how many participants is enough for qualitative research

Sample Size Policy for Qualitative Studies Using In-Depth Interviews

• Published: 12 September 2012
• Volume 41 , pages 1319–1320, ( 2012 )

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• Shari L. Dworkin 1  

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In recent years, there has been an increase in submissions to the Journal that draw on qualitative research methods. This increase is welcome and indicates not only the interdisciplinarity embraced by the Journal (Zucker, 2002 ) but also its commitment to a wide array of methodologies.

For those who do select qualitative methods and use grounded theory and in-depth interviews in particular, there appear to be a lot of questions that authors have had recently about how to write a rigorous Method section. This topic will be addressed in a subsequent Editorial. At this time, however, the most common question we receive is: “How large does my sample size have to be?” and hence I would like to take this opportunity to answer this question by discussing relevant debates and then the policy of the Archives of Sexual Behavior . Footnote 1

The sample size used in qualitative research methods is often smaller than that used in quantitative research methods. This is because qualitative research methods are often concerned with garnering an in-depth understanding of a phenomenon or are focused on meaning (and heterogeneities in meaning )—which are often centered on the how and why of a particular issue, process, situation, subculture, scene or set of social interactions. In-depth interview work is not as concerned with making generalizations to a larger population of interest and does not tend to rely on hypothesis testing but rather is more inductive and emergent in its process. As such, the aim of grounded theory and in-depth interviews is to create “categories from the data and then to analyze relationships between categories” while attending to how the “lived experience” of research participants can be understood (Charmaz, 1990 , p. 1162).

There are several debates concerning what sample size is the right size for such endeavors. Most scholars argue that the concept of saturation is the most important factor to think about when mulling over sample size decisions in qualitative research (Mason, 2010 ). Saturation is defined by many as the point at which the data collection process no longer offers any new or relevant data. Another way to state this is that conceptual categories in a research project can be considered saturated “when gathering fresh data no longer sparks new theoretical insights, nor reveals new properties of your core theoretical categories” (Charmaz, 2006 , p. 113). Saturation depends on many factors and not all of them are under the researcher’s control. Some of these include: How homogenous or heterogeneous is the population being studied? What are the selection criteria? How much money is in the budget to carry out the study? Are there key stratifiers (e.g., conceptual, demographic) that are critical for an in-depth understanding of the topic being examined? What is the timeline that the researcher faces? How experienced is the researcher in being able to even determine when she or he has actually reached saturation (Charmaz, 2006 )? Is the author carrying out theoretical sampling and is, therefore, concerned with ensuring depth on relevant concepts and examining a range of concepts and characteristics that are deemed critical for emergent findings (Glaser & Strauss, 1967 ; Strauss & Corbin, 1994 , 2007 )?

While some experts in qualitative research avoid the topic of “how many” interviews “are enough,” there is indeed variability in what is suggested as a minimum. An extremely large number of articles, book chapters, and books recommend guidance and suggest anywhere from 5 to 50 participants as adequate. All of these pieces of work engage in nuanced debates when responding to the question of “how many” and frequently respond with a vague (and, actually, reasonable) “it depends.” Numerous factors are said to be important, including “the quality of data, the scope of the study, the nature of the topic, the amount of useful information obtained from each participant, the use of shadowed data, and the qualitative method and study designed used” (Morse, 2000 , p. 1). Others argue that the “how many” question can be the wrong question and that the rigor of the method “depends upon developing the range of relevant conceptual categories, saturating (filling, supporting, and providing repeated evidence for) those categories,” and fully explaining the data (Charmaz, 1990 ). Indeed, there have been countless conferences and conference sessions on these debates, reports written, and myriad publications are available as well (for a compilation of debates, see Baker & Edwards, 2012 ).

Taking all of these perspectives into account, the Archives of Sexual Behavior is putting forward a policy for authors in order to have more clarity on what is expected in terms of sample size for studies drawing on grounded theory and in-depth interviews. The policy of the Archives of Sexual Behavior will be that it adheres to the recommendation that 25–30 participants is the minimum sample size required to reach saturation and redundancy in grounded theory studies that use in-depth interviews. This number is considered adequate for publications in journals because it (1) may allow for thorough examination of the characteristics that address the research questions and to distinguish conceptual categories of interest, (2) maximizes the possibility that enough data have been collected to clarify relationships between conceptual categories and identify variation in processes, and (3) maximizes the chances that negative cases and hypothetical negative cases have been explored in the data (Charmaz, 2006 ; Morse, 1994 , 1995 ).

The Journal does not want to paradoxically and rigidly quantify sample size when the endeavor at hand is qualitative in nature and the debates on this matter are complex. However, we are providing this practical guidance. We want to ensure that more of our submissions have an adequate sample size so as to get closer to reaching the goal of saturation and redundancy across relevant characteristics and concepts. The current recommendation that is being put forward does not include any comment on other qualitative methodologies, such as content and textual analysis, participant observation, focus groups, case studies, clinical cases or mixed quantitative–qualitative methods. The current recommendation also does not apply to phenomenological studies or life history approaches. The current guidance is intended to offer one clear and consistent standard for research projects that use grounded theory and draw on in-depth interviews.

Editor’s note: Dr. Dworkin is an Associate Editor of the Journal and is responsible for qualitative submissions.

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Dworkin, S.L. Sample Size Policy for Qualitative Studies Using In-Depth Interviews. Arch Sex Behav 41 , 1319–1320 (2012). https://doi.org/10.1007/s10508-012-0016-6

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Published : 12 September 2012

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How many participants do I need for qualitative research?

For those new to the qualitative research space, there’s one question that’s usually pretty tough to figure out, and that’s the question of how many participants to include in a study. Regardless of whether it’s research as part of the discovery phase for a new product, or perhaps an in-depth canvas of the users of an existing service, researchers can often find it difficult to agree on the numbers. So is there an easy answer? Let’s find out.

Here, we’ll look into the right number of participants for qualitative research studies. If you want to know about participants for quantitative research, read Nielsen Norman Group’s article .

Getting the numbers right

So you need to run a series of user interviews or usability tests and aren’t sure exactly how many people you should reach out to. It can be a tricky situation – especially for those without much experience. Do you test a small selection of 1 or 2 people to make the recruitment process easier? Or, do you go big and test with a series of 10 people over the course of a month? The answer lies somewhere in between.

It’s often a good idea (for qualitative research methods like interviews and usability tests) to start with 5 participants and then scale up by a further 5 based on how complicated the subject matter is. You may also find it helpful to add additional participants if you’re new to user research or you’re working in a new area.

What you’re actually looking for here is what’s known as saturation.

Understanding saturation

Whether it’s qualitative research as part of a master’s thesis or as research for a new online dating app, saturation is the best metric you can use to identify when you’ve hit the right number of participants.

In a nutshell, saturation is when you’ve reached the point where adding further participants doesn’t give you any further insights. It’s true that you may still pick up on the occasional interesting detail, but all of your big revelations and learnings have come and gone. A good measure is to sit down after each session with a participant and analyze the number of new insights you’ve noted down.

Interestingly, in a paper titled How Many Interviews Are Enough? , authors Greg Guest, Arwen Bunce and Laura Johnson noted that saturation usually occurs with around 12 participants in homogeneous groups (meaning people in the same role at an organization, for example). However, carrying out ethnographic research on a larger domain with a diverse set of participants will almost certainly require a larger sample.

Ensuring you’ve hit the right number of participants

How do you know when you’ve reached saturation point? You have to keep conducting interviews or usability tests until you’re no longer uncovering new insights or concepts.

While this may seem to run counter to the idea of just gathering as much data from as many people as possible, there’s a strong case for focusing on a smaller group of participants. In The logic of small samples in interview-based , authors Mira Crouch and Heather McKenzie note that using fewer than 20 participants during a qualitative research study will result in better data. Why? With a smaller group, it’s easier for you (the researcher) to build strong close relationships with your participants, which in turn leads to more natural conversations and better data.

There's also a school of thought that you should interview 5 or so people per persona. For example, if you're working in a company that has well-defined personas, you might want to use those as a basis for your study, and then you would interview 5 people based on each persona. This maybe worth considering or particularly important when you have a product that has very distinct user groups (e.g. students and staff, teachers and parents etc).

How your domain affects sample size

The scope of the topic you’re researching will change the amount of information you’ll need to gather before you’ve hit the saturation point. Your topic is also commonly referred to as the domain.

If you’re working in quite a confined domain, for example, a single screen of a mobile app or a very specific scenario, you’ll likely find interviews with 5 participants to be perfectly fine. Moving into more complicated domains, like the entire checkout process for an online shopping app, will push up your sample size.

As Mitchel Seaman notes : “Exploring a big issue like young peoples’ opinions about healthcare coverage, a broad emotional issue like postmarital sexuality, or a poorly-understood domain for your team like mobile device use in another country can drastically increase the number of interviews you’ll want to conduct.”

In-person or remote

Does the location of your participants change the number you need for qualitative user research? Well, not really – but there are other factors to consider.

• Budget: If you choose to conduct remote interviews/usability tests, you’ll likely find you’ve got lower costs as you won’t need to travel to your participants or have them travel to you. This also affects…
• Participant access: Remote qualitative research can be a lifesaver when it comes to participant access. No longer are you confined to the people you have physical access to — instead you can reach out to anyone you’d like.
• Quality: On the other hand, remote research does have its downsides. For one, you’ll likely find you’re not able to build the same kinds of relationships over the internet or phone as those in person, which in turn means you never quite get the same level of insights.

Is there value in outsourcing recruitment?

Recruitment is understandably an intensive logistical exercise with many moving parts. If you’ve ever had to recruit people for a study before, you’ll understand the need for long lead times (to ensure you have enough participants for the project) and the countless long email chains as you discuss suitable times.

Outsourcing your participant recruitment is just one way to lighten the logistical load during your research. Instead of having to go out and look for participants, you have them essentially delivered to you in the right number and with the right attributes.

We’ve got one such service at Optimal Workshop, which means it’s the perfect accompaniment if you’re also using our platform of UX tools. Read more about that here .

So that’s really most of what there is to know about participant recruitment in a qualitative research context. As we said at the start, while it can appear quite tricky to figure out exactly how many people you need to recruit, it’s actually not all that difficult in reality.

Overall, the number of participants you need for your qualitative research can depend on your project among other factors. It’s important to keep saturation in mind, as well as the locale of participants. You also need to get the most you can out of what’s available to you. Remember: Some research is better than none!

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How Many Participants Do I Need? A Guide to Sample Estimation

As a qualitative mentor, a question I am frequently asked is, “How do I select the right sample size?”. There is no short answer or hard and fast rule for this. As with all things, there is nuance here, and much of this depends on other factors of your study. The purpose of this blog post is to provide you with strategies to select the appropriate sample for your qualitative study.

When students ask me what their sample needs to be, my first response is to look at the literature. In your literature review , you reviewed studies with methodologies similar to yours. Look at what others who have conducted studies like your own have used as samples. Start to model yours on these estimates. This will provide you with a good start to estimate your sample size.

The key to finding the right number of participants to recruit is to estimate the point at which you will reach data saturation, or when you are not gleaning new information as you add participants. Practically speaking, this means that you are not creating new codes or modifying your codebook anymore. Guest et al. (2006) found that in homogeneous studies using purposeful sampling, like many qualitative studies, 12 interviews should be sufficient to achieve data saturation.

However, there are qualifications here, including specifics of a data set as well as a researcher’s experience or tendency to lump or split categories. More recently, Hagaman and Wutich (2017) explored how many interviews were needed to identify metathemes, or those overarching themes, in qualitative research. In contrast to Guest’s (2006) work, and in a very different study, Hagaman and Wutich (2017) found that a larger sample of between 20-40 interviews was necessary to detect those metathemes.

You can see that between these two articles, there is variation in sample size and the number of participants necessary to reach data saturation. These should, however, provide some guidance and a starting point for thinking about your own sample. At a minimum, you probably want to begin with a sample of 12-15 participants. Plan to add more as needed if you do not believe you have reached saturation in that amount.

Guest, G., Bunce, A., & Johnson, L. (2006). How many interviews are enough?: An experiment with data saturation and variability. Field Methods , 18(1), 59.82. https://doi.org/10.1177/1525822X05279903

Hagaman, A. K., & Wutich, A. (2017). How many interviews are enough to identify metathemes in multisited and cross-cultural research? Another perspective on Guest, Bunce, and Johnson’s (2006) landmark study. Field Methods , 29(1), 23-41. https://doi.org/10.1177/1525822X16640447

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Sample Size in Qualitative Interview Studies: Guided by Information Power

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• 1 1 University of Copenhagen, Copenhagen, Denmark.
• 2 2 Uni Research Health, Bergen, Norway.
• 3 3 University of Bergen, Bergen, Norway.
• PMID: 26613970
• DOI: 10.1177/1049732315617444

Sample sizes must be ascertained in qualitative studies like in quantitative studies but not by the same means. The prevailing concept for sample size in qualitative studies is "saturation." Saturation is closely tied to a specific methodology, and the term is inconsistently applied. We propose the concept "information power" to guide adequate sample size for qualitative studies. Information power indicates that the more information the sample holds, relevant for the actual study, the lower amount of participants is needed. We suggest that the size of a sample with sufficient information power depends on (a) the aim of the study, (b) sample specificity, (c) use of established theory, (d) quality of dialogue, and (e) analysis strategy. We present a model where these elements of information and their relevant dimensions are related to information power. Application of this model in the planning and during data collection of a qualitative study is discussed.

Keywords: information power; methodology; participants; qualitative; sample size; saturation.

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What’s in a Number? Understanding the Right Sample Size for Qualitative Research

• May 3, 2019

By Julia Schaefer

Unlike quantitative research , numbers matter less when doing qualitative research.

It’s about quality, not quantity. So what’s in a number?

When thinking about sample size, it’s really important to ensure that you understand your target and have recruited the right people for the study. Whether your company is targeting moms from the Midwest with household incomes of $70k+, or teens who use Facebook for more than 8 hours a week, it’s crucial to understand the goals and objectives of the study and how the right target can help answer your essential research questions.

Determining the Right Sample Size For Qualitative Research Tip #1: Right Size for Qualitative Research

A high-quality panel includes much more than just members who are pulled from a general population. The right respondents for the study will have met all the criteria line-items identified from quantitative research studies and check the boxes that the client has identified through their own research. Only participants who match the audience specifications and background relevance expressed by the client should be actively recruited.

Determining the Right Sample Size For Qualitative Research Tip #2: No Two Studies are Alike

Choosing an appropriate study design is an important factor to consider when determining which sample size to use. There are various methods that can be used to gather insightful data, but not all methods may be applicable to your study and your project goal. In-depth interviews , focus groups , and ethnographic research are the most common methods used in qualitative market research. Each method can provide unique information and certain methods are more relevant than others. The types of questions being studied play an equally important role in deciding on a sample size.

Determining the Right Sample Size For Qualitative Research Tip #3:  Principle of Saturation and Diminishing Returns

Understanding the difference of which qualitative study to use is very important. Your study should have a large enough sample size to uncover a variety of opinions, and the sample size should be limited at the point of saturation.

Saturation occurs when adding more participants to the study does not result in obtaining additional perspectives or information. One can say there is a point of diminishing returns with larger samples, as it leads to more data but doesn’t necessarily lead to more information. A sample size should be large enough to sufficiently describe the phenomenon of interest, and address the research question at hand. However, a large sample size risks having repetitive and redundant data.

The objective of qualitative research is to reduce discovery failure, while quantitative research aims to reduce estimation error. As qualitative research works to obtain diverse opinions from a sample size on a client’s product/service/project, saturated data does benefit the project findings. As part of the analysis framework, one respondent’s opinion is enough to generate a code.

The Magic Number? Between 15-30

Based on research conducted on this issue, if you are building similar segments within the population, InterQ’s recommendation for in-depth interviews is to have a sample size of 15-30. In some cases, a minimum of 10 is sufficient, assuming there has been integrity in the recruiting process. With the goal to maintain a rigorous recruiting process, studies have noted having a sample size as little as 10 can be extremely fruitful, and still yield strong results.

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Qualitative study design: Sampling

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As part of your research, you will need to identify "who" you need to recruit or work with to answer your research question/s. Often this population will be quite large (such as nurses or doctors across Victoria), or they may be difficult to access (such as people with mental health conditions). Sampling is a way that you can choose a smaller group of your population to research and then generalize the results of this across the larger population.

There are several ways that you can sample. Time, money, and difficulty or ease in reaching your target population will shape your sampling decisions. While there are no hard and fast rules around how many people you should involve in your research, some researchers estimate between 10 and 50 participants as being sufficient depending on your type of research and research question (Creswell & Creswell, 2018). Other study designs may require you to continue gathering data until you are no longer discovering new information ("theoretical saturation") or your data is sufficient to answer your question ("data saturation").

Why is it important to think about sampling?

It is important to match your sample as far as possible to the broader population that you wish to generalise to. The extent to which your findings can be applied to settings or people outside of who you have researched ("generalisability") can be influenced by your sample and sampling approach. For example, if you have interviewed homeless people in hospital with mental health conditions, you may not be able to generalise the results of this to every person in Australia with a mental health condition, or every person who is homeless, or every person who is in hospital. Your sampling approach will vary depending on what you are researching, but you might use a non-probability or probability (or randomised) approach.

Non-Probability sampling approaches

Non-Probability sampling is not randomised, meaning that some members of your population will have a higher chance of being included in your study than others. If you wanted to interview homeless people with mental health conditions in hospital and chose only homeless people with mental health conditions at your local hospital, this would be an example of convenience sampling; you have recruited participants who are close to hand. Other times, you may ask your participants if they can recommend other people who may be interested in the study: this is an example of snowball sampling. Lastly, you might want to ask Chief Executive Officers at rural hospitals how they support their staff mental health; this is an example of purposive sampling.

Examples of non-probability sampling include:

• Purposive (judgemental)
• Convenience

Probability (Randomised) sampling

Probability sampling methods are also called randomised sampling. They are generally preferred in research as this approach means that every person in a population has a chance of being selected for research. Truly randomised sampling is very complex; even a simple random sample requires the use of a random number generator to be used to select participants from a list of sampling frame of the accessible population. For example, if you were to do a probability sample of homeless people in hospital with a mental health condition, you would need to develop a table of all people matching this criteria; allocate each person a number; and then use a random number generator to find your sample pool. For this reason, while probability sampling is preferred, it may not be feasible to draw out a probability sample.

Things to remember:

• Sampling involves selecting a small subsection of your population to generalise back to a larger population
• Your sampling approach (probability or non-probability) will reflect how you will recruit your participants, and how generalisable your results are to the wider population
• How many participants you include in your study will vary based on your research design, research question, and sampling approach

Further reading:

Babbie, E. (2008). The basics of social research (4th ed). Belmont: Thomson Wadsworth

Creswell, J.W. & Creswell, J.D. (2018). Research design: Qualitative, quantitative and mixed methods approaches (5th ed). Thousand Oaks: SAGE

Salkind, N.J. (2010) Encyclopedia of research design. Thousand Oaks: SAGE Publications

Vasileiou, K., Barnett, J., Thorpe, S., & Young, T. (2018). Characterising and justifying sample size sufficiency in interview-based studies: systematic analysis of qualitative health research over a 15-year period. BMC Medical Research Methodology, 18(148)

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Riddle me this: How many interviews (or focus groups) are enough?

Emily Namey

This blog post is the final in a series of three sampling-focused posts.

The first two posts in this series describe commonly used research sampling strategies and provide some guidance on how to choose from this range of sampling methods . Here we delve further into the sampling world and address sample sizes for qualitative research and evaluation projects. Specifically, we address the often-asked question: How many in-depth interviews/focus groups do I need to conduct for my study?

Within the qualitative literature (and community of practice), the concept of “saturation” – the point when incoming data produce little or no new information – is the well-accepted standard by which sample sizes for qualitative inquiry are determined ( Guest et al., 2006 ; Guest and MacQueen, 2008 ). There’s just one small problem with this: saturation, by definition, can be determined only during or after data analysis. And most of us need to justify our sample sizes (to funders, ethics committees, etc.) before collecting data!

Until relatively recently, researchers and evaluators had to rely on rules of thumb or their personal experiences to estimate how many qualitative data collection events they needed for a study; empirical data to support these sample sizes were virtually non-existent. This began to change a little over a decade ago. Morgan and colleagues (2002) decided to plot (and publish!) the number of new concepts identified in successive interviews across four datasets. They found that nearly no new concepts were found after 20 interviews. Extrapolating from their data, we see that the first five to six in-depth interviews produced the majority of new data, and approximately 80% to 92% of concepts were identified within the first 10 interviews.

Building on this work, Guest et al. (2006) conducted a systematic inductive thematic analysis of 60 in-depth interviews among female sex workers in West Africa. Of the 114 themes identified in the entire dataset, 80 (70%) turned up in the first six interviews, and 100 themes (92%) were identified within the first 12 interviews (Figure 1). Additionally, those 100 themes comprised 97% of the most common (highest prevalence) themes, indicating that the “big ones” were evident early on.

Figure 1. Number of new codes identified in batches of six individual interviews ( Guest et al., 2006 )

Since Guest et al.’s publication in 2006, other researchers have confirmed that 6-12 interviews seem to be a sweet spot for the number of qualitative interviews needed to reach saturation. We provide the following table as a summary.

“But what about focus groups?” you ask. An empirically-based study by Coenen et al. (2012) (gated) found that five focus groups were enough to reach saturation for their inductive thematic analysis. In a recent methodological study (gated), we followed a similar approach used by Guest et al. (2006) and monitored thematic discovery and code creation after each of 40 focus groups conducted among African-American men in North Carolina on the topic of health-seeking behavior (more on this study and its methodological findings here ). We found the majority of themes were identified within the first focus group, and nearly all of the important (read most frequently expressed) themes were discovered within the first three focus groups (Figure 2).

Figure 2. Average number of new codes identified per focus group (focus groups randomly ordered) ( Guest et al., 2016 )

These data from our study suggest that a sample size of two to three focus groups will likely capture about 80% of themes on a topic — including those most broadly shared — in a study with a relatively homogeneous population, and using a semi-structured guide. As few as three to six focus groups are likely enough to identify 90% of important themes.

Note that these sample sizes, for both interviews and focus groups, apply per sub-population of interest. Note too that thematic saturation will vary based on a number of factors (keep watch for a future blog post) and sample size should be adjusted accordingly.

Use this catchy poem to remember how many in-depth interviews or focus groups you need.

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• Research article
• Open access
• Published: 21 November 2018

Characterising and justifying sample size sufficiency in interview-based studies: systematic analysis of qualitative health research over a 15-year period

• Konstantina Vasileiou   ORCID: orcid.org/0000-0001-5047-3920 1 ,
• Julie Barnett 1 ,
• Susan Thorpe 2 &
• Terry Young 3  

BMC Medical Research Methodology volume  18 , Article number:  148 ( 2018 ) Cite this article

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Choosing a suitable sample size in qualitative research is an area of conceptual debate and practical uncertainty. That sample size principles, guidelines and tools have been developed to enable researchers to set, and justify the acceptability of, their sample size is an indication that the issue constitutes an important marker of the quality of qualitative research. Nevertheless, research shows that sample size sufficiency reporting is often poor, if not absent, across a range of disciplinary fields.

A systematic analysis of single-interview-per-participant designs within three health-related journals from the disciplines of psychology, sociology and medicine, over a 15-year period, was conducted to examine whether and how sample sizes were justified and how sample size was characterised and discussed by authors. Data pertinent to sample size were extracted and analysed using qualitative and quantitative analytic techniques.

Our findings demonstrate that provision of sample size justifications in qualitative health research is limited; is not contingent on the number of interviews; and relates to the journal of publication. Defence of sample size was most frequently supported across all three journals with reference to the principle of saturation and to pragmatic considerations. Qualitative sample sizes were predominantly – and often without justification – characterised as insufficient (i.e., ‘small’) and discussed in the context of study limitations. Sample size insufficiency was seen to threaten the validity and generalizability of studies’ results, with the latter being frequently conceived in nomothetic terms.

Conclusions

We recommend, firstly, that qualitative health researchers be more transparent about evaluations of their sample size sufficiency, situating these within broader and more encompassing assessments of data adequacy . Secondly, we invite researchers critically to consider how saturation parameters found in prior methodological studies and sample size community norms might best inform, and apply to, their own project and encourage that data adequacy is best appraised with reference to features that are intrinsic to the study at hand. Finally, those reviewing papers have a vital role in supporting and encouraging transparent study-specific reporting.

Peer Review reports

Sample adequacy in qualitative inquiry pertains to the appropriateness of the sample composition and size . It is an important consideration in evaluations of the quality and trustworthiness of much qualitative research [ 1 ] and is implicated – particularly for research that is situated within a post-positivist tradition and retains a degree of commitment to realist ontological premises – in appraisals of validity and generalizability [ 2 , 3 , 4 , 5 ].

Samples in qualitative research tend to be small in order to support the depth of case-oriented analysis that is fundamental to this mode of inquiry [ 5 ]. Additionally, qualitative samples are purposive, that is, selected by virtue of their capacity to provide richly-textured information, relevant to the phenomenon under investigation. As a result, purposive sampling [ 6 , 7 ] – as opposed to probability sampling employed in quantitative research – selects ‘information-rich’ cases [ 8 ]. Indeed, recent research demonstrates the greater efficiency of purposive sampling compared to random sampling in qualitative studies [ 9 ], supporting related assertions long put forward by qualitative methodologists.

Sample size in qualitative research has been the subject of enduring discussions [ 4 , 10 , 11 ]. Whilst the quantitative research community has established relatively straightforward statistics-based rules to set sample sizes precisely, the intricacies of qualitative sample size determination and assessment arise from the methodological, theoretical, epistemological, and ideological pluralism that characterises qualitative inquiry (for a discussion focused on the discipline of psychology see [ 12 ]). This mitigates against clear-cut guidelines, invariably applied. Despite these challenges, various conceptual developments have sought to address this issue, with guidance and principles [ 4 , 10 , 11 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 ], and more recently, an evidence-based approach to sample size determination seeks to ground the discussion empirically [ 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 ].

Focusing on single-interview-per-participant qualitative designs, the present study aims to further contribute to the dialogue of sample size in qualitative research by offering empirical evidence around justification practices associated with sample size. We next review the existing conceptual and empirical literature on sample size determination.

Sample size in qualitative research: Conceptual developments and empirical investigations

Qualitative research experts argue that there is no straightforward answer to the question of ‘how many’ and that sample size is contingent on a number of factors relating to epistemological, methodological and practical issues [ 36 ]. Sandelowski [ 4 ] recommends that qualitative sample sizes are large enough to allow the unfolding of a ‘new and richly textured understanding’ of the phenomenon under study, but small enough so that the ‘deep, case-oriented analysis’ (p. 183) of qualitative data is not precluded. Morse [ 11 ] posits that the more useable data are collected from each person, the fewer participants are needed. She invites researchers to take into account parameters, such as the scope of study, the nature of topic (i.e. complexity, accessibility), the quality of data, and the study design. Indeed, the level of structure of questions in qualitative interviewing has been found to influence the richness of data generated [ 37 ], and so, requires attention; empirical research shows that open questions, which are asked later on in the interview, tend to produce richer data [ 37 ].

Beyond such guidance, specific numerical recommendations have also been proffered, often based on experts’ experience of qualitative research. For example, Green and Thorogood [ 38 ] maintain that the experience of most qualitative researchers conducting an interview-based study with a fairly specific research question is that little new information is generated after interviewing 20 people or so belonging to one analytically relevant participant ‘category’ (pp. 102–104). Ritchie et al. [ 39 ] suggest that studies employing individual interviews conduct no more than 50 interviews so that researchers are able to manage the complexity of the analytic task. Similarly, Britten [ 40 ] notes that large interview studies will often comprise of 50 to 60 people. Experts have also offered numerical guidelines tailored to different theoretical and methodological traditions and specific research approaches, e.g. grounded theory, phenomenology [ 11 , 41 ]. More recently, a quantitative tool was proposed [ 42 ] to support a priori sample size determination based on estimates of the prevalence of themes in the population. Nevertheless, this more formulaic approach raised criticisms relating to assumptions about the conceptual [ 43 ] and ontological status of ‘themes’ [ 44 ] and the linearity ascribed to the processes of sampling, data collection and data analysis [ 45 ].

In terms of principles, Lincoln and Guba [ 17 ] proposed that sample size determination be guided by the criterion of informational redundancy , that is, sampling can be terminated when no new information is elicited by sampling more units. Following the logic of informational comprehensiveness Malterud et al. [ 18 ] introduced the concept of information power as a pragmatic guiding principle, suggesting that the more information power the sample provides, the smaller the sample size needs to be, and vice versa.

Undoubtedly, the most widely used principle for determining sample size and evaluating its sufficiency is that of saturation . The notion of saturation originates in grounded theory [ 15 ] – a qualitative methodological approach explicitly concerned with empirically-derived theory development – and is inextricably linked to theoretical sampling. Theoretical sampling describes an iterative process of data collection, data analysis and theory development whereby data collection is governed by emerging theory rather than predefined characteristics of the population. Grounded theory saturation (often called theoretical saturation) concerns the theoretical categories – as opposed to data – that are being developed and becomes evident when ‘gathering fresh data no longer sparks new theoretical insights, nor reveals new properties of your core theoretical categories’ [ 46 p. 113]. Saturation in grounded theory, therefore, does not equate to the more common focus on data repetition and moves beyond a singular focus on sample size as the justification of sampling adequacy [ 46 , 47 ]. Sample size in grounded theory cannot be determined a priori as it is contingent on the evolving theoretical categories.

Saturation – often under the terms of ‘data’ or ‘thematic’ saturation – has diffused into several qualitative communities beyond its origins in grounded theory. Alongside the expansion of its meaning, being variously equated with ‘no new data’, ‘no new themes’, and ‘no new codes’, saturation has emerged as the ‘gold standard’ in qualitative inquiry [ 2 , 26 ]. Nevertheless, and as Morse [ 48 ] asserts, whilst saturation is the most frequently invoked ‘guarantee of qualitative rigor’, ‘it is the one we know least about’ (p. 587). Certainly researchers caution that saturation is less applicable to, or appropriate for, particular types of qualitative research (e.g. conversation analysis, [ 49 ]; phenomenological research, [ 50 ]) whilst others reject the concept altogether [ 19 , 51 ].

Methodological studies in this area aim to provide guidance about saturation and develop a practical application of processes that ‘operationalise’ and evidence saturation. Guest, Bunce, and Johnson [ 26 ] analysed 60 interviews and found that saturation of themes was reached by the twelfth interview. They noted that their sample was relatively homogeneous, their research aims focused, so studies of more heterogeneous samples and with a broader scope would be likely to need a larger size to achieve saturation. Extending the enquiry to multi-site, cross-cultural research, Hagaman and Wutich [ 28 ] showed that sample sizes of 20 to 40 interviews were required to achieve data saturation of meta-themes that cut across research sites. In a theory-driven content analysis, Francis et al. [ 25 ] reached data saturation at the 17th interview for all their pre-determined theoretical constructs. The authors further proposed two main principles upon which specification of saturation be based: (a) researchers should a priori specify an initial analysis sample (e.g. 10 interviews) which will be used for the first round of analysis and (b) a stopping criterion , that is, a number of interviews (e.g. 3) that needs to be further conducted, the analysis of which will not yield any new themes or ideas. For greater transparency, Francis et al. [ 25 ] recommend that researchers present cumulative frequency graphs supporting their judgment that saturation was achieved. A comparative method for themes saturation (CoMeTS) has also been suggested [ 23 ] whereby the findings of each new interview are compared with those that have already emerged and if it does not yield any new theme, the ‘saturated terrain’ is assumed to have been established. Because the order in which interviews are analysed can influence saturation thresholds depending on the richness of the data, Constantinou et al. [ 23 ] recommend reordering and re-analysing interviews to confirm saturation. Hennink, Kaiser and Marconi’s [ 29 ] methodological study sheds further light on the problem of specifying and demonstrating saturation. Their analysis of interview data showed that code saturation (i.e. the point at which no additional issues are identified) was achieved at 9 interviews, but meaning saturation (i.e. the point at which no further dimensions, nuances, or insights of issues are identified) required 16–24 interviews. Although breadth can be achieved relatively soon, especially for high-prevalence and concrete codes, depth requires additional data, especially for codes of a more conceptual nature.

Critiquing the concept of saturation, Nelson [ 19 ] proposes five conceptual depth criteria in grounded theory projects to assess the robustness of the developing theory: (a) theoretical concepts should be supported by a wide range of evidence drawn from the data; (b) be demonstrably part of a network of inter-connected concepts; (c) demonstrate subtlety; (d) resonate with existing literature; and (e) can be successfully submitted to tests of external validity.

Other work has sought to examine practices of sample size reporting and sufficiency assessment across a range of disciplinary fields and research domains, from nutrition [ 34 ] and health education [ 32 ], to education and the health sciences [ 22 , 27 ], information systems [ 30 ], organisation and workplace studies [ 33 ], human computer interaction [ 21 ], and accounting studies [ 24 ]. Others investigated PhD qualitative studies [ 31 ] and grounded theory studies [ 35 ]. Incomplete and imprecise sample size reporting is commonly pinpointed by these investigations whilst assessment and justifications of sample size sufficiency are even more sporadic.

Sobal [ 34 ] examined the sample size of qualitative studies published in the Journal of Nutrition Education over a period of 30 years. Studies that employed individual interviews ( n  = 30) had an average sample size of 45 individuals and none of these explicitly reported whether their sample size sought and/or attained saturation. A minority of articles discussed how sample-related limitations (with the latter most often concerning the type of sample, rather than the size) limited generalizability. A further systematic analysis [ 32 ] of health education research over 20 years demonstrated that interview-based studies averaged 104 participants (range 2 to 720 interviewees). However, 40% did not report the number of participants. An examination of 83 qualitative interview studies in leading information systems journals [ 30 ] indicated little defence of sample sizes on the basis of recommendations by qualitative methodologists, prior relevant work, or the criterion of saturation. Rather, sample size seemed to correlate with factors such as the journal of publication or the region of study (US vs Europe vs Asia). These results led the authors to call for more rigor in determining and reporting sample size in qualitative information systems research and to recommend optimal sample size ranges for grounded theory (i.e. 20–30 interviews) and single case (i.e. 15–30 interviews) projects.

Similarly, fewer than 10% of articles in organisation and workplace studies provided a sample size justification relating to existing recommendations by methodologists, prior relevant work, or saturation [ 33 ], whilst only 17% of focus groups studies in health-related journals provided an explanation of sample size (i.e. number of focus groups), with saturation being the most frequently invoked argument, followed by published sample size recommendations and practical reasons [ 22 ]. The notion of saturation was also invoked by 11 out of the 51 most highly cited studies that Guetterman [ 27 ] reviewed in the fields of education and health sciences, of which six were grounded theory studies, four phenomenological and one a narrative inquiry. Finally, analysing 641 interview-based articles in accounting, Dai et al. [ 24 ] called for more rigor since a significant minority of studies did not report precise sample size.

Despite increasing attention to rigor in qualitative research (e.g. [ 52 ]) and more extensive methodological and analytical disclosures that seek to validate qualitative work [ 24 ], sample size reporting and sufficiency assessment remain inconsistent and partial, if not absent, across a range of research domains.

Objectives of the present study

The present study sought to enrich existing systematic analyses of the customs and practices of sample size reporting and justification by focusing on qualitative research relating to health. Additionally, this study attempted to expand previous empirical investigations by examining how qualitative sample sizes are characterised and discussed in academic narratives. Qualitative health research is an inter-disciplinary field that due to its affiliation with medical sciences, often faces views and positions reflective of a quantitative ethos. Thus qualitative health research constitutes an emblematic case that may help to unfold underlying philosophical and methodological differences across the scientific community that are crystallised in considerations of sample size. The present research, therefore, incorporates a comparative element on the basis of three different disciplines engaging with qualitative health research: medicine, psychology, and sociology. We chose to focus our analysis on single-per-participant-interview designs as this not only presents a popular and widespread methodological choice in qualitative health research, but also as the method where consideration of sample size – defined as the number of interviewees – is particularly salient.

Study design

A structured search for articles reporting cross-sectional, interview-based qualitative studies was carried out and eligible reports were systematically reviewed and analysed employing both quantitative and qualitative analytic techniques.

We selected journals which (a) follow a peer review process, (b) are considered high quality and influential in their field as reflected in journal metrics, and (c) are receptive to, and publish, qualitative research (Additional File  1 presents the journals’ editorial positions in relation to qualitative research and sample considerations where available). Three health-related journals were chosen, each representing a different disciplinary field; the British Medical Journal (BMJ) representing medicine, the British Journal of Health Psychology (BJHP) representing psychology, and the Sociology of Health & Illness (SHI) representing sociology.

Search strategy to identify studies

Employing the search function of each individual journal, we used the terms ‘interview*’ AND ‘qualitative’ and limited the results to articles published between 1 January 2003 and 22 September 2017 (i.e. a 15-year review period).

Eligibility criteria

To be eligible for inclusion in the review, the article had to report a cross-sectional study design. Longitudinal studies were thus excluded whilst studies conducted within a broader research programme (e.g. interview studies nested in a trial, as part of a broader ethnography, as part of a longitudinal research) were included if they reported only single-time qualitative interviews. The method of data collection had to be individual, synchronous qualitative interviews (i.e. group interviews, structured interviews and e-mail interviews over a period of time were excluded), and the data had to be analysed qualitatively (i.e. studies that quantified their qualitative data were excluded). Mixed method studies and articles reporting more than one qualitative method of data collection (e.g. individual interviews and focus groups) were excluded. Figure  1 , a PRISMA flow diagram [ 53 ], shows the number of: articles obtained from the searches and screened; papers assessed for eligibility; and articles included in the review (Additional File  2 provides the full list of articles included in the review and their unique identifying code – e.g. BMJ01, BJHP02, SHI03). One review author (KV) assessed the eligibility of all papers identified from the searches. When in doubt, discussions about retaining or excluding articles were held between KV and JB in regular meetings, and decisions were jointly made.

PRISMA flow diagram

Data extraction and analysis

A data extraction form was developed (see Additional File  3 ) recording three areas of information: (a) information about the article (e.g. authors, title, journal, year of publication etc.); (b) information about the aims of the study, the sample size and any justification for this, the participant characteristics, the sampling technique and any sample-related observations or comments made by the authors; and (c) information about the method or technique(s) of data analysis, the number of researchers involved in the analysis, the potential use of software, and any discussion around epistemological considerations. The Abstract, Methods and Discussion (and/or Conclusion) sections of each article were examined by one author (KV) who extracted all the relevant information. This was directly copied from the articles and, when appropriate, comments, notes and initial thoughts were written down.

To examine the kinds of sample size justifications provided by articles, an inductive content analysis [ 54 ] was initially conducted. On the basis of this analysis, the categories that expressed qualitatively different sample size justifications were developed.

We also extracted or coded quantitative data regarding the following aspects:

Journal and year of publication

Number of interviews

Number of participants

Presence of sample size justification(s) (Yes/No)

Presence of a particular sample size justification category (Yes/No), and

Number of sample size justifications provided

Descriptive and inferential statistical analyses were used to explore these data.

A thematic analysis [ 55 ] was then performed on all scientific narratives that discussed or commented on the sample size of the study. These narratives were evident both in papers that justified their sample size and those that did not. To identify these narratives, in addition to the methods sections, the discussion sections of the reviewed articles were also examined and relevant data were extracted and analysed.

In total, 214 articles – 21 in the BMJ, 53 in the BJHP and 140 in the SHI – were eligible for inclusion in the review. Table  1 provides basic information about the sample sizes – measured in number of interviews – of the studies reviewed across the three journals. Figure  2 depicts the number of eligible articles published each year per journal.

The publication of qualitative studies in the BMJ was significantly reduced from 2012 onwards and this appears to coincide with the initiation of the BMJ Open to which qualitative studies were possibly directed.

Pairwise comparisons following a significant Kruskal-Wallis Footnote 2 test indicated that the studies published in the BJHP had significantly ( p  < .001) smaller samples sizes than those published either in the BMJ or the SHI. Sample sizes of BMJ and SHI articles did not differ significantly from each other.

Sample size justifications: Results from the quantitative and qualitative content analysis

Ten (47.6%) of the 21 BMJ studies, 26 (49.1%) of the 53 BJHP papers and 24 (17.1%) of the 140 SHI articles provided some sort of sample size justification. As shown in Table  2 , the majority of articles which justified their sample size provided one justification (70% of articles); fourteen studies (25%) provided two distinct justifications; one study (1.7%) gave three justifications and two studies (3.3%) expressed four distinct justifications.

There was no association between the number of interviews (i.e. sample size) conducted and the provision of a justification (rpb = .054, p  = .433). Within journals, Mann-Whitney tests indicated that sample sizes of ‘justifying’ and ‘non-justifying’ articles in the BMJ and SHI did not differ significantly from each other. In the BJHP, ‘justifying’ articles ( Mean rank  = 31.3) had significantly larger sample sizes than ‘non-justifying’ studies ( Mean rank  = 22.7; U = 237.000, p  < .05).

There was a significant association between the journal a paper was published in and the provision of a justification (χ 2 (2) = 23.83, p  < .001). BJHP studies provided a sample size justification significantly more often than would be expected ( z  = 2.9); SHI studies significantly less often ( z  = − 2.4). If an article was published in the BJHP, the odds of providing a justification were 4.8 times higher than if published in the SHI. Similarly if published in the BMJ, the odds of a study justifying its sample size were 4.5 times higher than in the SHI.

The qualitative content analysis of the scientific narratives identified eleven different sample size justifications. These are described below and illustrated with excerpts from relevant articles. By way of a summary, the frequency with which these were deployed across the three journals is indicated in Table  3 .

Saturation was the most commonly invoked principle (55.4% of all justifications) deployed by studies across all three journals to justify the sufficiency of their sample size. In the BMJ, two studies claimed that they achieved data saturation (BMJ17; BMJ18) and one article referred descriptively to achieving saturation without explicitly using the term (BMJ13). Interestingly, BMJ13 included data in the analysis beyond the point of saturation in search of ‘unusual/deviant observations’ and with a view to establishing findings consistency.

Thirty three women were approached to take part in the interview study. Twenty seven agreed and 21 (aged 21–64, median 40) were interviewed before data saturation was reached (one tape failure meant that 20 interviews were available for analysis). (BMJ17). No new topics were identified following analysis of approximately two thirds of the interviews; however, all interviews were coded in order to develop a better understanding of how characteristic the views and reported behaviours were, and also to collect further examples of unusual/deviant observations. (BMJ13).

Two articles reported pre-determining their sample size with a view to achieving data saturation (BMJ08 – see extract in section In line with existing research ; BMJ15 – see extract in section Pragmatic considerations ) without further specifying if this was achieved. One paper claimed theoretical saturation (BMJ06) conceived as being when “no further recurring themes emerging from the analysis” whilst another study argued that although the analytic categories were highly saturated, it was not possible to determine whether theoretical saturation had been achieved (BMJ04). One article (BMJ18) cited a reference to support its position on saturation.

In the BJHP, six articles claimed that they achieved data saturation (BJHP21; BJHP32; BJHP39; BJHP48; BJHP49; BJHP52) and one article stated that, given their sample size and the guidelines for achieving data saturation, it anticipated that saturation would be attained (BJHP50).

Recruitment continued until data saturation was reached, defined as the point at which no new themes emerged. (BJHP48). It has previously been recommended that qualitative studies require a minimum sample size of at least 12 to reach data saturation (Clarke & Braun, 2013; Fugard & Potts, 2014; Guest, Bunce, & Johnson, 2006) Therefore, a sample of 13 was deemed sufficient for the qualitative analysis and scale of this study. (BJHP50).

Two studies argued that they achieved thematic saturation (BJHP28 – see extract in section Sample size guidelines ; BJHP31) and one (BJHP30) article, explicitly concerned with theory development and deploying theoretical sampling, claimed both theoretical and data saturation.

The final sample size was determined by thematic saturation, the point at which new data appears to no longer contribute to the findings due to repetition of themes and comments by participants (Morse, 1995). At this point, data generation was terminated. (BJHP31).

Five studies argued that they achieved (BJHP05; BJHP33; BJHP40; BJHP13 – see extract in section Pragmatic considerations ) or anticipated (BJHP46) saturation without any further specification of the term. BJHP17 referred descriptively to a state of achieved saturation without specifically using the term. Saturation of coding , but not saturation of themes, was claimed to have been reached by one article (BJHP18). Two articles explicitly stated that they did not achieve saturation; instead claiming a level of theme completeness (BJHP27) or that themes being replicated (BJHP53) were arguments for sufficiency of their sample size.

Furthermore, data collection ceased on pragmatic grounds rather than at the point when saturation point was reached. Despite this, although nuances within sub-themes were still emerging towards the end of data analysis, the themes themselves were being replicated indicating a level of completeness. (BJHP27).

Finally, one article criticised and explicitly renounced the notion of data saturation claiming that, on the contrary, the criterion of theoretical sufficiency determined its sample size (BJHP16).

According to the original Grounded Theory texts, data collection should continue until there are no new discoveries ( i.e. , ‘data saturation’; Glaser & Strauss, 1967). However, recent revisions of this process have discussed how it is rare that data collection is an exhaustive process and researchers should rely on how well their data are able to create a sufficient theoretical account or ‘theoretical sufficiency’ (Dey, 1999). For this study, it was decided that theoretical sufficiency would guide recruitment, rather than looking for data saturation. (BJHP16).

Ten out of the 20 BJHP articles that employed the argument of saturation used one or more citations relating to this principle.

In the SHI, one article (SHI01) claimed that it achieved category saturation based on authors’ judgment.

This number was not fixed in advance, but was guided by the sampling strategy and the judgement, based on the analysis of the data, of the point at which ‘category saturation’ was achieved. (SHI01).

Three articles described a state of achieved saturation without using the term or specifying what sort of saturation they had achieved (i.e. data, theoretical, thematic saturation) (SHI04; SHI13; SHI30) whilst another four articles explicitly stated that they achieved saturation (SHI100; SHI125; SHI136; SHI137). Two papers stated that they achieved data saturation (SHI73 – see extract in section Sample size guidelines ; SHI113), two claimed theoretical saturation (SHI78; SHI115) and two referred to achieving thematic saturation (SHI87; SHI139) or to saturated themes (SHI29; SHI50).

Recruitment and analysis ceased once theoretical saturation was reached in the categories described below (Lincoln and Guba 1985). (SHI115). The respondents’ quotes drawn on below were chosen as representative, and illustrate saturated themes. (SHI50).

One article stated that thematic saturation was anticipated with its sample size (SHI94). Briefly referring to the difficulty in pinpointing achievement of theoretical saturation, SHI32 (see extract in section Richness and volume of data ) defended the sufficiency of its sample size on the basis of “the high degree of consensus [that] had begun to emerge among those interviewed”, suggesting that information from interviews was being replicated. Finally, SHI112 (see extract in section Further sampling to check findings consistency ) argued that it achieved saturation of discursive patterns . Seven of the 19 SHI articles cited references to support their position on saturation (see Additional File  4 for the full list of citations used by articles to support their position on saturation across the three journals).

Overall, it is clear that the concept of saturation encompassed a wide range of variants expressed in terms such as saturation, data saturation, thematic saturation, theoretical saturation, category saturation, saturation of coding, saturation of discursive themes, theme completeness. It is noteworthy, however, that although these various claims were sometimes supported with reference to the literature, they were not evidenced in relation to the study at hand.

Pragmatic considerations

The determination of sample size on the basis of pragmatic considerations was the second most frequently invoked argument (9.6% of all justifications) appearing in all three journals. In the BMJ, one article (BMJ15) appealed to pragmatic reasons, relating to time constraints and the difficulty to access certain study populations, to justify the determination of its sample size.

On the basis of the researchers’ previous experience and the literature, [30, 31] we estimated that recruitment of 15–20 patients at each site would achieve data saturation when data from each site were analysed separately. We set a target of seven to 10 caregivers per site because of time constraints and the anticipated difficulty of accessing caregivers at some home based care services. This gave a target sample of 75–100 patients and 35–50 caregivers overall. (BMJ15).

In the BJHP, four articles mentioned pragmatic considerations relating to time or financial constraints (BJHP27 – see extract in section Saturation ; BJHP53), the participant response rate (BJHP13), and the fixed (and thus limited) size of the participant pool from which interviewees were sampled (BJHP18).

We had aimed to continue interviewing until we had reached saturation, a point whereby further data collection would yield no further themes. In practice, the number of individuals volunteering to participate dictated when recruitment into the study ceased (15 young people, 15 parents). Nonetheless, by the last few interviews, significant repetition of concepts was occurring, suggesting ample sampling. (BJHP13).

Finally, three SHI articles explained their sample size with reference to practical aspects: time constraints and project manageability (SHI56), limited availability of respondents and project resources (SHI131), and time constraints (SHI113).

The size of the sample was largely determined by the availability of respondents and resources to complete the study. Its composition reflected, as far as practicable, our interest in how contextual factors (for example, gender relations and ethnicity) mediated the illness experience. (SHI131).

Qualities of the analysis

This sample size justification (8.4% of all justifications) was mainly employed by BJHP articles and referred to an intensive, idiographic and/or latently focused analysis, i.e. that moved beyond description. More specifically, six articles defended their sample size on the basis of an intensive analysis of transcripts and/or the idiographic focus of the study/analysis. Four of these papers (BJHP02; BJHP19; BJHP24; BJHP47) adopted an Interpretative Phenomenological Analysis (IPA) approach.

The current study employed a sample of 10 in keeping with the aim of exploring each participant’s account (Smith et al. , 1999). (BJHP19).

BJHP47 explicitly renounced the notion of saturation within an IPA approach. The other two BJHP articles conducted thematic analysis (BJHP34; BJHP38). The level of analysis – i.e. latent as opposed to a more superficial descriptive analysis – was also invoked as a justification by BJHP38 alongside the argument of an intensive analysis of individual transcripts

The resulting sample size was at the lower end of the range of sample sizes employed in thematic analysis (Braun & Clarke, 2013). This was in order to enable significant reflection, dialogue, and time on each transcript and was in line with the more latent level of analysis employed, to identify underlying ideas, rather than a more superficial descriptive analysis (Braun & Clarke, 2006). (BJHP38).

Finally, one BMJ paper (BMJ21) defended its sample size with reference to the complexity of the analytic task.

We stopped recruitment when we reached 30–35 interviews, owing to the depth and duration of interviews, richness of data, and complexity of the analytical task. (BMJ21).

Meet sampling requirements

Meeting sampling requirements (7.2% of all justifications) was another argument employed by two BMJ and four SHI articles to explain their sample size. Achieving maximum variation sampling in terms of specific interviewee characteristics determined and explained the sample size of two BMJ studies (BMJ02; BMJ16 – see extract in section Meet research design requirements ).

Recruitment continued until sampling frame requirements were met for diversity in age, sex, ethnicity, frequency of attendance, and health status. (BMJ02).

Regarding the SHI articles, two papers explained their numbers on the basis of their sampling strategy (SHI01- see extract in section Saturation ; SHI23) whilst sampling requirements that would help attain sample heterogeneity in terms of a particular characteristic of interest was cited by one paper (SHI127).

The combination of matching the recruitment sites for the quantitative research and the additional purposive criteria led to 104 phase 2 interviews (Internet (OLC): 21; Internet (FTF): 20); Gyms (FTF): 23; HIV testing (FTF): 20; HIV treatment (FTF): 20.) (SHI23). Of the fifty interviews conducted, thirty were translated from Spanish into English. These thirty, from which we draw our findings, were chosen for translation based on heterogeneity in depressive symptomology and educational attainment. (SHI127).

Finally, the pre-determination of sample size on the basis of sampling requirements was stated by one article though this was not used to justify the number of interviews (SHI10).

Sample size guidelines

Five BJHP articles (BJHP28; BJHP38 – see extract in section Qualities of the analysis ; BJHP46; BJHP47; BJHP50 – see extract in section Saturation ) and one SHI paper (SHI73) relied on citing existing sample size guidelines or norms within research traditions to determine and subsequently defend their sample size (7.2% of all justifications).

Sample size guidelines suggested a range between 20 and 30 interviews to be adequate (Creswell, 1998). Interviewer and note taker agreed that thematic saturation, the point at which no new concepts emerge from subsequent interviews (Patton, 2002), was achieved following completion of 20 interviews. (BJHP28). Interviewing continued until we deemed data saturation to have been reached (the point at which no new themes were emerging). Researchers have proposed 30 as an approximate or working number of interviews at which one could expect to be reaching theoretical saturation when using a semi-structured interview approach (Morse 2000), although this can vary depending on the heterogeneity of respondents interviewed and complexity of the issues explored. (SHI73).

In line with existing research

Sample sizes of published literature in the area of the subject matter under investigation (3.5% of all justifications) were used by 2 BMJ articles as guidance and a precedent for determining and defending their own sample size (BMJ08; BMJ15 – see extract in section Pragmatic considerations ).

We drew participants from a list of prisoners who were scheduled for release each week, sampling them until we reached the target of 35 cases, with a view to achieving data saturation within the scope of the study and sufficient follow-up interviews and in line with recent studies [8–10]. (BMJ08).

Similarly, BJHP38 (see extract in section Qualities of the analysis ) claimed that its sample size was within the range of sample sizes of published studies that use its analytic approach.

Richness and volume of data

BMJ21 (see extract in section Qualities of the analysis ) and SHI32 referred to the richness, detailed nature, and volume of data collected (2.3% of all justifications) to justify the sufficiency of their sample size.

Although there were more potential interviewees from those contacted by postcode selection, it was decided to stop recruitment after the 10th interview and focus on analysis of this sample. The material collected was considerable and, given the focused nature of the study, extremely detailed. Moreover, a high degree of consensus had begun to emerge among those interviewed, and while it is always difficult to judge at what point ‘theoretical saturation’ has been reached, or how many interviews would be required to uncover exception(s), it was felt the number was sufficient to satisfy the aims of this small in-depth investigation (Strauss and Corbin 1990). (SHI32).

Meet research design requirements

Determination of sample size so that it is in line with, and serves the requirements of, the research design (2.3% of all justifications) that the study adopted was another justification used by 2 BMJ papers (BMJ16; BMJ08 – see extract in section In line with existing research ).

We aimed for diverse, maximum variation samples [20] totalling 80 respondents from different social backgrounds and ethnic groups and those bereaved due to different types of suicide and traumatic death. We could have interviewed a smaller sample at different points in time (a qualitative longitudinal study) but chose instead to seek a broad range of experiences by interviewing those bereaved many years ago and others bereaved more recently; those bereaved in different circumstances and with different relations to the deceased; and people who lived in different parts of the UK; with different support systems and coroners’ procedures (see Tables 1 and 2 for more details). (BMJ16).

Researchers’ previous experience

The researchers’ previous experience (possibly referring to experience with qualitative research) was invoked by BMJ15 (see extract in section Pragmatic considerations ) as a justification for the determination of sample size.

Nature of study

One BJHP paper argued that the sample size was appropriate for the exploratory nature of the study (BJHP38).

A sample of eight participants was deemed appropriate because of the exploratory nature of this research and the focus on identifying underlying ideas about the topic. (BJHP38).

Further sampling to check findings consistency

Finally, SHI112 argued that once it had achieved saturation of discursive patterns, further sampling was decided and conducted to check for consistency of the findings.

Within each of the age-stratified groups, interviews were randomly sampled until saturation of discursive patterns was achieved. This resulted in a sample of 67 interviews. Once this sample had been analysed, one further interview from each age-stratified group was randomly chosen to check for consistency of the findings. Using this approach it was possible to more carefully explore children’s discourse about the ‘I’, agency, relationality and power in the thematic areas, revealing the subtle discursive variations described in this article. (SHI112).

Thematic analysis of passages discussing sample size

This analysis resulted in two overarching thematic areas; the first concerned the variation in the characterisation of sample size sufficiency, and the second related to the perceived threats deriving from sample size insufficiency.

Characterisations of sample size sufficiency

The analysis showed that there were three main characterisations of the sample size in the articles that provided relevant comments and discussion: (a) the vast majority of these qualitative studies ( n  = 42) considered their sample size as ‘small’ and this was seen and discussed as a limitation; only two articles viewed their small sample size as desirable and appropriate (b) a minority of articles ( n  = 4) proclaimed that their achieved sample size was ‘sufficient’; and (c) finally, a small group of studies ( n  = 5) characterised their sample size as ‘large’. Whilst achieving a ‘large’ sample size was sometimes viewed positively because it led to richer results, there were also occasions when a large sample size was problematic rather than desirable.

‘Small’ but why and for whom?

A number of articles which characterised their sample size as ‘small’ did so against an implicit or explicit quantitative framework of reference. Interestingly, three studies that claimed to have achieved data saturation or ‘theoretical sufficiency’ with their sample size, discussed or noted as a limitation in their discussion their ‘small’ sample size, raising the question of why, or for whom, the sample size was considered small given that the qualitative criterion of saturation had been satisfied.

The current study has a number of limitations. The sample size was small (n = 11) and, however, large enough for no new themes to emerge. (BJHP39). The study has two principal limitations. The first of these relates to the small number of respondents who took part in the study. (SHI73).

Other articles appeared to accept and acknowledge that their sample was flawed because of its small size (as well as other compositional ‘deficits’ e.g. non-representativeness, biases, self-selection) or anticipated that they might be criticized for their small sample size. It seemed that the imagined audience – perhaps reviewer or reader – was one inclined to hold the tenets of quantitative research, and certainly one to whom it was important to indicate the recognition that small samples were likely to be problematic. That one’s sample might be thought small was often construed as a limitation couched in a discourse of regret or apology.

Very occasionally, the articulation of the small size as a limitation was explicitly aligned against an espoused positivist framework and quantitative research.

This study has some limitations. Firstly, the 100 incidents sample represents a small number of the total number of serious incidents that occurs every year. 26 We sent out a nationwide invitation and do not know why more people did not volunteer for the study. Our lack of epidemiological knowledge about healthcare incidents, however, means that determining an appropriate sample size continues to be difficult. (BMJ20).

Indicative of an apparent oscillation of qualitative researchers between the different requirements and protocols demarcating the quantitative and qualitative worlds, there were a few instances of articles which briefly recognised their ‘small’ sample size as a limitation, but then defended their study on more qualitative grounds, such as their ability and success at capturing the complexity of experience and delving into the idiographic, and at generating particularly rich data.

This research, while limited in size, has sought to capture some of the complexity attached to men’s attitudes and experiences concerning incomes and material circumstances. (SHI35). Our numbers are small because negotiating access to social networks was slow and labour intensive, but our methods generated exceptionally rich data. (BMJ21). This study could be criticised for using a small and unrepresentative sample. Given that older adults have been ignored in the research concerning suntanning, fair-skinned older adults are the most likely to experience skin cancer, and women privilege appearance over health when it comes to sunbathing practices, our study offers depth and richness of data in a demographic group much in need of research attention. (SHI57).

‘Good enough’ sample sizes

Only four articles expressed some degree of confidence that their achieved sample size was sufficient. For example, SHI139, in line with the justification of thematic saturation that it offered, expressed trust in its sample size sufficiency despite the poor response rate. Similarly, BJHP04, which did not provide a sample size justification, argued that it targeted a larger sample size in order to eventually recruit a sufficient number of interviewees, due to anticipated low response rate.

Twenty-three people with type I diabetes from the target population of 133 ( i.e. 17.3%) consented to participate but four did not then respond to further contacts (total N = 19). The relatively low response rate was anticipated, due to the busy life-styles of young people in the age range, the geographical constraints, and the time required to participate in a semi-structured interview, so a larger target sample allowed a sufficient number of participants to be recruited. (BJHP04).

Two other articles (BJHP35; SHI32) linked the claimed sufficiency to the scope (i.e. ‘small, in-depth investigation’), aims and nature (i.e. ‘exploratory’) of their studies, thus anchoring their numbers to the particular context of their research. Nevertheless, claims of sample size sufficiency were sometimes undermined when they were juxtaposed with an acknowledgement that a larger sample size would be more scientifically productive.

Although our sample size was sufficient for this exploratory study, a more diverse sample including participants with lower socioeconomic status and more ethnic variation would be informative. A larger sample could also ensure inclusion of a more representative range of apps operating on a wider range of platforms. (BJHP35).

‘Large’ sample sizes - Promise or peril?

Three articles (BMJ13; BJHP05; BJHP48) which all provided the justification of saturation, characterised their sample size as ‘large’ and narrated this oversufficiency in positive terms as it allowed richer data and findings and enhanced the potential for generalisation. The type of generalisation aspired to (BJHP48) was not further specified however.

This study used rich data provided by a relatively large sample of expert informants on an important but under-researched topic. (BMJ13). Qualitative research provides a unique opportunity to understand a clinical problem from the patient’s perspective. This study had a large diverse sample, recruited through a range of locations and used in-depth interviews which enhance the richness and generalizability of the results. (BJHP48).

And whilst a ‘large’ sample size was endorsed and valued by some qualitative researchers, within the psychological tradition of IPA, a ‘large’ sample size was counter-normative and therefore needed to be justified. Four BJHP studies, all adopting IPA, expressed the appropriateness or desirability of ‘small’ sample sizes (BJHP41; BJHP45) or hastened to explain why they included a larger than typical sample size (BJHP32; BJHP47). For example, BJHP32 below provides a rationale for how an IPA study can accommodate a large sample size and how this was indeed suitable for the purposes of the particular research. To strengthen the explanation for choosing a non-normative sample size, previous IPA research citing a similar sample size approach is used as a precedent.

Small scale IPA studies allow in-depth analysis which would not be possible with larger samples (Smith et al. , 2009). (BJHP41). Although IPA generally involves intense scrutiny of a small number of transcripts, it was decided to recruit a larger diverse sample as this is the first qualitative study of this population in the United Kingdom (as far as we know) and we wanted to gain an overview. Indeed, Smith, Flowers, and Larkin (2009) agree that IPA is suitable for larger groups. However, the emphasis changes from an in-depth individualistic analysis to one in which common themes from shared experiences of a group of people can be elicited and used to understand the network of relationships between themes that emerge from the interviews. This large-scale format of IPA has been used by other researchers in the field of false-positive research. Baillie, Smith, Hewison, and Mason (2000) conducted an IPA study, with 24 participants, of ultrasound screening for chromosomal abnormality; they found that this larger number of participants enabled them to produce a more refined and cohesive account. (BJHP32).

The IPA articles found in the BJHP were the only instances where a ‘small’ sample size was advocated and a ‘large’ sample size problematized and defended. These IPA studies illustrate that the characterisation of sample size sufficiency can be a function of researchers’ theoretical and epistemological commitments rather than the result of an ‘objective’ sample size assessment.

Threats from sample size insufficiency

As shown above, the majority of articles that commented on their sample size, simultaneously characterized it as small and problematic. On those occasions that authors did not simply cite their ‘small’ sample size as a study limitation but rather continued and provided an account of how and why a small sample size was problematic, two important scientific qualities of the research seemed to be threatened: the generalizability and validity of results.

Generalizability

Those who characterised their sample as ‘small’ connected this to the limited potential for generalization of the results. Other features related to the sample – often some kind of compositional particularity – were also linked to limited potential for generalisation. Though not always explicitly articulated to what form of generalisation the articles referred to (see BJHP09), generalisation was mostly conceived in nomothetic terms, that is, it concerned the potential to draw inferences from the sample to the broader study population (‘representational generalisation’ – see BJHP31) and less often to other populations or cultures.

It must be noted that samples are small and whilst in both groups the majority of those women eligible participated, generalizability cannot be assumed. (BJHP09). The study’s limitations should be acknowledged: Data are presented from interviews with a relatively small group of participants, and thus, the views are not necessarily generalizable to all patients and clinicians. In particular, patients were only recruited from secondary care services where COFP diagnoses are typically confirmed. The sample therefore is unlikely to represent the full spectrum of patients, particularly those who are not referred to, or who have been discharged from dental services. (BJHP31).

Without explicitly using the term generalisation, two SHI articles noted how their ‘small’ sample size imposed limits on ‘the extent that we can extrapolate from these participants’ accounts’ (SHI114) or to the possibility ‘to draw far-reaching conclusions from the results’ (SHI124).

Interestingly, only a minority of articles alluded to, or invoked, a type of generalisation that is aligned with qualitative research, that is, idiographic generalisation (i.e. generalisation that can be made from and about cases [ 5 ]). These articles, all published in the discipline of sociology, defended their findings in terms of the possibility of drawing logical and conceptual inferences to other contexts and of generating understanding that has the potential to advance knowledge, despite their ‘small’ size. One article (SHI139) clearly contrasted nomothetic (statistical) generalisation to idiographic generalisation, arguing that the lack of statistical generalizability does not nullify the ability of qualitative research to still be relevant beyond the sample studied.

Further, these data do not need to be statistically generalisable for us to draw inferences that may advance medicalisation analyses (Charmaz 2014). These data may be seen as an opportunity to generate further hypotheses and are a unique application of the medicalisation framework. (SHI139). Although a small-scale qualitative study related to school counselling, this analysis can be usefully regarded as a case study of the successful utilisation of mental health-related resources by adolescents. As many of the issues explored are of relevance to mental health stigma more generally, it may also provide insights into adult engagement in services. It shows how a sociological analysis, which uses positioning theory to examine how people negotiate, partially accept and simultaneously resist stigmatisation in relation to mental health concerns, can contribute to an elucidation of the social processes and narrative constructions which may maintain as well as bridge the mental health service gap. (SHI103).

Only one article (SHI30) used the term transferability to argue for the potential of wider relevance of the results which was thought to be more the product of the composition of the sample (i.e. diverse sample), rather than the sample size.

The second major concern that arose from a ‘small’ sample size pertained to the internal validity of findings (i.e. here the term is used to denote the ‘truth’ or credibility of research findings). Authors expressed uncertainty about the degree of confidence in particular aspects or patterns of their results, primarily those that concerned some form of differentiation on the basis of relevant participant characteristics.

The information source preferred seemed to vary according to parents’ education; however, the sample size is too small to draw conclusions about such patterns. (SHI80). Although our numbers were too small to demonstrate gender differences with any certainty, it does seem that the biomedical and erotic scripts may be more common in the accounts of men and the relational script more common in the accounts of women. (SHI81).

In other instances, articles expressed uncertainty about whether their results accounted for the full spectrum and variation of the phenomenon under investigation. In other words, a ‘small’ sample size (alongside compositional ‘deficits’ such as a not statistically representative sample) was seen to threaten the ‘content validity’ of the results which in turn led to constructions of the study conclusions as tentative.

Data collection ceased on pragmatic grounds rather than when no new information appeared to be obtained ( i.e. , saturation point). As such, care should be taken not to overstate the findings. Whilst the themes from the initial interviews seemed to be replicated in the later interviews, further interviews may have identified additional themes or provided more nuanced explanations. (BJHP53). …it should be acknowledged that this study was based on a small sample of self-selected couples in enduring marriages who were not broadly representative of the population. Thus, participants may not be representative of couples that experience postnatal PTSD. It is therefore unlikely that all the key themes have been identified and explored. For example, couples who were excluded from the study because the male partner declined to participate may have been experiencing greater interpersonal difficulties. (BJHP03).

In other instances, articles attempted to preserve a degree of credibility of their results, despite the recognition that the sample size was ‘small’. Clarity and sharpness of emerging themes and alignment with previous relevant work were the arguments employed to warrant the validity of the results.

This study focused on British Chinese carers of patients with affective disorders, using a qualitative methodology to synthesise the sociocultural representations of illness within this community. Despite the small sample size, clear themes emerged from the narratives that were sufficient for this exploratory investigation. (SHI98).

The present study sought to examine how qualitative sample sizes in health-related research are characterised and justified. In line with previous studies [ 22 , 30 , 33 , 34 ] the findings demonstrate that reporting of sample size sufficiency is limited; just over 50% of articles in the BMJ and BJHP and 82% in the SHI did not provide any sample size justification. Providing a sample size justification was not related to the number of interviews conducted, but it was associated with the journal that the article was published in, indicating the influence of disciplinary or publishing norms, also reported in prior research [ 30 ]. This lack of transparency about sample size sufficiency is problematic given that most qualitative researchers would agree that it is an important marker of quality [ 56 , 57 ]. Moreover, and with the rise of qualitative research in social sciences, efforts to synthesise existing evidence and assess its quality are obstructed by poor reporting [ 58 , 59 ].

When authors justified their sample size, our findings indicate that sufficiency was mostly appraised with reference to features that were intrinsic to the study, in agreement with general advice on sample size determination [ 4 , 11 , 36 ]. The principle of saturation was the most commonly invoked argument [ 22 ] accounting for 55% of all justifications. A wide range of variants of saturation was evident corroborating the proliferation of the meaning of the term [ 49 ] and reflecting different underlying conceptualisations or models of saturation [ 20 ]. Nevertheless, claims of saturation were never substantiated in relation to procedures conducted in the study itself, endorsing similar observations in the literature [ 25 , 30 , 47 ]. Claims of saturation were sometimes supported with citations of other literature, suggesting a removal of the concept away from the characteristics of the study at hand. Pragmatic considerations, such as resource constraints or participant response rate and availability, was the second most frequently used argument accounting for approximately 10% of justifications and another 23% of justifications also represented intrinsic-to-the-study characteristics (i.e. qualities of the analysis, meeting sampling or research design requirements, richness and volume of the data obtained, nature of study, further sampling to check findings consistency).

Only, 12% of mentions of sample size justification pertained to arguments that were external to the study at hand, in the form of existing sample size guidelines and prior research that sets precedents. Whilst community norms and prior research can establish useful rules of thumb for estimating sample sizes [ 60 ] – and reveal what sizes are more likely to be acceptable within research communities – researchers should avoid adopting these norms uncritically, especially when such guidelines [e.g. 30 , 35 ], might be based on research that does not provide adequate evidence of sample size sufficiency. Similarly, whilst methodological research that seeks to demonstrate the achievement of saturation is invaluable since it explicates the parameters upon which saturation is contingent and indicates when a research project is likely to require a smaller or a larger sample [e.g. 29 ], specific numbers at which saturation was achieved within these projects cannot be routinely extrapolated for other projects. We concur with existing views [ 11 , 36 ] that the consideration of the characteristics of the study at hand, such as the epistemological and theoretical approach, the nature of the phenomenon under investigation, the aims and scope of the study, the quality and richness of data, or the researcher’s experience and skills of conducting qualitative research, should be the primary guide in determining sample size and assessing its sufficiency.

Moreover, although numbers in qualitative research are not unimportant [ 61 ], sample size should not be considered alone but be embedded in the more encompassing examination of data adequacy [ 56 , 57 ]. Erickson’s [ 62 ] dimensions of ‘evidentiary adequacy’ are useful here. He explains the concept in terms of adequate amounts of evidence, adequate variety in kinds of evidence, adequate interpretive status of evidence, adequate disconfirming evidence, and adequate discrepant case analysis. All dimensions might not be relevant across all qualitative research designs, but this illustrates the thickness of the concept of data adequacy, taking it beyond sample size.

The present research also demonstrated that sample sizes were commonly seen as ‘small’ and insufficient and discussed as limitation. Often unjustified (and in two cases incongruent with their own claims of saturation) these findings imply that sample size in qualitative health research is often adversely judged (or expected to be judged) against an implicit, yet omnipresent, quasi-quantitative standpoint. Indeed there were a few instances in our data where authors appeared, possibly in response to reviewers, to resist to some sort of quantification of their results. This implicit reference point became more apparent when authors discussed the threats deriving from an insufficient sample size. Whilst the concerns about internal validity might be legitimate to the extent that qualitative research projects, which are broadly related to realism, are set to examine phenomena in sufficient breadth and depth, the concerns around generalizability revealed a conceptualisation that is not compatible with purposive sampling. The limited potential for generalisation, as a result of a small sample size, was often discussed in nomothetic, statistical terms. Only occasionally was analytic or idiographic generalisation invoked to warrant the value of the study’s findings [ 5 , 17 ].

Strengths and limitations of the present study

We note, first, the limited number of health-related journals reviewed, so that only a ‘snapshot’ of qualitative health research has been captured. Examining additional disciplines (e.g. nursing sciences) as well as inter-disciplinary journals would add to the findings of this analysis. Nevertheless, our study is the first to provide some comparative insights on the basis of disciplines that are differently attached to the legacy of positivism and analysed literature published over a lengthy period of time (15 years). Guetterman [ 27 ] also examined health-related literature but this analysis was restricted to 26 most highly cited articles published over a period of five years whilst Carlsen and Glenton’s [ 22 ] study concentrated on focus groups health research. Moreover, although it was our intention to examine sample size justification in relation to the epistemological and theoretical positions of articles, this proved to be challenging largely due to absence of relevant information, or the difficulty into discerning clearly articles’ positions [ 63 ] and classifying them under specific approaches (e.g. studies often combined elements from different theoretical and epistemological traditions). We believe that such an analysis would yield useful insights as it links the methodological issue of sample size to the broader philosophical stance of the research. Despite these limitations, the analysis of the characterisation of sample size and of the threats seen to accrue from insufficient sample size, enriches our understanding of sample size (in)sufficiency argumentation by linking it to other features of the research. As the peer-review process becomes increasingly public, future research could usefully examine how reporting around sample size sufficiency and data adequacy might be influenced by the interactions between authors and reviewers.

The past decade has seen a growing appetite in qualitative research for an evidence-based approach to sample size determination and to evaluations of the sufficiency of sample size. Despite the conceptual and methodological developments in the area, the findings of the present study confirm previous studies in concluding that appraisals of sample size sufficiency are either absent or poorly substantiated. To ensure and maintain high quality research that will encourage greater appreciation of qualitative work in health-related sciences [ 64 ], we argue that qualitative researchers should be more transparent and thorough in their evaluation of sample size as part of their appraisal of data adequacy. We would encourage the practice of appraising sample size sufficiency with close reference to the study at hand and would thus caution against responding to the growing methodological research in this area with a decontextualised application of sample size numerical guidelines, norms and principles. Although researchers might find sample size community norms serve as useful rules of thumb, we recommend methodological knowledge is used to critically consider how saturation and other parameters that affect sample size sufficiency pertain to the specifics of the particular project. Those reviewing papers have a vital role in encouraging transparent study-specific reporting. The review process should support authors to exercise nuanced judgments in decisions about sample size determination in the context of the range of factors that influence sample size sufficiency and the specifics of a particular study. In light of the growing methodological evidence in the area, transparent presentation of such evidence-based judgement is crucial and in time should surely obviate the seemingly routine practice of citing the ‘small’ size of qualitative samples among the study limitations.

A non-parametric test of difference for independent samples was performed since the variable number of interviews violated assumptions of normality according to the standardized scores of skewness and kurtosis (BMJ: z skewness = 3.23, z kurtosis = 1.52; BJHP: z skewness = 4.73, z kurtosis = 4.85; SHI: z skewness = 12.04, z kurtosis = 21.72) and the Shapiro-Wilk test of normality ( p  < .001).

Abbreviations

British Journal of Health Psychology

British Medical Journal

Interpretative Phenomenological Analysis

Sociology of Health & Illness

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Acknowledgments

We would like to thank Dr. Paula Smith and Katharine Lee for their comments on a previous draft of this paper as well as Natalie Ann Mitchell and Meron Teferra for assisting us with data extraction.

This research was initially conceived of and partly conducted with financial support from the Multidisciplinary Assessment of Technology Centre for Healthcare (MATCH) programme (EP/F063822/1 and EP/G012393/1). The research continued and was completed independent of any support. The funding body did not have any role in the study design, the collection, analysis and interpretation of the data, in the writing of the paper, and in the decision to submit the manuscript for publication. The views expressed are those of the authors alone.

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JB and TY conceived the study; KV, JB, and TY designed the study; KV identified the articles and extracted the data; KV and JB assessed eligibility of articles; KV, JB, ST, and TY contributed to the analysis of the data, discussed the findings and early drafts of the paper; KV developed the final manuscript; KV, JB, ST, and TY read and approved the manuscript.

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Additional Files

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Editorial positions on qualitative research and sample considerations (where available). (DOCX 12 kb)

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List of eligible articles included in the review ( N  = 214). (DOCX 38 kb)

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Citations used by articles to support their position on saturation. (DOCX 14 kb)

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Vasileiou, K., Barnett, J., Thorpe, S. et al. Characterising and justifying sample size sufficiency in interview-based studies: systematic analysis of qualitative health research over a 15-year period. BMC Med Res Methodol 18 , 148 (2018). https://doi.org/10.1186/s12874-018-0594-7

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Articles and blog posts

How to choose the right sample size for a qualitative study… and convince your supervisor that you know what you’re doing.

The question of how many participants are enough for a qualitative interview is, in my opinion, one of the most difficult questions to find an answer to in the literature. In fact, many authors who set out to find specific guidelines on the ideal sample size in qualitative research in the literature have also concluded that these are “virtually non-existent” (Guest, Bunce and Johnson, 2005: 59).   This is particularly unfortunate, given that as a student planning to undertake your research, one of the things that will be most likely to be asked of you is to indicate, and justify, the number of participants in your planned study (this also includes your PhD proposal in which you are expected to give as much detail of the study as possible).

If you, then, turn to the literature, hoping to find advice from some of the great minds in research methodology, you are likely to find them evading the question and often hiding behind the term “saturation” which refers to the point at which gathering new data does not provide any new theoretical insights into the studied phenomenon. Although the concept of saturation may also be controversial, not least because the longer you explore, analyse and reflect on your data, you are always likely to find something “new” in it, it has come to be the guiding concept in establishing sample size in many qualitative studies. As Guest, Bunce and Johnson (2005) rightly point out, however

“although the idea of saturation is helpful at the conceptual level, it provides little practical guidance for estimating sample sizes for robust research prior to data collection”

     (Guest, Bunce and Johnson, 2005: 59)

In other words – how in the world are we supposed to know when we will reach saturation PRIOR TO THE STUDY???

My advice is to use the available literature on the point of saturation and use it to justify your decision regarding the sample size. I did it for my PhD study, as I was growing frustrated that I really have to justify my decision to include 20 participants for an interview, even though I had read dozens of reports in which this number, or smaller, was common (“are you going to interview 20 participants just because others did?”). I just felt that this would be enough, and my common sense, which as I learnt throughout my PhD was the last thing that anyone would care about, was telling me the same thing. In order to support my decision with the literature, however, and considering that there are hardly any guidelines for establishing sample size , I decided to try to reach some sort of conclusion as to how many participants are enough to reach saturation and use it as my main argument for establishing the size of the sample.

So what does the literature tell us about this? Just as there is not single answer as to what sample size is sufficient, there is no single answer to the question of what sample size is sufficient to reach theoretical saturation .  Such factors as heterogeneity of the studied population, the scope of the study and the adopted methods and their application (e.g. the length of the interviews) are believed, however, to have a central role in achieving this (cf. Baker and Edwards, 2012; Guest, Bunce and Johnson, 2005; Mason, 2010). Mason’s (2010) analysis of 560 PhD studies that adopted a qualitative interview as their main method revealed that the most common sample size in qualitative research is between 15 and 50 participants, with 20 being the average sample size in grounded theory studies (which was also the type of study I was undertaking). Guest, Bunce and Johnson (2005) used data from their own study to conclude that 88% of the codes they developed when analysing the data from 60 qualitative interviews were created by the time 12 interviews had been conducted.

These findings helped me in arguing that my initial sample size was going to be 20. “Given the detailed design of the study, which includes triangulation of the data and methods”, I argued, “I believe that this number will enable me to make valid judgements about the general trends emerging in the data”. I also stated that I am planning to recruit more participants, should the saturation not occur.

I hope that this article will help you in your quest to determine the sample size for your study and give you an idea of how you can go about arguing that it is a well thought-through decision. Do remember, however, that 20 participants may be enough for one study and not enough, or too many, for another. The point of this article was not to argue that 20 participants is a universally right number for a qualitative study, but rather to point to the fact that there is no such universally right number and that you are not the only one struggling to find guidelines regarding the interview sample size, as well as to put forward the concept of saturation as one of possible principles that may guide you in deciding how many participants to recruit for your study.

If you have any questions regarding this topic, comment below or send me a message through my Facebook page .

• UPDATE – see my Facebook page for my response to the question about the relevance of “saturation” for Phenomenological research

References:

Baker, S. & Edwards, R. (eds., 2012). How many qualitative interviews is enough? Expert voices and early career reflections on sampling and cases in qualitative research. National Centre for Research Methods , 1-42.

Guest, G., Bunce, A. & Johnson, L. (2005). How many interviews are enough? An experiment with data saturation and variability. Field Methods, 18 (1), 59-82.

Mason, M. (2010). Sample Size and Saturation in PhD Studies Using Qualitative Interviews. Forum Qualitative Sozialforschung / Forum: Qualitative Social Research, 11 (3).

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Qualitative Research Part II: Participants, Analysis, and Quality Assurance

This is the second of a two-part series on qualitative research. Part 1 in the December 2011 issue of Journal of Graduate Medical Education provided an introduction to the topic and compared characteristics of quantitative and qualitative research, identified common data collection approaches, and briefly described data analysis and quality assessment techniques. Part II describes in more detail specific techniques and methods used to select participants, analyze data, and ensure research quality and rigor.

If you are relatively new to qualitative research, some references you may find especially helpful are provided below. The two texts by Creswell 2008 and 2009 are clear and practical. 1 , 2 In 2008, the British Medical Journal offered a series of short essays on qualitative research; the references provided are easily read and digested. 3 – , 8 For those wishing to pursue qualitative research in more detail, a suggestion is to start with the appropriate chapters in Creswell 2008, 1 and then move to the other texts suggested. 9 – , 11

To summarize the previous editorial, while quantitative research focuses predominantly on the impact of an intervention and generally answers questions like “did it work?” and “what was the outcome?”, qualitative research focuses on understanding the intervention or phenomenon and exploring questions like “why was this effective or not?” and “how is this helpful for learning?” The intent of qualitative research is to contribute to understanding. Hence, the research procedures for selecting participants, analyzing data, and ensuring research rigor differ from those for quantitative research. The following sections address these approaches. table 1 provides a comparative summary of methodological approaches for quantitative and qualitative research.

A Comparison of Qualitative and Quantitative Methodological Approaches

Data collection methods most commonly used in qualitative research are individual or group interviews (including focus groups), observation, and document review. They can be used alone or in combination. While the following sections are written in the context of using interviews or focus groups to collect data, the principles described for sample selection, data analysis, and quality assurance are applicable across qualitative approaches.

Selecting Participants

Quantitative research requires standardization of procedures and random selection of participants to remove the potential influence of external variables and ensure generalizability of results. In contrast, subject selection in qualitative research is purposeful; participants are selected who can best inform the research questions and enhance understanding of the phenomenon under study. 1 , 8 Hence, one of the most important tasks in the study design phase is to identify appropriate participants. Decisions regarding selection are based on the research questions, theoretical perspectives, and evidence informing the study.

The subjects sampled must be able to inform important facets and perspectives related to the phenomenon being studied. For example, in a study looking at a professionalism intervention, representative participants could be considered by role (residents and faculty), perspective (those who approve/disapprove the intervention), experience level (junior and senior residents), and/or diversity (gender, ethnicity, other background).

The second consideration is sample size. Quantitative research requires statistical calculation of sample size a priori to ensure sufficient power to confirm that the outcome can indeed be attributed to the intervention. In qualitative research, however, the sample size is not generally predetermined. The number of participants depends upon the number required to inform fully all important elements of the phenomenon being studied. That is, the sample size is sufficient when additional interviews or focus groups do not result in identification of new concepts, an end point called data saturation . To determine when data saturation occurs, analysis ideally occurs concurrently with data collection in an iterative cycle. This allows the researcher to document the emergence of new themes and also to identify perspectives that may otherwise be overlooked. In the professionalism intervention example, as data are analyzed, the researchers may note that only positive experiences and views are being reported. At this time, a decision could be made to identify and recruit residents who perceived the experience as less positive.

Data Analysis

The purpose of qualitative analysis is to interpret the data and the resulting themes, to facilitate understanding of the phenomenon being studied. It is often confused with content analysis, which is conducted to identify and describe results. 12 In the professionalism intervention example, content analysis of responses might report that residents identified the positive elements of the innovation to be integration with real patient cases, opportunity to hear the views of others, and time to reflect on one's own professionalism. An interpretive analysis, on the other hand, would seek to understand these responses by asking questions such as, “Were there conditions that most frequently elicited these positive responses?” Further interpretive analysis might show that faculty engagement influenced the positive responses, with more positive features being described by residents who had faculty who openly reflected upon their own professionalism or who asked probing questions about the cases. This interpretation can lead to a deeper understanding of the results and to new ideas or theories about relationships and/or about how and why the innovation was or was not effective.

Interpretive analysis is generally seen as being conducted in 3 stages: deconstruction, interpretation, and reconstruction. 11 These stages occur after preparing the data for analysis, ie, after transcription of the interviews or focus groups and verification of the transcripts with the recording.

• Deconstruction refers to breaking down data into component parts in order to see what is included. It is similar to content analysis mentioned above. It requires reading and rereading interview or focus group transcripts and then breaking down data into categories or codes that describe the content.
• Interpretation follows deconstruction and refers to making sense of and understanding the coded data. It involves comparing data codes and categories within and across transcripts and across variables deemed important to the study (eg, year of residency, discipline, engagement of faculty). Techniques for interpreting data and findings include discussion and comparison of codes among research team members while purposefully looking for similarities and differences among themes, comparing findings with those of other studies, exploring theories which might explain relationships among themes, and exploring negative results (those that do not confirm the dominant themes) in more detail.
• Reconstruction refers to recreating or repackaging the prominent codes and themes in a manner that shows the relationships and insights derived in the interpretation phase and that explains them more broadly in light of existing knowledge and theoretical perspectives. Generally one or two central concepts will emerge as central or overarching, and others will appear as subthemes that further contribute to the central concepts. Reconstruction requires contextualizing the findings, ie, positioning and framing them within existing theory, evidence, and practice.

Ensuring Research Quality and Rigor

Within qualitative research, two main strategies promote the rigor and quality of the research: ensuring the quality or “authenticity” of the data and the quality or “trustworthiness” of the analysis. 8 , 12 These are similar in many ways to ensuring validity and reliability, respectively, in quantitative research.

 1. Authenticity of the data refers to the quality of the data and data collection procedures. Elements to consider include:

  • Sampling approach and participant selection to enable the research question to be addressed appropriately (see “Selecting Participants” above) and reduce the potential of having a biased sample.

  •  Data triangulation refers to using multiple data sources to produce a more comprehensive view of the phenomenon being studied, eg, interviewing both residents and faculty and using multiple residency sites and/or disciplines.

  • Using the appropriate method to answer the research questions, considering the nature of the topic being explored, eg, individual interviews rather than focus groups are generally more appropriate for topics of a sensitive nature.

  • Using interview and other guides that are not biased or leading, ie, that do not ask questions in a way that may lead the participant to answer in a particular manner.

  • The researcher's and research team's relationships to the study setting and participants need to be explicit, eg, describe the potential for coercion when a faculty member requests his or her own residents to participate in a study.

  • The researcher's and team members' own biases and beliefs relative to the phenomenon under study must be made explicit, and, when necessary, appropriate steps must be taken to reduce their impact on the quality of data collected, eg, by selecting a neutral “third party” interviewer.

 2. Trustworthiness of the analysis refers to the quality of data analysis. Elements to consider when assessing the quality of analysis include:

  • Analysis process: is this clearly described, eg, the roles of the team members, what was done, timing, and sequencing? Is it clear how the data codes or categories were developed? Does the process reflect best practices, eg, comparison of findings within and among transcripts, and use of memos to record decision points?

  • Procedure for resolving differences in findings and among team members: this needs to be clearly described.

  • Process for addressing the potential influence the researchers' views and beliefs may have upon the analysis.

  • Use of a qualitative software program: if used, how was this used?

In summary, this editorial has addressed 3 components of conducting qualitative research: selecting participants, performing data analysis, and assuring research rigor and quality. See table 2 for the key elements for each of these topics.

Conducting Qualitative Research: Summary of Key Elements

JGME editors look forward to reading medical education papers employing qualitative methods and perspectives. We trust these two editorials may be helpful to potential authors and readers, and we welcome your comments on this subject.

Joan Sargeant, PhD, is Professor in the Division of Medical Education, Dalhousie University, Halifax, Nova Scotia, Canada.

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Qualitative Research

What is qualitative research.

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

The Basic Idea

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Thomas Kuhn

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

Paul Felix Lazarsfeld

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

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

George Herbert Mead

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

Consequences

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

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

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

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

Controversies

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

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

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

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

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

Linking Adult Behaviors to Childhood Experiences

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

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

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

Understanding Voter Turnout

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

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

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

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

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• Published: 30 August 2024

A qualitative investigation of financial decision-making and enabling factors among ethnic minority young adults in Hong Kong

• Esther Yin-Nei Cho 1  

Humanities and Social Sciences Communications volume  11 , Article number:  1113 ( 2024 ) Cite this article

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Current understanding of financial decision-making among racial/ethnic minority young adults is limited: day-to-day financial decisions of racial/ethnic minorities are underexamined, younger racial/ethnic minorities receive limited attention, studies on racial/ethnic minorities are mainly conducted in Western societies, and research on financial literacy and decision-making is predominantly quantitative in nature. Against this backdrop, this study utilized a qualitative approach to examine a range of financial decision-making among ethnic minority young adults in Hong Kong, including personal budgeting, spending, financial planning, the use of financial products, debt management, and the detection of financial fraud. Individual interviews were conducted with 53 Pakistani, Indian, Nepalese, and Filipino participants aged 18 to 29 who employed various budgeting strategies and faced challenges. Their spending was modest, and they espoused various spending philosophies. Many saved approximately one-third of their income using saving tactics and setting financial goals, and investing in both Hong Kong and their home countries. Informal borrowing was common, though some sought alternative loans. One-third used credit cards, with accompanying occasional risks. Despite employing protective tactics, they still fell victim to scams. Factors facilitating their financial decision-making include family social capital, intrapersonal characteristics, social dynamics factors, command of knowledge, and facilitative contextual circumstances. This study addresses knowledge gaps by providing an in-depth understanding of financial decision-making among ethnic minority young adults in a non-Western context. It has significant implications for timely and tailored financial literacy education for minority societal members.

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Introduction.

Extensive attention has been given to studying and promoting financial literacy, as shown by the burgeoning literature on the subject (e.g., Angrisani et al., 2021 ; Atkinson and Messy, 2012 ; Kempson, 2009 ; Lusardi and Mitchell, 2007 ), financial literacy incorporated as a national priority (OECD, 2015a ), and the proliferation of financial education programs worldwide (Kaiser and Menkhoff, 2020 ). The primary reason for this attention and effort lies in the growing awareness of the generally low levels of financial literacy across the world (e.g., Lusardi, 2019 ; Lusardi and Mitchell, 2011a ) and its impact on financial well-being, which, in turn, influences overall individual and societal well-being (Grohmann et al., 2018 ).

There is no universal definition of financial literacy, but the definitions used in the literature are essentially similar (e.g., Atkinson and Messy, 2012 ; Hung et al., 2009 ; OECD, 2015b ). For instance, financial literacy is defined as the “knowledge of basic economic and financial concepts, as well as the ability to use that knowledge and other financial skills to manage financial resources effectively for a lifetime of financial well-being” (Hung et al., 2009 , p.12) or “a combination of awareness, knowledge, skill, attitude, and behavior necessary to make sound financial decisions and ultimately achieve individual financial well-being” (Atkinson and Messy, 2012 , p.14). The terms “financial literacy” and “financial capability” are often used interchangeably (e.g., Muir et al., 2017 ; Xiao et al., 2014 ), referring to the ability to apply appropriate financial knowledge and engage in financial behaviors to achieve financial well-being (Xiao et al., 2014 ), though it may also include access to financial resources (Johnson and Sherraden, 2007 ).

These slightly different definitions converge around three interrelated ideas. First, financial literacy consists of basic elements, such as knowledge, attitudes, skills, and behavior, necessary for making financial decisions. Second, it involves the ability to apply these elements for sound financial decision-making. Third, financial literacy ultimately affects financial well-being through improved financial decision-making. Therefore, the extent of individuals’ financial literacy is not merely determined by their knowledge but also by how well they apply knowledge in their decision-making, which requires practice and judgement (Worthington, 2006 ). To fully understand people’s financial literacy, it is also necessary to examine their financial decisions in terms of both their practice and perceptions.

Disparities in financial literacy among different population groups have been documented based on characteristics such as age, gender, education, race/ethnicity, income level, and marital status (e.g., Brown and Graf, 2013 ; Lusardi et al., 2010 ; Lusardi and Mitchell, 2011a , 2011b ). Racial/ethnic minorities comprise one of the most vulnerable groups (Al-Bahrani et al., 2019 ; Angrisani et al., 2021 ; Brown and Graf, 2013 ; Lusardi and Mitchell, 2011b ). For example, Black and Hispanic individuals in the USA tend to score lower on financial literacy questions than Whites (Lusardi and Mitchell, 2011b ). While it is recognized that racial/ethnic minorities have lower levels of financial knowledge, a more comprehensive understanding of their financial literacy is still needed.

First, racial/ethnic minorities’ financial decision-making has not been sufficiently examined. Existing studies focus on banking accounts (Barcellos and Zamarro, 2021 ; Kim et al., 2016 ; Lusardi, 2005 ), credit use and debts (Ekanem, 2013 ; Gaur et al., 2020 ; Goodstein et al., 2021 ; Yao et al., 2011 ), asset holding (Lusardi, 2005 ), and retirement planning (Kim et al., 2021 ). Other important day-to-day financial decisions are less understood, such as budgeting, savings, using other financial products, and detecting financial fraud.

Second, younger members of racial/ethnic minorities, who face double challenges, have received limited attention. As racial/ethnic minorities, they already have low levels of financial literacy. As younger adults, they are more financially vulnerable than their older counterparts. Not only do they have lower levels of financial knowledge, such as inflation, compound interest, and risk diversification (Lusardi et al., 2010 ; Lusardi and Mitchell, 2011a ), but they also face more financial challenges due to longer life spans, more financial decisions to make, and greater financial risks in an increasingly complex global financial environment.

Third, most studies on racial/ethnic minorities have been conducted in Western societies, particularly the USA, with more limited research conducted in other contexts, such as Asian societies.

Fourth, research on financial literacy is predominantly quantitative (Goyal and Kumar, 2021 ; Kelley et al., 2021 ). Qualitative studies are few, particularly regarding racial/ethnic minorities (Ekanem, 2013 ; Gaur et al., 2020 ). While quantitative studies provide a broad perspective on the subject matter, qualitative studies offer an in-depth understanding of how individuals perceive and make meaning of their financial decisions. This information is valuable for informing financial literacy education and thus improving financial decision-making.

This study examined a range of financial decisions made by ethnic minority young adults in Hong Kong using qualitative inquiry to address these limitations. By adopting a qualitative approach, the study focuses on generating themes that may not be captured in quantitative studies relying on statistical figures. It extends the literature by providing a deeper understanding of the financial decisions made by younger ethnic minority individuals within a non-Western context. The findings also reveal factors facilitating sound financial decision-making among ethnic minority younger people, particularly in Hong Kong. These findings have important implications for tailoring “just-in-time” financial literacy education to meet their specific needs, as opposed to a “one-size-fits-all” approach (Goyal and Kumar, 2021 ).

In the following, after briefly highlighting the relevant literature on financial literacy and financial decisions, the findings on ethnic minority young adults regarding different areas of financial decision-making will be presented. Factors facilitating their financial decision-making will be identified, and implications for financial literacy education and further research discussed.

A brief overview of financial literacy and financial decisions

Patterns of financial literacy.

Financial literacy levels are associated with various socioeconomic factors, including age, gender, education, parental education, employment status, marital status, area of residence, and race and ethnicity. Financial literacy exhibits a bell curve distribution with age. It is lower among young and old individuals than those in the middle of the life cycle (Atkinson and Messy, 2012 ; Brown and Graf, 2013 ). For instance, less than one-third of young adults possess basic concepts about inflation, risk diversification, and compound interest (Lusardi et al., 2010 ; Lusardi and Mitchell, 2011a ). Regarding gender, women tend to have lower levels of financial literacy than men. They have less financial knowledge about debt, inflation, risk diversification, and compound interest (Brown and Graf, 2013 ; Lusardi and Mitchell, 2011a ; Lusardi and Tufano, 2015 ) and are less likely to plan for retirement (Herd et al., 2012 ). Educational attainment is positively related to financial literacy (Herd et al., 2012 ; Klapper et al., 2012 ; Lusardi and Mitchell, 2007 , 2011a ). Less well-educated people are less likely to answer financial literacy questions correctly and tend to indicate not knowing the answer (Lusardi and Mitchell, 2011a ). Individuals without a college degree are less likely to understand concepts about inflation, risk diversification, and simple interest calculations (Herd et al., 2012 ). More educated people tend to have positive attitudes towards retirement planning (van Rooij et al., 2011a ) and possess a bank account (Klapper et al., 2012 ). Parental education, particularly mothers’ education, and parents’ possession of stock or retirement accounts are positively related to financial literacy (Lusardi et al., 2010 ). Fathers’ education is positively associated with their daughters’ financial literacy (Mahdavi and Horton, 2014 ). In terms of employment status, employed individuals have substantially higher levels of financial literacy than those who are unemployed or retired (Brown and Graf, 2013 ; Bucher-Koenen and Lusardi, 2011 ). Marital status is also related to financial literacy levels, with married people tending to have higher levels than single individuals (Brown and Graf, 2013 ). In terms of area of residence, those who live in a city score better in financial knowledge than their rural counterparts (Klapper and Panos, 2011 ). As for race and ethnicity, individuals belonging to the racial majority or being native-born have higher financial literacy levels (Brown and Graf, 2013 ; Lusardi and Mitchell, 2007 , 2011b ). For example, African Americans and Hispanics in the USA have lower financial literacy than Whites (Al-Bahrani et al., 2019 ; Lusardi and Mitchell, 2007 , 2011b ). In Switzerland, foreign citizens, especially immigrants with a non-German native language, exhibit lower financial literacy than native-born individuals (Brown and Graf, 2013 ). Students from an immigrant background also have lower financial literacy than other students (OECD, 2014 ).

The association between financial literacy and financial decision-making

Financial literacy is crucial for making sound financial decisions and avoiding costly mistakes. Empirical findings show that financial literacy is associated with various outcomes of financial decision-making, including day-to-day financial management, financial planning, using financial products, debt management, and detecting financial scams.

First, financial literacy can lead to better day-to-day financial management, such as responsible family budgeting, timely bill payments, and avoiding impulsive purchases (Akben-Selcuk, 2015 ; Atkinson and Messy, 2012 ; Hilgert et al., 2003 ; Perry and Morris, 2005 ). For example, a study of college students shows that those with higher financial literacy are more likely to pay bills on time and have a budget in place (Akben-Selcuk, 2015 ). Second, financial literacy is associated with better financial planning. Financially literate individuals are more likely to engage in savvy and active saving behavior (Akben-Selcuk, 2015 ; de Bassa Scheresberg, 2013 ; Deuflhard et al., 2019 ; Klapper et al., 2012 ). They are more likely to plan for retirement and save for emergencies (de Bassa Scheresberg, 2013 ). Third, financial literacy is related to better debt management. Individuals with better debt literacy will avoid high-cost borrowing, high transaction costs, and higher fees (Lusardi and Tufano, 2015 ; de Bassa Scheresberg, 2013 ). They also adopt better credit card behavior, which minimizes fees and interest charges resulting from late payments, cash advances, and paying only the minimum amount due (Lusardi and Tufano, 2015 ; Mottola, 2013 ). Fourth, financial literacy influences the use of financial products. Individuals with higher levels of financial literacy are less likely to be unbanked and use alternative financial services, such as payday loans (Kim and Lee, 2018 ). It is also associated with greater participation in investment and savvy investment decisions. Financially literate people tend to evaluate financial products carefully (Atkinson and Messy, 2012 ) and be more involved in the stock market (Almenberg and Dreber, 2015 ; van Rooij et al., 2011b ). Finally, financial literacy can increase the ability to detect financial fraud. Findings show that a one standard deviation increase in financial knowledge increases the probability of fraud detection by three percentage points (Engels et al., 2020 ).

Financial decisions of racial/ethnic minorities

Research on financial decisions made by racial/ethnic minorities has mostly focused on using financial products, debt management and credit use, and retirement planning.

Regarding financial products, African Americans and Hispanics in the USA are less likely to have a bank account and hold asset investments, such as stocks, than Whites (Kim et al., 2016 ; Lusardi, 2005 ; Shanbhag, 2022 ). Another study examined community development credit unions providing affordable financial services, such as mortgages, to help African Americans save money and build assets (Nembhard, 2013 ). Newly arrived immigrants in Australia demonstrated low utilization of financial products and services, such as ATM cards, bank savings accounts, and credit cards (Zuhair et al., 2015 ).

As for debt, around 80% of Chinese American respondents in a study on debt ownership held some type of debt, such as credit cards, mortgages, and instalment loans (Yao et al., 2011 ). Age, the presence of children under 18, health, income, and amount of financial or non-financial assets are associated with the probability of borrowing. Other studies have explored the attitudes of Black and other minority ethnic entrepreneurs experiencing bankruptcy in England (Ekanem, 2013 ) or Pacific Island adults in New Zealand towards debt, money, or bankruptcy (Gaur et al., 2020 ). Significant racial/ethnic differences in credit use have also been reported. Approximately 75% of White, 80% of Asian, 50% of Hispanic, and 45% of Black households use bank credit, in terms of a credit card or a personal loan or line of credit from a bank. However, nonbank credit, such as payday loans, is more predominant among Black and Hispanic households (Goodstein et al., 2021 ).

Studies on retirement planning show that ethnic minorities have less savings for retirement than Whites (Gough and Adami, 2013 ) and are also less motivated to hold retirement savings even after controlling for different socio-economic characteristics (Kim et al., 2021 ).

Ethnic minorities in Hong Kong

Despite growing efforts to promote financial literacy among people in Hong Kong in recent years, such as establishing the Investor and Financial Education Council as a public organization to promote financial education in Hong Kong, ethnic minority younger adults are still largely overlooked. In terms of research, the financial literacy of ethnic minority young adults or even ethnic minority communities is underexplored. Existing survey findings only show disparities in financial literacy between younger and older adults in the general population, with the former performing poorly, particularly in timely bill payments, making ends meet without borrowing, and keeping up with their financial affairs (Investor Education Centre, 2018 ). Financial education programs targeting ethnic minorities are also limited. Only 0.6% of the 661 financial education initiatives conducted between 2011 and 2015 were intended for the ethnic minority population (Investor Education Centre, 2015 ).

Ethnic minorities in Hong Kong refer to the non-Chinese population, which makes up 8.4% of the total population (Census and Statistics Department, 2022 ). Most are Filipino and Indonesian, constituting 32.5% and 22.9%, respectively, and most (more than 90%) of these are foreign domestic helpers living in their employers’ homes. South Asians, including Pakistanis, Indians, and Nepalese, make up 16.5% of the ethnic minority population. The rest are mostly White people and other Asians, such as Korean and Japanese, who often enjoy a higher social and economic status in the city and are not the focus of this study. After excluding the Filipina and Indonesian domestic helpers, Pakistanis, Indians, Nepalese, and Filipinos represent the largest proportion of the ethnic minority population in Hong Kong and are the focus of this study. These individuals may have migrated to Hong Kong with their families or were born in Hong Kong. Some of them may have acquired a certain level of English and Cantonese, the local language, especially if they have received education in Hong Kong.

In Hong Kong, ethnic minority younger adults are likely to perform less well in financial literacy and financial decisions than the general population, which is largely made up of ethnic Chinese. This is because they generally fare poorly in terms of education and employment. For example, school attendance rates for ethnic minorities in the age groups 3–5, 12–17, and 18–24 years were 90.7%, 96.2%, and 29.2%, respectively, compared to 92.5%, 97.8%, and 51.8% for the whole population in 2016 (Census and Statistics Department, 2017 ). As regards occupation, 35% of Nepalese, 35% of Pakistani, and 25% of Indian individuals were engaged in elementary jobs, such as cleaners, laborers, and food preparation assistants, compared to 21% of the general population (Census and Statistics Department, 2017 ).

Drawing on the literature, this study examined the financial decision-making of ethnic minority young adults in Hong Kong and posed the following research questions:

What are the experiences of ethnic minority young adults, in terms of practice or strategies and perceptions, in different areas of financial decision-making, including day-to-day financial management (personal budgeting and spending), financial planning, using financial products, debt management, and detecting financial fraud?

What factors enable ethnic minority young adults to make sound financial decisions?

This study employed a qualitative approach, using individual in-depth interviews, to examine the financial decision-making of ethnic minority young adults in their daily lives. The rich data gathered from qualitative inquiry can provide a nuanced understanding of human behavior, which involves practice and judgement. Semi-structured interviews allow participants to express their thoughts in their own words, which is particularly beneficial for delving into a poorly understood topic.

Participants and data collection

In this study, Pakistani, Indian, Nepalese, and Filipino participants were recruited through NGOs that provided services for ethnic minority young adults and international offices of universities using purposive sampling. In addition to ethnicities, young adults who were 18 to 29 years old, permanent residents of Hong Kong, and students or employed were recruited. Table 1 summarizes the participants’ background characteristics. Fifty-three ethnic minority young adults aged between 18 and 29 years were recruited: 16 Pakistani, 13 Indian, 13 Nepalese, and 11 Filipino. Thirty-five were aged 18–23, and 18 were aged 24–29. There were 30 males and 23 females. Thirty-two were employed at the time of the interview, and 21 were students. The occupations of those in employment included elementary jobs (e.g., security guards), service workers (e.g., customer service), associate professionals (e.g., program workers in NGOs), and professionals (e.g., software developers). Many ethnic minority students had part-time jobs ( n  = 12), such as cashiers, tutors, football coaches, and delivery workers. Other students depended on their parents for financial support ( n  = 9). Most participants were pursuing or had attained at least a bachelor’s degree ( n  = 30). Sub-degree education being pursued or attained included associate degrees, higher diplomas, or foundation diplomas ( n  = 11). The education level of the remaining participants ranged from Secondary 3 to 6 ( n  = 12). Students’ monthly earnings ranged from US$90 to $2500; more than half received US$1250 or less ( n  = 18). Working participants’ monthly earnings ranged from US$625 to $3560, most receiving between US$1250 and $2500 ( n  = 16).

The Research Ethics Committee of the university to which the author was affiliated provided ethical approval before the study commenced. Before interviewing, participants’ informed consent was obtained after explaining the study’s objectives and principles of confidentiality and voluntary participation. Each interview took place in an NGO or university and generally lasted between 60 and 75 min.

Interview questions

The interview questions were developed to gather information on a range of financial decisions based on the literature on financial literacy and financial decisions, including day-to-day financial management (personal budgeting and spending), financial planning, using financial products, debt management, and detecting financial fraud. Participants were asked about their practices or strategies and perceptions of each area of financial decision-making. The interviews were conducted in English.

The audio recordings of individual interviews were transcribed verbatim. Following Braun and Clarke ( 2006 ), thematic analysis was employed to identify, analyze, and report major themes within the data. The researchers first familiarized themselves with the data through repeated readings. They then developed initial codes to capture the meaningful aspects of the data. These codes were further organized into potential themes, and the relevant data associated with each code were collated within the potential themes. The potential themes were refined through careful review to ensure the coherence of data within each of them and that they were distinct. Once the refinements were finalized, the themes were named to accurately reflect their essence.

The following findings present the practices, strategies and perceptions of various financial decisions. Table 2 summarizes the major themes., which also align with particular components of financial literacy, including financial knowledge, attitudes, and behavior (Atkinson and Messy, 2012 ).

Personal budgeting

Spending- or saving-centric approach in practice.

Most participants had developed habits of monthly budgeting, using saving- or spending-centric approaches. The former involves setting a savings amount and then spending the remainder, whereas the latter involves setting a spending limit and then saving the remainder. For example, one participant was more conscious of his savings:

I set in mind that every month I have a certain percentage to be saved and not to be touched. The rest is like spendable expenses, so I don’t have to go crazy saving mode. (18Indian, M/26 y, W, Degree) Footnote 1

Digital tools, parental monitoring, and mental bucketing as strategies

Participants employed various strategies in practice, including digital tools, parental monitoring, and mental bucketing. The digital tools they utilized included budgeting apps, Excel spreadsheets, online banking, and calendar or note taking apps in their phone. Some examples of budgeting apps to keep track of budgets were Zoho Expense, Ahorro, Mobills, Money Manager, Spendee, and Savings Planner.

I have this app Mobills …I just type all my expenses in where I spent the money so it helps me track if I have exceeded the monthly limit. (27Nepalese, M/20 y, S, Degree)

Some participants relied on online banking, e-statements, or Excel spreadsheets to keep track of their budgets. One participant primarily used credit cards for spending: “I check my monthly statement and like …oh, this month I spent more on food. I should cut it down a bit.” (18Indian, M, WA, 26 y, Degree) Another participant updated his budget sheet almost daily, “I make sure I don’t cross the budget for daily food expenditures, so I separate expenditures of breakfast, lunch, and dinner. (35Filipino, M/28 y, W, S7)

Parental monitoring in budgeting was common, where parents set spending limits or kept the money to prevent their children from overspending. Participants were positive about parental monitoring:

I gave all my earnings to my mom and she’ll help save for me. After deducting the savings, she’ll allocate some for my spending. (11Pakistani, M/20 y, S, S6)

They won’t let me spend my own money so that they can keep track of what I do. …I’ll always show my mom what I bought. …I can say it is ‘control’ …but it’s good to have monitoring. (1Indian, F/23 y, S, Master’s)

However, some participants simply allocated money into different categories mentally. One said, “I don’t like keeping notes. Everything is in my mind.” (47Indian, M/18 y, W, S4), while another responded, “I just keep them in my mind, divided by categories.” (40Nepalese, F/21 y, W, SD)

Parental influence and experiential learning

Participants indicated that they acquired budgeting ideas through observing their parents and learning by doing, especially after earning their first income.

I’m learning from him [father], like how to save up money, how to spend it wisely, and how to spend it on only the important things and not to waste the money. (2Pakistani, M/22 y, S, SD)

It was around my university years when I was doing a part-time job and earning some money …my own concept of saving started to form. (18Indian, M/26 y, W, Degree)

Perceptions of budgeting

Most participants perceived budgeting positively, agreeing that it could provide a sense of control against overspending, as one said, “If you don’t have a budget, it’s really easy to overspend on stuff and you can’t control your money.” (47Indian, M/18 y, W, S4). Budgeting was also seen as a form of psychological restraint, evoking a sense of guilt when budget limits were exceeded, and fostering discipline for conscious spending:

It makes me feel guilty …kind of a warning …a yellow light that you’re spending more than you’re supposed to. … It’s psychological when I see a big number in the amount of expenses. (29Filipino, F/22 y, S, Degree)

However, many expressed the difficulty of maintaining a budgeting habit due to economic and personal challenges. Limited funds and high living costs posed economic challenges as there was not a lot of money to go around, as expressed by one participant, “I don’t really have a lot of money. …I don’t know how I can track it.” (4Indian, M/21 y, S, Degree) Another said, “It’s very difficult because nowadays all the things are pricey, but you just have a limited amount of money.” (28Filipino, F/19 y, S, S6)

Personal challenges relate to feelings that budgeting is demanding, requires much self-discipline, and causes stress. Some participants found it demanding as it was time-consuming and involved excessive work.

It sounds, you know, ridiculous to me …somewhat a waste of time. There’s a lot of data. (15Pakistani, F/25 y, S, Degree)

It’s tedious and it takes time to write down all the details. …The effort needed to keep track of things demotivates me. (34Indian, M/30 y, W, Degree)

Others found it difficult because they struggled with self-control. One said, “I want to buy many things like this and that. …It’s hard for me as I could not control myself.” (42Nepalese, F/25 y, W, SD) Others were reluctant to budget because it induced too much stress:

I think budgeting gives me a lot of stress. I just want to focus on making money, so I don’t have to worry about it. (31Filipino, M/22 y, S, Degree)

Constantly checking is kind of torturing me. …If I check it too much, I’ll get sad about my expenditure. (18Indian, M/26 y, W, Degree)

Nevertheless, a smaller proportion of participants who showed qualities such as determination and mathematical competence did not find budgeting as hard.

It’s just the willpower of a person. I don’t think there’s too much difficulty for me. (32Indian, M/29 y, W, Degree)

I have a strong mathematical background since I studied math a lot, so I don’t think numbers are a problem for me. (17Nepalese, M/18 y, S, Degree)

Spending decisions

Modest spending.

Many participants appeared to spend modestly and consciously. They generally allocated a higher portion of their budgets to basic needs. As many lived with their parents, they mostly spent money on food and transportation. Other major expenses included tuition fees, financial support for their families, rent, and personal entertainment.

I’d say 50% goes toward my food. …Insurance and everything, I’d say 20%. (38Indian, M/23 y, W, SD)

Half of my money goes to food and transportation, and the other half I’m saving for school fees and all that. (2Pakistani, M/22 y, S, SD)

Deferred purchase, bargain shopping, and one-time payment as strategies

Strategies in spending decisions included deferred purchases, bargain shopping, and one-time payments. One strategy employed was to re-evaluate spending decisions by deferring purchases:

When I shop, I double-think. … I’ll buy it a day or two later …to think about if I truly need it or not. (22Pakistani, F/25 y, W, S6)

Another common strategy was bargain shopping. Participants described how they bargain-hunted or waited for sales to get the best value for money.

If I go to buy a pair of shoes, then I like to go through the whole mall and see, you know, which one is really worth the money. (4Indian, M/21 y, S, Degree)

I’ll try my best to use as little money as I can. …I’ll check where I can get it the cheapest. (51Pakistani, M/25 y, W, Degree)

When making purchases, most preferred a one-time lump sum payment to avoid interest charges. One participant talked about the extra charges:

I used to buy in instalments with credit cards and I spent a lot, and I couldn’t pay some of the bills….Now I pay in lump sum, I find this very clear to your mind. …Nobody is calling you to pay for the minimum. (43Nepalese, M/28 y, W, Degree)

However, some paid in instalments, incurring interest on expensive products or when the budget was tight. Generally, an item costing more than HK$1000 (approximately US$125) was considered expensive.

If it’s around HK$500–$1000 (US$63–$125), I’ll spend a lump sum. But if it’s HK$5000 or HK$6,000 (US$625 or $750) like that, I’ll usually spend it on instalment. …When making it 12 months, I only need to pay HK$500. (51Pakistani, M/25 y, W, Degree)

Spending philosophies

Participants shared their perceptions about spending, revealing various spending philosophies such as differentiating between needs and wants, viewing spending as a work incentive, and embracing YOLO (You Only Live Once) spending. Conscious spenders distinguished between must-haves and nice-to-haves, ensuring they spent on what was necessary rather than what was desired.

When you buy something …you have to ask yourself whether you need it or want it, like you just think it’s cute. (25Pakistani, F/19 y, S, Master’s)

I often question whether I really need it …especially when it comes to luxury items like clothes and shoes. But for food, I do not compromise; for health, I do not compromise. (17Nepalese, M/18 y, S, Degree)

Some participants showed that spending was a motivation to work hard, as one said: “I base how much I work on my expenses. If I have many expenses coming up, I’ll try to work more.” (3Indian, M/21 y, S, Degree). Others embraced YOLO spending as a means of seeking happiness:

I didn’t want to decide how I was going to spend it. …You should never restrict yourself. Of course, you have savings. But for your spending, you should just go with whatever makes you happier. (18Indian, M/26 y, W, Degree)

You only live once! … It’s good to spend a little bit on something expensive. …With the money I earned …I deserve at least some to use on myself. (32Indian, M/29 y, W, Degree)

Financial planning

Savings habits and setting savings goals.

Many participants established a habit of saving. More than half said they allocated at least 30% of their monthly salary or pocket money to savings. Some started to save in childhood, but many did so after their first employment while their earnings served as resources for hands-on learning. One participant said, “When I started to earn my own money, I didn’t want to spend all of it. I want to save and learn about investments.” (29Filipino, F/22 y, S, Degree)

Depending on their life stage, those who saved set various saving goals. In addition to saving for education, some saved to buy property, start a family, build a business in their home country, or for retirement. Some described the goals:

I’ve always wanted to start a piggery business. …In the Philippines, …a full roasted pig we call it Lechon. It’s in every celebration. …There’s a market for that. …I want to start one because my uncle, sisters, and brothers are good at that. (29Filipino, F/22 y, S, Degree)

For the very long term, like for retirement, I’m setting aside 20% of my salary to invest in stocks and bonds. (34Indian, M/30 y, W, Degree)

Gaining financial autonomy was also mentioned as a goal, as recounted by one participant:

I’m never going to focus too much on my future husband. I’m not going to be financially dependent on another person. …I always thought …I’d get educated and then earn money. I’d not be together [with someone] and be scared of splitting just because of money. (10Nepalese, F/21 y, S, Degree)

External restraints and personal tricks as strategies

Participants employed various savings strategies. In addition to saving money in bank accounts, they used external assistance or restraints as strategies by having their parents or boyfriend save it for them:

My parents don’t want me to be spoiled with so much money. We often see that people who start earning money do some bad stuff, like getting into drugs, gaming, or going out with friends a lot. …I’m not doing all these. …But still, they keep my money. (49Filipino, M/19 y, W, S6)

I’ll give half of it [salary] to my boyfriend so I won’t be able to touch it. The remaining is for my spending. …He has a better concept of saving than me …and he helps me save. (16Indian, F/27 y, W, Degree)

Participants reported using various personal hacks, such as opening separate bank accounts for specified uses:

I have two different bank accounts. One is strictly for saving money. …The other one is for paying bills and spending on things like necessities. (35Filipino, M/28 y, W, S7)

When I started my job, I only had a Hang Seng bank account. Then I specifically opened an HSBC account to keep my education savings there. …If you see a large amount of money, it makes you less intelligent about your expenditure because it projects an illusion that you have a lot of money. (48Indian, M/24 y, W, Degree)

Another example was a four-wallet strategy to divide money into smaller portions for designated purposes:

One wallet is for saving money. …If I buy something and I get some money left, I put it in the second wallet. The third wallet is for putting money that I couldn’t touch, like paying for my violin lessons and the dentist. …The fourth wallet is for transportation. (30Filipino, F/21 y, W, SD)

Another strategy was simply stashing cash away under the mattress or in other hidden places to reduce its accessibility:

I have like HK$10,000 (US$1250) under my mattress. Every month I have HK$1000 (US$12.5) …a hundred of $10 s …put inside my mattress, and I would sleep on it. My goal is …to the point if I can’t sleep properly, I have enough money. …Some people have their piggy bank I have my mattress. (31Filipino, M/22 y, S, Degree)

Sometimes I took all the money out and put it in a more hidden place like I can literally forget about it. (28Filipino, F/19 y, S, S6)

Perceptions of financial planning

Most participants agreed that financial planning and saving were important. Some thought of it as a grown-up responsibility. As adults, they were responsible for making financial plans and avoiding irresponsible purchases:

I already feel ashamed that I’ve been asking for pocket money from my parents. …I think it’s because we’re Asian, …we depend a lot on our parents. I don’t really want to live like that. …I want to be able to stand up on my feet. (10Nepalese, F/21 y, S, Degree)

I feel like after turning 18, …it’s important to budget your money, save it, invest it, and not make stupid and foolish purchases. (19Indian, M/19 y, S, Degree)

Financial planning was seen as a safeguard against financial shocks, offering a sense of emotional wellness or peace of mind as they knew they had backup resources. This was particularly important after they experienced the COVID-19 pandemic and became motivated to be well-prepared:

It taught me that no job is stable …even pilots get laid off. …Your income is not always there. You always have to be prepared for it. (41Nepalese, M/22 y, W, Degree)

You can have a fire break out in your house, you can have your stuff get stolen, you can get hit by cancer, and even this pandemic. So financial planning is extremely important. (21Pakistani, F/23 y, W, Degree)

It’s like a comfort …in case anything goes wrong in your life. It’s always good to have a backup plan …and you always have something to protect you. (35Filipino, M/28 y, W, S7)

Nevertheless, not all participants were positive about financial planning; some valued income generation over saving money:

Saving isn’t super important to me because I feel I should be earning more than I should be able to save. …If I am earning more, I don’t have to worry about saving. (31Filipino, M/22 y, S, Degree)

Some also felt they were not good at saving because of inadequate self-discipline and limited money: “The reality …is that my income is really not a lot at all. And I recognize there’s a limit on how much I can stretch, even if I really want to stretch it.” (36Filipino, M/26 y, W, Degree)

The use of financial products

A diverse range of financial products.

Participants reported using various financial products or investments. Insurance was most frequently mentioned, followed by stocks, and other choices, including cryptocurrency, index funds, and forex trading. Buying property or gold in their home country as conventional investments was popular, as the older generations have done.

Different types of insurance, including life, medical, accident, and critical illness, were purchased and considered safe and flexible:

My insurance is three years old. …If something bad happens, I can use it. If I don’t use it after 20 years, it’s my money, so it’s like a saving. (43Nepalese, M/28 y, W, Degree)

All of them are index funds because the management cost is low and it’s simple to set up. It’s set and forget, no need to actively manage. (34Indian, M/30 y, W, Degree)

Buying property or gold in the home country was popular. Like their parents, they made or were planning to make these investments as they believed their value would steadily increase:

Dad bought properties in Pakistan and the values increase every year as it’s on the main side of the road. …The more convenient the properties, the higher the price it is. …Three are under my name, others under my siblings’ name. (22Pakistani, F/25 y, W, S6)

Buying property is safer compared to stocks. …Buying it overseas is a lot safer …because the property in Hong Kong is a lot more expensive. (31Filipino, M/22 y, S, Degree)

I can use this gold in my wedding … it’s kind of holding money because I don’t think the gold price will drop. It’s a good investment. (53Nepalese, F/25 y, W, Degree)

Parental support, peer mentoring, and self-education as strategies

Participants employed various means of obtaining information and experiencing financial products, including parental support, peer assistance, and self-education with online resources. Some parents were supportive by providing funds for hands-on learning in stock investment or opportunities for joint investment:

My dad gave me a small amount of money just to learn. …Because the only way you can learn is you do it yourself. …He helped me set up my account and everything and then I started. (19Indian, M/19 y, S, Degree)

I invested with the help of my mom. …She invested and got a return and she gave me the interests. (10Nepalese, F/21 y, S, Degree)

Assistance from financially savvy friends was also a way to enhance their knowledge and gain experience in stocks, insurance, or setting up a business:

I have a group of friends and we all invest in stocks. We like to give each other tips like, “I’m going to invest in this …maybe you should take a look at this.” Or sometimes before they invest, they ask “What do you think about this company?” And then I do my research …like we help each other. (19Indian, M/19 y, S, Degree)

My friends are in Pakistan …their family has been investing in property and stocks. …They bought their own shisha lounge recently. …I discussed with them: What was the cost? How much should I save for starting up this kind of stuff? (22Pakistani, F/25 y, W, S6)

Another strategy was self-education, by reading news, studying company information, and surfing the internet and YouTube for tutorials and knowledge:

I see the performance of their company around 5 or 10 years. Then I see the future analysis …how the company will perform in the future. (13Pakistani, M/23 y, W, Degree)

There are a lot of tutorials online or on YouTube. … There are also a lot of good pages that talk about investing. … It’s easily obtainable. (10Nepalese, F/21 y, S, Degree)

Perceptions of using financial products

Participants expressed different views about using financial products. The favorable view held that financial products acted as a passive form of income and could help protect against inflation, as one participant expressed, “It’s good to buy stocks because it’s like passive income. You can do your job when it also generates income.” (43Nepalese, M/28 y, W, Degree)

However, some viewed it unfavorably as they thought investment carried substantial risk. In particular, stock investment was akin to gambling, which involved taking chances and the possibility of losing hard-earned money:

You are literally gambling …the price of shares would rise or fall suddenly. …Just in days, you could lose so much. That’s why my aim is to look for a professional job so that I don’t have to depend on unexpected business. (17Nepalese, M/18 y, S, Degree)

Some others held unfavorable views due to their own or their families’ and friends’ negative experiences resulting from poor understanding of financial products:

I bought stock and I sold it. …If I had kept it a bit longer, I could have gotten a much higher return. …I just sold it based on rumors that the stock won’t go up. (27Nepalese, M/20 y, S, Degree)

My uncle didn’t know how to play it. He just went to the bank and was told to invest this and that without any explanation. …In the end, he lost a lot of money. (26Nepalese, F/21 y, S, Degree)

Sometimes, the lack of understanding of financial products could result from language barriers. One participant referred to the Mandatory Provident Fund (MPF), a compulsory pension fund in Hong Kong, as an example:

If you go to work, your employer won’t tell you what’s this or that. They just give you the MPF paper. …People don’t know what’s written there. They just sign it. Which product is better? They don’t know. (2Pakistani, M/22 y, S, SD)

Debt management

Borrowing money as a common practice.

It was quite common for participants to take out loans from different sources, including family, friends, the government, and financial institutions. Some borrowed money from their parents or siblings. Due to close family ties and strong support, paying back the loan was not always expected. Some would also borrow from friends despite feeling uneasy about it:

I had zero income and my wife is jobless. …I felt it was a shame to borrow from my parents. …I asked my brother who is in Qatar. …It’s like a brother thing. He just sent it to me and …no need to return it. (14Pakistani, M/28 y, W, Degree)

To be broke on the 25th of the month but your salary only comes on the 31st. …Those few days you have to live …so I have to borrow from my friend. (38Indian, M/23 y, W, SD)

Some participants who were or had been students took out government student loans for educational expenses:

Hong Kong is so expensive, and so are school fees. I can’t pay it all at once so I had to borrow from the government. (23Filipino, F/23 y, W, Degree)

Some participants borrowed money from banks to buy an apartment. Others borrowed from lending institutions charging high interest rates to pay for tuition fees, buy iPads, or pay off credit card debts. They described their own or their friends’ experiences:

I have a period of time without a job. I have to pay with a credit card every month. I’ve skipped one month …and they started to call me and I was irritated. …Then I realized …why I wouldn’t start to do research tracking the annual rate, and at last, I decided to go to this loan company. (26Nepalese, F/21 y, S, Degree)

My friend found it hard to pay back because the interest rate was high. …She graduated last year and she has only worked for a few months. …She has to pay for the loan and to pay for her credit cards. (22Pakistani, F/25 y, W, S6)

Mostly safe credit card usage with some risks

Approximately one-third of participants owned a credit card. Occasionally, some used their parents’, siblings’, or friends’ credit cards, with approval, when they could not get their own, as illustrated by one participant:

My friend doesn’t use her credit card much. …I just took hers, bought things, and on the same spot transferred money to her account. (22Pakistani, F/25 y, W, S6)

Most credit card users could settle their bills on time, like one who said, “Unlike others who may pay it last minute. I pay it immediately after receiving the statements.” (48Indian, M/24 y, W, Degree)

However, some participants only paid the minimum due on credit cards, especially due to ignorance about interest charges. One did not know the consequences of doing so:

I was studying for an associate degree and I wanted to get as high marks as possible. I thought that if I got into the university then I could pay for them all afterwards, so there’s no pressure if I give minimum payment every month. …I didn’t realize about the interest. I swiped a lot. (26Nepalese, F/21 y, S, Degree)

Perceptions of debt management

Participants considered borrowing money was shameful and could hurt their social relationships. Borrowing money was associated with shame and guilt, especially for people capable of working, instead of borrowing money from others:

We have everything to earn money. … We’re healthy. We have all the physical and mental ability to work. …So we don’t have to depend on other people. (5Indian, M/22 y, S, Degree)

The shame is that …if God has given me a healthy body and I have my hands fine, if I can walk, if I can work, then why go ask someone for anything? (14Pakistani, M/28 y, W, Degree)

Others thought that borrowing money could create tensions with friends or relatives, especially if money was not returned:

Some friends of mine have taken money from me …but they don’t return it. … They’ll say, “I still don’t have money.” …What the bank does is good …charge the interest from them. (52Indian, F/29 y, W, Master’s)

You lend money to relatives or friends …but they might not return it to you. They might not pick up your phones. They might go away from the city. …That’s what I’ve heard….I don’t think they call the police …at the end they are family. (17Nepalese, M/18 y, S, Degree)

Participants considered credit cards to be convenient, and they enjoyed the reward systems. One said, “It’s like an Octopus card Footnote 2 but is more widely used, especially for online shopping. And it’s convenient …you can accumulate points for more savings.” (35Filipino, M/28 y, W, S7) However, many were also aware that credit card use could lead to uncontrollable spending because they could easily overlook how much they had spent:

If I had one, I would go non-stop shopping because I have pressure at work. Who wouldn’t go shopping after work? (38Indian, M/23 y, W, SD)

When you take out your money, you know your limit. Like if your wallet has $5,000 and you’re using it, you’ll notice how much money you’ve left. But credit cards …you’ll keep using it. (8Pakistani, M/23 y, W, SD)

Detecting fraud

Fraud victimization experiences.

Participants were vulnerable to fraud; some shared stories about falling or almost falling for scams or had heard about friends being scammed, relating to possible charity scams, unnecessary lab tests, online gaming, investment fraud, and money lent but not returned. One participant believed he had been scammed when he was asked for a donation on the street:

I’ve been scammed once on the street by a man who’s requesting money for their own institution from their own country. It involves children who are sick. …Because I was young and naive, I didn’t ask them for validation. Although he wanted to scam more money at the time, I didn’t carry too much. (35Filipino, M/28 y, W, S7)

There were unnecessary medical lab tests:

They said they got funding from the government. They did 10 different cancer tests on me for $4000. My mom was very angry about why I did it. She said it’s a scam because I’m so young. I won’t have any cancer right now. (1Indian, F/23 y, S, Master’s)

Money was lost due to an online scam:

There was once an email …saying if you put $10,000 on this account, we’ll give you $20,000 …that kind of scam …but I didn’t do it. …The second time when I bought a computer game online, they just asked me to send some money in advance. …They totally scammed me and then blocked me. (44Nepalese, M/20 y, W, S6)

Friends had also experienced investment fraud:

I have a friend who invested in …some sort of software soccer game. …He saw an advertisement online in a newspaper. He invested and then the money was just gone. …He lost HK$5000. (6Pakistani, M/25 y, W, S6)

They called and encouraged my friend to put in money and said, “…This is very good. You can earn a lot. You can be a rich person. You can do whatever you want to do.” She put a little bit to see. After six months, they kept calling and saying she was doing well, she could do better. And they got everything on that scam and they never called back. (43Nepalese, M/28 y, W, Degree)

Strategies and perceptions for detecting fraud

Participants reported that the flood of suspicious calls and messages they received, and uncertainty about whether they were genuine or not, exposed them to potential scams.

I don’t know if it’s a scam. …I got calls for buying currencies from them. They told me the whole plan, and I’d even go into a discussion and I was close to paying them. I’ve been near that. (49Filipino, M/19 y, W, S6)

Once I borrowed money and after that many financial companies have my number. …They ask what my name is and ask for my information. …I didn’t give them because I know they might want to get my bank information … it’s not safe. (8Pakistani, M/23 y, W, SD)

They also talked about how to avoid scams by understanding their psychology as emotional manipulation to induce feelings of guilt:

They try to confuse you with a lot of situations to guilt trip you. They make you feel bad about other people. They try to trick you into thinking that your life is a lot better than theirs. …They can make you feel good about giving money. … They’re mentally threatening you not in a bad way. …If you have a strong personality, you can fight back easily. But if you’re naive, it can be quite difficult. (35Filipino, M/28 y, W, S7)

Participants reported pretending they did not understand Cantonese (the local spoken language in Hong Kong) or simply ignoring dubious calls or messages as tactics to tackle potential scams:

I think it’s funny because I can speak okay Cantonese. Whenever I get calls from banks or something, I always ask, “Can you speak in English?” and then they just disconnect. (22Pakistani, F/25 y, W, S6)

Some unknown WhatsApp messages are frequent. But I’d ignore them as I know they are dangerous. (30Filipino, F/21 y, W, SD)

This study has various implications. It contributes to conceptual or theoretical understanding, provides insights into practical strategies, and offers directions for further research.

Knowledge or theoretical contributions

Financial decision-making experiences.

This study has contributed knowledge to addressing the research gap by revealing the financial decision-making experiences of younger ethnic minorities in a non-Western context. We examined their behaviors, strategies, and perceptions across a range of financial decisions, including personal budgeting, spending, financial planning, the use of financial products, debt management, and detecting fraud. Many ethnic minority young adults practiced budgeting, using digital tools, parental monitoring, and mental bucketing. They learned about budgeting by observing their parents and gaining hands-on experience with their own earnings. Budgeting was challenging due to limited funds, high living expenses, time demands, stress, and self-control issues. Most were modest spenders, prioritizing basic needs like food and transportation and employing strategies like deferred purchases, bargain shopping, and lump-sum payments. Some opted for instalment payments for expensive items, and when their budget was tight. When spending, they differentiated between needs and wants, sought value for money, worked to meet their spending needs, and purchased for happiness. Saving at least one-third of their monthly income, they utilized external assistance and personal tricks. Their long-term saving goals encompassed education, housing, family, business, retirement, and female autonomy. Financial planning was perceived as an adult responsibility, a safeguard against emergencies, and ensuring peace of mind. They invested in insurance, stocks, cryptocurrency, index funds, forex trading, property, and gold. Parental support, peer mentoring, and self-learning influenced their investment decisions. Lack of knowledge and language barriers may contribute to negative perceptions or experiences of financial products. Informal borrowing from family and friends was commonplace, while others resorted to government or lending institution loans. Around one-third owned a credit card. Most used them safely, but risks exist when using someone else’s card, or they are ignorant about interest charges. They were aware of financial scams and employed preventive strategies like understanding the psychology of scams and ignoring scammers, although they occasionally fell victim to fraud.

Enabling factors to financial decision-making

Factors affecting financial literacy are widely understood in the literature, but less has been examined regarding the factors affecting financial decision-making. Based on the financial decision-making experiences, we further identified various factors or conditions that facilitated ethnic minority young adults’ financial decision-making and enabled them to make better financial decisions. While some other factors acted as barriers, awareness of these barriers and taking action to address them can transform them into enabling factors. The enabling factors include family social capital, intrapersonal characteristics, social dynamics factors, command of knowledge, and facilitative contextual circumstances. These insights can help devise financial literacy education for ethnic minority young adults.

Family social capital. Family social capital enables families to leverage both material and symbolic resources to benefit their members (Furstenberg and Kaplan, 2004 ). In this study family social capital played a crucial role in participants’ financial decision-making, as shown by the resources and support derived from the family relationships, including the passing down of money-related attitudes, norms, and behavior from one generation to another and between siblings. Both intergenerational support and sibling support are key components of this family social capital. In the study, intergenerational support was demonstrated through parental role modeling and involvement. While participants did not mention direct teaching of financial education by parents, parents served as role models from whom their children observed and learned financial attitudes and behaviors. This was how participants acquired their ideas of budgeting. Parents also actively coached financial decision-making by monitoring budgeting, setting spending limits, supervising saving, providing funds to help set up stock accounts, offering joint investment opportunities, and providing financial assistance. Sibling support refers to the emotional and practical support provided by siblings. Study participants sought help from their siblings or provided financial assistance to one another during financial difficulties, as shown by their lending money to each other to avoid unnecessary interest charges that may arise from resorting to other sources. Strong family social capital can be attributed to cultural values emphasizing family relationships, filial piety, and respect for parents.

Intrapersonal characteristics. Intrapersonal characteristics, which comprise personal attributes and life perspectives, are evident in facilitating ethnic minority young adults’ financial decision-making. Personal attributes such as self-motivation, self-discipline, and other competencies play a role. Self-motivation is an inner force that compels behavior (Waitley, 2010 ) and gives people energy to initiate actions and persist in efforts to attain a goal (Robbins and Judge, 2022 ). This study revealed self-motivation to be important in financial decision-making, such as budgeting, as it is difficult for those with lower motivation to sustain a budgeting habit when they consider budgeting as demanding, time consuming, and excessive in work. Self-discipline involves being able to control one’s impulses and desires in favor of long-term goals (American Psychological Association, 2023 ). Participants expressed the importance of self-discipline in successful budgeting, saving, and spending. Math competencies ease financial decisions. Those with numeracy skills tend to feel it easy to engage in budgeting.

Life perspectives are about people’s overall views of life, which include personal philosophies and future orientation and facilitate ethnic minority young adults’ financial decisions. Personal philosophies, which are values and attitudes that can be shaped by personal experiences and family and cultural influences, guide people’s decisions. Spending philosophies can be part of an expression of personal philosophies. Study participants exhibited various personal philosophies, such as simplicity-based, enjoyment-based, and work-to-spend philosophies, reflected in their spending philosophies. Simplicity-based living philosophy emphasizes a minimalist lifestyle over material possessions, as evident in the differentiation between needs and wants in spending philosophy. Enjoyment-based living philosophy values pleasures and living in the present moment, as reflected in the YOLO style of spending philosophy. A work-to-spend philosophy underscores the importance of working hard to support desired spending levels and is shown by the work-as-incentive spending philosophy.

Future orientation is the ability to anticipate future events, give them personal meaning, and operate with them mentally (Nurmi, 1991 ). It is associated with future-oriented behaviors, such as planning and delayed gratification (Strathman et al., 1994 ). This study suggests that individuals with saving goals tend to have a stronger future orientation as they plan for long-term objectives such as education, starting a family, property investments, and retirement. Those who practice delayed gratification by deferring purchases also show future-oriented tendencies.

Social dynamics factors. Social dynamics factors include peer support and vigilance within ethnic communities. Peer support involves ethnic minority young adults helping each other to make financial decisions through monitoring, mentoring, and collaborating to keep track of each other’s financial behaviors towards goals, offer practical advice in planning decisions, and share tips and efforts in decision-making, respectively. For example, peer monitoring serves as a social restraint to help those who struggle with saving. Peer advice is sought concerning investments in their home countries. Collaboration facilitates joint decision-making on buying stocks. Peers, along with parents, also serve as financial socialization agents.

Vigilance in ethnic minority communities is needed to prevent exploitation, as trust is often presumed within these communities. In the study, trust was demonstrated in the common practice of informal borrowing. Although informal loans can be enforced by social or community ties, they are not without risk. Without legal loan agreements, the possibility of bad debts or scams can arise, and did occur within participants’ communities.

Knowledge proficiency. Knowledge proficiency refers to the command of knowledge essential for making informed financial decisions. There are two types of knowledge. The first applies to a range of financial concepts required to navigate choices in everyday financial situations, such as knowledge of effective saving strategies, information on different financial products, and interest charges for instalment plans, loans, and minimum payments on credit cards. It is important, as the study revealed possible risks and negative experiences among participants stemming from a lack of caution or knowledge, like stashing cash away and ignorance of high interest rates when repaying minimum amounts on credit card debts or loans from lending companies. This type of knowledge is also important considering the potential issue of misinformation. Many participants were interested in using financial products such as insurance policies and stocks in Hong Kong and property investment in their home countries. However, their reliance on self-learning through online resources, such as YouTube’s KOL, or listening to peers exposed them to the risks of misinformation. For instance, one participant regretted making a poor decision to sell stocks based on hearsay, lacking proper knowledge of how stocks work.

The second type of knowledge involves protection against fraud. While participants tried to avoid suspicious messages and calls, some fell victim to various scams, accentuating the importance of being equipped with proactive measures, as the ones used, simply ignoring them, appear passive. Familiarizing oneself with common forms of fraud, exercising caution with offers that seem too good to be true, accessing scam alert information, knowing how to report scams, and understanding one’s legal rights when encountering scams would be good anti-fraud measures to learn.

Facilitative contextual circumstances. Various contextual circumstances, including leverage of real-life lessons, access to technology, and language accessibility, can be influential in ethnic minority young adults’ financial decisions. This study shows that the employment and pandemic experiences have been translated into real-life lessons to acquire financial knowledge and attitudes. The first earnings from employment nurtured the ideas of budgeting and financial planning, and provided opportunities for acquiring relevant skills. This suggests that promoting financial planning strategies and saving habits earlier, at least before starting employment, is beneficial. Individuals can avoid making unnecessary mistakes and enter smoothly the world of work that requires many financial decisions. Due to the pandemic, some participants experienced a positive change in their financial attitudes. They realized the importance of preparing for economic uncertainty and were eager to improve their financial planning.

Technology not only provides easy access to online financial materials, but can also facilitate financial decision-making using digital tools, which are particularly useful for following budgeting and tracking expenses. As many participants considered budgeting to be arduous, it can be made easier by adopting technological aids.

Finally, language accessibility can affect the acquisition of financial literacy. Participants’ negative experiences with financial products, such as bank products or MPF, for instance, largely stemmed from a lack of understanding that can also be compounded by a language barrier.

Enriched understanding of financial socialization

Family social capital as an enabling factor of financial decisions aligns with the theory of financial socialization, referring to the process of developing values, attitudes, standards, norms, knowledge, and behaviors promoting financial viability and individual well-being (Danes, 1994 ). Research shows that parents are important socialization agents influencing financial attitudes, such as credit attitudes (Norvilitis et al., 2006 ). Despite arguments suggesting that parental importance declines as children get older (Danes, 1994 ) and peers take on greater influence (John, 1999 ), this study shows that ethnic minority young adults continue to rely heavily on their parents for financial guidance. The findings of this study extend the understanding of financial socialization processes by recognizing the persistent and exceptionally influential roles of ethnic minority parents. Other research also supports that ethnic minority young adults seek parental advice on important education and employment decisions (Chan et al., 2020 ).

Practical implications

The findings on enabling factors and various behaviors shed light on practical suggestions for enhancing financial literacy education, which, in turn, improves the financial decision-making of ethnic minority young adults.

First, in relation to family social capital, if parental influence remains strong in young adulthood, it may be strategically beneficial to involve ethnic minority parents, either as target participants or partners, in tailored financial literacy education.

Second, to promote holistic financial literacy education for ethnic minority young adults, it is necessary to address their specific personal attributes and life perspectives as attitude components, in addition to increasing general financial knowledge and skills. Self-discipline, self-motivation, spending philosophies, and future orientation could be positively fostered by taking into account the unique challenges they face in financial literacy education.

Third, in response to social dynamic factors, while ensuring the accuracy of shared financial information, peer influence can be capitalized on for effective financial literacy education by utilizing collaboration as a learning approach and developing peer mentoring to optimize mutual learning experiences. Also, addressing vigilance in community trust and the potential risks associated with informal loans are important topics to be included in financial literacy education.

Fourth, concerning knowledge proficiency, financial literacy education should incorporate the two essential types of knowledge required for making financial decisions. This includes knowledge about everyday financial situations—such as the use of various financial products, the consequences of different credit card payment options, and the interest rate information associated with formal debts—as well as knowledge about proactive anti-fraud strategies.

Fifth, in response to facilitative contextual circumstances, the current post-pandemic period is an opportune time to offer ethnic minority young adults financial literacy education to capitalize on their increased motivation to learn and improve their financial decisions. Also, as smartphone use is indispensable among young people, including ethnic minorities, user-friendly budgeting apps that fit well their financial situations can help make budgeting efficient, stress-free, and engaging. Moreover, it is important to provide financial literacy education that takes into consideration language needs to ensure a thorough grasp of financial concepts. For instance, interpretation support can ease language barriers. However, in the long run, policy interventions in the educational system, such as remedial language support and learning Chinese at a young age, are necessary.

Last, various financial behaviors prone to mental accounting bias should be addressed in financial literacy education to equip ethnic minority young adults with the skills to make optimal decisions. Mental accounting refers to the cognitive operations to organize, create mental labels, and keep track of money or financial activities (Thaler, 1985 ). An important concept in this theory is that money is fungible or interchangeable, regardless of its source or purpose. However, people often violate this principle and see money differently, resulting in suboptimal decisions. For instance, some participants might treat credit cards as different mental accounts. They were willing to spend more on credit cards compared to cash, as there seems to be no loss at the time of purchase and the payment can be deferred. This could lead to overspending. Also, in saving, some might stash cash away under the mattress, ignoring the interest earnings from a savings account. Other possible behaviors could be funding a low-interest savings account while carrying high-interest debt.

Research implications

Further research can address several issues or limitations. First, since ethnic Chinese young adults did not participate in this study, their inclusion in future research would facilitate a more comprehensive investigation. As young adults, they likely share similarities, such as spending philosophies, self-learning about financial information, and exposure to potential scams. However, differences may also exist in certain areas. The use of external restraint and personal hacks in financial matters, such as strong roles of parents and boyfriends in monitoring spending, and stashing cash away was less commonly observed among Chinese young adults. Informal borrowing and property investment in their home country were also unique characteristics of ethnic minority young adults. Further research can confirm these possibilities.

Second, this study may not fully reflect the situation of ethnic minority young adults with a lower socio-economic status. This is because the sample was generally well educated, as half of the participants had an undergraduate degree, and almost one-fifth educated to secondary education. In addition, the interviews were conducted in English, indicating a good command of the language among the participants. Future research may include those who are less socioeconomically advantaged as they may have different mechanisms surrounding financial decision-making.

Third, the relative influence of parents and peers across life stages, as well as differences in intrapersonal characteristics as facilitating factors between ethnic minority and non-ethnic minority young people, can be investigated to offer insights into tailored financial literacy education.

Moreover, we acknowledge the limitation of small sample size in a qualitative study, which aims to reveal themes for the financial literacy of ethnic minority young adults, an underexamined group. A future quantitative study for a larger population will be needed to allow for a broader generalization.

This study examined financial decision-making among ethnic minority young adults in Hong Kong and identified major enabling factors for their financial decision-making. Ethnic minority young adults employed strategies for budgeting, but they also found budgeting challenging. They had various spending philosophies, while basic needs were mostly a priority. Saving at least one-third of their income was common, and they had long-term financial planning goals. They used financial products both in Hong Kong and their home countries. Informal borrowing was common, despite some turning to other sources of loans. One-third used credit cards, incurring occasional risks. They were aware of scams and employed protective tactics, but still fell victim to scams.

Enabling factors to financial decisions included family social capital, intrapersonal characteristics, social dynamics factors, knowledge proficiency, and facilitative contextual circumstances. To enhance financial decision-making among ethnic minority young adults, the following can be considered. First, leveraging parental influence by involving them in financial education efforts. Second, fostering positive financial attitudes alongside increasing financial knowledge for a holistic financial education. Third, optimizing peer influence through collaborative learning and peer mentoring and raising awareness about community trust and potential issues with informal borrowing. Fourth, covering financial concepts for everyday financial decision-making and mental accounting bias, as well as practical knowledge for fraud prevention. Fifth, capitalizing on pre-employment and post-pandemic periods for timely financial education. Sixth, developing tailored digital tools and language support for specific ethnic communities. Finally, conducting further research is necessary. This includes the inclusion of ethnic Chinese and ethnic minority young people from various socioeconomic backgrounds and investigating the relative importance of parental and peer influence across different age groups. Moreover, comparing the intrapersonal characteristics as facilitating factors between ethnic minority and non-ethnic minority young people and expanding studies to include a larger population to enable generalization are also important.

Data availability

The data analysed during this study are not publicly available to protect research participant privacy but are available from the corresponding author upon reasonable request.

Information in parentheses denotes participant ID with ethnicity, gender and age, status as studying or working (S or W), and educational level, respectively. Education level may refer to the level of secondary school (e.g., S6), sub-degree (SD), Bachelor’s degree (Degree), or Master’s degree (Master’s).

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Acknowledgements

The research project was funded by the Investor and Financial Education Council in Hong Kong while the author was working at Hong Kong Baptist University. The research was conducted at that time. This paper was supported by the Children and Youth Research Centre and an Institutional Development Grant of Saint Francis University, Hong Kong, following the author’s transition to the new position at that university.

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Facilitators and barriers of midwife-led model of care at public health institutions of dire Dawa city, Eastern Ethiopia, 2022: a qualitative study

• Mickiale Hailu 1 ,
• Aminu Mohammed 1 ,
• Daniel Tadesse 1 ,
• Neil Abdurashid 1 ,
• Legesse Abera 1 ,
• Samrawit Ali 2 ,
• Yesuneh Dejene 2 ,
• Tadesse Weldeamaniel 1 ,
• Meklit Girma 3 ,
• Tekleberhan Hailemariam 1 ,
• Netsanet Melkamu 1 ,
• Tewodros Getnet 1 ,
• Yibekal Manaye 1 ,
• Tariku Derese 1 ,
• Muluken Yigezu 1 ,
• Natnael Dechasa 1 &
• Anteneh Atle 1  

BMC Health Services Research volume  24 , Article number:  998 ( 2024 ) Cite this article

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The midwife-led model of care is woman-centered and based on the premise that pregnancy and childbirth are normal life events, and the midwife plays a fundamental role in coordinating care for women and linking with other health care professionals as required. Worldwide, this model of care has made a great contribution to the reduction of maternal and child mortality. For example, the global under-5 mortality rate fell from 42 deaths per 1,000 live births in 2015 to 39 in 2018. The neonatal mortality rate fell from 31 deaths per 1,000 live births in 2000 to 18 deaths per 1,000 in 2018. Even if this model of care has a pivotal role in the reduction of maternal and newborn mortality, in recent years it has faced many challenges.

To explore facilitators and barriers to a midwife-led model of care at a public health institution in Dire Dawa, Eastern Ethiopia, in 2021.

Methodology

: A qualitative approach was conducted at Dire Dawa public health institution from March 1–April 30, 2022. Data was collected using a semi-structured, in-depth interview tool guide, focused group discussions, and key informant interviews. A convenience sampling method was implemented to select study participants, and the data were analyzed thematically using computer-assisted qualitative data analysis software Atlas.ti7. The thematic analysis with an inductive approach goes through six steps: familiarization, coding, generating themes, reviewing themes, defining and naming themes, and writing up.

Two major themes were driven from facilitators of the midwife-led model of care (professional pride and good team spirit), and seven major themes were driven from barriers to the midwife-led model of care (lack of professional development, shortage of resources, unfair risk or hazard payment, limited organizational power of midwives, feeling of demoralization absence of recognition from superiors, lack of work-related security).

The midwifery-led model of care is facing considerable challenges, both pertaining to the management of the healthcare service locally and nationally. A multidisciplinary and collaborative effort is needed to solve those challenges.

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Introduction

A midwife-led model of care is defined as care where “the midwife is the lead professional in the planning, organization, and delivery of care given to a woman from the initial booking to the postnatal period“ [ 1 ]. Within these models, midwives are, however, in partnership with the woman, the lead professional with responsibility for the assessment of her needs, planning her care, referring her to other professionals as appropriate, and ensuring the provision of maternity services. Most industrialized countries with the lowest mortality and morbidity rates of mothers and infants are those in which midwifery is a valued and integral pillar of the maternity care system [ 2 , 3 , 4 , 5 ].

Over the past 20 years, midwife-led model of care (MLC) has significantly lowered mother and infant mortality across the globe. In 2018, there were 39 deaths for every 1,000 live births worldwide, down from 42 in 2015. From 31 deaths per 1,000 live births in 2000 to 18 deaths per 1,000 in 2018, the neonatal mortality rate (NMR) decreased. The midwifery-led care approach is regarded as the gold standard of care for expectant women in many industrialized nations, including Canada, Australia, the United Kingdom, Sweden, the Netherlands, Norway, and Denmark. Evidence from those nations demonstrates that women and babies who get midwife-led care, as opposed to alternative types of care, experience favorable maternal outcomes, fewer interventions, and lower rates of fetal loss or neonatal death [ 6 , 7 , 8 ].

In Pakistan, the MLC was accompanied by many challenges. Some of the challenges were political threats, a lack of diversity (midwives had no opportunities for collaborating with other midwives outside their institutions), long duty hours and low remuneration, a lack of a career ladder, and a lack of socialization (the health centers are isolated from other parts of the country due to relative geographical inaccessibility, transportation issues, and a lack of infrastructure). Currently, in Pakistan, 276 women die for every 100,000 live births, and the infant mortality rate is 74/1000. But the majority of these deaths are preventable through the midwife-led care model [ 7 ].

The MLC in African countries has faced many challenges. Shortages of resources, work overload, low inter-professional collaboration between health facilities, lack of personal development, lack of a well-functioning referral system, societal challenges, family life troubles, low professional autonomy, and unmanageable workloads are the main challenges [ 8 ].

Due to the aforementioned challenges, Sub Saharan Africa (SSA) is currently experiencing the highest rate of infant mortality (1 in 13) and is responsible for 86% of all maternal fatalities worldwide. As a result, it is imperative to look at the MLC issues in low-income countries, which continue to be responsible for 99% of all maternal and newborn deaths worldwide [ 8 , 9 ].

Ethiopia’s has a Maternal mortality rate (MMR) and NMR of 412 per 100,000 live births and 33 per 1000 live births, respectively, remain high, making Ethiopia one of the largest contributors to the global burden of maternal and newborn deaths, placed 4th and 6th, although MLC could prevent a total of 83% of all neonatal and maternal fatalities in an environment that supports it. The MMR & infant mortality rate (IMR) in the research area were indistinguishable from that, at 150 per 100,000 live births and 67 fatalities per 1,000 live births, respectively [ 10 , 11 , 12 , 13 ].

Since the Federal Ministry of Health is currently viewing midwifery-led care as an essential tool in reducing the maternal mortality ratio and ending preventable deaths of newborns, exploring the facilitators and barriers of MLC may have a great contribution to make in reducing maternal and newborn mortality [ 14 ]. Since there has been no study done in Ethiopia or the study area regarding the facilitators and barriers of MLC, the aim of this research was to explore the facilitators and barriers of MLC in Dire Dawa City public health institutions.

In so doing, the research attempted to address the following research questions:

What were the facilitators for a midwife-led model of care at the Dire Dawa city public health institution?

What were the barriers to a midwife-led model of care at the Dire Dawa city public health institution?

Study setting and design

Institutional based qualitative study was conducted from March 01-April 30, 2022 in Dire Dawa city. Dire Dawa city is one of the federal city administrations in Ethiopia which is located at the distance of 515killo meters away from Addis Ababa (the capital city) to the east. The city administration has 9 urban and 38 rural kebeles (kebeles are the smallest administrative unit in Ethiopia). There are 2 government hospitals, 5 private hospitals, 15 health centers, and 33 health posts. The current metro area population of Dire Dawa city is 426,129.Of which 49.8% of them are males and 50.2% females. The total number of women in reproductive age group (15–49 years) is 52,673 which account 15.4% of the total population. It has hot temperature with a mean of 25 degree centigrade [ 15 ].

Study population and sampling procedure

The source population for this study included all midwives who worked at Dire Dawa City public health facilities as well as key informants from appropriate organizations (the focal person for the Ethiopian Midwives Association and maternal and child health (MCH) team leaders). The study encompassed basically 41 healthcare professionals who worked in Dire Dawa public health institutions in total, and the final sample size was decided based on the saturation of the data or information.

From the total 15 Health centers and 2 Governmental Hospitals found in Dire Dawa city administration, 8 Health centers and 2 Governmental Hospitals were selected by non-probability purposive sampling method. In addition to that a non-probability convenience sampling method was used to select midwives who were working in Dire Dawa city public health institutions and key informants from the relevant organization such as Ethiopian midwives association focal person and MCH team leaders. Midwives who were working for at least six months in the institution were taken as inclusion criteria while those who were working as a free service were excluded from the study.

Data collection tool and procedures

Focus groups, in-depth interviews, and key informant interviews were used in collecting data. A voice recorder, a keynote-keeping, and a semi-structured interview tool were all used to conduct the interviews. Voluntary informed written consent was obtained from the study participant’s before they participated in the study. Then an in-depth interview and focus group discussion were held with midwives chosen from various healthcare organizations. The MCH department heads and the Dire Dawa branch of the Ethiopian Midwife Association served as the key informants. In-depth interview (IDI) and key informant interviews (KII) with participants took place only once and lasted for roughly 50–60 min. In the midwives’ duty room, the interview was held. Six to eight people participated in focus group discussions (FGD), which lasted 90 to 100 min. Two midwives with experience in gathering qualitative data gathered the information.

Data quality control

The qualitative design is prone for bias but open-ended questions were used to avoid acquiescence and 2 day proper training was given for the data collector regarding taking keynotes and recording using a tape recorder. For consistency and possible modification, a pretest was done in one FGD and In-depth interviews at non selected health institutions of Dire Dawa city administrations. A detailed explanation was given for the study participants about the objectives of the study prior to the actual data collections. All (FGDs, key informant interview and In-depth interviews) were taken in a silent place.

Data analysis

Atlas.ti7, a qualitative data analysis program, was used for analyzing the data thematically. An inductive approach to thematic analysis involves six steps: familiarization, coding, generation of themes, review of themes, defining and naming of themes, and writing up. By listening to the taped interview again, the data was transcribed. The participants’ well-spoken verbatim was used to extract and describe the inductive meanings of the statements. The data was then coded after that. Each code describes the concept or emotion made clear in that passage of text. Then we look at the codes we’ve made, search for commonalities, and begin to develop themes. To ensure the data’s accuracy and representation, the generated themes were reviewed. Themes were defined and named, and then the analysis of the data was written up.

Trustworthiness of data

Meeting standards of trustworthiness by addressing credibility, conformability, and transferability ensures the quality of qualitative research. Data triangulation, data collection from various sites and study participants, the use of multiple data collection techniques (IDI, KII, and FGD), multiple peer reviews of the proposal, and the involvement of more than two researchers in the coding, analysis, and interpretation decisions are all instances of the methods that were used in order to fulfill the criteria for credibility. To increase its transferability to various contexts, the study gave details of the context, sample size and sampling method, eligibility criteria, and interview processes. To ensure conformability, the research paths were maintained throughout the study in accordance with the work plan [ 16 , 17 ].

Background characteristics of the study participants

In this study, a total of 41 health care providers who are working in Dire Dawa public health facilities participated in the three FGDs, six KIIs, and fifteen IDIs. The years of experience of study participants range from one year to 12 years. The participants represented a wide age range (30–39 years), and the educational status of the respondents ranged from diploma to master’s degree. (Table  1 )

As shown in Table  2 , from the qualitative analysis of the data, two major themes were driven from facilitators of MLC, and seven major themes were driven from barriers to MLC. (Table  2 ).

Facilitators of midwife-led model of care at a public health institution of Dire Dawa city, Eastern Ethiopia, in 2021

Professional pride.

This study found that saving the lives of mothers and newborns was a strong facilitator. Specifically, it was motivational to have skills within the midwifery domain, such as managing the full continuum of care during pregnancy and labour, supporting women in having normal physiologic births, being able to handle complications, and building relationships with the women and the community, as mentioned below by one of the IDI participants.

“I am so proud since I am a midwife; nothing is more satisfying than seeing a pregnant mother give birth almost without complications. I always see their smile and happiness on their faces , especially in the postpartum period , and they warmly thank me and say , “Here is your child; he or she is yours.” They bless me a lot. Even sometimes , when they sew me in the transport area , cafeteria , or other area , they thank me warmly , and some of them also want to invite me to something else. The sum total of those things motivates me to be in this profession or to provide midwifery care.“ IDI participants.

This finding is also supported by other participants in FGD.

“We have learned and promised to work as midwives. We are proud of our profession , to help women and children’s health. The greatest motivation is that we are midwives , we love the profession , and we are contributing a great role in decreasing maternal and child mortality….” FGD discussant.

Good teamwork

The research revealed that good midwifery teamwork and good social interaction within the staff have become facilitators of MLC. FGD participants share their experiences of working in a team.

“In our facility , all the midwives have good teamwork; we have good communication , and we share client information accurately and timely. In case a severe complication happens , we manage it as a team , and we try to cover the gap if some of our staff are absent. Further from that , we do have good social interactions in the case of weeding , funeral ceremonies , and other social activities. We do have good team spirit; we work as a team in the clinical area , and we also have good social relationships. “If some of our staff gets sick or if she or he has other social issues , the other free staff will cover her or his task.” FGD discussant.

Another participant from IDI also shared the same experience regarding their good teamwork and their social interactions.

“As a maternal and child health team , we do have a good team spirit , not only with midwives but also with other professions. We are not restricted by the ward that we assign. If there is a caseload in any unit , some midwives will volunteer to help the other team. Most of the time in the night , we admit more than 3 or 4 labouring mothers at the same time. Since in our health center only one midwife is assigned in the night , we always call nurses to help us. This is our routine experience.” IDI participants.

Barriers of midwife-led model of care at a public health institution of Dire Dawa city, Eastern Ethiopia, in 2021

Lack of professional development.

This study revealed that insufficient opportunities for further education and updated training were the main barriers for MLC. Even the few trainings and update courses that were actually arranged were unavailable to them, either because they did not meet the criteria seated or because the people who work in administration were selected. Even though opportunities are not arranged for them to upgrade themselves through self-sponsored. One of the participants from IDI narrates her opinion about opportunities for further education as follows:

“Training and updates are not sufficient; currently we are almost working with almost old science. For example , the new obstetrics management protocol for 2021 has been released from the ministry of health , and many things have changed there. But we did not receive any training or even announcements. Even the few trainings and update courses that were truly organized and turned in to us are unavailable since the selection criteria are not fair. As a result , we miss those trainings either because we did not meet the selection criteria or because those who work in administration are prioritized.” IDI participant.

FGD discussants also support this idea. She mentioned that even though opportunities are not arranged for them to upgrade themselves through self-sponsorship,

“There is almost no educational opportunity in our institution. Every year , one or two midwives may get institutional sponsorship. Midwives that will be selected for this opportunity are those who have served for more than five to ten years. Imagine that to get this chance , every midwife is expected to serve five or more years. Not only this , even if staff want to learn or upgrade at governmental or private colleges through self-sponsored programmes , whether at night or in an extension programme , they are not cooperative. Let me share with you my personal experience. Before two years , I personally started my MSc degree at Dire Dawa University in a weekend programme , and I have repeatedly asked the management bodies to let me free on weekends and to compensate me at night or any time from Monday to Friday. Since they refuse to accept my concern , I withdraw from the programme.“ FGD discussant.

Shortage of resource

The finding indicates that a shortage of equipment, staff, and rooms or wards was a challenge for MLC. Midwives claimed they were working with few staff, insufficient essential supplies, and advanced materials. This lack of equipment endangers both the midwives and their patients. One of the participants from IDI narrates her opinion about the shortage of resources as follows:

“Of course there is a shortage of resources in our hospital , like gloves and personal protective devices. Even the few types of medical equipment available , like the autoclave , forceps , vacuum delivery couch , and BP apparatus , are outdated , and some of them are unfunctional. If you see the Bp apparatus we used in ANC , it is digital but full of false positives. When I worked in the ANC , I did not trust it and always brought the analogue one from other wards. This is the routine experience of every staff member.“ IDI participants.

Another participant from IDI also shared the same experience regarding the crowdedness of rooms or wards.

“In our health center , there are no adequate wards or rooms. For example , the delivery ward and postnatal ward are almost in one room. Postnatal mothers and neonates did not get enough rest and sleep because of the sound of laboring mothers. Not only is this , but even the antenatal care and midwifery duty rooms are also very narrow.“ IDI participants.

The study also revealed midwifery staff were pressured to work long hours because they were understaffed, which in turn affected the quality of midwifery care. The experience of a certain midwife is shared as follows:

“I did not think that the management bodies understood the risk and stress that we midwives face. They did not want to consider the risk of midwives even equal to that of other disciplines but lower than the others. For example , in our health centre , during the night , only one midwife is assigned for the next 12 hours , but if you see in the nurse department , two or more nurses are assigned at night in the emergency ward.” IDI participants.

The discussion affirms the fact that being understaffed and not having an adequate allocation of midwife professionals on night shifts are affecting labouring mothers’ ability to get sufficient health midwifery care. The above narration is also supported by the FGD discussant.

“In our case , only one midwife is assigned to the labour ward during the night shift. I think this is the main challenge for midwives that needs attention. Let me share with you my experience that happened months before. While I was on night shift , two labouring mothers were fully dilated within three or four minutes. It was very difficult for me , to manage two labouring mothers at the same time. Immediately , I call one of my nurse friends from the emergency department to help me. If my friend was so busy , what could happen to the labouring mother and also to me? This is not only my experience but also the routine experience of other midwives.” FGD discussant.

Unfair risk or hazard payments

It is reported that the compensation amount paid for risk is lower than in other health professions. The health risks are not any less, but the remuneration system failed to capture the need to fairly compensate midwifery professionals. The narration from the FGD discussant regarding unfair payment is mentioned below.

“Only 470 ETB is paid for midwives as risk payments , which is incomparable with the risks that midwives are facing. But contrary to that , the risk payments for nurses (in emergencies) are about 1200 Ethiopian birr (ETB) , and Anesthesia is 1000 ETB. I did not want to compare my profession with other disciplines , but with the lowest cost , how the risk of midwifery cannot be equal to that of nursing and other professions. I did not know whose professionals made such types of unfair decisions and with what scientific background or base this calculation was done . ” FGD discussant.

The above finding is also supported by an IDI participant.

“………………………….Even though the midwifery profession is full of risks , with the current Ethiopian health care system , midwives are being paid the lowest risk payments compared to other disciplines…………….” IDI participants.

Limited organizational power of midwives

Midwives’ interviews reported that limited senior midwifery positions in the health system have become the challenge of midwifery care. This constrains the decision-making power and capability of midwives. This was compounded by limited opportunities for midwifery personnel to address their concerns to the responsible bodies, as stated by one of the key informants.

“Our staff has many concerns , especially professional-related concerns , which can contribute to the quality of midwifery care. Personally , as department head , I have tried to address those concerns in different management meetings at different times. But since the leadership positions are dominated by other disciplines , many of our staff concerns have not been solved yet. But let me tell you my personal prediction… If those concerns are not solved early and if this trend continues , the quality of midwifery care will be in danger.“ Participant from Key Informant.

The above finding is also supported by another IDI participant.

“In our hospital , at every hierarchal and structural level , midwives are not well represented. That is why all of our challenges or concerns have not been solved yet. For example , as a structure in the Dire Dawa Health Office (DDHO) , there is a team of management related to maternal and child health. But unfortunately , those professionals working there are not midwives. I was one of three midwives chosen to meet with Dr. X (former DDHO leader) to discuss this issue. At the time , we were reaching an agreement that two or three midwives would be represented on that team. But since a few months later the leader resigned , the issue has not gotten a solution yet.“ IDI participant.

Feeling of demoralization

One of the main concerns reported by the participants during the interviews was a feeling of demoralization induced by both their clients and their supervisors about barriers to midwifery care. They reported having been verbally abused by their patients, something that made them feel that their hard work was being undermined, as stated by an FGD participant.

“I don’t think there is any midwife who would be happy for anybody to lose their baby , or that there is any midwife who would want a woman to die. These things are accidents , but the patient and leaders will always blame the midwife.” FDG discussant.

A narration from an IDI participant also mentioned the following:

“……….If something happens , like a conflict with the patients or clients , the management is on the patient side. Not only that , the way in which they communicate with us is in an aggressive or disrespectful manner . ” IDI participant.

Absence of recognition or /motivation from superiors

This study revealed that midwives experience a loss of motivation at work due to limited support from their superiors. Their effort is used only for reporting purposes. A midwife from FGD shared her experience as follows.

“In our scenario , till the nearest time , the maternal and child health services are provided in a good way. But this was not easy; it is the cumulative effort of midwives. But unfortunately , only those in managerial positions are recognized. Nothing was done for us despite our efforts. To me , our efforts are used only for reporting purposes.” FGD discussant.

This finding was also supported by IDI participants.

“Even though we have good achievements in the MCH services , there is no motivation mechanism done to motivate midwives.” But if something or a minor mistake happens , they are on the front lines to intimidate us or write a warning letter. Generally , their concern is a report or a number issue. We are tired of such types of scenarios.” IDI participant.

Insufficient of work-related security

One of the main concerns reported by the participants during the interviews was the work related security, which has become a challenge for MLC. The midwives’ work environment was surrounded by insecurity, especially during night shifts, when midwives were facing verbal and even physical attack, as mentioned by participants.

“In the labour ward , especially at night , we face many security-related issues. The families of labouring mothers , especially those who are young , are very aggressive. Sometimes they even want to enter the delivery room. They did not hear what we told them to do , but if they hear any labour sounds from their family , they disturb the whole ward. This leads to verbal abuse , and sometimes we face physical abuse. There may be one or two security personnel at the main gate , but since the delivery ward is far from the main gate , they do not know what is happening in the delivery ward. When things become beyond our scope , we call security guards. Immediately after the security guards go back , similar things will continue. What makes it difficult to manage such situations is that only one midwife is assigned at night , and labouring mothers will not get quality midwifery care.” IDI participant.

FGD discussants also shared their experience that their working environment is full of insecurity.

“In case any complications occur , especially at night , it is very difficult to tell the labouring mother’s family or husband unless we call security personnel. It is not only swearing that we face but also that they intimidate us.” FDG discussant.

Discussions

The aim of this study was to explore facilitators’ and barriers to a midwifery-led model of care at Dire Dawa public health facilities. In this study, professional pride was the main facilitator of the midwifery-led model of care. Another qualitative study that examined the midwifery care challenges and factors that motivate them to remain in their workplace lends confirmation to this conclusion. It was found that a strong feeling of love for their work was the main facilitator’s midwifery-led model of care [ 9 ]. Having a good team spirit was also another facilitator’s midwifery-led model of care in our study. Another study’s findings confirmed this one, which emphasizes that building relationships with the midwives, women, and community was the driving force behind providing midwifery care [ 7 , 18 ].

The midwives in this study expressed a need for additional professional training, updates, and competence as part of their continuing professional development. Similar findings have been reported in the worldwide literature that midwives were struggling for survival due to a lack of limited in-service training opportunities to improve their knowledge and skills [ 19 ]. This phenomenon does not seem to differ between settings in high-, middle-, and low-income countries [ 7 , 9 , 18 ], in which midwives experienced difficult work situations due to a lack of professional development to autonomously manage work tasks, which made them feel frustrated, guilty, and inadequate. As such, this can contribute to distress and burnout, which in turn prevent midwives from being able to provide quality care and can eventually cause them to leave the profession [ 19 ].

Shortages of resources (shortage of staff, lack of physical space, and equipment) were the other reported barriers to midwifery care explored in this study. They reported that they are working in an environment with a shortage of resources, which leads to poor patient outcomes. This finding is supported by many other studies conducted around the globe [ 20 , 21 , 22 , 23 ]. Another qualitative finding, which likewise supports the aforementioned finding, which emphasizes that a shortage of resources was reported as a barrier to providing adequate midwifery care [ 19 ]. Delivery attended by skilled personnel with appropriate supplies and equipment has been found to be strongly associated with a reduction in child and maternal mortality [ 24 ].

The feeling of demoralization and lack of motivation from their superiors were other barriers to midwifery care explored in this study. This finding is concurrent with other studies conducted around the globe [ 19 , 25 , 26 , 28 ]. The above finding is also is in accord with another qualitative narration, which emphasizes that feelings of demoralization and a lack of motivation were the main challenges of midwifery care [ 22 ]. Positive support from supervisors has been demonstrated to be important for the quality of services that health workers are able to deliver. In the World Health Organization’s report on improving performance in healthcare, the WHO stresses that supportive supervision can contribute to the improved performance of health workers [ 27 ].

Unfair risk payment was the other challenge identified by the current study. Even though there is no difference in the risk they face among health professionals, the risk payment for midwives is very low compared to others. This finding was in conformity with another qualitative narration, which emphasizes that the lack of an equitable remuneration system was experienced by the DRC midwives, and it has also been confirmed to be highly problematic in other studies in low- and middle-income settings [ 7 , 8 , 22 , 28 ], leading to serious challenges. In settings where salaries are extremely low or unpredictable, proper remuneration is seen as crucial to worker motivation and the quality of midwifery care [ 29 , 30 ].

The limited organizational power of midwives was another identified challenge of MLC. This finding was in step with other studies that emphasize that limited senior midwifery positions in the health system constrain the decision-making power and capability of midwives. This was compounded by limited opportunities for midwifery personnel to address their concerns to the responsible bodies. Hence, midwives need to take control of their own situations. When midwives are included in customizing their work environments, it has proven to result in improved quality of care for women and newborns around the globe [ 8 , 15 ].

Lack of work-related security was another barrier to MLC explored in this study, in which the midwives’ work environment was surrounded by insecurity, especially during night shifts, when midwives are facing verbal and even physical attack, as mentioned by participants. This finding is supported by many other studies conducted around the globe [ 22 , 23 , 25 , 31 ]. The above finding is also in agreement with another qualitative narration, which emphasizes that the midwives’ work environment was surrounded by insecurity, especially during night shifts due to a lack of available security personnel; they often felt frightened on their way to and from work [ 7 ]. In order for midwives to provide quality care, it is crucial to create supportive work environments by ensuring sufficient pre-conditions, primarily security issues [ 31 ].

Conclusions

The study findings contribute to a better understanding of the facilitators’ and barriers of a midwifery-led model of care in the case of Dire Dawa public health facilities. Professional pride and having good team spirit were the main facilitators of midwifery-led model care. Contrary to that, insufficient professional development, shortage of resources, feeling of demoralization, lack of motivation, limited organizational power of midwives, unfair risk payment, and lack of work-related security were the main barriers to a midwifery-led model of care in the case of Dire Dawa public health facilities. Generally, midwifery care is facing considerable challenges, both pertaining to the management of the healthcare service locally and nationally.

Study implications

The findings of the study have implications for midwifery care practices in Eastern Ethiopia. Addressing these areas could potentially contribute to the reduction of IMR and MMR.

Strengths and limitations

The first strength of the study is that the participants represented different healthcare facilities, both urban and rural, thereby offering deeper and more varied experiences and reflections. A second strength is using a midwife as a moderator. She or he understood the midwives’ situation, thereby making the participants feel more comfortable and willing to share their stories. However, focusing solely on the perspective of the midwives is a limitation.

Recommendations

To overcome the barriers of midwifery care, based on the result of this study and in accordance with the 2020 Triad Statement made by the International Council of Nurses, the International Confederation of Midwives, and the World Health Organization, it is suggested that policymakers, Ethiopian federal ministry of health, Dire dawa health office, and regulators in Dire Dawa city and settings with similar conditions coordinate actions in the following:

To the Ethiopian federal ministry of health (FMOH)

Should strengthen regular and continuous educational opportunities, trainings, and updates for midwives, prioritizing and enforcing policies to include adequate and reasonable remuneration and hazard payment for midwives. Support midwifery leadership at all levels of the health system to contribute to health policy development and decision-making.

To dire Dawa health Bureau

Ensure decent working conditions and an enabling environment for midwives. This includes reasonable working hours, occupational safety, safe staffing levels, and merit-based opportunities for career progression. Special efforts must be made to ensure safe, respectful, and enabling workplaces for midwives operating on the night shift. Midwifery leaders should be involved in management bodies within an appropriate legal framework. Made regular mentorships on the functionality of different diagnostic instruments in respective health facilities.

To Dire Dawa public health facility’s

Create an arena for dialogue and implement a more supportive leadership style at the respective health facilities. Should address professional-related concerns of midwives early. Ensure midwives’ representation at the management bodies. Ensure the selection criteria for educational opportunities and different trainings are fair and inclusive. Ensure the safety and security of midwives, especially those who work night shifts. Should assign adequate staff (midwives and security guards) to the night shifts.

Ethiopian midwifery association

Should influence different stakeholders to solve midwife’s concerns like hazards payment and educational opportunity.

Data availability

All the datasets for this study are available from the corresponding author upon request.

Abbreviations

Focused group discussion

In-depth interview

Infant mortality rate

Key informant interview

Maternal and child health

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Neonatal mortality rate

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Acknowledgements

We are very grateful to Dire Dawa University for the financial support for this study and to the College of Medicine and Health for its monitoring ship. All study participants for their willingness to respond to our questionnaire.

this work has been funded by Dire Dawa University for data collection purposes. The Dire Dawa University College of Medicine and Health Sciences was involved in the project through monitoring and evaluation of the work from the beginning to the result submission. However, this organization was not involved in the design, analysis, critical review of its intellectual content, or manuscript preparation, and its budget did not include publication.

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Contributions

MH developed the study proposal, served as the primary lead for study implementation and data analysis/interpretation, and was a major contributor in writing and revising all drafts of the paper. AM, DT, NA, LA, and SA supported study implementation and data analysis, and contributed to writing the initial draft of the paper. YD, TW, MG, TH and, NM supported study recruitment and contributed to writing the final draft of the paper. TG, YM, TD, MY, ND and, AA conceptualized, acquired funding, and led protocol development for the study, co-led study implementation and data analysis/interpretation, and was a major contributor in writing and revising all drafts of the paper. All authors contributed to its content. All authors read and approved the final manuscript.

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Correspondence to Mickiale Hailu .

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All methods were followed in accordance with relevant guidelines and regulations. The institutional review board of Dire Dawa University has also examined and evaluated it for its methodological approach and ethical concerns. Ethical clearance was obtained from Dire Dawa University Institutional Review Board and an official letter from research affairs directorate office of Dire Dawa University was submitted to Dire Dawa health office and it was distributed to selected health institutions. Voluntary informed written consent was obtained from the study participant’s right after the objectives of the study were explained to the study participants and confidentiality of the study participants was assured throughout the study period. Participants were informed that they have the right to terminate the discussion (interview) or they can’t answer any questions they didn’t want to answer.

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Hailu, M., Mohammed, A., Tadesse, D. et al. Facilitators and barriers of midwife-led model of care at public health institutions of dire Dawa city, Eastern Ethiopia, 2022: a qualitative study. BMC Health Serv Res 24 , 998 (2024). https://doi.org/10.1186/s12913-024-11417-x

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Received : 03 September 2023

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DOI : https://doi.org/10.1186/s12913-024-11417-x

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