 :54). Atkinson’s position is more definite: “the current state of qualitative research and research methods is confused” ( 2005 :3–4).

Qualitative research is about interpretation (Blumer 1969 ; Strauss and Corbin 1998 ; Denzin and Lincoln 2003 ), or Verstehen [understanding] (Frankfort-Nachmias and Nachmias 1996 ). It is “multi-method,” involving the collection and use of a variety of empirical materials (Denzin and Lincoln 1998; Silverman 2013 ) and approaches (Silverman 2005 ; Flick 2007 ). It focuses not only on the objective nature of behavior but also on its subjective meanings: individuals’ own accounts of their attitudes, motivations, behavior (McIntyre 2005 :127; Creswell 2009 ), events and situations (Bryman 1989) – what people say and do in specific places and institutions (Goodwin and Horowitz 2002 :35–36) in social and temporal contexts (Morrill and Fine 1997). For this reason, following Weber ([1921-22] 1978), it can be described as an interpretative science (McIntyre 2005 :127). But could quantitative research also be concerned with these questions? Also, as pointed out below, does all qualitative research focus on subjective meaning, as some scholars suggest?

Others also distinguish qualitative research by claiming that it collects data using a naturalistic approach (Denzin and Lincoln 2005 :2; Creswell 2009 ), focusing on the meaning actors ascribe to their actions. But again, does all qualitative research need to be collected in situ? And does qualitative research have to be inherently concerned with meaning? Flick ( 2007 ), referring to Denzin and Lincoln ( 2005 ), mentions conversation analysis as an example of qualitative research that is not concerned with the meanings people bring to a situation, but rather with the formal organization of talk. Still others, such as Ragin ( 1994 :85), note that qualitative research is often (especially early on in the project, we would add) less structured than other kinds of social research – a characteristic connected to its flexibility and that can lead both to potentially better, but also worse results. But is this not a feature of this type of research, rather than a defining description of its essence? Wouldn’t this comment also apply, albeit to varying degrees, to quantitative research?

In addition, Strauss ( 2003 ), along with others, such as Alvesson and Kärreman ( 2011 :10–76), argue that qualitative researchers struggle to capture and represent complex phenomena partially because they tend to collect a large amount of data. While his analysis is correct at some points – “It is necessary to do detailed, intensive, microscopic examination of the data in order to bring out the amazing complexity of what lies in, behind, and beyond those data” (Strauss 2003 :10) – much of his analysis concerns the supposed focus of qualitative research and its challenges, rather than exactly what it is about. But even in this instance we would make a weak case arguing that these are strictly the defining features of qualitative research. Some researchers seem to focus on the approach or the methods used, or even on the way material is analyzed. Several researchers stress the naturalistic assumption of investigating the world, suggesting that meaning and interpretation appear to be a core matter of qualitative research.

We can also see that in this category there is no consensus about specific qualitative methods nor about qualitative data. Many emphasize interpretation, but quantitative research, too, involves interpretation; the results of a regression analysis, for example, certainly have to be interpreted, and the form of meta-analysis that factor analysis provides indeed requires interpretation However, there is no interpretation of quantitative raw data, i.e., numbers in tables. One common thread is that qualitative researchers have to get to grips with their data in order to understand what is being studied in great detail, irrespective of the type of empirical material that is being analyzed. This observation is connected to the fact that qualitative researchers routinely make several adjustments of focus and research design as their studies progress, in many cases until the very end of the project (Kalof et al. 2008 ). If you, like Becker, do not start out with a detailed theory, adjustments such as the emergence and refinement of research questions will occur during the research process. We have thus found a number of useful reflections about qualitative research scattered across different sources, but none of them effectively describe the defining characteristics of this approach.

Although qualitative research does not appear to be defined in terms of a specific method, it is certainly common that fieldwork, i.e., research that entails that the researcher spends considerable time in the field that is studied and use the knowledge gained as data, is seen as emblematic of or even identical to qualitative research. But because we understand that fieldwork tends to focus primarily on the collection and analysis of qualitative data, we expected to find within it discussions on the meaning of “qualitative.” But, again, this was not the case.

Instead, we found material on the history of this approach (for example, Frankfort-Nachmias and Nachmias 1996 ; Atkinson et al. 2001), including how it has changed; for example, by adopting a more self-reflexive practice (Heyl 2001), as well as the different nomenclature that has been adopted, such as fieldwork, ethnography, qualitative research, naturalistic research, participant observation and so on (for example, Lofland et al. 2006 ; Gans 1999 ).

We retrieved definitions of ethnography, such as “the study of people acting in the natural courses of their daily lives,” involving a “resocialization of the researcher” (Emerson 1988 :1) through intense immersion in others’ social worlds (see also examples in Hammersley 2018 ). This may be accomplished by direct observation and also participation (Neuman 2007 :276), although others, such as Denzin ( 1970 :185), have long recognized other types of observation, including non-participant (“fly on the wall”). In this category we have also isolated claims and opposing views, arguing that this type of research is distinguished primarily by where it is conducted (natural settings) (Hughes 1971:496), and how it is carried out (a variety of methods are applied) or, for some most importantly, by involving an active, empathetic immersion in those being studied (Emerson 1988 :2). We also retrieved descriptions of the goals it attends in relation to how it is taught (understanding subjective meanings of the people studied, primarily develop theory, or contribute to social change) (see for example, Corte and Irwin 2017 ; Frankfort-Nachmias and Nachmias 1996 :281; Trier-Bieniek 2012 :639) by collecting the richest possible data (Lofland et al. 2006 ) to derive “thick descriptions” (Geertz 1973 ), and/or to aim at theoretical statements of general scope and applicability (for example, Emerson 1988 ; Fine 2003 ). We have identified guidelines on how to evaluate it (for example Becker 1996 ; Lamont 2004 ) and have retrieved instructions on how it should be conducted (for example, Lofland et al. 2006 ). For instance, analysis should take place while the data gathering unfolds (Emerson 1988 ; Hammersley and Atkinson 2007 ; Lofland et al. 2006 ), observations should be of long duration (Becker 1970 :54; Goffman 1989 ), and data should be of high quantity (Becker 1970 :52–53), as well as other questionable distinctions between fieldwork and other methods:

Field studies differ from other methods of research in that the researcher performs the task of selecting topics, decides what questions to ask, and forges interest in the course of the research itself . This is in sharp contrast to many ‘theory-driven’ and ‘hypothesis-testing’ methods. (Lofland and Lofland 1995 :5)

But could not, for example, a strictly interview-based study be carried out with the same amount of flexibility, such as sequential interviewing (for example, Small 2009 )? Once again, are quantitative approaches really as inflexible as some qualitative researchers think? Moreover, this category stresses the role of the actors’ meaning, which requires knowledge and close interaction with people, their practices and their lifeworld.

It is clear that field studies – which are seen by some as the “gold standard” of qualitative research – are nonetheless only one way of doing qualitative research. There are other methods, but it is not clear why some are more qualitative than others, or why they are better or worse. Fieldwork is characterized by interaction with the field (the material) and understanding of the phenomenon that is being studied. In Becker’s case, he had general experience from fields in which marihuana was used, based on which he did interviews with actual users in several fields.

Grounded Theory

Another major category we identified in our sample is Grounded Theory. We found descriptions of it most clearly in Glaser and Strauss’ ([1967] 2010 ) original articulation, Strauss and Corbin ( 1998 ) and Charmaz ( 2006 ), as well as many other accounts of what it is for: generating and testing theory (Strauss 2003 :xi). We identified explanations of how this task can be accomplished – such as through two main procedures: constant comparison and theoretical sampling (Emerson 1998:96), and how using it has helped researchers to “think differently” (for example, Strauss and Corbin 1998 :1). We also read descriptions of its main traits, what it entails and fosters – for instance, an exceptional flexibility, an inductive approach (Strauss and Corbin 1998 :31–33; 1990; Esterberg 2002 :7), an ability to step back and critically analyze situations, recognize tendencies towards bias, think abstractly and be open to criticism, enhance sensitivity towards the words and actions of respondents, and develop a sense of absorption and devotion to the research process (Strauss and Corbin 1998 :5–6). Accordingly, we identified discussions of the value of triangulating different methods (both using and not using grounded theory), including quantitative ones, and theories to achieve theoretical development (most comprehensively in Denzin 1970 ; Strauss and Corbin 1998 ; Timmermans and Tavory 2012 ). We have also located arguments about how its practice helps to systematize data collection, analysis and presentation of results (Glaser and Strauss [1967] 2010 :16).

Grounded theory offers a systematic approach which requires researchers to get close to the field; closeness is a requirement of identifying questions and developing new concepts or making further distinctions with regard to old concepts. In contrast to other qualitative approaches, grounded theory emphasizes the detailed coding process, and the numerous fine-tuned distinctions that the researcher makes during the process. Within this category, too, we could not find a satisfying discussion of the meaning of qualitative research.

Defining Qualitative Research

In sum, our analysis shows that some notions reappear in the discussion of qualitative research, such as understanding, interpretation, “getting close” and making distinctions. These notions capture aspects of what we think is “qualitative.” However, a comprehensive definition that is useful and that can further develop the field is lacking, and not even a clear picture of its essential elements appears. In other words no definition emerges from our data, and in our research process we have moved back and forth between our empirical data and the attempt to present a definition. Our concrete strategy, as stated above, is to relate qualitative and quantitative research, or more specifically, qualitative and quantitative work. We use an ideal-typical notion of quantitative research which relies on taken for granted and numbered variables. This means that the data consists of variables on different scales, such as ordinal, but frequently ratio and absolute scales, and the representation of the numbers to the variables, i.e. the justification of the assignment of numbers to object or phenomenon, are not questioned, though the validity may be questioned. In this section we return to the notion of quality and try to clarify it while presenting our contribution.

Broadly, research refers to the activity performed by people trained to obtain knowledge through systematic procedures. Notions such as “objectivity” and “reflexivity,” “systematic,” “theory,” “evidence” and “openness” are here taken for granted in any type of research. Next, building on our empirical analysis we explain the four notions that we have identified as central to qualitative work: distinctions, process, closeness, and improved understanding. In discussing them, ultimately in relation to one another, we make their meaning even more precise. Our idea, in short, is that only when these ideas that we present separately for analytic purposes are brought together can we speak of qualitative research.

Distinctions

We believe that the possibility of making new distinctions is one the defining characteristics of qualitative research. It clearly sets it apart from quantitative analysis which works with taken-for-granted variables, albeit as mentioned, meta-analyses, for example, factor analysis may result in new variables. “Quality” refers essentially to distinctions, as already pointed out by Aristotle. He discusses the term “qualitative” commenting: “By a quality I mean that in virtue of which things are said to be qualified somehow” (Aristotle 1984:14). Quality is about what something is or has, which means that the distinction from its environment is crucial. We see qualitative research as a process in which significant new distinctions are made to the scholarly community; to make distinctions is a key aspect of obtaining new knowledge; a point, as we will see, that also has implications for “quantitative research.” The notion of being “significant” is paramount. New distinctions by themselves are not enough; just adding concepts only increases complexity without furthering our knowledge. The significance of new distinctions is judged against the communal knowledge of the research community. To enable this discussion and judgements central elements of rational discussion are required (cf. Habermas [1981] 1987 ; Davidsson [ 1988 ] 2001) to identify what is new and relevant scientific knowledge. Relatedly, Ragin alludes to the idea of new and useful knowledge at a more concrete level: “Qualitative methods are appropriate for in-depth examination of cases because they aid the identification of key features of cases. Most qualitative methods enhance data” (1994:79). When Becker ( 1963 ) studied deviant behavior and investigated how people became marihuana smokers, he made distinctions between the ways in which people learned how to smoke. This is a classic example of how the strategy of “getting close” to the material, for example the text, people or pictures that are subject to analysis, may enable researchers to obtain deeper insight and new knowledge by making distinctions – in this instance on the initial notion of learning how to smoke. Others have stressed the making of distinctions in relation to coding or theorizing. Emerson et al. ( 1995 ), for example, hold that “qualitative coding is a way of opening up avenues of inquiry,” meaning that the researcher identifies and develops concepts and analytic insights through close examination of and reflection on data (Emerson et al. 1995 :151). Goodwin and Horowitz highlight making distinctions in relation to theory-building writing: “Close engagement with their cases typically requires qualitative researchers to adapt existing theories or to make new conceptual distinctions or theoretical arguments to accommodate new data” ( 2002 : 37). In the ideal-typical quantitative research only existing and so to speak, given, variables would be used. If this is the case no new distinction are made. But, would not also many “quantitative” researchers make new distinctions?

Process does not merely suggest that research takes time. It mainly implies that qualitative new knowledge results from a process that involves several phases, and above all iteration. Qualitative research is about oscillation between theory and evidence, analysis and generating material, between first- and second -order constructs (Schütz 1962 :59), between getting in contact with something, finding sources, becoming deeply familiar with a topic, and then distilling and communicating some of its essential features. The main point is that the categories that the researcher uses, and perhaps takes for granted at the beginning of the research process, usually undergo qualitative changes resulting from what is found. Becker describes how he tested hypotheses and let the jargon of the users develop into theoretical concepts. This happens over time while the study is being conducted, exemplifying what we mean by process.

In the research process, a pilot-study may be used to get a first glance of, for example, the field, how to approach it, and what methods can be used, after which the method and theory are chosen or refined before the main study begins. Thus, the empirical material is often central from the start of the project and frequently leads to adjustments by the researcher. Likewise, during the main study categories are not fixed; the empirical material is seen in light of the theory used, but it is also given the opportunity to kick back, thereby resisting attempts to apply theoretical straightjackets (Becker 1970 :43). In this process, coding and analysis are interwoven, and thus are often important steps for getting closer to the phenomenon and deciding what to focus on next. Becker began his research by interviewing musicians close to him, then asking them to refer him to other musicians, and later on doubling his original sample of about 25 to include individuals in other professions (Becker 1973:46). Additionally, he made use of some participant observation, documents, and interviews with opiate users made available to him by colleagues. As his inductive theory of deviance evolved, Becker expanded his sample in order to fine tune it, and test the accuracy and generality of his hypotheses. In addition, he introduced a negative case and discussed the null hypothesis ( 1963 :44). His phasic career model is thus based on a research design that embraces processual work. Typically, process means to move between “theory” and “material” but also to deal with negative cases, and Becker ( 1998 ) describes how discovering these negative cases impacted his research design and ultimately its findings.

Obviously, all research is process-oriented to some degree. The point is that the ideal-typical quantitative process does not imply change of the data, and iteration between data, evidence, hypotheses, empirical work, and theory. The data, quantified variables, are, in most cases fixed. Merging of data, which of course can be done in a quantitative research process, does not mean new data. New hypotheses are frequently tested, but the “raw data is often the “the same.” Obviously, over time new datasets are made available and put into use.

Another characteristic that is emphasized in our sample is that qualitative researchers – and in particular ethnographers – can, or as Goffman put it, ought to ( 1989 ), get closer to the phenomenon being studied and their data than quantitative researchers (for example, Silverman 2009 :85). Put differently, essentially because of their methods qualitative researchers get into direct close contact with those being investigated and/or the material, such as texts, being analyzed. Becker started out his interview study, as we noted, by talking to those he knew in the field of music to get closer to the phenomenon he was studying. By conducting interviews he got even closer. Had he done more observations, he would undoubtedly have got even closer to the field.

Additionally, ethnographers’ design enables researchers to follow the field over time, and the research they do is almost by definition longitudinal, though the time in the field is studied obviously differs between studies. The general characteristic of closeness over time maximizes the chances of unexpected events, new data (related, for example, to archival research as additional sources, and for ethnography for situations not necessarily previously thought of as instrumental – what Mannay and Morgan ( 2015 ) term the “waiting field”), serendipity (Merton and Barber 2004 ; Åkerström 2013 ), and possibly reactivity, as well as the opportunity to observe disrupted patterns that translate into exemplars of negative cases. Two classic examples of this are Becker’s finding of what medical students call “crocks” (Becker et al. 1961 :317), and Geertz’s ( 1973 ) study of “deep play” in Balinese society.

By getting and staying so close to their data – be it pictures, text or humans interacting (Becker was himself a musician) – for a long time, as the research progressively focuses, qualitative researchers are prompted to continually test their hunches, presuppositions and hypotheses. They test them against a reality that often (but certainly not always), and practically, as well as metaphorically, talks back, whether by validating them, or disqualifying their premises – correctly, as well as incorrectly (Fine 2003 ; Becker 1970 ). This testing nonetheless often leads to new directions for the research. Becker, for example, says that he was initially reading psychological theories, but when facing the data he develops a theory that looks at, you may say, everything but psychological dispositions to explain the use of marihuana. Especially researchers involved with ethnographic methods have a fairly unique opportunity to dig up and then test (in a circular, continuous and temporal way) new research questions and findings as the research progresses, and thereby to derive previously unimagined and uncharted distinctions by getting closer to the phenomenon under study.

Let us stress that getting close is by no means restricted to ethnography. The notion of hermeneutic circle and hermeneutics as a general way of understanding implies that we must get close to the details in order to get the big picture. This also means that qualitative researchers can literally also make use of details of pictures as evidence (cf. Harper 2002). Thus, researchers may get closer both when generating the material or when analyzing it.

Quantitative research, we maintain, in the ideal-typical representation cannot get closer to the data. The data is essentially numbers in tables making up the variables (Franzosi 2016 :138). The data may originally have been “qualitative,” but once reduced to numbers there can only be a type of “hermeneutics” about what the number may stand for. The numbers themselves, however, are non-ambiguous. Thus, in quantitative research, interpretation, if done, is not about the data itself—the numbers—but what the numbers stand for. It follows that the interpretation is essentially done in a more “speculative” mode without direct empirical evidence (cf. Becker 2017 ).

Improved Understanding

While distinction, process and getting closer refer to the qualitative work of the researcher, improved understanding refers to its conditions and outcome of this work. Understanding cuts deeper than explanation, which to some may mean a causally verified correlation between variables. The notion of explanation presupposes the notion of understanding since explanation does not include an idea of how knowledge is gained (Manicas 2006 : 15). Understanding, we argue, is the core concept of what we call the outcome of the process when research has made use of all the other elements that were integrated in the research. Understanding, then, has a special status in qualitative research since it refers both to the conditions of knowledge and the outcome of the process. Understanding can to some extent be seen as the condition of explanation and occurs in a process of interpretation, which naturally refers to meaning (Gadamer 1990 ). It is fundamentally connected to knowing, and to the knowing of how to do things (Heidegger [1927] 2001 ). Conceptually the term hermeneutics is used to account for this process. Heidegger ties hermeneutics to human being and not possible to separate from the understanding of being ( 1988 ). Here we use it in a broader sense, and more connected to method in general (cf. Seiffert 1992 ). The abovementioned aspects – for example, “objectivity” and “reflexivity” – of the approach are conditions of scientific understanding. Understanding is the result of a circular process and means that the parts are understood in light of the whole, and vice versa. Understanding presupposes pre-understanding, or in other words, some knowledge of the phenomenon studied. The pre-understanding, even in the form of prejudices, are in qualitative research process, which we see as iterative, questioned, which gradually or suddenly change due to the iteration of data, evidence and concepts. However, qualitative research generates understanding in the iterative process when the researcher gets closer to the data, e.g., by going back and forth between field and analysis in a process that generates new data that changes the evidence, and, ultimately, the findings. Questioning, to ask questions, and put what one assumes—prejudices and presumption—in question, is central to understand something (Heidegger [1927] 2001 ; Gadamer 1990 :368–384). We propose that this iterative process in which the process of understanding occurs is characteristic of qualitative research.

Improved understanding means that we obtain scientific knowledge of something that we as a scholarly community did not know before, or that we get to know something better. It means that we understand more about how parts are related to one another, and to other things we already understand (see also Fine and Hallett 2014 ). Understanding is an important condition for qualitative research. It is not enough to identify correlations, make distinctions, and work in a process in which one gets close to the field or phenomena. Understanding is accomplished when the elements are integrated in an iterative process.

It is, moreover, possible to understand many things, and researchers, just like children, may come to understand new things every day as they engage with the world. This subjective condition of understanding – namely, that a person gains a better understanding of something –is easily met. To be qualified as “scientific,” the understanding must be general and useful to many; it must be public. But even this generally accessible understanding is not enough in order to speak of “scientific understanding.” Though we as a collective can increase understanding of everything in virtually all potential directions as a result also of qualitative work, we refrain from this “objective” way of understanding, which has no means of discriminating between what we gain in understanding. Scientific understanding means that it is deemed relevant from the scientific horizon (compare Schütz 1962 : 35–38, 46, 63), and that it rests on the pre-understanding that the scientists have and must have in order to understand. In other words, the understanding gained must be deemed useful by other researchers, so that they can build on it. We thus see understanding from a pragmatic, rather than a subjective or objective perspective. Improved understanding is related to the question(s) at hand. Understanding, in order to represent an improvement, must be an improvement in relation to the existing body of knowledge of the scientific community (James [ 1907 ] 1955). Scientific understanding is, by definition, collective, as expressed in Weber’s famous note on objectivity, namely that scientific work aims at truths “which … can claim, even for a Chinese, the validity appropriate to an empirical analysis” ([1904] 1949 :59). By qualifying “improved understanding” we argue that it is a general defining characteristic of qualitative research. Becker‘s ( 1966 ) study and other research of deviant behavior increased our understanding of the social learning processes of how individuals start a behavior. And it also added new knowledge about the labeling of deviant behavior as a social process. Few studies, of course, make the same large contribution as Becker’s, but are nonetheless qualitative research.

Understanding in the phenomenological sense, which is a hallmark of qualitative research, we argue, requires meaning and this meaning is derived from the context, and above all the data being analyzed. The ideal-typical quantitative research operates with given variables with different numbers. This type of material is not enough to establish meaning at the level that truly justifies understanding. In other words, many social science explanations offer ideas about correlations or even causal relations, but this does not mean that the meaning at the level of the data analyzed, is understood. This leads us to say that there are indeed many explanations that meet the criteria of understanding, for example the explanation of how one becomes a marihuana smoker presented by Becker. However, we may also understand a phenomenon without explaining it, and we may have potential explanations, or better correlations, that are not really understood.

We may speak more generally of quantitative research and its data to clarify what we see as an important distinction. The “raw data” that quantitative research—as an idealtypical activity, refers to is not available for further analysis; the numbers, once created, are not to be questioned (Franzosi 2016 : 138). If the researcher is to do “more” or “change” something, this will be done by conjectures based on theoretical knowledge or based on the researcher’s lifeworld. Both qualitative and quantitative research is based on the lifeworld, and all researchers use prejudices and pre-understanding in the research process. This idea is present in the works of Heidegger ( 2001 ) and Heisenberg (cited in Franzosi 2010 :619). Qualitative research, as we argued, involves the interaction and questioning of concepts (theory), data, and evidence.

Ragin ( 2004 :22) points out that “a good definition of qualitative research should be inclusive and should emphasize its key strengths and features, not what it lacks (for example, the use of sophisticated quantitative techniques).” 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. Qualitative research, as defined here, is consequently a combination of two criteria: (i) how to do things –namely, generating and analyzing empirical material, in an iterative process in which one gets closer by making distinctions, and (ii) the outcome –improved understanding novel to the scholarly community. Is our definition applicable to our own study? In this study we have closely read the empirical material that we generated, and the novel distinction of the notion “qualitative research” is the outcome of an iterative process in which both deduction and induction were involved, in which we identified the categories that we analyzed. We thus claim to meet the first criteria, “how to do things.” The second criteria cannot be judged but in a partial way by us, namely that the “outcome” —in concrete form the definition-improves our understanding to others in the scientific community.

We have defined qualitative research, or qualitative scientific work, in relation to quantitative scientific work. Given this definition, qualitative research is about questioning the pre-given (taken for granted) variables, but it is thus also about making new distinctions of any type of phenomenon, for example, by coining new concepts, including the identification of new variables. This process, as we have discussed, is carried out in relation to empirical material, previous research, and thus in relation to theory. Theory and previous research cannot be escaped or bracketed. According to hermeneutic principles all scientific work is grounded in the lifeworld, and as social scientists we can thus never fully bracket our pre-understanding.

We have proposed that quantitative research, as an idealtype, is concerned with pre-determined variables (Small 2008 ). Variables are epistemically fixed, but can vary in terms of dimensions, such as frequency or number. Age is an example; as a variable it can take on different numbers. In relation to quantitative research, qualitative research does not reduce its material to number and variables. If this is done the process of comes to a halt, the researcher gets more distanced from her data, and it makes it no longer possible to make new distinctions that increase our understanding. We have above discussed the components of our definition in relation to quantitative research. Our conclusion is that in the research that is called quantitative there are frequent and necessary qualitative elements.

Further, comparative empirical research on researchers primarily working with ”quantitative” approaches and those working with ”qualitative” approaches, we propose, would perhaps show that there are many similarities in practices of these two approaches. This is not to deny dissimilarities, or the different epistemic and ontic presuppositions that may be more or less strongly associated with the two different strands (see Goertz and Mahoney 2012 ). Our point is nonetheless that prejudices and preconceptions about researchers are unproductive, and that as other researchers have argued, differences may be exaggerated (e.g., Becker 1996 : 53, 2017 ; Marchel and Owens 2007 :303; Ragin 1994 ), and that a qualitative dimension is present in both kinds of work.

Several things follow from our findings. The most important result is the relation to quantitative research. In our analysis we have separated qualitative research from quantitative research. The point is not to label individual researchers, methods, projects, or works as either “quantitative” or “qualitative.” By analyzing, i.e., taking apart, the notions of quantitative and qualitative, we hope to have shown the elements of qualitative research. Our definition captures the elements, and how they, when combined in practice, generate understanding. As many of the quotations we have used suggest, one conclusion of our study holds that qualitative approaches are not inherently connected with a specific method. Put differently, none of the methods that are frequently labelled “qualitative,” such as interviews or participant observation, are inherently “qualitative.” What matters, given our definition, is whether one works qualitatively or quantitatively in the research process, until the results are produced. Consequently, our analysis also suggests that those researchers working with what in the literature and in jargon is often called “quantitative research” are almost bound to make use of what we have identified as qualitative elements in any research project. Our findings also suggest that many” quantitative” researchers, at least to some extent, are engaged with qualitative work, such as when research questions are developed, variables are constructed and combined, and hypotheses are formulated. Furthermore, a research project may hover between “qualitative” and “quantitative” or start out as “qualitative” and later move into a “quantitative” (a distinct strategy that is not similar to “mixed methods” or just simply combining induction and deduction). More generally speaking, the categories of “qualitative” and “quantitative,” unfortunately, often cover up practices, and it may lead to “camps” of researchers opposing one another. For example, regardless of the researcher is primarily oriented to “quantitative” or “qualitative” research, the role of theory is neglected (cf. Swedberg 2017 ). Our results open up for an interaction not characterized by differences, but by different emphasis, and similarities.

Let us take two examples to briefly indicate how qualitative elements can fruitfully be combined with quantitative. Franzosi ( 2010 ) has discussed the relations between quantitative and qualitative approaches, and more specifically the relation between words and numbers. He analyzes texts and argues that scientific meaning cannot be reduced to numbers. Put differently, the meaning of the numbers is to be understood by what is taken for granted, and what is part of the lifeworld (Schütz 1962 ). Franzosi shows how one can go about using qualitative and quantitative methods and data to address scientific questions analyzing violence in Italy at the time when fascism was rising (1919–1922). Aspers ( 2006 ) studied the meaning of fashion photographers. He uses an empirical phenomenological approach, and establishes meaning at the level of actors. In a second step this meaning, and the different ideal-typical photographers constructed as a result of participant observation and interviews, are tested using quantitative data from a database; in the first phase to verify the different ideal-types, in the second phase to use these types to establish new knowledge about the types. In both of these cases—and more examples can be found—authors move from qualitative data and try to keep the meaning established when using the quantitative data.

A second main result of our study is that a definition, and we provided one, offers a way for research to clarify, and even evaluate, what is done. Hence, our definition can guide researchers and students, informing them on how to think about concrete research problems they face, and to show what it means to get closer in a process in which new distinctions are made. The definition can also be used to evaluate the results, given that it is a standard of evaluation (cf. Hammersley 2007 ), to see whether new distinctions are made and whether this improves our understanding of what is researched, in addition to the evaluation of how the research was conducted. By making what is qualitative research explicit it becomes easier to communicate findings, and it is thereby much harder to fly under the radar with substandard research since there are standards of evaluation which make it easier to separate “good” from “not so good” qualitative research.

To conclude, our analysis, which ends with a definition of qualitative research can thus both address the “internal” issues of what is qualitative research, and the “external” critiques that make it harder to do qualitative research, to which both pressure from quantitative methods and general changes in society contribute.

Acknowledgements

Financial Support for this research is given by the European Research Council, CEV (263699). The authors are grateful to Susann Krieglsteiner for assistance in collecting the data. The paper has benefitted from the many useful comments by the three reviewers and the editor, comments by members of the Uppsala Laboratory of Economic Sociology, as well as Jukka Gronow, Sebastian Kohl, Marcin Serafin, Richard Swedberg, Anders Vassenden and Turid Rødne.

Biographies

is professor of sociology at the Department of Sociology, Uppsala University and Universität St. Gallen. His main focus is economic sociology, and in particular, markets. He has published numerous articles and books, including Orderly Fashion (Princeton University Press 2010), Markets (Polity Press 2011) and Re-Imagining Economic Sociology (edited with N. Dodd, Oxford University Press 2015). His book Ethnographic Methods (in Swedish) has already gone through several editions.

is associate professor of sociology at the Department of Media and Social Sciences, University of Stavanger. His research has been published in journals such as Social Psychology Quarterly, Sociological Theory, Teaching Sociology, and Music and Arts in Action. As an ethnographer he is working on a book on he social world of big-wave surfing.

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Contributor Information

Patrik Aspers, Email: [email protected] .

Ugo Corte, Email: [email protected] .

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Inductive content analysis: A guide for beginning qualitative researchers

• Danya F Vears Murdoch Children's Research Institute Melbourne Law School, University of Melbourne
• Lynn Gillam Children's Bioethics Centre, The Royal Children's Hospital Melbourne School of Population and Global Health, University of Melbourne

Inductive content analysis (ICA), or qualitative content analysis, is a method of qualitative data analysis well-suited to use in health-related research, particularly in relatively small-scale, non-complex research done by health professionals undertaking research-focused degree courses. For those new to qualitative research, the methodological literature on ICA can be difficult to navigate, as it employs a wide variety of terminology and gives a number of different descriptions of when and how to carry it out.

In this article, we describe in plain language what ICA is, highlight how it differs from deductive content analysis and thematic analysis, and discuss the key aspects to consider when making decisions about employing ICA in qualitative research. Using a study investigating practices and views around genetic testing in children as an example, we provide a clear step-by-step account of analysing text using ICA. 

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Qualitative Research Journal

ISSN : 1443-9883

Article publication date: 31 October 2018

Issue publication date: 15 November 2018

The purpose of this paper is to explain the rationale for choosing the qualitative approach to research human resources practices, namely, recruitment and selection, training and development, performance management, rewards management, employee communication and participation, diversity management and work and life balance using deductive and inductive approaches to analyse data. The paper adopts an emic perspective that favours the study of transfer of human resource management practices from the point of view of employees and host country managers in subsidiaries of western multinational enterprises in Ghana.

Design/methodology/approach

Despite the numerous examples of qualitative methods of data generation, little is known particularly to the novice researcher about how to analyse qualitative data. This paper develops a model to explain in a systematic manner how to methodically analyse qualitative data using both deductive and inductive approaches.

The deductive and inductive approaches provide a comprehensive approach in analysing qualitative data. The process involves immersing oneself in the data reading and digesting in order to make sense of the whole set of data and to understand what is going on.

Originality/value

This paper fills a serious gap in qualitative data analysis which is deemed complex and challenging with limited attention in the methodological literature particularly in a developing country context, Ghana.

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Azungah, T. (2018), "Qualitative research: deductive and inductive approaches to data analysis", Qualitative Research Journal , Vol. 18 No. 4, pp. 383-400. https://doi.org/10.1108/QRJ-D-18-00035

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Inductive Approach (Inductive Reasoning)

Inductive approach, also known in inductive reasoning, starts with the observations and theories are proposed towards the end of the research process as a result of observations [1] .  Inductive research “involves the search for pattern from observation and the development of explanations – theories – for those patterns through series of hypotheses” [2] . No theories or hypotheses would apply in inductive studies at the beginning of the research and the researcher is free in terms of altering the direction for the study after the research process had commenced.

It is important to stress that inductive approach does not imply disregarding theories when formulating research questions and objectives. This approach aims to generate meanings from the data set collected in order to identify patterns and relationships to build a theory; however, inductive approach does not prevent the researcher from using existing theory to formulate the research question to be explored. [3] Inductive reasoning is based on learning from experience. Patterns, resemblances and regularities in experience (premises) are observed in order to reach conclusions (or to generate theory).

Application of Inductive Approach (Inductive Reasoning) in Business Research

Inductive reasoning begins with detailed observations of the world, which moves towards more abstract generalisations and ideas [4] . When following an inductive approach, beginning with a topic, a researcher tends to develop empirical generalisations and identify preliminary relationships as he progresses through his research. No hypotheses can be found at the initial stages of the research and the researcher is not sure about the type and nature of the research findings until the study is completed.

As it is illustrated in figure below, “inductive reasoning is often referred to as a “bottom-up” approach to knowing, in which the researcher uses observations to build an abstraction or to describe a picture of the phenomenon that is being studied” [5]

Here is an example:

My nephew borrowed $100 last June but he did not pay back until September as he had promised (PREMISE). Then he assured me that he will pay back until Christmas but he didn’t (PREMISE). He also failed in to keep his promise to pay back in March (PREMISE). I reckon I have to face the facts. My nephew is never going to pay me back (CONCLUSION).

Generally, the application of inductive approach is associated with qualitative methods of data collection and data analysis, whereas deductive approach is perceived to be related to quantitative methods . The following table illustrates such a classification from a broad perspective:

However, the statement above is not absolute, and in some instances inductive approach can be adopted to conduct a quantitative research as well. The following table illustrates patterns of data analysis according to type of research and research approach .

When writing a dissertation in business studies it is compulsory to specify the approach of are adopting. It is good to include a table comparing inductive and deductive approaches similar to one below [6] and discuss the impacts of your choice of inductive approach on selection of primary data collection methods and research process.

My e-book,  The Ultimate Guide to Writing a Dissertation in Business Studies: a step by step assistance  contains discussions of theory and application of research approaches. The e-book also explains all stages of the  research process  starting from the  selection of the research area  to writing personal reflection. Important elements of dissertations such as  research philosophy ,  research design ,  methods of data collection ,  data analysis  and  sampling  are explained in this e-book in simple words.

John Dudovskiy

[1] Goddard, W. & Melville, S. (2004) “Research Methodology: An Introduction” 2nd edition, Blackwell Publishing

[2] Bernard, H.R. (2011) “Research Methods in Anthropology” 5 th edition, AltaMira Press, p.7

[3] Saunders, M., Lewis, P. & Thornhill, A. (2012) “Research Methods for Business Students” 6 th  edition, Pearson Education Limited

[4] Neuman, W.L. (2003) “Social Research Methods: Qualitative and Quantitative Approaches” Allyn and Bacon

[5] Lodico, M.G., Spaulding, D.T &Voegtle, K.H. (2010) “Methods in Educational Research: From Theory to Practice” John Wiley & Sons, p.10

[6] Source: Alexandiris, K.T. (2006) “Exploring Complex Dynamics in Multi Agent-Based Intelligent Systems” Pro Quest

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Qualitative Research

What is qualitative research.

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

The Basic Idea

Theory, meet practice.

TDL is an applied research consultancy. In our work, we leverage the insights of diverse fields—from psychology and economics to machine learning and behavioral data science—to sculpt targeted solutions to nuanced problems.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Thomas Kuhn

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

Paul Felix Lazarsfeld

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

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

George Herbert Mead

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

Consequences

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

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

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

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

Controversies

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

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

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

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

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

Linking Adult Behaviors to Childhood Experiences

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

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

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

Understanding Voter Turnout

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

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

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

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

About the Author

Emilie Rose Jones

Emilie currently works in Marketing & Communications for a non-profit organization based in Toronto, Ontario. She completed her Masters of English Literature at UBC in 2021, where she focused on Indigenous and Canadian Literature. Emilie has a passion for writing and behavioural psychology and is always looking for opportunities to make knowledge more accessible. 

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Speaker 1: In this video, we're going to dive into the topic of qualitative coding, which you'll need to understand if you plan to undertake qualitative analysis for any dissertation, thesis, or research project. We'll explain what exactly qualitative coding is, the different coding approaches and methods, and how to go about coding your data step by step. So go ahead, grab a cup of coffee, grab a cup of tea, whatever works for you, and let's jump into it. Hey, welcome to Grad Coach TV, where we demystify and simplify the oftentimes intimidating world of academic research. My name's Emma, and today we're going to explore qualitative coding, an essential first step in qualitative analysis. If you'd like to learn more about qualitative analysis or research methodology in general, we've also got videos covering those topics, so be sure to check them out. I'll include the links below. If you're new to Grad Coach TV, hit that subscribe button for more videos covering all things research related. Also, if you're looking for hands-on help with your qualitative coding, check out our one-on-one coaching services, where we hold your hand through the coding process step by step. Alternatively, if you're looking to fast track your coding, we also offer a professional coding service, where our seasoned qualitative experts code your data for you, ensuring high-quality initial coding. If that sounds interesting to you, you can learn more and book a free consultation at gradcoach.com. All right, with that out of the way, let's get into it. To kick things off, let's start by understanding what a code is. At the simplest level, a code is a label that describes a piece of content. For example, in the sentence, pigeons attacked me and stole my sandwich, you could use pigeons as a code. This code would simply describe that the sentence involves pigeons. Of course, there are many ways you could code this, and this is just one approach. We'll explore the different ways in which you can code later in this video. So, qualitative coding is simply the process of creating and assigning codes to categorize data extracts. You'll then use these codes later down the road to derive themes and patterns for your actual qualitative analysis. For example, thematic analysis or content analysis. It's worth It's worth noting that coding and analysis can take place simultaneously. In fact, it's pretty much expected that you'll notice some themes emerge while you code. That said, it's important to note that coding does not necessarily involve identifying themes. Instead, it refers to the process of labeling and grouping similar types of data, which in turn will make generating themes and analyzing the data more manageable. You might be wondering then, why should I bother with coding at all? Why not just look for themes from the outset? Well, coding is a way of making sure your data is valid. In other words, it helps ensure that your analysis is undertaken systematically, and that other researchers can review it. In the world of research, we call this transparency. In other words, coding is the foundation of high quality analysis, which makes it an essential first step. Right, now that we've got a plain language definition of coding on the table, the next step is to understand what types of coding exist. Let's start with the two main approaches, deductive and inductive coding. With deductive coding, you as the researcher begin with a set of pre-established codes and apply them to your data set, for example, a set of interview transcripts. Inductive coding, on the other hand, works in reverse, as you start with a blank canvas and create your set of codes based on the data itself. In other words, the codes emerge from the data. Let's take a closer look at both of these approaches. With deductive coding, you'll make use of predetermined codes, also called a priori codes, which are developed before you interact with the present data. This usually involves drawing up a set of codes based on a research question or previous research from your literature review. You could also use an existing code set from the codebook of a previous study. For example, if you were studying the eating habits of college students, you might have a research question along the lines of, what foods do college students eat the most? As a result of this research question, you might develop a code set that includes codes such as sushi, pizza, and burgers. You'd then code your data set using only these codes, regardless of what you find in the data. On the upside, the deductive approach allows you to undertake your analysis with a very tightly focused lens and quickly identify relevant data, avoiding distractions and detours. The downside, of course, is that you could miss out on some very valuable insights as a result of this tight predetermined focus. Now let's look at the opposite approach, inductive coding. As I mentioned earlier, this type of coding involves jumping right into the data without predetermined codes and developing the codes based on what you find within the data. For example, if you were to analyze a set of open-ended interview question responses, you wouldn't necessarily know which direction the conversation would flow. If a conversation begins with a discussion of cats, it might go on to include other animals too. And so, you'd add these codes as you progress with your analysis. Simply put, with inductive coding, you go with the flow of the data. Inductive coding is great when you're researching something that isn't yet well understood because the coding derived from the data helps you explore the subject. Therefore, this approach to coding is usually adopted when researchers want to investigate new ideas or concepts or when they want to create new theories. So, as you can see, the inductive and deductive approaches represent two ends of a spectrum, but this doesn't mean that they're mutually exclusive. You can also take a hybrid approach where you utilize a mix of both. For example, if you've got a set of codes you've derived from a literature review or a previous study, in other words, a deductive approach, but you still don't have a rich enough code set to capture the depth of your qualitative data, you can combine deductive and inductive approaches, which we call a hybrid approach. To adopt a hybrid approach, you'll begin your analysis with a set of a priori codes, in other words, a deductive approach, and then add new codes, in other words, an inductive approach, as you work your way through the data. Essentially, the hybrid coding approach provides the best of both worlds, which is why it's pretty common to see this in research. All right, now that we've covered what qualitative coding is and the overarching approaches, let's dive into the actual coding process and look at how to undertake the coding. So, let's take a look at the actual coding process step by step. Whether you adopt an inductive or deductive approach, your coding will consist of two stages, initial coding and line-by-line coding. In the initial coding stage, the objective is to get a general overview of the data by reading through and understanding it. If you're using an inductive approach, this is also where you'll develop an initial set of codes. Then in the second stage, line-by-line coding, you'll delve deeper into the data and organize it into a formalized set of codes. Let's take a look at these stages of qualitative coding in more detail. Stage one, initial coding. The first step of the coding process is to identify the essence of the text and code it accordingly. While there are many qualitative analysis software options available, you can just as easily code text-based data using Microsoft Word's comments feature. In fact, if it's your first time coding, it's oftentimes best to just stick with Word as this eliminates the additional need to learn new software. Importantly, you should avoid the temptation of any sort of automated coding software or service. No matter what promises they make, automated software simply cannot compare to human-based coding as it can't understand the subtleties of language and context. Don't waste your time with this. In all likelihood, you'll just end up having to recode everything yourself anyway. Okay, so let's take a look at a practical example of the coding process. Assume you had the following interview data from two interviewees. In the initial stage of coding, you could assign the code of pets or animals. These are just initial fairly broad codes that you can and will develop and refine later. In the initial stage, broad rough codes are fine. They're just a starting point which you will build onto later when you undertake line-by-line coding. So, at this stage, you're probably wondering how to decide what codes to use, especially when there are so many ways to read and interpret any given sentence. Well, there are a few different coding methods you can adopt and the right method will depend on your research aims and research questions. In other words, the way you code will depend on what you're trying to achieve with your research. Five common methods utilized in the initial coding stage include in vivo coding, process coding, descriptive coding, structural coding, and value coding. These are not the only methods available, but they're a useful starting point. Let's take a look at each of them to understand how and when each method could be useful. Method number one, in vivo coding. When you use in vivo coding, you make use of a participant's own words rather than your interpretation of the data. In other words, you use direct quotes from participants as your codes. By doing this, you'll avoid trying to infer meaning by staying as close to the original phrases and words as possible. In vivo coding is particularly useful when your data are derived from participants who speak different languages or come from different cultures. In cases like these, it's often difficult to accurately infer meaning thanks to linguistic and or cultural differences. For example, English speakers typically view the future as in front of them and the past as behind them. However, this isn't the same in all cultures. Speakers of Aymara view the past as in front of them and the future as behind them. Why? Because the future is unknown. It must be out of sight or behind them. They know what happened in the past so their perspective is that it's positioned in front of them where they can see it. In a scenario like this one, it's not possible to derive the reason for viewing the past as in front and the future as behind without knowing the Aymara culture's perception of time. Therefore, in vivo coding is particularly useful as it avoids interpretation errors. While this case is a unique one, it illustrates the point that different languages and cultures can view the same things very differently, which would have major impacts on your data. Method number two, process coding. Next up, there's process coding, which makes use of action-based codes. Action-based codes are codes that indicate a movement or procedure. These actions are often indicated by gerunds, that is words ending in ing. For example, running, jumping, or singing. Process coding is useful as it allows you to code parts of data that aren't necessarily spoken but that are still important to understand the meaning of the text. For example, you may have action codes such as describing a panda, singing a song, or arguing with a relative. Another example would be if a participant were to say something like, I have no idea where she is. A sentence like this could be interpreted in many different ways depending on the context and movements of the participant. The participant could, for example, shrug their shoulders, which would indicate that they genuinely don't know where the girl is. Alternatively, they could wink, suggesting that they do actually know where the girl is. Simply put, process coding is useful as it allows you to, in a concise manner, identify occurrences in a set of data that are not necessarily spoken and to provide a dynamic account of events. Method number three, descriptive coding. Descriptive coding is a popular coding method that aims to summarize extracts by using a single word that encapsulates the general idea of the data. These words will typically describe the data in a highly condensed manner, which allows you as the researcher to quickly refer to the content. For example, a descriptive code could be food, when coding a video clip that involves a group of people discussing what they ate throughout the day, or cooking, when coding an image showing the steps of a recipe. Descriptive coding is very useful when dealing with data that appear in forms other than text. For example, video clips, sound recordings, or images. It's also particularly useful when you want to organize a large data set by topic area. This makes descriptive coding a popular choice for many research projects. Method number four, structural coding. True to its name, structural coding involves labeling and describing specific structural attributes of the data. Generally, it includes coding according to answers of the questions of who, what, where, and how, rather than the actual topics expressed in the data. For example, if you were coding a collection of dissertations, which would be quite a large data set, structural coding might be useful as you could code according to different sections within each of these documents. Coding what centric labels, such as hypotheses, literature review, and methodology, would help you to efficiently refer to sections and navigate without having to work through sections of data all over again. So, structural coding is useful when you want to access segments of data quickly, and it can help tremendously when you're dealing with large data sets. Structural coding can also be useful for data from open-ended survey questions. This data may initially be difficult to code as they lack the set structure of other forms of data, such as an interview with a strict closed set of questions to be answered. In this case, it would be useful to code sections of data that answer certain questions, such as who, what, where, and how. Method number five, values coding. Last but not least, values-based coding involves coding excerpts that relate to the participant's worldviews. Typically, this type of coding focuses on excerpts that provide insight regarding the values, attitudes, and beliefs of the participants. In practical terms, this means you'd be looking for instances where your participants say things like, I feel, I think that, I need, and it's important that, as these sorts of statements often provide insight into their values, attitudes, and beliefs. Values coding is therefore very useful when your research aims and research questions seek to explore cultural values and interpersonal experiences and actions, or when you're looking to learn about the human experience. All right, so we've looked at five popular methods that can be used in the initial coding stage. As I mentioned, this is not a comprehensive list, so if none of these sound relevant to your project, be sure to look up alternative coding methods to find the right fit for your research aims. The five methods we've discussed allow you to arrange your data so that it's easier to navigate during the next stage, line-by-line coding. While these methods can all be used individually, it's important to know that it's possible, and quite often beneficial, to combine them. For example, when conducting initial coding with interview data, you could begin by using structural coding to indicate who speaks when. Then, as a next step, you could apply descriptive coding so that you can navigate to and between conversation topics easily. As with all design choices, the right method or combination of methods depends on your research aims and research questions, so think carefully about what you're trying to achieve with your research. Then, select the method or methods that make sense in light of that. So, to recap, the aim of initial coding is to understand and familiarize yourself with your data, to develop an initial code set, if you're taking an inductive approach, and to take the first shot at coding your data. Once that's done, you can move on to the next stage, line-by-line coding. Let's do it. Line-by-line coding is pretty much exactly what it sounds like, reviewing your data line-by-line, digging deeper, refining your codes, and assigning additional codes to each line. With line-by-line coding, the objective is to pay close attention to your data, to refine and expand upon your coding, especially when it comes to adopting an inductive approach. For example, if you have a discussion of beverages and you previously just coded this as beverages, you could now go deeper and code more specifically, such as coffee, tea, and orange juice. The aim here is to scratch below the surface. This is the time to get detailed and specific so that you can capture as much richness from the data as possible. In the line-by-line coding process, it's useful to code as much data as possible, even if you don't think you're going to use it. As you go through this process, your coding will become more thorough and detailed, and you'll have a much better understanding of your data as a result of this. This will be incredibly valuable in the analysis phase, so don't cut corners here. Take your time to work through your data line-by-line and apply your mind to see how you refine your coding as much as possible. Keep in mind that coding is an iterative process, which means that you'll move back and forth between interviews or documents to apply the codes consistently throughout your data set. Be careful to clearly define each code and update previously coded excerpts if you adjust or update the definition of any code, or if you split any code into narrower codes. Line-by-line coding takes time, so don't rush it. Be patient and work through your data meticulously to ensure you develop a high-quality code set. Stage three, moving from coding to analysis. Once you've completed your initial and line-by-line coding, the next step is to start your actual qualitative analysis. Of course, the coding process itself will get you in analysis mode, and you'll probably already have some insights and ideas as a result of it, so you should always keep notes of your thoughts as you work through the coding process. When it comes to qualitative data analysis, there are many different methods you can use, including content analysis, thematic analysis, and discourse analysis. The analysis method you adopt will depend heavily on your research aims and research questions. We cover qualitative analysis methods on the Grad Coach blog, so we're not going to go down that rabbit hole here, but we'll discuss the important first steps that build the bridge from qualitative coding to qualitative analysis. So, how do you get started with your analysis? Well, each analysis will be different, but it's useful to ask yourself the following more general questions to get the wheels turning. What actions and interactions are shown in the data? What are the aims of these interactions and excerpts? How do participants interpret what is happening, and how do they speak about it? What does their language reveal? What are the assumptions made by the participants? What are the participants doing? Why do I want to learn about this? What am I trying to find out? As with initial coding and line-by-line coding, your qualitative analysis can follow certain steps. The first two steps will typically be code categorization and theme identification. Let's look at these two steps. Code categorization, which is the first step, is simply the process of reviewing everything you've coded and then creating categories that can be used to guide your future analysis. In other words, it's about bundling similar or related codes into categories to help organize your data effectively. Let's look at a practical example. If you were discussing different types of animals, your codes may include dogs, llamas, and lions. In the process of code categorization, you could label, in other words, categorize these three animals as mammals, whereas you could categorize flies, crickets, and beetles as insects. By creating these code categories, you will be making your data more organized, as well as enriching it so that you can see new connections between different groups of codes. Once you've categorized your codes, you can move on to the next step, which is to identify the themes in your data. Let's look at the theme identification step. From the coding and categorization processes, you'll naturally start noticing themes. Therefore, the next logical step is to identify and clearly articulate the themes in your data set. When you determine themes, you'll take what you've learned from the coding and categorization stages and synthesize it to develop themes. This is the part of the analysis process where you'll begin to draw meaning from your data and produce a narrative. The nature of this narrative will, of course, depend on your research aims, your research questions, and the analysis method you've chosen. For example, content analysis or thematic analysis. So, keep these factors front of mind as you scan for themes, as they'll help you stay aligned with the big picture. All right, now that we've covered both the what and the how of qualitative coding, I want to quickly share some general tips and suggestions to help you optimize your coding process. Let's rapid fire. One, before you begin coding, plan out the steps you'll take and the coding approach and method or methods you'll follow to avoid inconsistencies. Two, when adopting a deductive approach, it's best to use a codebook with detailed descriptions of each code right from the start of the coding process. This will ensure that you apply codes consistently based on their descriptions and will help you keep your work organized. Three, whether you adopt an inductive or deductive approach, keep track of the meanings of your codes and remember to revisit these as you go along. Four, while coding, keep your research aims, research questions, coding methods, and analysis method front of mind. This will help you to avoid directional drift, which happens when coding is not kept consistent. Five, if you're working in a research team with multiple coders, make sure that everyone has been trained and clearly understands how codes need to be assigned. If multiple coders are pulling in even slightly different directions, you will end up with a mess that needs to be redone. You don't want that. So keep these five tips in mind and you'll be on the fast track to coding success. And there you have it, qualitative coding in a nutshell. Remember, as with every design choice in your dissertation, thesis, or research project, your research aims and research questions will have a major influence on how you approach the coding. So keep these two elements front of mind every step of the way and make sure your coding approach and methods align well. If you enjoyed the video, hit the like button and leave a comment if you have any questions. Also, be sure to subscribe to the channel for more research-related content. If you need a helping hand with your qualitative coding or any part of your research project, remember to check out our private coaching service where we work with you on a one-on-one basis, chapter by chapter, to help you craft a winning piece of research. If that sounds interesting to you, book a free consultation with a friendly coach at gradcoach.com. As always, I'll include a link below. That's all for this episode of Grad Coach TV. Until next time, good luck.

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Creating "a Safe Place to Go": Yarning With Health Workers About Stroke Recovery Care for Aboriginal Stroke Survivors-A Qualitative Study

Affiliations.

• 1 Hunter Stroke Service, Hunter New England Local Health District, New Lambton Heights, NSW, Australia.
• 2 Heart and Stroke Program, Hunter Medical Research Institute, New Lambton Heights, NSW, Australia.
• 3 School of Health Sciences, The University of Newcastle, Newcastle, NSW, Australia.
• 4 Consumer With Lived Experience, Kempsey Community Health Centre, Kempsey, NSW, Australia.
• 5 School of Medicine and Public Health, The University of Newcastle, Newcastle, NSW, Australia.
• 6 School of Medical and Health Sciences, Edith Cowan University, Joondalup, WA, Australia.
• 7 Newcastle's Department of Rural Health, University of Newcastle, Tamworth, NSW, Australia.
• 8 Community Elder, Tamworth Community Health Centre, Tamworth, NSW, Australia.
• 9 Hunter New England Health Local Health District, New Lambton Heights, NSW, Australia.
• 10 Consumer With Lived Experience, Tamworth Community Health Centre, Tamworth, NSW, Australia.
• 11 Hunter New England Local Health District, Tamworth, NSW, Australia.
• 12 School of Health, University of New England, Armidale, NSW, Australia.
• PMID: 39197158
• DOI: 10.1177/10497323241268776

Stroke affects Aboriginal people at disproportionate rates compared to other populations in Australia. Aboriginal peoples are less likely to receive a timely stroke diagnosis, or timely culturally responsive treatment, as there are very few stroke resources and recovery plans that have been developed by Aboriginal peoples for Aboriginal peoples. Understanding how to develop and implement culturally responsive stroke care requires research approaches that are informed by and with Aboriginal people. A qualitative Indigenous research methodology including "yarning" was undertaken to understand the experiences of both Aboriginal and non-Aboriginal health workers from nine health services providing stroke rehabilitation and recovery support to Aboriginal people living within the participating communities. Data were analyzed using an inductive approach driven by an Indigenous research approach. Yarns revealed three themes: (i) the role of culturally safe health environments to support stroke survivors, their family, and health workers; and how (ii) complicated, under-resourced systems impede the capacity to support stroke survivors; and (iii) collaborative and adaptive practices prevent people "falling through the cracks." This study highlights the need to scrutinize the cultural safety of health care, current health systems, workforce, and culture and how these influence the capacity of health workers to provide care that is responsive to the individual needs of Aboriginal stroke survivors and their families. These learnings will inform the co-design of a culturally responsive stroke recovery care strategy to improve the recovery experience and health and well-being of Aboriginal people and their families living with stroke.

Keywords: Aboriginal and Torres Strait Islander; Aboriginal stroke; Australia; Indigenous research; qualitative research; service providers; stroke; yarning.

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

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• Open access
• Published: 31 August 2024

Experiences, barriers and perspectives of midwifery educators, mentors and students implementing the updated emergency obstetric and newborn care-enhanced pre-service midwifery curriculum in Kenya: a nested qualitative study

• Duncan N. Shikuku 1 , 2 ,
• Sarah Bar-Zeev 3 ,
• Alice Norah Ladur 2 ,
• Helen Allott 2 ,
• Catherine Mwaura 4 ,
• Peter Nandikove 5 ,
• Alphonce Uyara 6 ,
• Edna Tallam 7 ,
• Eunice Ndirangu 8 ,
• Lucy Waweru 9 ,
• Lucy Nyaga 9 ,
• Issak Bashir 10 ,
• Carol Bedwell 2 &
• Charles Ameh 2 , 11 , 12  

BMC Medical Education volume  24 , Article number:  950 ( 2024 ) Cite this article

Metrics details

Introduction

To achieve quality midwifery education, understanding the experiences of midwifery educators and students in implementing a competency-based pre-service curriculum is critical. This study explored the experiences of and barriers to implementing a pre-service curriculum updated with emergency obstetric and newborn care (EmONC) skills by midwifery educators, students and mentors in Kenya.

This was a nested qualitative study within the cluster randomised controlled trial investigating the effectiveness of an EmONC enhanced midwifery curriculum delivered by trained and mentored midwifery educators on the quality of education and student performance in 20 colleges in Kenya. Following the pre-service midwifery curriculum EmONC update, capacity strengthening of educators through training (in both study arms) and additional mentoring of intervention-arm educators was undertaken. Focus group discussions were used to explore the experiences of and barriers to implementing the EmONC-enhanced curriculum by 20 educators and eight mentors. Debrief/feedback sessions with 6–9 students from each of the 20 colleges were conducted and field notes were taken. Data were analysed thematically using Braun and Clarke’s six step criteria.

Themes identified related to experiences were: (i) relevancy of updated EmONC-enhanced curriculum to improve practice, (ii) training and mentoring valued as continuous professional development opportunities for midwifery educators, (iii) effective teaching and learning strategies acquired – peer teaching (teacher-teacher and student-student), simulation/scenario teaching and effective feedback techniques for effective learning and, (iv) effective collaborations between school/academic institution and hospital/clinical staff promoted effective training/learning. Barriers identified were (i) midwifery faculty shortage and heavy workload vs. high student population, (ii) infrastructure gaps in simulation teaching – inadequate space for simulation and lack of equipment inventory audits for replenishment (iii) inadequate clinical support for students due to inadequate clinical sites for experience, ineffective supervision and mentoring support, lack/shortage of clinical mentors and untrained hospital/clinical staff in EmONC and (iv) limited resources to support effective learning.

Findings reveal an overwhelmed midwifery faculty and an urgent demand for students support in clinical settings to acquire EmONC competencies for enhanced practice. For quality midwifery education, adequate resources and regulatory/policy directives are needed in midwifery faculty staffing and development. A continuous professional development specific for educators is needed for effective student teaching and learning of a competency-based pre-service curriculum.

Peer Review reports

Approximately one third of all maternal and neonatal deaths are due to poor quality maternal and newborn care [ 1 ]. Midwifery delivered interventions including skilled attendance at birth, provision of emergency obstetric and newborn care (EmONC) and family planning are central to averting the preventable maternal deaths, newborn deaths and stillbirths [ 2 ]. However, midwifery education and training in low- and middle-income countries is substandard leading to suboptimal quality of care [ 3 ]. The World Health Organization (WHO) recommends that midwifery educators should possess competencies to support theoretical learning, learning in the clinical areas, assessment and evaluation of students and midwifery practice [ 4 ]. The International Confederation of Midwives (ICM) defines assessment as a systematic process for collecting qualitative and quantitative data to measure, evaluate or appraise performance against specified outcomes or competencies. On the other hand, it defines evaluation as the systematic process for collecting qualitative and quantitative data to measure or evaluate the overall provision of and outcomes of a course of studies [ 5 ]. Evidence suggests that midwifery educators are insufficiently prepared for their teaching role [ 4 , 6 ]. The ICM recommends that at least 50% of the midwifery curriculum to be practical-based with opportunities for clinical and community experience [ 5 ]. In many countries, this does not occur. The inadequately prepared midwifery faculty compounded with a deficient curriculum compared to international standards and limited practical clinical experience for students affect the quality of midwifery graduates and subsequent quality of care [ 7 , 8 , 9 , 10 , 11 ]. As a result, midwifery educators are expected to structure their curriculum and develop learning activities that enable midwifery graduates to learn the knowledge and develop skills and behaviours essential for midwifery practice. The acquired competencies promote the role of the midwife to assess, diagnose, act, intervene, consult and refer as necessary, including providing emergency interventions [ 12 ].

The WHO, United Nations Population Fund (UNFPA), United Nations International Children’s Emergency Fund (UNICEF) and ICM recommend that skilled health personnel (includes midwives) as part of a team should be competent to perform all the signal functions of EmONC, to optimize the health and well-being of women and newborns [ 13 ]. Competency as defined in the Global Standards for Midwifery Education by ICM refers to the combined utilisation of personal abilities and attributes, skills and knowledge to effectively perform a job, role, function, task, or duty [ 5 ]. However, evidence shows that midwifery graduates are inadequately prepared with limited support and lack requisite competencies needed to function adequately as skilled health personnel after graduation [ 7 , 8 , 9 , 14 , 15 ]. Thus, midwifery graduates should achieve essential clinical competence – defined as a combination of knowledge, skill, attitude, judgment and ability needed for providing safe and effective care without any need for supervision [ 16 ]. Key barriers leading to suboptimal clinical competence include a deficient and largely didactic curriculum, educators/faculty who are less confident with clinical teaching compared to theoretical classroom teaching, inadequate teaching resources/equipment, insufficient clinical exposure of students for practice, absence of clinical supervisors and mentors and poor relationship with qualified hospital/clinical staff [ 3 , 7 , 8 , 9 , 14 , 15 , 17 , 18 , 19 ].

Emergency obstetric and newborn care training helps improve the knowledge and skills of skilled health personnel, change in clinical practice and improved maternal and newborn health outcomes [ 20 ]. The Kenya national Ministry of Health (MoH) included EmONC training for skilled health personnel in the National Health Policy 2014–2030 and Health Sector Strategic Plan 2018–2023 as a priority to improve the quality of maternity care and subsequent maternal and newborn health outcomes [ 21 , 22 ]. Introducing the training at pre-service with a supporting curriculum has the potential for greater returns on midwifery investments [ 23 ]. Funded by Foreign, Commonwealth and Development Office, Liverpool School of Tropical Medicine supported the Kenya MoH through the Nursing Council of Kenya and Kenya Medical Training College to conduct a detailed review of their national training syllabi and curriculum respectively. Curriculum content integrating EmONC and teaching methods were updated [ 24 ] aligned to the WHO and ICM competencies for midwifery practitioners and educators. This approach was designed to shift from the largely theoretical training to a competency-based skills training for graduates. This was followed by a bundle of interventions to build/strengthen the capacity of the training institutions and midwifery educators. The programme equipped the training colleges’ skills laboratories with EmONC training equipment. Blended (virtual and face-to-face) learning workshops for educators focusing on teaching (theory and practical/clinical EmONC skills), students’ assessments and giving effective feedback were conducted to improve their capacity to deliver the updated EmONC-enhanced curriculum. Supportive follow-up mentoring of midwifery educators in sampled colleges was implemented to build their professional skills in teaching, assessments and effective feedback. This bundle of interventions was evaluated and demonstrated improved educators’ knowledge, skills and confidence in teaching and EmONC skills [ 24 , 25 ]. Consequently, midwifery students’ knowledge and skills in EmONC improved before graduation [ 26 ]. Although the investments were promising, understanding experiences of educators and students is critical for a successful and sustainable implementation of the pre-service competency-based curriculum, scale up and uptake of the bundle of interventions.

Previous studies largely evaluated the changes in knowledge, skills and confidence of educators and students after programme training interventions [ 24 , 25 , 27 , 28 ]. However, studies focusing on experiences of the target group (either the educators or student group only) after midwifery educator capacity strengthening interventions are limited [ 29 , 30 , 31 , 32 ]. Experiences of students and educators enable midwifery educators to improve the design of the courses and support systems in place for effective teaching and learning [ 18 , 33 ]. Exploring students’ experiences is critical in determining what students find important and promoting their learning process [ 32 , 34 ]. This is relevant in designing training programmes that facilitate students’ learning and application of acquired competencies into practice.

This was a nested qualitative study within the broader cluster randomised controlled trial that assessed the effectiveness of a pre-service EmONC-enhanced midwifery curriculum delivered by trained and mentored midwifery educators in Kenya [ 35 ]. The objectives of this study were to explore the experiences, barriers and understand the perspectives of educators, students, and external mentors for educators to successfully implement an updated EmONC-enhanced curriculum during pre-service training. Findings are relevant to improve the design, delivery, uptake and scale-up of the pre-service midwifery programme for competent midwifery graduates as part of accelerating progress towards achieving maternal and newborn health sustainable development goals and universal health coverage.

Study design

This was a qualitative descriptive study using focussed group discussions (FGDs) and field notes nested within a cluster randomised controlled trial reported in a separate paper [ 35 ]. Qualitative descriptive studies generate data that describe the ‘who, what, and where of events or experiences’ from a subjective perspective [ 36 ]. Qualitative studies in trials are important in interpretation of trial findings and enhances the understanding of how contextual barriers and facilitators may influence outcomes [ 37 , 38 ]. Insights from qualitative studies can also inform implementation if the intervention is successful. This is because they can help trialists ‘to be sensitive to the human beings who participate in trials’ [ 38 ]. The objective was to understand the experiences of educators, students and mentors, challenges encountered and opportunities for improving the delivery and implementation of the updated EmONC-enhanced midwifery curriculum in Kenya.

The Kirkpatrick model is an effective tool with four levels for evaluating training programmes [ 39 ]. Level 1 (Participants’ reaction to the programme experience) helps to understand how satisfying, engaging and relevant participants find the experience. Level 2 (Learning) measures the changes in knowledge, skills and confidence after training. Level 3 (Behaviour) measures the degree to which participants apply what they learned during training when they are back on job or impact of training to their practice. This level is critical as it can also reveal where participants might need help to successfully implement what was learned. Level 4 (Results) measures the degree to which targeted outcomes occur because of training. The findings from this study are further analysed using the Kirkpatrick model at level 1 (experiences of educators and students) and level 3 (application of what was learned and areas for further support and investment) to improve the quality of pre-service midwifery education and training.

The focus group discussions explored the experiences of educators with the updated content, clinical teaching and skills demonstration, peer teaching and support, clinical supervision and mentoring of students, and effective feedback. Also, institutional challenges/bottlenecks and support required to implementing the updated curriculum. Students feedback on the teaching of the updated curriculum, clinical placements, clinical support supervision and mentoring during placements was documented. Mentors’ experiences and perspectives on the uptake of mentorship intervention by educators were explored. Additional components from mentors included strengths observed during the mentorship intervention (educators and institutional); bottlenecks experienced in the mentoring intervention and opportunities for support and improvement. The study is reported in accordance with the COnsolidated criteria for REporting Qualitative research (COREQ) (Supplementary Material) [ 40 ].

Study setting

This study was conducted in 20 (12 intervention arm and 8 control arm colleges) of the 52 KMTCs randomly selected in Kenya offering the integrated nursing and midwifery training programme in Kenya (Kenya Registered Community Health Nursing – KRCHN programme). This is the predominant direct entry programme offered at diploma level for nursing and midwifery workforce in the country. Each KMTC has two intakes of 50 students each per year (March and September), thus approximately 50 final year nursing and midwifery students are expected to graduate per intake. The duration of the diploma programme is three years with no internship period after graduation. Midwifery content and clinical placements are distributed across the three years of training. Students are posted to the respective hospitals (offering comprehensive EmONC services) attached to the training colleges for their clinical placements for practice and clinical experience. This is critical to reinforce theoretical learning, develop their clinical skills and attitudes for practice. A common curriculum by KMTC approved by the Nursing Council of Kenya is used for midwifery education in all colleges.

Intervention

Liverpool School of Tropical Medicine supported the review and update of the predominant nursing and midwifery training curriculum for training of nurse midwives at diploma level in Kenya in 2020/2021. The curriculum review and update were conducted by selected midwifery educators and practitioners. The output was a pre-service curriculum with EmONC content. Following the review, midwifery educators from both study arms (intervention and control) received training on the new content to strengthen their capacity to deliver the EmONC-enhanced curriculum. Training used Liverpool School of Tropical Medicine’s adapted Emergency Obstetric Care and Newborn Care Skilled Health Personnel training package [ 41 ]. This package has been used by LSTM in collaboration with MoH in over 15 low- and middle- income countries to strengthen the capacity of maternity care providers for quality EmONC service delivery [ 42 ]. Educators in the intervention study arm received additional mentoring and peer support on teaching and EmONC skills every three months for 12 months.

Mentoring support intervention

This was conducted every three months after the training for 12 months in the intervention colleges. A group of eight experienced EmONC faculty consisting of midwifery educators and obstetricians were recruited and trained as mentors. Educators were from university or midwifery training colleges not included in the study and they did not form part of the master trainers. They received a virtual one-day mentorship training facilitated by the corresponding author and an LSTM – UK senior MNH specialist experienced in EmONC capacity strengthening and pedagogy. Training focused on introduction to mentoring, building effective working relationships, giving effective feedback, handling difficult situations during mentorship, and teaching methods. The training used interactive lectures, discussions, and case studies. Mentorship sessions were a full day intervention per college for educators and focused on teaching skills, EmONC skills and drills and giving effective feedback to promote learning among students especially on performance of critical lifesaving EmONC skills or scenarios.

Structured participant observation of teaching sessions (theoretical or practical) and support by mentors for midwifery educators were also conducted in the intervention study arm at 3, 9 and 12 months after the training. Key elements of good quality teaching and learning were observed including: [ 1 ] teaching style, [ 2 ] use of visual aids, [ 3 ] teaching environment and [ 4 ] student involvement using a standardized observation checklist [ 43 ].

LSTM’s lead researcher (corresponding author) based in Nairobi Kenya conducted quality assurance visits to some of the mentoring sessions for all mentors. At the end of the mentoring visit, debrief sessions were held by the mentor, mentees, and the campus administration as necessary. The debrief provided feedback and areas that needed institutional support to promote quality teaching and learning. On occasions where the lead researcher was not present at the mentoring visit, the mentor recorded and shared field notes on key strengths observed, areas for further support and the action points proposed by the mentees for development.

Participants

A convenience sampling approach was used to select participants that were already enrolled in the trial to take part in the FGDs. Twelve [ 12 ] intervention arm educators, eight [ 8 ] control arm educators and eight [ 8 ] mentors participated in the FGDs. Each training college was represented by one midwifery educator.

A total sample of 146 final year nursing-midwifery students (KRCHN March 2020 class), the first group to be taught the updated EmONC-enhanced curriculum participated in the study. Due to the variability in the number of students per college, 20 clusters of 6–9 students, selected through stratified systematic sampling who participated in the knowledge and skills assessments participated in the debrief sessions.

Data collection

Three virtual FGDs were conducted at six months of the implementation (February 2022) with the intervention and control colleges’ educators and mentors by the corresponding author using semi-structured interview guides. The adapted interview topic guides were piloted and validated in a previous study [ 28 ]. These guides were also reviewed by study team members with experience in qualitative research. Each FGD lasted between 60 and 90 min. Respondent/member validation/check was routinely applied during the interview discussions to ensure that participants’ responses were accurately interpreted [ 44 ]. The FGDs were audio-recorded with permission from participants and transcribed verbatim in English. New emerging data from educators and mentors was routinely collected during the study implementation period. This strategy was employed due to the information power from a sample of participants but with rich relevant information for the study in qualitative research [ 45 ]. Although the corresponding author was not a faculty member with the KMTC, his status was known to the participants.

Two debriefing sessions moderated by the corresponding author and two independent assessors per college were held with students immediately after completing the knowledge and skills assessments between December 2022 and March 2023. The independent assessors were midwives and obstetricians working as midwifery educators in public or private training institutions and/or in clinicals and experienced EmONC faculty. They worked in pairs per college and were blinded to the intervention implemented and study arms. Details on the assessments are reported in a different paper [ 35 ]. In the first debrief, lasting between 30 and 60 min, were conducted immediately after the assessments by the corresponding author and the two assessors with the students for every college. These were confidential and not recorded to allow students express themselves freely on their experiences with the completed assessments, curriculum content covered, clinical placements and support received during maternity clinical placements. The second debrief lasted between 15 and 30 min and included the available institutional midwifery faculty/administration, students and the research team. Field notes were taken during the students debrief sessions by the corresponding author. Due to the potentially sensitive nature of the students’ feedback in the first debrief, general findings were shared with the college midwifery faculty and administration during the second debrief. Areas of strengths, opportunities and weak sections that needed additional support for improvement were highlighted.

Data management and analysis

Preparation for data analysis involved a rigorous process of transcription of recorded FGDs. Data analysis was led by the lead researcher, but the other authors contributed by reviewing the transcripts and quality checks. Collaborative thematic framework analysis by Braun and Clarke (2006) was used as it provides clear steps to follow, is flexible and uses a very structured process and enables transparency and team working [ 44 ]. Due to the small number of transcripts, computer assisted coding in Microsoft Word using the margin and comments tool was applied for the FGD transcripts and manual coding of text for the field notes. The six steps by Braun and Clarke in thematic analysis were conducted: (i) familiarising oneself with the data – the lead researcher listened to all of the audio recordings while reviewing the transcripts, looking for recurring issues/inconsistencies and, identifying possible categories and sub-categories of data; (ii) generating initial codes – both deductive (using topic guides/research questions) and inductive coding (recurrent views, phrases, patterns from the data) were conducted to derive the codes and enhance transparency of the study. The lead researcher generated a comprehensive list of codes. A second author with expertise in qualitative research separately analysed a selection of transcripts and then compared codes, agreed codes and broad themes; (iii) searching for themes by collating initial codes into potential sub-themes/themes; each transcript was reviewed to refine sub-themes/themes and an exhaustive list of sub-themes/themes was generated (iv) reviewing themes by generating a thematic map (code book) of the analysis; data were mapped to identify prevalence (new and old) of themes; again, two authors compared and validated the interpretations using one transcript (v) defining and naming themes through repeated, systematic and collaborative analysis of transcripts (ongoing analysis to refine the specifics of each sub-theme/theme, and the overall story the analysis tells); and (vi) writing findings/producing a report – findings were written up as descriptive accounts with illustrative quotes from the transcripts. Trustworthiness was achieved by (i) respondent validation/check during the interviews for accurate data interpretation; (ii) using a criterion for thematic analysis; (iii) returning to the data repeatedly to check for accuracy in interpretation; (iv) quality checks and discussions with the study team with expertise in mixed methods research [ 44 , 46 ].

Reflexivity

Due to the sensitive nature of the feedback from educators, students and mentors, the lead researcher had good awareness of who and where to address the emerging concerns from the study. These concerns together with programme achievements, challenges and best practices were disseminated to the KMTC management during the joint LSTM – MoH programme knowledge, management and learning dissemination events and policy forums. There was real benefit in the lead researcher being a near-peer to the participants as he was a male midwife educated and trained in Kenya and Uganda and an Associate Fellow of the Higher Education Academy, United Kingdom. He could relate to certain aspects of the educators and students’ experience of skills teaching and clinical placement as he had previous experience both as a midwifery student and adjunct faculty in the two countries. This also helped him to ask for points of clarification about certain aspects of the midwifery academic experience, educator and student experience, particularly around clinical skills teaching, organisation of clinical placements and midwifery support during the clinical placements. In addition, this allowed him sufficient distance to ask questions and not take the discussion contents personally. Use of multiple methods of data collection (knowledge surveys, direct observations through objective structured clinical evaluation of skills and debriefing after students assessments/field notes) enhanced triangulation of findings to give detailed descriptions and broad perspectives important in understanding the implementation of the updated EmONC-enhanced curriculum [ 46 ].

Eight of the 14 research team members who participated designing the study, data collection and data analysis were midwifery and obstetric faculty staff, with only two being from KMTC. They reflected that they found some comments about the educators and students experiences with clinical teaching and support supervision troubling as they held teaching roles in their respective training institutions.

Demographic characteristics of participants

All 20 midwifery educators were nurse-midwives by profession with majority ( n  = 12, 60%) being holders of a bachelor’s degree and aged 40–49 years ( n  = 9, 45%) and half of the midwifery educators being male ( n  = 10, 50%). Majority of mentors were males ( n  = 7, 87.5%), holders of master’s degrees ( n  = 5, 62.5%) and aged 40–49 years ( n  = 4, 50%). Equal number of mentors were either obstetricians ( n  = 4, 50%) or midwives ( n  = 4, 50%) (Table  1 ).

Experiences of educators, mentors and students on the implementation of the updated curriculum

The experiences from educators, external mentors and students are presented and organized into four broad themes: (1) relevancy of updated EmONC-enhanced curriculum to enhance practice, (2) continuous professional development opportunities for midwifery educators, (3) effective teaching and learning strategies and, (4) effective collaboration between school and hospital staff for effective training.

Relevancy of the updated EmONC-enhanced curriculum to enhance practice

Experiences on the EmONC content in the curriculum revealed three major sub-themes: (i) positive reactions to the EmONC content, (ii) demand for EmONC training and, (iii) approaches and time constraints in delivery of the content.

Positive reaction to EmONC content

Integrating EmONC within the pre-service midwifery curriculum was acknowledged as important and relevant to potentially improve the quality of midwifery care. Educators found the content useful and integrated it within their classroom and clinical teaching. Educators also reinforced the importance to introduce students to the EmONC-enhanced curriculum so that when they complete their training programme, they have the know-how and confidence to deal with obstetric emergencies.

“During the clinicals they have been able to apply the skills they have been taught. The EmONC has been of great help, they don’t panic when they see an emergency. They are able to attend to clients with confidence, even when they are alone. When the other qualified staff is not available or maybe they have a shortage, they are able to support care and not just be spectators.” Educator, intervention colleges FGD.

Mentors recounted that students loved to participate actively in skills demonstrations as it helped in mastery of skills and application of learned theory. Students recollected that skills demonstrations were conducted in the classroom/skills lab before their clinical placements. This was useful as they could link theory to practice and apply the learned skill when in the clinical placements. They found the EmONC content relevant in the maternity ward placements when they experienced complicated maternal cases that required specific EmONC care. The classroom knowledge and skills demonstrations in EmONC built their confidence in anticipating, detecting and handling obstetric emergencies.

“And my students are appreciating it. It is very important for these people to have this knowledge and they usually tell me they have not gotten any experience as good as the one that is being introduced by the EmONC” Educator, control colleges FGD. “They were feedback reports of students in clinical placement in various areas…. One of the students was able to use one of the skills of manual removal of a placenta. I did not believe that with the training they would have such confidence.” Mentor, FGD.

Demand for pre-service EmONC training

Reports from both intervention and control colleges showed that there was demand for EmONC training from students in upper classes who had completed the midwifery theory and clinical placements without the practical EmONC skills training. This was to build their skills and confidence in handling emergency obstetric cases before exiting the training programmes.

“And we were able to go through it, it was really intense. We were able to go through it with the teachers themselves, the lecturers and then with the students. And I think after that the word went around, the students started demanding that they also be taken through the skills” Educator, intervention colleges FGD.

Approaches and time constraints to deliver EmONC skills

Major approaches used to deliver EmONC within the updated curriculum were either as a blocked 5-day training during an ‘EmONC week’ (only by two colleges, one from each study arm) or specific skills taught within the topic lesson plans in the classroom/skills lab. Although EmONC content was taught in classroom/skills labs, time was cited by educators from both study arms as a key challenge in delivering the content effectively. This was largely due to the reduced time from the initial 3.5 year-nursing and midwifery curriculum to 3 years. As a result, each college had to design their teaching activities to accommodate the EmONC skills within the available limited curriculum time – either as a blocked course for five days or specific skills demonstrated within the topics taught. In addition, staffing levels within institutions in both study arms was a critical factor in the adopted approach to deliver the EmONC content.

“The curriculum is very comprehensive in terms of the EmONC training. But at the same time, we have reduced the number of years in that the curriculum is currently three years, instead of the three and a half. That time is too little to teach the theory sessions and then have the practical skills demonstrations, but we try to combine it during the teaching sessions. I find that it is a bit inadequate.” Educator, control colleges FGD.

Team teaching was identified as a potential solution used in two institutions to deliver blocked EmONC training during the EmONC weeks. The team-teaching included faculty from nursing and midwifery, clinical medicine (reproductive health) and integrated with a few hospital staff.

Students identified that skills demonstrations were often provided in the classroom/skills lab but they had limited opportunities for repeated return demonstrations. This they claimed was due to the inadequate time for the skills demonstrations in the classroom. Hence, practical learning was expected to take place during their clinical placements or at their own time in the skills labs. During the OSCE assessments, gaps were identified in student’s ability to identify, set up or use the right equipment for skills practice.

Continuous professional development opportunities for midwifery educators

Educators from both study arms acknowledged the training on EmONC and teaching techniques as a capacity strengthening and professional development opportunity. They found the training important as it built/strengthened their skills and confidence in applying different interactive teaching techniques for theory and skills to promote learning and helped educators in lesson planning.

“I feel more confident teaching alongside my colleague in terms of teaching midwifery skills through the demonstrations and both in the skills lab and follow up in the clinical area.” Educator, control colleges FGD.

There were initial fears and anxiety on the role and conduct of mentorship intervention among educators. Mentors reported that some educators initially were reluctant of the initiative as they thought it was a supervisory, assessment or audit visit for fault finding.

“They (educators) thought that it (mentorship) was more of supervision than support. They thought it was an assessment” Mentor, FGD.

Despite the initial anxiety and fears about the role of mentorship intervention, the mentoring support in the intervention colleges was greatly accepted and welcomed after understanding the goals and the implementation strategy by the mentors. Educators and mentors also acknowledged the administrative and logistical support received from the institutional managers to participate in the mentorship programme. Educators were enthusiastic and reported the mentoring intervention as supportive, encouraging and was greatly appraised for building the confidence of the educators particularly in EmONC skills teaching/demonstrations to students.

“And us as the lecturers it has really boosted our confidence in terms of our skills lab sessions…We had not been very confident in our skills lab sessions.” Educator, intervention colleges FGD.

Educators and students liked the use of external mentors drawn from other institutions with different expertise and experiences in midwifery and obstetrics during the lessons. Intervention stimulated and encouraged consultations and updates for capacity strengthening in midwifery, obstetrics and gynecology through the interactive mentoring sessions. Mentors complemented the educators during the teaching sessions of the updated curriculum in both theory and skills demonstrations. Students were also encouraged and actively participated in the teaching sessions as they could ask questions and receive feedback on topical concerns. Improved teaching techniques were effective in promoting confidence and learning among both educators and students.

“We have been able to learn a lot. It is through that mentor support that we have been updated about the resuscitation of the newborn, the current practices, .… shoulder dystocia, the best way to teach the skills….mentor demonstrated and updated us on the content like magnesium sulphate use and management of eclampsia and pre-eclampsia. We were able to be updated and shown how to train the student on the same.” Educator, intervention colleges FGD.

Although educators were flexible in planning and scheduling the mentoring visits, mentors expressed challenges with time constraints in some colleges in scheduling and completing the mentoring activities. This was largely due to the shortage of faculty and competing school activities involving examinations, students’ follow-up, and other administrative/management responsibilities.

Mentors identified that educators were more knowledgeable in theory compared to skills teaching and thus the need for regular hands-on refresher trainings to improve their skills teaching capacity. To promote the mentoring programme, the mentors and educators formed a WhatsApp community of practice group where resources including current guidelines, policies, updates, relevant literature and books could be shared. This platform promoted peer to peer support and sharing of best practices.

Effective teaching strategies

Participants mentioned effective strategies which aided their teaching and learning experiences presented as sub themes below.

Peer teaching and support/team teaching effective for learning

Peer teaching and support emerged as a key solution to complement the strengths and weaknesses of the educators and students. This included teacher – teacher, teacher – hospital staff, or student – student as below.

Teacher peer teaching and support

Educators highlighted the value in peer teaching and support although this was practiced in a few colleges. This included teacher-to-teacher or teacher-to-hospital midwife for theoretical or clinical skills teaching. Occasionally, midwifery educators collaborated and conducted team teaching of skills with the clinical medicine faculty. It improved interaction and mentoring for colleagues. This was largely in the skills teaching although was also observed and applied in some theoretical sessions. For those who had an opportunity to practice, they commended the approach as an opportunity for them to complement their strengths and weaknesses in skills teaching. In addition, this provided an avenue for them to receive supportive feedback from colleagues to improve their teaching skills.

“And us as the lecturers it has really boosted our confidence… It really built our confidence and now when we go through our peer-to-peer teaching, if one of us is not confident in a particular skill we even go through it ourselves first, we correct each other, we improve each other, and I think that is something unique and we appreciate.” Educator, intervention colleges FGD. “I was very impressed when I found that they had called in one midwife staff from the labour ward, to come and help them demonstrate (EmONC skill). We agree it was a resource that they could tap on… they need to do that practice with the staff and other competent people in the clinical area before teaching.” Mentor, FGD.

Educators reported that they consulted with one another on emerging updates on specific topics before teaching. Where resources allowed, educators combined with hospital staff to jointly deliver specific EmONC skills to students. This promoted peer support and was beneficial in ensuring that the classroom teaching resonated with the clinical practice.

Student facilitators for peer teaching and support

Educators in a few colleges used students to facilitate teaching to their fellow students particularly in EmONC skills. Those identified as student facilitators were either (i) those pursuing advanced diploma qualification in midwifery (ii) senior students in a similar nursing and midwifery programme or (iii) more competent student peers from the same class. Coaching of student facilitators by educators was also acknowledged to strengthen their confidence and competence. Student facilitators also provided personalised support for their peers with specific weaknesses in skills during/after practical teaching sessions. Educators found this approach beneficial as it encouraged active interaction and engagement between learners and promoted learning. Educators observed that students learnt faster from their colleagues as it also motivated the weaker students to strive to achieve similar competencies as their peers. In one of the intervention colleges, student facilitators were integrated in the hospital team to participate by facilitating some EmONC skills sessions to the qualified maternity staff during their weekly continuous professional development activities in the hospital.

“The students are divided into groups with each lecturer so that the lecturer demonstrates, and the students give the return demonstrations, and we ensure that everyone is hands-on. And as we are with the students, we pick those good students who have managed to master the skills very well and encourage them to mentor the other students.” Educator, intervention colleges FGD. “You see, for the students, they will learn better from one another, rather than me. I think that is proven. When you learn from someone who is almost a peer, you are able to understand better. Sometimes a lecturer will be using a language, they may see as if a language is difficult for them. But when they extend the content among one another, they are able to understand it better.” Educator, control colleges FGD. “On this peer teaching, when we have an EmONC demonstration, when we have one lecturer doing a demonstration, we invite others (lecturers) to participate. Normally we use the senior students who have done that content and have already been assessed. We request them to help the other students and mentor them and supervise.” Educator, control colleges FGD.

Participatory teaching methods

Educators and students commended the use of active and participatory teaching techniques to enhance learning. Consequently, mentors observed that mentorship improved the teaching practices of the educators including use of audio-visuals in teaching to promote learning. These included skills demonstrations with return demonstrations, use of small groups discussions for assignments and skills teaching and overall engagement/interaction with learners during teaching sessions. Educators expressed increased confidence and competence in leading EmONC skills teaching. They also integrated videos in the teaching of EmONC skills. However, mentors reported that use of scenarios and facilitating clinical teaching for students was irregularly practiced by the educators. Low confidence of educators in select skills was highlighted as a barrier contributing to low uptake of some of the effective interactive teaching techniques.

“After we taught (classroom), we went to the skills lab where we demonstrated with the students where I think we got the feedback from the students and they really appreciated those sessions.” Educator, intervention colleges FGD.

It was also observed by mentors that in some colleges, educators trained in EmONC only participated in theoretical teaching but not practical skills teaching. This was because some specific courses/lessons, for instance, obstetric emergencies, were assigned to a specific educator. Others recounted that the training received was short/inadequate and needed more refresher trainings to build more confidence.

“The biggest gap there is the fact that the lecturers trained are not teaching the practical part of it. Some were trained but they were not teaching. And there was only one teaching abnormal delivery, who was given all the tasks of demonstrating the skills. And I found that to be a challenge to keep up with the curriculum” Mentor, FGD.

Although there was remarkable improvement in skills teaching, mentors observed that the large number of students was a barrier to effective skills teaching with return demonstrations.

Feedback for effective learning

Effective feedback in teaching and learning was also highlighted. Educators from both study arms reported that feedback after clinical skills assessments was provided to improve the students. Observations during the students’ feedback sessions provided strong sentiments both critical of and appreciating the quality of the teachings and support students receive from their teachers. Some students acknowledged the constructive feedback received from educators with clear corrective measures to promote learning. However, some expressed fears that some educators provided feedback that was inappropriate, untimely and ineffective for learning and development. For some, they felt the feedback received was demeaning, disrespectful and discouraging for learning and received in an inappropriate environment.

“For the effective feedback to the students, we usually give the feedback as they demonstrate as we support them. We also have OSCE of the clinical areas and after that assessment we give marks, then we are also able to give the feedback to the students and the shortcomings of the students” Educator, control colleges FGD.

Educators integrated online platforms for receiving anonymous feedback on teaching sessions. However, this was sparsely used by educators from both study arms.

“… we have frequent interaction with the students, generally, in all lessons, they give feedback online, because now we have the Google platform where we can quickly get surveys and get feedback from the students.” Educator, intervention colleges FGD.

Effective collaboration between school and hospital staffs for effective training

Collaboration between colleges and hospitals emerged as an important theme that promoted effective learning. This included collaboration between educators and hospital midwives to jointly support and mentor students in their clinical placements and co-facilitating EmONC skills teaching (due to faculty shortage, deficiencies in some skills and to align theoretical classroom teaching with clinical teaching and practice). Other collaborations included support with hospital equipment for skills training where appropriate and co-assessment of students in their clinical placements. Educators emphasized the need for strong collaborations between the training institutions and hospitals for the benefit of the students.

“When we are doing the skills lab, for our students, during the skills lab time, sometimes we invite the midwives from the clinical area to help us demonstrate the skills. And we feel this is important for the students to have a contact with the clinical midwives so that when they get to the clinical area, they are already familiar with each other, and this improves on their confidence, and they appreciate.” Educator, intervention colleges FGD. “At the clinical area, there is also a day that we go through the EmONC skills together using mannequins.…We usually involve everyone – the midwives, the medical officers, the clinical officers and also to appreciate the teamwork in managing the mothers and the neonates….” Educator, intervention colleges FGD. “I was very impressed when I found that they had called in one midwife staff from the labour ward, to come and help them demonstrate (EmONC skill). We agree it was a resource that they could tap on… they need to do that practice with the staff and other competent people in the clinical area before teaching.” Mentor, FGD.

Challenges in implementing the updated pre-service midwifery curriculum

Challenges in implementing the EmONC-enhanced curriculum in pre-service institutions are presented in four themes below: (1) midwifery faculty shortage and workload, (2) infrastructure gaps in simulation teaching, (3) inadequate clinical support for students and, (4) limited resources to support effective learning.

Midwifery faculty shortage and workload

The ICM defines a midwifery faculty as a group of qualified individuals who teach students in a midwifery programme. This includes the following: midwife teachers; experts from other disciplines; and clinical preceptors/teachers [ 5 ]. Midwifery educators from both study arms reported an acute shortage of qualified nursing and midwifery educators to support the midwifery training programme. This shortage was attributed to the large number of nursing and midwifery students in the programme, heavy nursing and midwifery content to be covered, multiple academic activities including teaching, support supervision/mentoring of students, conducting theoretical and clinical assessments and other non-academic administrative roles. Due to the heavy workload, educators indicated that participating in effective teaching for skills and supervision/mentoring of students in the clinical areas during their clinical placements for experience and learning was a challenge. Shortage of midwifery faculty was also highlighted as a key challenge in the uptake of peer teaching and support among educators due to competing priorities and workload. To mitigate the shortage of qualified midwifery educators, institutions relied on hospital nurses and midwives to provide support to students during their clinical placements.

“Having only four lecturers from KMTC is a really big challenge. Out of those four lecturers, one is the head of department and the other is a deputy principal….So we manage to do only one students’ follow-up in a placement of maternity” Educator, intervention colleges FGD. “Now when we come to the EmONC skills demonstrations, it has been mandatory that we must take the students to the skills lab and include it as well in teaching. But unfortunately, with demonstrations, we cannot do a complete full EMOC because of the shortage of the staff trained to do the same.” Educator, control colleges FGD.

Mentors also emphasized the need for professional development for all midwifery faculty in the institutions. This was attributed to the fact that fewer educators were confident to conduct EmONC skills teaching effectively and no clinical mentors/preceptors specifically assigned to support clinical teaching and learning of students while in their clinical placements. For institutions that offer advanced diploma training for midwives, educators reported that students pursuing the advanced diploma midwifery programmes were requested to support with clinical skills teaching and demonstrations.

Due to the shortage of educators and competing institutional activities, mentors observed that occasionally, it was difficult to have a whole group of midwifery educators participating in the mentorship programme on the intervention day within the institution. Mentors and educators also reflected that the acute shortage of midwifery faculty negatively influenced the quality of training and education including teaching, support in clinical placements for skills acquisition and assessments.

“And also we are few, it is overwhelming when we have to do the EmONC activities and the other teaching activities and the other college activities.” Educator, control colleges FGD.

Infrastructure gaps in simulation teaching

All colleges reported availability of EmONC training equipment although some could benefit from replenishment or repairs. For most colleges, they reported effective collaboration with the hospitals’ staff for support in skills teaching when required. However, there were challenges with the availability of skills labs/classrooms, inadequate space in the skills lab for skills teaching/demonstrations and storage of equipment, worn out equipment that needed replenishment/repairs or lack of consumables. There were also gaps in skills lab equipment inventory with sporadic/infrequent monitoring of equipment availability and functionality through dedicated audits. To mitigate against the inadequate/lack of skills labs, some colleges modified teaching classrooms to act as skills labs for skills demonstrations during teaching sessions while others modified the multi-purpose halls for skills demonstrations with students.

A common feature across all the colleges was that the skills labs were not freely accessible to students for skills practice because of (i) lack of dedicated skills lab technicians (ii) overwhelmed educators participating in teaching, assessments, students’ follow-up during clinical placements and other administrative roles, (iii) inadequate time for skills teaching and practice and (iii) security of the equipment in the skills lab.

“The challenge we have is infrastructure. We have a small skills lab…We organise our classes where we teach, we organise the sessions there and the equipment and we are able to teach them well” Educator, intervention college FGD. “At the same time, when you are teaching this skill, the time is so limited. The students cannot practice enough, and you can’t leave the students in the skills lab on their own, because of the security and safety of our equipment. So they need somebody to be there all the time maybe to demonstrate and do a return demonstration…Because you have other activities to attend to. Maybe you have another class or you need to be somewhere else. So it becomes a challenge because these students want to engage and you are involved in other activities” Educator, control colleges FGD.

Skills lab personnel for safe keeping and maintenance of training equipment, support skills lab functionality and students for skills demonstrations were sparsely available across the study colleges. Although the skills labs were almost adequately equipped with training equipment in all colleges, mentors also identified that educators were often unfamiliar with how to utilise some equipment in the skills labs. This was highlighted to contribute to low skills lab utilisation for skills teaching and demonstrations.

“The lecturer is there though they do not visit the skills lab frequently. Some of the lecturers don’t know what is in the skills lab such as the EmONC kit and where to find it and how to use them (equipment).” Mentor, FGD.

Inadequate clinical support for students

Across the two study arms, students experienced inadequate support during their clinical placements. Most times, students reported that they largely participated by observing provision of emergency obstetric care services and rarely were they involved in the care. Educators confirmed that feedback from students showed that there was a variation or conflicting information from the classroom teaching and the hospital practices in some health facilities. Four main sub-themes under the theme were: (i) inadequate hospitals for clinical experience, (ii) hospital staff trained on EmONC, (iii) ineffective supervision and mentoring support for students and (iv) no clinical mentors to support clinical teaching and learning.

Inadequate comprehensive EmONC hospitals for clinical experience

High numbers of students and training schools (nursing/medical and clinical medicine programmes) vs. inadequate high volume/comprehensive EmONC health facilities for clinical experience and learning was highlighted as a major challenge. As a result, alternative options of hospitals away from the training region or lower level/basic EmONC health facilities were integrated and formed part of the clinical placement sites for students. Congestion of different cadre of students in clinical placements was a key factor that inhibited effective learning. At the basic EmONC health facilities, students commented that most of the time, they completed their placements without experiencing and/or participating in the management of some obstetric cases like obstructed labour, shoulder dystocia, breech presentation and newborn resuscitation in birth asphyxia. It was also observed that some students completed their clinical placements without having clinical placements and participating in care of obstetric emergencies in a comprehensive EmONC hospital.

Untrained hospital staff in EmONC

In some hospitals, educators enthused about the availability of EmONC-trained midwives who supported students while in their clinical placements. This promoted harmony between the classroom teaching and clinical practice which enhanced positive student learning and experience.

“In fact, when we go for clinical supervision, we find that they are being taken through the skills, they speak in one language which is a real advantage to us and I think the challenge comes when we start taking our students out of this hospital then the supervision becomes challenging.” Educator, intervention colleges FGD. “Clinical supervision, we are lucky, all the midwives in labour ward are trained in EmONC and help to train our students. Our students are giving us positive feedback when it comes to EmONC” Educator, control colleges FGD.

However, outdated clinical practices were also observed and learned by students in clinical placements in some training hospitals they were attached to. This was attributed to lack of/irregular training or professional development opportunities on EmONC for healthcare workers working in maternity.

“When the students have given us feedback about the clinical area, they have been giving us very negative feedback about the clinical practices which are going on…We had realised the staff had not been updated about the EmONC, all of them and the county nurse was notified and she has given me a feedback that they are planning to put a nurse there who has done the training, the on-job training. Also, they are planning in the next financial year to include the EmONC training to at least update the midwives working in the maternity area.” Educator, intervention colleges FGD.

Ineffective supervision and mentoring support for students

Feedback from educators and students revealed sporadic supervision visits by educators with no standard schedule for students support in most colleges, inefficient/lack of mentoring support in clinical placements by educators and hospital staff, untrained hospital staff providing clinical support. Students revealed that most visits by educators were only conducted towards the end of the clinical placement to prepare students for their clinical placement assessments. Locally developed institutional specific monitoring forms/tools for supervisory visits to be completed by the students and the visiting educator were available in only two of the 20 participating colleges. Most times, students were pessimistic about clinical teaching and learning as they expressed that their educators only visited and enquired about their general welfare including accommodation and upkeep while out of college for their clinical placements. Also, students rarely had opportunities to express challenges they experienced in their clinical placements including clinical teaching. Surprise findings included educators not involved in teaching midwifery also participating in the supervisory visits. The FGDs revealed that some ineligible and clinically inexperienced educators participated in the clinical supervisory visits for financial gains. Some educators also acknowledged that they lacked the clinical experience to provide mentoring support to the students.

“So, as I say the specific mentoring within the clinical placement might not be very much applicable in our setups because of the workload. So, we rely on the staff that are within the hospital to do the mentoring, us what we do is basically clinical supervision and mentoring, but it will not be as comprehensive as it would be if we had a specific mentor within the hospital centre.” Intervention college FGD. “Okay the only challenge I would say is when it comes to the clinical supervision outside the (college training hospital). I don’t know why people are seeing money instead of teaching. You find that people are not qualified or trained in EmONC in midwifery teaching, but they want to make a follow-up.” Intervention college FGD.

No clinical mentors to support clinical teaching and learning

Availability/lack of clinical mentors to support students during their clinical placements was highlighted by both educators and students. There were no dedicated clinical mentors employed by the colleges to support students while on clinical placements. Instead, colleges relied on hospital staff who had other primary duties in the clinical departments to provide mentoring support to students. Students and educators reiterated that for cases where they had a hospital staff assigned as a mentor, this was a secondary role that depended on the ward/unit activities.

“We have a big challenge when it comes to mentoring because we don’t have full-fledged mentors who are specifically handling students. What we have is somebody in the hospital, but that person has some other duties or some other roles.” Intervention college FGD. “It would have been better if we had mentors within the clinical placements who could be staying with the students for quite some time compared to lecturers having to go back to the clinical placement and mentor the students.” Intervention college FGD. “With clinical supervision and mentoring, we are still working on it so much, though we still have these bottleneck issues in term of the mentors in the hospital. We do not have them specifically to support students.” Control college FGD.

Limited resources to support effective learning

Although some colleges received some administrative support to engage hospital staff to support during EmONC skills teaching and mentoring of students, financial constraints emerged as a key challenge for institutionalizing and sustaining the initiatives. Educators reported limited resources by institutions to support academic functions to promote learning among students. Key areas affected were (i) clinical support supervision visits by educators for students during their clinical placements, (ii) recruitment of additional dedicated educators, clinical mentors and skills lab technicians to support clinical teaching and mentoring, (iii) refresher training for educators to update their knowledge and skills (iv) facilitating hospital staff and clinical mentors to effectively support institutional educators with skills/clinical teaching and mentoring of students, (v) expand skills lab infrastructure and replenishment of skills training equipment and consumables, (vi) motivation/support for student facilitators during their dedicated mentoring of colleagues and (vii) facilitated coffee/lunch breaks for students to fully participate in scheduled EmONC trainings.

“On clinical supervision, we have been going to the other clinical placement sites that they have been giving us. When the students are rotating within the college training hospital, we are able to do two or more supervisions but there is a challenge when we take our students far away because we cannot be facilitated to do supervisions more than twice in one place.” Intervention college FGD.

Mentors’ perspective on the future of mentorship

Mentors strongly recommended the institutionalizing of the mentoring intervention within the training institutions as part of the continuous professional development for educators. Mentors from the KMTC emphasized the need to institutionalize intervention in respective regions and establish regional hubs for refresher trainings for educators to strengthen their knowledge, skills and confidence. To consolidate learning, mentors expressed the need for blocked time for EmONC training – preferably for final year students before their exit into service delivery; encourage team/peer teaching and skills demonstrations for midwifery and clinical medicine students; develop a critical mass of student facilitators to support fellow students at free time and ensure access to the skills labs for skills practice. Appropriate recognition of the student facilitators and highly competent educators who supported mentoring of their colleagues was recommended as motivation for the selfless support of the passionate faculty. Importantly, it was emphasized that updates and guidelines should be jointly disseminated to the pre-service and in-service midwifery workforce to promote seamless classroom teaching and clinical practice.

Main findings

Our study explored experiences of educators, students and mentors (Kirkpatrick level 1) and application of what was learned into practice (Kirkpatrick level 3) in the implementation of an EmONC-enhanced curriculum. Challenges and areas for further support and investment to improve the quality of pre-service midwifery education and training were also identified. Key experiences include: (i) educators and students reacted positively to the EmONC content, (ii) the capacity strengthening training and mentoring of educators improved their knowledge, skills and confidence in teaching the EmONC-enhanced curriculum (iii) students applied the acquired EmONC knowledge and skills in their clinical practice during their clinical placements. Key interventions and improvements reported include: (i) educators improved their teaching skills by integrating participatory teaching methods (ii) educators adopted peer teaching and team teaching in their practice and (iii) improved feedback mechanisms between educators and students. Despite the positive reaction to the updated curriculum and capacity strengthening initiatives, key challenges with (i) midwifery faculty shortages (ii) high number of students in the programme (iii) inadequate time for delivery of the updated curriculum and (iv) inadequate clinical support for students in the clinical placements were identified. Strong collaborations between the training institutions and hospital staff were critical for strengthening the quality of pre-service education. However, resources including teaching infrastructure, supporting faculty and equipment replenishment were identified as key to the successful implementation of a competency-based curriculum.

Interpretation of our findings

Our findings are important as they are aligned and respond to WHO’s 7-step action plan to improving the quality of midwifery education [ 17 ], ICM’s global standards for midwifery education [ 5 ] and the global strategic directions for nursing and midwifery 2021–2025 [ 47 ].

This study demonstrated that a mentorship intervention improved educators’ knowledge, skills and confidence in skills teaching and integration of feedback mechanisms during teaching sessions. The mentorship intervention provided a much valued and needed opportunity for continuous professional development to update/improve their competencies for effective teaching. Joint specific programmes involving clinical midwives who participate in mentoring students during their clinical placements are important for enhanced learning and optimal clinical practice. Mentoring has been shown to improve skills acquisition, understanding of the professional role, personal and professional development. Mentoring relationships for student to student (peer), midwife to student, and midwife to new graduate midwife have been evaluated [ 48 , 49 , 50 , 51 ]. However, studies evaluating the role of mentorship for midwifery educators are limited.

Our findings are similar to other studies that showed that midwifery educators were not competent enough in their professional teaching roles particularly skills teaching [ 7 , 9 , 18 , 52 ]. Challenges identified include an overwhelmed faculty compared with the high numbers of students in the programme. This is a barrier to effective theory and practical skills teaching, clinical mentoring and support, assessments and providing effective feedback for learning and improvement. In addition, teaching infrastructure (skills labs and equipment) and hospital placement sites are inadequate and overstretched. This finding is similar to other studies conducted in LMICs [ 10 , 15 , 18 , 53 , 54 , 55 ] and may impact the uptake and scale-up of the mentorship programme in the future. Overstretched hospital placement sites and inadequate teaching infrastructure have been shown to have a direct negative impact on the quality of education and midwifery graduates produced for service delivery [ 3 , 17 ]. In competency-based education, active learner participation and accountability must be encouraged [ 56 ]. Training programmes are expected to integrate simulation skills training in their curricula before the clinical placements for clinical practical experience. Evidence shows that simulation and skills training make the students feel prepared and confident before clinical practice [ 31 ]. Although ICM recommends institutions to consider students vs. teacher ratios for effective training and education, the actual ratios are not prescribed. Therefore, training schools should design curriculum and programmes with a balanced context-specific teacher-student ratio, including clinical preceptors-student ratio, appropriate teaching and evaluation methods to promote learning and available resources for effective education as recommended by the ICM [ 5 ].

Our study findings compare to other studies where there is weak, ineffective or lack of supervisory follow-up support during the clinical placements for clinical experiences [ 18 , 19 , 32 , 52 , 53 , 55 , 57 ]. Curriculum implementation in the clinical area is a critical component to effective pre-service midwifery education and quality of midwifery graduates [ 7 ]. Clinical placements are essential for quality pre-service training and education and development of clinical competence [ 58 ]. During the clinical placements, students are exposed to the real practical settings and expected to apply the knowledge and skills acquired from classroom teaching under supervision. This experience helps students to develop mastery and right attitudes for practice. The International Association for Health Professions Education emphasizes that direct supervision and mentorship of students positively affects student development and patient outcome. For impact, supervision should be structured with regular scheduled meetings, provide essential constructive feedback regularly and should be aligned to students’ learning outcomes in the clinical placement [ 59 ]. In addition, effective supervisors/clinical teachers should have good interpersonal skills, good teaching skills and be clinically competent and knowledgeable [ 59 , 60 ]. Competent and updated educators and clinical midwives in training hospitals are critical for effective support of learning for midwifery students through supervision and mentoring in the clinical settings. Evidence shows that learning opportunities for students during clinical placements increase when there is joint support from academics/faculty and recognized, motivated preceptors in the clinical environment [ 29 , 61 , 62 , 63 ]. The collective team of qualified individuals who teach students in a midwifery programme (midwife teachers; experts from other disciplines; and clinical preceptors/teachers) are important faculty to prepare competent midwifery workforce [ 5 ].

Our findings showed that peer education was an approach practiced by both educators and students in theory and clinical skills teaching. Evidence suggests that peer education creates a safe supportive learning environment, learners view near-peer teachers as effective role models and increases confidence among learners and teachers [ 64 ]. Peer education as a complementary method in teaching along with the didactic approach have been found appropriate and effective [ 65 ]. Peer teaching increase student’s confidence and performance in clinical practice and improve learning in the psychomotor and cognitive domains [ 65 , 66 ]. When effectively used, students can share skills, experiences, and knowledge as equals. Also, it encourages feedback between students and saves time for the educators/preceptors [ 67 ]. Although the use of students’ peer teaching is associated with positive outcomes, students should be provided with adequate supervision and coaching by faculty and clinical mentors. Peer teaching approach can be ineffective with poor student learning due to incompatible students’ personalities and learning styles [ 66 ]. Therefore, careful consideration and support is required for this approach in midwifery education and training.

A one-off training in EmONC for final year midwifery students before graduation can consolidate the knowledge and skills learned over the years through classroom and clinical experience. However, learning opportunities on patients can be limited. Therefore, simulation-based education can facilitate learning hands-on clinical examination and procedural skills, using mannequins and realistic part-task and high-fidelity simulators prior to approaching patients [ 68 ]. Evidence has shown that simulation trainings improve knowledge, skills, self-efficacy, and satisfaction in learning. Additionally, they can reduce anxiety among learners before exit into the workforce [ 69 , 70 , 71 ]. However, resources (human, financial and infrastructure – space, equipment, and consumables) are essential to support the initiative across all the colleges. Sustainability should be considered, and midwifery education managers must therefore plan and allocate resources to implement the EmONC updated midwifery curriculum for optimal impact.

Strengths and limitations

To the best of our knowledge, this was the first study that explored experiences of educators, their mentors and students on the implementation of an EmONC-enhanced midwifery curriculum in Kenya. The study was conducted in KMTC, the largest trainer of the nursing and midwifery workforce in Kenya. Findings led to the 2024 KMTC nursing and midwifery curriculum review and allocation of 40-hours of EmONC specific content implemented in all the public mid-level training colleges in Kenya. This is to allow each institution to teach/facilitate EmONC training for final year midwifery students as a blocked standardised training to consolidate the knowledge/skills learned during the programme. The FGDs were considered adequate due to their information power for qualitative research (indicating that the more information the sample holds, relevant for the actual study, the lower amount of participants is needed) [ 45 , 72 ]. Qualitative data was collected from multiple groups (educators in both study groups, mentors and students) and this enhanced data triangulation and improved the credibility of the findings [ 73 ]. Use of both inductive and deductive coding demonstrated rigor and helped uncover new themes/patterns in data, was more objective, reliable, flexible and adaptable to new information [ 44 , 74 ]. The study was conducted in sampled public mid-level nursing and midwifery training colleges and may affect the generalizability of the findings. As such, it may not be representative of the experiences of all the nursing and midwifery educators and students in Kenya.

Implications

Our findings showed the value of training and mentorship interventions improved educators’ knowledge and skills. For effective education, curricula reviews should be followed with specific capacity strengthening of educators to deliver the updated curricula. To achieve this, sustainable, specific, and relevant skills-based professional development programmes should be designed and targeted to ensure that midwifery faculty are competent to provide quality education. To strengthen practical skills training, midwifery educators should keep their own clinical skills up to date in clinical practice on a regular basis – annually to demonstrate evidence and complement professional development. Relevant policy and opportunities for clinical experience by educators to improve their supervisory roles in the clinical areas for midwifery students should be considered.

Training programmes should ensure that students have sufficient midwifery practice experience in facility-based and community settings to attain the current ICM Essential Competencies for Midwifery Practice. For adequate preparation of competent midwifery graduates, support in skills acquisition through simulation training and supervision and mentoring during clinical placements for practice should be strengthened. Educators and clinical mentors should be regularly updated to deliver a harmonised competency-based curriculum. Opportunities for structured constructive feedback should be provided to enhance student learning of key clinical skills.

Future research on return on investments is needed. The impact of an updated EmONC-enhanced curriculum delivered within the pre-service education and strengthened midwifery faculty on maternal and newborn health outcomes is needed.

Midwifery faculty and students reacted positively to the updated competency-based curriculum as relevant for practice. Training and mentoring intervention improved educators’ competencies to deliver the updated EmONC-enhanced curriculum. The study reveals an overwhelmed midwifery faculty and an urgent demand for students support in clinical settings to acquire the international ICM competencies for practice. There are regulatory challenges: high number of students verses faculty, lack of clinical practice for the midwifery academic faculty and lack of mandatory regular professional development opportunities for specific clinical and teaching skills competencies for educators. Ineffective clinical supervision and mentoring of students during clinical placements due to low numbers of competent faculty hinders effective student learning. Although the bundle of interventions was effective in improving institutional capacity, a policy for regular professional development of midwifery educators is needed for sustainability. Midwifery training institutions should refocus resources towards educator recruitment, skills training equipment, training and deployment midwifery educator and clinical mentors for optimal return on investments.

Data availability

The transcripts/datasets generated and/or analysed during the current study are not publicly available due to the confidentiality of the data but are available from the corresponding author on request.

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Acknowledgements

The study was made possible through the financial support of the FCDO for the four-year Reducing Maternal and Newborn Deaths Programme in Kenya (2019 – 2023). Special acknowledgement to the KMTC headquarters and campuses’ management, midwifery educators and students who participated in the study. Also, we specially appreciate the experts who participated in the review of the curriculum, training and mentoring of educators and assessment of students. Gratitude to Dr. Paul Nyongesa and Dr. Fiona Dickinson for support with study ethics processes. Lastly, the authors would like to acknowledge the special technical and logistical support provided by the LSTM – Kenya team during the curriculum reviews, capacity strengthening interventions and data collection (David Ndakalu, Roselynne Githinji, Diana Bitta, Esther Wasike, Onesmus Maina, Martin Eyinda, Veneranda Kamanu and Evans Koitaba).

The study was funded by the Foreign, Commonwealth and Development Office (FCDO) as part of the four-year “Reducing Maternal and Newborn Deaths Programme in Kenya.” The FCDO were not involved in the research – study design; in the collection, analysis and interpretation of data; in the writing of the report; and in the decision to submit the article for publication.

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DNS and CA conceptualised and designed the study protocol; designed the mentoring intervention and data collection tools. DNS, PN and AU conducted the FGDs and student debrief sessions. DNS coded and analysed the data and interpreted the results, drafted the primary manuscript, reviewed, and prepared it for publication. ANL provided qualitative expertise on methods, analysis, interpretation of findings and substantively reviewed the draft manuscript. SBZ, HA, CM, ET, EN, LW, LN, IB and CB participated in the design of the study procedures and substantively reviewed the drafts and final manuscript. CA obtained funding for the study, provided oversight in investigation, analysis, interpretation and substantially reviewed the manuscript drafts. All the authors read and approved the final manuscript.

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The study was approved by Liverpool School of Tropical Medicine’s Research and Ethics Committee (REC 20–050), Moi University/Moi Teaching and Referral Hospital Institutional Research and Ethics Committee (IREC) (IREC FAN: 0003764), Kenya Medical Training College (KMTC/ADM/74/Vol VI) and National Commission for Science, Technology, and Innovation (License No: NACOSTI/P/21/8931). Study participants received an electronic detailed study information booklet containing all information about the study. Written informed consent was obtained from participants. Participation was voluntary with an option to withdraw at any time with no consequences. Transcripts were anonymized with pseudonyms used to maintain confidentiality. Assessments and debrief meetings were conducted in a designated private space within the colleges for privacy.

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Shikuku, D.N., Bar-Zeev, S., Ladur, A. et al. Experiences, barriers and perspectives of midwifery educators, mentors and students implementing the updated emergency obstetric and newborn care-enhanced pre-service midwifery curriculum in Kenya: a nested qualitative study. BMC Med Educ 24 , 950 (2024). https://doi.org/10.1186/s12909-024-05872-7

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• Christine Namugwanya 1 ,
• Angella Baita 1 ,
• Peter James Elyanu 1 ,
• Patricia Nahirya Ntege 1 ,
• Dithan Kiragga 1 ,
• Carol Birungi 4 ,
• Adeodata Rukyalekere Kekitiinwa 1 ,
• Agnes Kiragga 5 ,
• Moorine Peninah Sekadde 6 ,
• Nicole-Austin Salazar 7 ,
• Anna Maria Mandalakas 8 &
• Philippa Musoke 9  

AIDS Research and Therapy volume  21 , Article number:  59 ( 2024 ) Cite this article

Metrics details

Introduction

People living with HIV (PLHIV) have a 20-fold risk of tuberculosis (TB) disease compared to HIV-negative people. In 2021, the uptake of TB preventive treatment among the children and adolescents living with HIV at the Baylor-Uganda HIV clinic was 45%, which was below the national target of 90%. Minimal evidence documents the enablers and barriers to TB preventive treatment (TPT) initiation and completion among children and adolescents living with HIV(CALHIV). We explored the facilitators and barriers to TPT initiation and completion among CALHIV among adolescents aged 10-19years and caretakers of children below 18years.

We conducted a qualitative study from February 2022 to March 2023, at three paediatric and adolescent HIV treatment centers in Uganda. In-depth interviews were conducted at TPT initiation and after completion for purposively selected health workers, adolescents aged 10–19 years living with HIV, and caretakers of children aged below 18years.

The desire to avoid TB disease, previous TB treatment, encouragement from family members, and ministry of health policies emerged as key facilitators for the children and adolescents to initiate TPT. Barriers to TPT initiation included; TB and HIV-related stigma, busy carer and adolescent work schedules, reduced social support from parents and family, history of drug side effects, high pill burden and fatigue, and perception of not being ill. TPT completion was enabled by combined TPT and ART refill visits, delivery of ART and TPT within the community, and continuous education and counseling from health workers. Reported barriers to TPT completion included TB and HIV-related stigma, long waiting time. Non-disclosure of HIV status by caretakers to CALHIV and fear of side effects was cited by health workers as a barrier to starting TPT. Facilitators of TPT initiation and completion reported by healthcare workers included patient and caretaker health education, counselling about benefits of TPT and risk of TB disease, having same appointment for TPT and ART refill to reduce patient waiting time, adolescent-friendly services, and appointment reminder phone calls.

The facilitators and barriers of TPT initiation and completion among CALHIV span from individual, to health system and structural factors. Health education about benefits of TPT and risk of TB, social support, adolescent-friendly services, and joint appointments for TPT and ART refill are major facilitators of TPT initiation and completion among CALHIV in Uganda.

Globally, 10.6 million people fell ill with tuberculosis (TB) in 2022, of which 12% were children below 15 years of age, and 23% reported in Africa [ 1 ]. People living with HIV (PLHIV) accounted for a disproportionate 6.7% of the TB cases and TB-HIV co-infection rates greater than 50% persist in numerous countries [ 1 ]. Out of the 1.6 million TB related deaths that occurred in 2021, 187,000 were among PLHIV, with 11% among children living with HIV [ 1 ].

Following TB exposure, PLHIV have a 20-fold increased life-time risk of progressing to TB disease, and up to 15% annual risk of TB disease, compared to the general population [ 2 ]. There is evidence that TB preventive treatment (TPT) in combination with anti-retroviral therapy (ART), reduces the risk of TB disease by up to 90% [ 3 , 4 ]. During the period 2018–2021, 10.6 million PLHIV received TPT globally, which was more than the targeted 6 million PLHIV. Nevertheless, there is minimal global data reporting TPT completion rates.

Uganda is one of the 30 countries categorized as high TB and TB/HIV burden by the World Health Organization (WHO) [ 1 ], with 74,799 TB patients reported in 2022, of which 32% were HIV-co-infected, and 12% were children below 15years of age [ 1 ]. Following three nation-wide TPT uptake campaigns led by the Ugandan ministry of health, 88.8% of the eligible PLHIV received TPT [ 5 ]. In Ugandan public health facilities, only 17% PLHIV initiated TPT out of the 93% who were eligible for TPT, with only 58% completing the full TPT course [ 6 ]. Some of the documented challenges contributing to such gaps in TPT uptake among PLHIV include; hesitancy of health workers to prescribe TPT for fear of promoting drug resistance, interrupted TPT supply, patients’ fear of additional pill burden and side-effects [ 6 ]. Non-completion of TPT was also associated with ART non-adherence, ART regime switch, and patient representation among adult PLHIV in rural Uganda [ 7 ]. Effective implementation of TPT, through addressing identified barriers and enhancing the facilitators of TPT [ 8 ], is key in reducing the burden of TB disease among PLHIV and bridging the TPT uptake and completion gaps [ 9 , 10 , 11 ]. However, there is limited data on TPT completion especially among PLHIV who are concurrently on ART. Therefore, it is important to understand the multi-faceted barriers and facilitators of initiating and completing TPT among the PLHIV. These may be related to the different healthcare system components such as; the clients or community, health policies, leadership and governance, drugs and logistics management, clinical information systems, service delivery, health workforce and financing [ 12 ]. Individual factors reported to facilitate TPT uptake and delivery among PLHIV in Tanzania include; alignment of ART and TPT visits, and TPT-related education and counseling. In South Africa, individual facilitators of TPT completion among PLHIV included; knowledge about TB and TPT, acceptance of one’s HIV status, having social support in the community and at the health facility, and desire for health preservation [ 13 ]. Individual barriers to TPT uptake and delivery included; perceived or previous experience of side effects, HIV stigma, pill burden, negative cultural and religious values, misunderstanding of TPT’s preventive role, financial burden of transport to the clinic and lost wages, and ineffective communication with the health workers [ 13 , 14 , 15 ].

Health care worker facilitators of TPT initiation among PLHIV include; comprehensive and collective planning, and supervision, presence of guidelines, TB-HIV training, positive attitude and being knowledgeable about TPT, known benefit of TPT, and effective health worker communication [ 8 , 13 , 16 ]. Health care worker and health system barriers to TPT delivery and uptake include; fear for isoniazid resistance due to interrupted drug supply, poor knowledge and attitude, misunderstanding about timing of TPT initiation, shortage of skilled health workers, variable TB screening practices and responsibilities, drug shortage [ 10 ], and contradicting guidelines from TB programs and HIV care programs [ 14 , 17 , 18 , 19 ]. In South Africa, lack of fidelity to national TPT guidelines was a barrier among health workers to initiation of TPT for PLHIV [ 20 ]. Absence of parental risk perception was reported as a barrier to TPT uptake among children in TB endemic areas [ 21 ]. Most of the documented facilitators and barriers to TPT initiation and completion are among adults, with limited reports for children, adolescents and their care takers.

Therefore, we conducted a qualitative study to explore the perceived and experienced barriers and facilitators to TPT initiation and completion among Ugandan children and adolescents living with HIV (CALHIV).

Theoretical orientation

A growing body of literature illustrates that health outcomes are progressively influenced by the environments within which individuals thrive and less by individual behaviors [ 22 ]. We therefore adopted the social ecological model (SEM) as a theoretical framework for analysis (see Fig.  1 below). The social-ecological model (SEM) of health promotion by McLeroy and colleagues states that health behaviour and promotion are interrelated and occur around multiple levels in the individual, interpersonal, institutional, community, and policy levels [ 23 ] This multifaceted perspective is important to understand and explicate barriers and facilitators of TPT initiation and completion among children and adolescents living with HIV, caregivers, and health care workers. The first level refers to individual factors that facilitate or inhibit a person’s choices, including personal stigma, limited knowledge about the prevention treatment, financial constraints and drug characteristics. The second level is interpersonal or network influences. An individual’s relationship with their closest caretakers, and family members influences their uptake and completion of preventative treatments. The third level is community perspectives, as children, caregivers and health care workers are influenced by community-held mass awareness campaigns community drug delivery services and community misconception about prevention treatments. The fourth level refers to health system (institutional) influences, including busy, unapproachable health care workers, limited access to the right treatment and the long waits. The final level refers to structural influences including the accessibility of the information and services related to TB.

Illustration of the SEM framework showing the interrelations at various levels

Study design and data collection methods

This qualitative study was part of a prospective cohort study conducted from February 2022 to March 2023; where CALHIV and their care takers were offered to choose either facility-based or community-based initiation and delivery of TPT. This was part of the differentiated TPT delivery among CALHIV in Uganda (COMBAT TB study).

Study setting

The study was conducted at three high-volume paediatric and adolescent HIV treatment clinics; Baylor College of Medicine Children’s Foundation-Uganda (Baylor-Uganda) center of excellence (COE) HIV clinic located in Mulago Hospital Kampala, Joint Clinical Research Center (JCRC) located in Lubowa, and the Makerere Joint AIDS Program (MJAP) ISS Clinic located on Mulago Hill in Kampala. The Baylor-Uganda clinic located about 4 km from the Kampala city center, provides comprehensive HIV care services for more than 4000 CALHIV out of more than 8000 PLHIV in care at the clinic. The JCRC Lubowa HIV clinic located in Wakiso district, 11 km from Kampala, and it provides comprehensive HIV care services to 1300 CALHIV out of 15,000 PLHIV in care. The MJAP ISS clinic located on Mulago Hill in Kampala, provides comprehensive HIV care services to 612 adolescents out of over 17,000 PLHIV in care. The three clinics run from Monday to Friday as one-stop-centers for care and research on HIV, TB and other HIV-related conditions. The HIV and TB care is provided by multi-disciplinary teams which include counselors, community health workers, peer educators, nurses, pharmacy staff, doctors and laboratory staff. The clients receive HIV prevention services, ART, TB preventive treatment and TB treatment. There is also screening and treatment of other opportunistic infections and non-communicable conditions like mental health issues, hypertension, and diabetes. The services are provided at the health facilities or within the community, based on the national HIV and TB treatment and prevention guidelines.

The CALHIV were screened for TB using the WHO-recommended TB symptom screening tool at every clinic visit. Individuals with TB symptoms completed a clinical evaluation, and TB diagnostic tests, such as Xpert MTB/RIF ultra, urine TB lipoarabinomannan (TB-LAM) for those with CD4 count < 200cells/ul, and chest X-ray. Patients diagnosed with TB then start TB treatment.

Individuals who were assessed as not having TB were considered eligible for TPT, such as; PLHIV above one year of age with no evidence of TB disease, PLHIV who are close contacts of TB patients, and PLHIV who have recently completed a full course of TB treatment. The ministry of health supplied the study sites with TPT drugs; initially isoniazid taken daily for six (6) months, and later rolled-out once weekly isoniazid and rifapentine for three months. The TPT is dispensed with pyridoxine, to prevent peripheral neuropathy, a common side-effect of isoniazid. Individuals who developed mild or moderate side effects, were usually advised to continue with the TPT while the side-effects were managed. If any individuals developed severe side effects, the TPT was withheld to first manage the side effects.

Individuals who initiated TPT within the differentiated delivery approach, had follow-up done via phone calls at two weeks and four weeks after TPT initiation. Follow-up was done at 3months after TPT initiation, and thereafter every three-months at the clinic or within the community to identify and manage side-effects, screen for TB symptoms, and assess adherence to the TPT and ART.

TB screening and diagnostic tests were done for participants with TB symptoms after starting TPT. Participants diagnosed with TB disease before completion of their full TPT course had their TPT stopped and TB treatment started. Adolescents living with HIV were eligible for the study if they were aged 10–19 years, initiating TPT, and completed or did not complete the full dose of TPT. Care takers were eligible for the study if their children aged < 18years living with HIV were initiating TPT, completed or did not complete the full dose of TPT and were willing to provide written informed consent. Health care workers were eligible if they were actively involved in providing TPT and willing to provide written informed consent.

Purposive sampling was done to select eligible health workers, adolescents aged 10-19years and parents or care takers of children who were eligible to start TPT.

During selection of adolescents and care takers, selection was done to try and achieve representation from; the three clinics, with almost equal numbers of; males and females, and age categories (10-14years, 15-19years), TPT completion status (completed, did not complete, missed doses or lost to follow-up), facility-based or community-based delivery models, and ART status (initiating ART or ART-experienced).

The health care workers in this study were involved in screening the children and adolescents for TB, assessing TPT eligibility, prescribing TPT, monitoring individuals on TPT, and providing TB-HIV counseling and guidance according to the national TB and leprosy control guidelines (24). Among the health workers, efforts were made to select equal numbers of males and females, and fair representation by different cadres (nurses, clinical officers, doctors, pharmacists).

Data collection procedure

A semi-structured interview guide was used for each category to obtain in-depth descriptions and valuable insights about the barriers and facilitators to TPT initiation and completion from the three categories of participants.

During the TPT initiation visits, qualitative in-depth interviews (IDIs) were conducted face to-face by an experienced male social scientist (DN), using the piloted interview guide for the data collection process. Interviews lasted between 30 and 45 min. Field notes were also made after each data collection session. Participants were recruited through purposive sampling with the help of the study nurse (CN) at three HIV clinics between June 2022 and August 2023. The IDIs were carried out with the CALHIV, Caretakers/parents and health workers. All the IDIs were held in a conducive place that was safe, neutral and with minimal distractions for the participants and the researcher. This place was either suggested by the interviewee or preset by the interviewer at the participating HIV clinics. Data collection was conducted in a language preferred by the participant, either English or Luganda. The interviewer (DN) took time at the outset of the discussions to develop a rapport with participants, acknowledging the sensitivity of the topic and creating a safe space for them to share their thoughts and experiences. Participants were fully informed about the purpose and objectives of the study, and they provided their informed consent to participate, indicating their understanding and agreement with the research goals and procedures. Approximately four months into the TPT study, participants were approached to participate in the second phase of IDIs for TPT completion.

Sample size

During TPT initiation, thirty (30) IDIs were carried out with the caretakers/parents and children ( N  = 30; 10 health workers, 10 CALHIV, and 10 Caretakers/parents). After TPT completion, interviews were conducted with 10 care takers, and 10 CALHIV. Participants were purposively sampled to represent those CALHIV who completed and those who did not complete or defaulted their TPT dose. The interview guide explored both the facilitators and the barriers for the TPT initiation and completion.

Data management and analysis

In-depth interviews were audio recorded, transcribed verbatim, and then translated into English for a hybrid approach of inductive and deductive thematic analysis [ 22 ] by two researchers (DN and PMA) experienced in qualitative methodology. The initial deductive coding was based on the five levels of the Social Ecological Model (SEM) in Fig.  1 above, and inductive coding was used to explore other themes that were not covered by the SEM. Three transcripts were initially selected and read through for familiarization and coded manually by DN. To ensure coding consistency, the developed codes were shared with the study principal investigator PMA to facilitate collaborative thematic analyses throughout [ 23 ]. All transcripts were imported into NVivo 14 and coded using the refined codebook by DN and PMA. The transcripts were not returned to the participants. The data was organized into pre-defined key themes outlined by the levels of the SEM. A framework approach using SEM was used for data analysis [ 25 ]. Themes and sub-themes were continually reviewed and refined to capture emerging new codes. Quotes were captured to highlight thematic areas and increase our understanding of the context. The methods and results were aligned to the consolidated criteria for reporting qualitative research (CORE-Q) [ 26 ].

A total of 50 IDIs were conducted for the selected participants (health workers ( N  = 10), adolescents ( N  = 10), care takers ( n  = 10) until saturation of content was achieved. Table  1 below summarises the demographic characteristics of the study participants.

Facilitators to initiation and completion of TPT among adolescents and children

From the IDIs, we found the following facilitators at individual level. Participants perceiving themselves as being at risk of contracting TB was a key facilitator to initiate and complete TPT. In addition, some care takers highlighted that the TPT will also help the child to have a good life without TB, but if she acquires TB and yet is already HIV positive, the child may be severally affected.

“Apart from the fact that it will help me to prevent TB, it will help me not to get TB and am assured that I will not get TB because TB is very risky, inconvenient and I will protect others because I know I am at a very high risk. So by taking the drugs, at least I know am protecting someone in case I get it, am protecting a family member, a sibling, a sister”. Male Adolescent 15 years.

Further analysis revealed that care takers and participants who were once diagnosed with TB and recovered narrated their agony and the experience of treating TB which they noted that they would not want to experience again. The experience they had with TB disease compelled them to initiate and complete their TPT dose.

“Another reason why I accepted my child to start on TPT is because my child has ever suffered from TB, and given that now we have the drugs for preventing it, I had no reason to resist it. I was afraid the child might acquire it again”. Female carer of 10-year-old adolescent.

The desire to remain free from TB emerged as a facilitator to initiating and completing TPT. The TPT was perceived as a breakthrough strategy to prevent acquisition of TB.

“Since I had an experience of a person with TB that I told you about, I didn’t want to wait until he is affected as it did to the other one I saw. So that forced me to ensure that the dose is completed”. Female caretaker of 14-year-old adolescent.

At the interpersonal level, support, care and encouragement from family, supervision from the caretakers also emerged as important facilitators to initiate and complete TPT. The participants remarked that receiving care and support (reminders) from immediate family encouraged them to complete their treatment.

“Like at home, there is my mother who always reminds me to take my drugs. That helped me to always take my drugs in time”. Female Adolescent, 18 years.

Community level facilitators included guidance and counseling, comprehensive information, mass awareness and sensitization about TPT. Participants mentioned that receiving adequate information and sensitization was helpful for their decision to initiate TPT. Participants reported that they received information from the health workers on how the child should take the medicine and how the treatment works to prevent the disease, something that encouraged most of them to start their children on treatment.

“The encouragement I got from doctors helped me to give treatment to my child for TB treatment which also made it easy for me to start him on TPT. I believe by the time the dose is completed the child will be okay. Doctors also sensitized us about the possible side effects of the drugs and they follow up with phone calls”.  Female care taker for a 7-year old child.

It emerged that information about the TPT made available by the health workers, with opportunities to discuss the treatment with the doctors, and making it known in the community, enabled the care givers to allow TPT to be given to their children and adolescents.

“When people are aware, it makes the services easy to access. Many people talk about other things on TVs and radios but they don’t take about TB. We have to tell people TB is real and a killer disease. You can also inform them in case someone sees the symptoms they should be screened for TB”. Medical doctor 01.

At the institutional and organizational level, participants preferred to have convenient services as a facilitator for the initiation and completion of the treatment. This was in terms of having TPT appointments scheduled on the same days of ART refill so that they can have all the drugs on the same appointment as this will reduce the time spent at the clinic and cost of repeat visits.

“The other issue is integrating those TPT refills with their usual clinic visits and community services so that they can readily receive the drugs at times without even wasting much time and transport to come to the clinic”. Medical doctor 02.

Among the healthcare providers, it emerged that many young people preferred to have the drugs taken to them so that they don’t have any excuses of not coming to the clinic for treatment.

“Also initiating TPT delivery models that reduce the transport costs and avoid missing clinical appointments and doses. Also to make sure their drugs are delivered before they are out of stock”. Nursing officer 01.

Besides the convenient services, health workers recognized mechanisms of following up the patients initiated on TPT or reminding them when to take their treatment as facilitator for the completion of TPT.

“We need to make mechanisms of follow ups when you put someone on TPT, you have to check on them to see how they are doing sometimes when you tell them to take the drug on Sunday it means they will even shift the ARVs to the same date”. Epidemiologist 01.

Health workers also cited frequent and friendly communication with children and caretakers in terms of the health talks at the clinic, calling the patients through the mobile phones and receive their feedback.

“Another thing is when you relate with children they bring out their challenges where you share and help them out. Smoothly they can cooperate and complete the six months’ TB preventive treatment". Study counsellor 01. “With the care takers, it is just a matter of explaining to them. It will not be hard for them if they have understood the importance of TPT and even the challenges will be less. The information should be explained in a way which is understood.” TB community linkage facilitator 01.

At the structural level, what emerged was having national policies and good performance indicators at the health facilities that are developed to create demand for the TPT among CALHIV has a great advantage and facilitates TPT uptake.

“Demand creation, tasking health workers. We have our weekly performance review and TPT is among the many indicators we track. Ministry of health asks us how many people are on TPT which helps the health worker to improve on performance and this will facilitate the uptake of TPT”. Medical officer 01.

Regular auditing and identifying the challenges and weaknesses at the facilitate level in relation to the prescription of the treatment emerged as a key facilitator for the uptake of TPT among CALHIV.

“We have reached that level where we appreciate if you find your health workers are not performing well, sit down as a unit and ask yourself on the weaknesses. If you planned to start 56 participants on TPT this week what happened, open the file and do file audits. You will discover interesting things other than patients missed to come or ask the pharmacist why were you not prescribing the drugs when there was even an alert”. Epidemiologist 02.

The following themes emerged as barriers to TPT initiation and completion at patient-level, structural, community and interpersonal levels.

We found the following individual-level barriers to TPT initiation and completion. One of the emerging barriers to initiate or complete their TPT was the stigma associated with taking TB or HIV drugs. The fear of being seen taking many pills on a daily basis was cited as affecting their emotional well-being and mental health.

“Stigma will always be there and I think it’s a reason why so many kids out there fear. Personally before, I didn’t have any problem taking my medicine. So when the stigma started I stopped taking medicine, I stopped caring, it really caused me a lot of mental damage and trauma”. Male Adolescent 18 years.

Where there is limited privacy, taking the treatment would be difficult. Participants also mentioned that they would fail to come for their HIV clinic appointments, for fear of being identified as HIV patients or TB patients.

“…the main challenge is the stigma of HIV which is a leading factor in the community. Some of them fail to come for their appointments because of stigma. They don’t want to be identified as HIV or TB-positive”. Medical officer 03.

The fear of drug-related side effects was reported as a key barrier to starting TPT. Participants expressed their fear of taking TPT treatment for fear of side effects based on their past experiences with different drugs. At TPT completion, experience of side-effects like dizziness and nausea emerged as barriers to TPT completion.

“It would make me feel nausea or feel like vomiting, headache and dizziness. Me I decided not to take them anymore… I even didn’t tell anyone”. Male adolescent, 12 years old.

High pill burden coupled with poor drug adherence also emerged as key barriers reported by the participants, especially if the child was also on ART regimens.

“Another issue is about the pill burden because these are people who are already on ARVs and then they are added more pills for TB so it becomes a lot for them”. Nursing officer 3. “The biggest barrier is adherence because it’s still a challenge to even those that are HIV negative. There are clients who are not used to taking treatment and if the treatment is for six months there will be a challenge of commitment to take the drugs every day.” Medical officer 03.

Among the caretakers, it emerged that pill fatigue created by taking tablets when a person is not sick with TB, caused many adolescents to miss their doses and some did not complete, even though they reported taking the drugs when it is not true.

“Some children fear taking drugs and time comes when the child is tired and no longer wants to take the medicine. … the child can pretend to be taking the medicine when it is not true because the child got tired of taking the drugs”. Female Caretaker of 8-year-old child. “That the medicine was a lot, and the child got tired of it, so she didn’t complete. “Sometimes she could say, “it is just for prevention, I will not take it”. The fact that the child didn’t have TB, she could not care at all”. Female caretaker of 15 years adolescent.

Caretakers expressed the discomfort of children taking pills with a bad smell, big size, unpleasant color and poorly packaged. Participants said that a pill with no smell, small size and attractive packaging would be easier to swallow.

“One, the smell of the medication might not be really good to the child, the pill size can be too big, you even see and say ooh! Female caretaker to 13-year-old adolescent.

It emerged that some adolescents and their caretakers are “ engaged in demanding jobs that may not allow time to collect their medication or they may forget to take it ”. Community Health linkage officer 01.

Forgetting to take the additional drugs also emerged as hinderance to complete the TPT.

“…when you work a lot and do not get time, because you are not used to it like ARVs, the busy schedule can also cause you from not taking the drugs. Male adolescent-18 years. “She is so forgetful. You always have to ask her whether she has taken the medicine. If you are not around, I just know she has not taken and that’s why she didn’t complete”. Female caretaker to a 16year-old adolescent.

At the interpersonal level, the change of caretakers and lack of support mainly from parents also emerged as key barriers to the completion of TPT.

“Some of them like children depend on their caretakers and sometimes we experience changes of the caretakers”. Nursing officer 04.

Among female caregivers, denial or restrictions by the husbands to come to the clinic for refills, also emerged as a barrier for TPT completion among their children

“For those that are married, their husbands don’t allow them to come to the clinic since it was not on the program”. Female caretaker 14 years child.

Financial constraints and lack of food contributed to delay in TPT initiation and failure to complete the treatment. Caretakers expressed concerns that certain medications require a specific diet to be effective, but they struggled to provide the necessary nutritional support, particularly for their school-aged children, which in turn impacted their ability to adhere to treatment regimens, as highlighted by one adolescent’s experience

“Ok the major challenge I faced at school is sometimes I don’t take medicine because I have not eaten. I know the medicine is very strong and I know it will affect my stomach. It will affect me so if am to take it on an empty stomach it wouldn’t be possible. So sometimes I just don’t take it because I know it will cause me effects”. Female Adolescent 18 years.

Failure of the caretakers to disclose HIV status to the children was cited as a barrier of children to initiate and take TPT treatment. One health worker noted that most mothers at home have never disclosed the reason why their children take these drugs daily, and when the husband is around they cannot take their drugs.

“There is also no disclosure especially to the children. So you find when the child doesn’t take the drugs because they do not understand why they are taking the drugs”. Medical doctor 04.

This has also been a challenge to trace TB contacts in families where the patient has never disclosed to the family members and as a result, children in these families miss the opportunity to take the TPT treatment.

“Disclosure is the problem when families have not yet disclosed, and someone comes down with TB. It is difficult to conduct contact tracing, for example on what ground are you asking the family about TB. So it is hard”. Epidemiologist 02.

At the community level, misconception about TPT and Community stigma associated to TB were some of the barriers identified. Further analysis revealed that some adolescents are so inquisitive about drugs and the intended benefit of taking the drugs. However, many are confused with the different sources of information about the benefits of the drugs. In addition, they did not understand how it could work to prevent infection. For example, there was a misconception about the dangers of taking medication when you are well. Some perceived that the government would introduce these treatments as a gateway to reducing their life span.

“Adolescents are very inquisitive. They keep questioning depending on the different sources of information they receive. So some of the questions are like, “don’t you think these are the drugs that stimulate our TB?” Most of them have those questions and I don’t know whether it’s propaganda now they keep saying “the government or the health facilities are trying to make us fall sick quickly and we even google some of these drugs kill the cells that could have protected our bodies”. This affects their TPT drug adherence”. Medical officer 02.

Participants also reported that there was stigma related to TB disease at health facilities and in the communities where patients reside. The situation worsens especially for adolescents in schools where students fail to take their medication until their next appointment because of the stigma from their fellow peers.

“Students may stigmatize you, which at times makes you not to take the drugs or hide it from them that you are not taking the drugs”. Female adolescent 18 years. “Yes, because they disturb you, they say that one is a TB patient, and they talk a lot. This caused me to miss the refill days”. Female adolescent 14 years.

At the institution level, the long waiting-time at the clinic emerged as a barrier to completing TPT. Participants revealed that they preferred quick access to services without having to spend long hours in queues waiting to receive the treatment.

“It’s just embarrassing, it’s just too much. The long waiting really makes me feel like opting out. That’s the truth I can tell you”. Female care takers to a 13-year-old adolescent. “I come early and leave late. That issue made it hard for me. Sometimes I tell her to go by herself but then I remember that she will not give in her complaints. Sometimes we missed coming”. Female caretaker to a 12-year-old adolescent.

Participants were concerned about the attitude of health workers when they are seeking services. This was viewed as a major barrier because they thought if the health workers are rude to the clients, they might not find it conducive to collect their treatment. This was echoed by some health workers who shared the experience that when patients are mistreated, they fail to come back until they are followed up.

“You may find when the person has failed to come on a clinic visit because he was mistreated by a nurse and has not been listened to. Then the person concludes by saying I will not come back”. When it comes to the next appointment, they don’t come back”. Medical officer 05.

Health care workers forgetting to prescribe the drugs at refill visits emerged as one of the barriers to TPT completion.

“Also to the prescribers, someone might have taken TPT like for three months and when they report back, the prescriber forgets to give the refill to add up the six months. So, a patient ends up missing the three months and restart the treatment again”. Medical officer 01.

Health care workers also commented that health facilities may lack essential medicines, and clients are advised to buy from private pharmacies which hinders completion.

At the structural level, participants reported that if the clinic was not within easy reach, they found it a problem to pick their drug refills. This required them to travel long distances with costly transport.

“Transport also affects us, there is a time when you have to come and get treatment but when you don’t have money and that’s why some people fail to come”. Female care giver to 12-year-old adolescent.

This qualitative study explored the perceived, and experienced facilitators, and barriers to TPT initiation and completion among children and adolescents living with HIV, as reported by the Ugandan health workers, adolescents, and care takers of children.

Parental support and supervision, perceived risk of TB disease, and previous experiences of TB treatment were reported by adolescents and care takers of children as the major facilitators of TPT initiation and completion. Similar to a Kenyan study by S. Ngugi et al. [ 15 ], this study found that provision of adequate information about TPT benefits and dosing by health workers, family and community support, and experience of treating children with TB were highlighted by care takers as facilitators that enabled their children to initiate and complete TPT. Social support is very key in determining TPT initiation and completion among CALHIV, calling for integration of psychosocial support in TPT programs.

Facilitators of TPT initiation and completion highlight the need to provide adolescent friendly services and integrated TB and HIV services to facilitate initiation and completion of TPT among adolescents living with HIV [ 8 ]. Adolescent friendly services should be accessible, acceptable, appropriate and delivered in safe and respectful environment by supportive healthcare providers (27, 28). These include promotive, preventive, curative, and referral health services (28).

The barriers to TPT initiation and completion reported by adolescents included; TB or HIV-related stigma, busy work schedules of the adolescents and care takers, reduced social support from parents and family, previous experience of side effects from other drugs, pill burden and fatigue when that are not sick, financial constraints to travel to the clinic, and lack of food to take with the medicines. The roll-out of shorter TPT regimens is very timely [ 9 ], and will most likely address concerns of pill burden and fatigue among CALHIV who are already receiving daily ART.

Although care takers identified barriers to TPT initiation and completion that were similar to those reported by the adolescents, care takers additionally reported barriers such as; pill size, burden and odour, misconception and misinformation about the benefits and duration of the TPT, long distances to the health facilities, and rude health workers. It is important to provide regular adherence support from TPT initiation to facilitate completion, and therefore the efficacious benefits of TPT.

In contrast to the study by Teklay G et al. [ 18 ], health workers did not report fear of creating isoniazid resistance as a barrier to TPT initiation among CALHIV. Barriers cited by health workers included; TB and HIV-related stigma, undisclosed HIV status to the CALHIV, misconceptions that TPT puts their life at risk, fear of side effects, missed opportunities due to forgetting by health workers, poor attitude of health workers towards the adolescents, long waiting hours, change of care takers, and lack of parental or social support. These are closely related to the contextual barriers reported by Nyarubamba R. F et al. in Tanzania [ 14 ], and Lai J et al. in Ethiopia [ 16 ]. Drug stock outs in some facilities were reported as barriers, similar to a study among health workers in Ethiopia [ 18 ].

Limitations

The purposively selected sample is not widely representative of the CALHIV and their care takers in high TB burden countries. Therefore, transferability of these results in other settings may vary based on; the social-ecological models used to assess patient perceptions, TB disease burden, patient/family education and support initiatives within the healthcare system. There were limited numbers of participants who did not complete TPT, limiting the depth of lived experiences about barriers to TPT completion among CALHIV. This study did not explore the perspectives of policy makers in TB care, as these are also important to guide concerted efforts to improve TPT uptake and completion among CALHIV. There was no quantitative data for triangulation with the qualitative results.

The in-depth interviews were conducted at TPT initiation and after TPT completion. This minimised recall bias. This enabled deeper understanding of both perceived and experienced facilitators and barriers to TPT initiation and completion among CALHIV.

The facilitators and barriers of TPT initiation and completion among CALHIV are diverse, spanning from individual factors to healthcare system and structural factors. Educating patients about the benefits of TPT and the need to reduce the risk of TB, facilitates TPT initiation and completion among CALHIV. Availability of social support, adolescent-friendly services, and integration of TPT refills into ART refill visits are also major facilitators of TPT initiation and completion among CALHIV.

TB and HIV-related stigma, high pill burden of TPT in addition to ART, non-disclosure of HIV status of the children and adolescents, lack of parental support, transport difficulties, and misconceptions about TPT side effects, were the major barriers to initiation and completion among these CALHIV. Therefore, it is important to implement patient-centered TB and TPT services for CALHIV and their caretakers, so as to improve TPT initiation and completion, ultimately, reducing TB burden in this high-risk population.

Recommendations

Provision of clear information about TPT and TB, psychosocial and adherence support, adolescent-friendly TB-HIV services, and integration of TPT delivery into ART delivery models, are promising strategies to improve the uptake and completion of TPT among children and adolescents living with HIV in high TB-HIV burden settings like Uganda. TPT completion is likely where services are offered within a family-centered approaches to enhance psychosocial support for adherence. We recommend integrating TPT delivery into existing ART delivery approaches, at health facility and community level, to enhance uptake and completion of TPT among CALHIV.

Data availability

The data that support the findings of this study are available on request from the corresponding author Dr Pauline Mary Amuge (PMA) [email protected], and the institutional representative [email protected] This is to ensure that the data is shared within the provisions of the protocol approved by the Makerere University School of Medicine research and ethics committee, as it was aimed to accomplish specified study objectives.

Abbreviations

Assisted Partner Notification

Anti-retroviral therapy

Anti-retroviral drugs

Children and Adolescents Living with HIV

Severe Acute Respiratory Syndrome due to Corona Virus-19

Differentiated Service Delivery

Differentiated Service Delivery Models

Human Immune-deficiency Virus

3months course of Isoniazid and Rifapentine

3months course of Isoniazid and Rifampicin

Integrated community case management

Isoniazid (isonicotinylhydrazide)

Isoniazid Preventive Therapy

Interrupted time series

Latent Tuberculosis Infection

Ministry of Health

National Drug Authority

National Tuberculosis and Leprosy control Program

Bacteriologically Confirmed Pulmonary Tuberculosis

Clinically Diagnosed Pulmonary Tuberculosis

People Living with HIV

Pulmonary Tuberculosis

• Tuberculosis

Tuberculosis Preventive Treatment

Village Health Team

World Health Organisation

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Acknowledgements

Baylor College of Medicine Children’s Foundation-Uganda: Henry Balwa, Susan Tukamuhebwa, Rachel Namuddu Kikabi, Florence Namuli, Kizito David, Wasswa George, Rogers Nizeyimana, Geofrey Musoba, Alex Tekakwo, Brenda Nakabuye, David Mpagi. Joint Clinical Research Center (JCRC) Lubowa: Flavia Nakato, Joan Nangiya, Henry Mugerwa, Drollah Ssebagala. Makerere Joint AIDS Program (MJAP) Mulago ISS Clinic Kampala Uganda: Douglas Musimbago, Fred Semitala.

This work was supported by the Collaborative Initiative for Paediatric HIV Education and Research (CIPHER) grant programme at the International AIDS Society (IAS), through the CIPHER Research grant awarded to PA for the period 1st November 2021 to 31st October 2023, for a project titled “Differentiated delivery of tuberculosis preventive treatment (TPT) within existing health facility and community HIV care models to improve TPT uptake and completion among children and adolescents living with HIV in Uganda following the COVID-19 pandemic.”

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Pauline Mary Amuge, Moses Mugerwa, Dickson Bbuye, Christine Namugwanya, Angella Baita, Peter James Elyanu, Patricia Nahirya Ntege, Dithan Kiragga & Adeodata Rukyalekere Kekitiinwa

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Department of Research and Clinical Care, Joint Clinical Research Center, Lubowa, Wakiso, Uganda

Diana Antonia Rutebarika

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School of Medicine, Johns Hopkins University, Baltimore, USA

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Global TB Program, Baylor College of Medicine, Houston, USA

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Contributions

PMA conceived the original concept. The funding was secured by PMA, PJE, PNN, ARK, AK, AMM, PM. The study was designed by PMA, PJE, MSP, AG, NAS, AMM, PM. Data was curated by PMA, DN, AB, DB, MM, CB, LK and CN. The data was analysed by DN and PMA. The project was co-ordinated by PMA, DN, MM, DB, DAR, and CB. The project technical advisors and mentors were; PJE, AK, ARK, AMM, NAS, MSP, AMM, PM. The original manuscript draft and responses to all author comments were written by PMA and DN. All authors reviewed and edited the original manuscript draft before submission. PMA and DN addressed all comments, and revised the manuscript. All authors reviewed and approved the final manuscript for publication.

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Correspondence to Pauline Mary Amuge .

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Written informed consent was obtained before data collection from participants aged ≥ 18 years, and parents/carers of children under 18years. Written informed assent was obtained from children aged 8years to under 18 years. All data were stored on encrypted computers. Filed notes and signed participant-informed consent forms were kept in a locked drawer at the study site. Participants’ names were not recorded anywhere during data collection. Each participant was given a unique identifying number to ensure confidentiality. The research teams did not include any identifying information that could have harmful consequences for the participants. Ethical approval was granted by the Makerere University school of medicine Research and Ethics Committee (17th June 2020, REF 2020 − 127), and the Uganda National Council for Science and Technology (12th November 2020; HS768ES).

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Amuge, P.M., Ndekezi, D., Mugerwa, M. et al. Facilitators and barriers to initiating and completing tuberculosis preventive treatment among children and adolescents living with HIV in Uganda: a qualitative study of adolescents, caretakers and health workers. AIDS Res Ther 21 , 59 (2024). https://doi.org/10.1186/s12981-024-00643-2

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Received : 10 June 2024

Accepted : 05 August 2024

Published : 29 August 2024

DOI : https://doi.org/10.1186/s12981-024-00643-2

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