Sampling in Interview-Based Qualitative Research: A Theoretical and Practical Guide

TL;DR: A four-point approach to sampling in qualitative interview-based research is presented and critically discussed in this article, which integrates theory and process for the following: (1) defining a sample universe, by way of specifying inclusion and exclusion criteria for potential participation; (2) deciding upon a sample size, through the conjoint consideration of epistemological and practical concerns; (3) selecting a sampling strategy, such as random sampling, convenience sampling, stratified sampling, cell sampling, quota sampling or a single-case selection strategy; and (4) sample sourcing, which includes

Abstract: Sampling is central to the practice of qualitative methods, but compared with data collection and analysis its processes have been discussed relatively little. A four-point approach to sampling in qualitative interview-based research is presented and critically discussed in this article, which integrates theory and process for the following: (1) defining a sample universe, by way of specifying inclusion and exclusion criteria for potential participation; (2) deciding upon a sample size, through the conjoint consideration of epistemological and practical concerns; (3) selecting a sampling strategy, such as random sampling, convenience sampling, stratified sampling, cell sampling, quota sampling or a single-case selection strategy; and (4) sample sourcing, which includes matters of advertising, incentivising, avoidance of bias, and ethical concerns pertaining to informed consent. The extent to which these four concerns are met and made explicit in a qualitative study has implications for its coherence, tran...

Summary

Introduction

• Sampling is central to the practice of qualitative methods, but compared with data collection and analysis, its processes are discussed relatively little.
• The extent to which these four concerns are met and made explicit in a qualitative study has implications for its coherence, transparency, impact and trustworthiness.

Keywords

• Sampling, purposive sampling, random sampling, theoretical sampling, case study, stratified sampling, quota sampling, sample size, recruitment attention in methodological textbooks and journals than its centrality to the process warrants (Mason, 2002).
• Therefore, all researchers must consider the homogeneity/heterogeneity trade-off for themselves and delineate a sample universe that is coherent with their research aims and questions, and with the amount of research resources they have at their disposal.
• Of all qualitative methodologies, Grounded Theory puts most emphasis on being flexible about sample size as a project progresses (Glaser, 1978).
• Sample size may be increased if ongoing data analysis leads the researcher to realise that he/she has omitted an important group or type of person from the original sample universe, who should be added to the sample in order to enhance the validity or transferability of the findings or theory (Silverman, 2010).
• For qualitative research, the danger of convenience sampling is that if the sample universe is broad, unwarranted generalisations may be attempted from a convenience sample.

Purposive sampling strategies

• Purposive sampling strategies are non-random ways of ensuring that particular categories of cases within a sampling universe are represented in the final sample of a project.
• The rationale for employing a purposive strategy is that the researcher assumes, based on their a-priori theoretical understanding of the topic being studied, that certain categories of individuals may have a unique, different or important perspective on the phenomenon in question and their presence in the sample should be ensured (Mason, 2002; Trost, 1986).
• Summarised below are stratified, cell, quota and theoretical sampling, which are all purposive strategies used in studies that employ multiple cases.
• Following this I describe significant case, intensity, deviant case, extreme case and typical case sampling, which are purposive strategies that are best employed when selecting a single case study.

Stratified sampling

• In a stratified sample, the researcher first selects the particular categories or groups of cases that he/she considers should be purposively included in the final sample.
• Here, the variable of ‘with children/without children’ is added to the divorce study sampling framework.
• As previously mentioned, to include a purposive sampling stratification there must be clear theoretical grounds for the categories used.
• Cell sampling be filled when gaining sample.
• This example is illustrated in Figure 3.

Quota sampling

• The process of quota sampling is a more flexible strategy than stratified or cell sampling.
• Instead of requiring fixed numbers of cases in particular categories, quota sampling sets out a series of categories and a minimum number of cases required for each one (Mason, 2002).
• As the sample is gathered, these quota are monitored to establish whether they are being met.
• A quota sample might list the following: 1. At least 10 couples whose experience pertains to moving their father into supported.
• Accommodation, and at least 10 whose experience pertains to their mother.

Theoretical sampling

• Theoretical sampling differs from the aforementioned purposive strategies, for it takes place during the collection and analysis of data, following provisional sampling and analysis of some data (Coyne, 1997; Strauss, 1987).
• An intensity sampling strategy was taken for the purposes of selecting a case study on early adult crisis; from a previous interview sample, individuals were selected who had provided a comprehensive account of both the inner and outer dimensions of their crisis experience, following which one person was selected randomly from this information-rich group (Robinson & Smith, 2010b).
• Ways of recruiting participants for interviews are only limited by a researcher’s ingenuity in how to disseminate the message of his/her research study to the sample universe.
• Recruiting interviewees within organisations presents particular advertising challenges.
• Having gained a list of interested individuals, consent from parents/guardians was received prior to arranging interviews.

The question of incentives and ‘respondent-driven sampling’

• When recruiting people into an interview study, the question of whether to offer them a financial incentive for participation is a key decision that the researcher must make.
• The benefits of incentives are that they increase the likelihood of participation by adding additional motivation, and also increase retention in longitudinal studies (Yancey, Ortega & Kumanyika, 2006).
• These individuals are then given a number of ‘recruitment coupons’.
• Key decisions to enhance rigour are the relationship of the sample to the sample universe, the appropriate choice of sampling strategy, the robustness of the sample sourcing approach, and the overall fit between research questions and total sample strategy.
• This criterion requires the research to have theoretical or practical relevance beyond the sample used.

Summary

• In summary, four points holistically encompass the challenge of sampling in interview-based qualitative studies: defining the sample universe, deciding on a sample size, selecting a sample strategy and sourcing cases.
• An Expanded Sourcebook, 2nd edition, also known as Qualitative Data Analysis.
• Psychological Methods, 4, 425-451. Smith, JA, Flowers, P & Larkin, M 2009, Interpretative phenomenological analysis: theory, method and research, Sage, London.
• A sampling technique for qualitative studies, also known as Statistically non-representative stratified sampling.

Full text

Qualitative Research in Psychology, in press
1
Sampling in interview-based qualitative research: A theoretical and practical guide
Abstract
Sampling is central to the practice of qualitative methods, but compared with data collection and
analysis, its processes are discussed relatively little. A four-point approach to sampling in qualitative
interview-based research is presented and critically discussed in this article, which integrates theory
and process for the following: (1) Defining a sample universe, by way of specifying inclusion and
exclusion criteria for potential participation; (2) Deciding upon a sample size, through the conjoint
consideration of epistemological and practical concerns; (3) Selecting a sampling strategy, such as
random sampling, convenience sampling, stratified sampling, cell sampling, quota sampling or a
single-case selection strategy; and (4) Sample sourcing, which includes matters of advertising,
incentivising, avoidance of bias, and ethical concerns pertaining to informed consent. The extent to
which these four concerns are met and made explicit in a qualitative study has implications for its
coherence, transparency, impact and trustworthiness.
Keywords
Sampling, purposive sampling, random sampling, theoretical sampling, case study, stratified
sampling, quota sampling, sample size, recruitment

Qualitative Research in Psychology, in press
2
Sampling is an important component of qualitative research design that has been given less
attention in methodological textbooks and journals than its centrality to the process warrants
(Mason, 2002). In order to help fill this void, the current article aims to provide academics, students
and practitioners in Psychology with a theoretically-informed and practical guide to sampling for use
in research that employs interviewing as data collection. Recognised methods in qualitative
psychology that commonly use interviews as a data source include Interpretative Phenomenological
Analysis (IPA), Grounded Theory, Thematic Analysis, Content Analysis, and some forms of Narrative
Analysis. This article presents theoretical and practical concerns within the framework of four ‘pan-
paradigmatic’ points: (1) setting a sample universe, (2) selecting a sample size, (3) devising a sample
strategy and (4) sample sourcing. Table 1 summarises the principle features of these. All of the
aforementioned methods can be used in conjunction with this four-point approach to sampling.
(Insert Table 1)
Point 1: Defining a sample universe
The first key concern in the four-point approach is defining the sample universe (also called ‘study
population’ or ‘target population’). This is the totality of persons from which cases may legitimately
be sampled in an interview study. To delineate a sample universe, a set of inclusion criteria or
exclusion criteria, or a combination of both, must be specified for the study (Luborsky & Rubinstein,
1995; Patton, 1990). Inclusion criteria should specify an attribute that cases must possess to qualify
for the study (e.g. a study on domestic violence that specifies that participants must be women who
have suffered partner violence that was reported to the police or social services), while exclusion
criteria must stipulate attributes that disqualify a case from the study (e.g. a study on exercise that
stipulates that participants must not be smokers). Together, these criteria draw a boundary around
the sample universe, as illustrated in Figure 1.
(Insert Figure 1)
Homogeneity and heterogeneity in the sample universe
The more inclusion and exclusion criteria that are used to define a sample universe, and the more
specific these criteria are, the more homogenous the sample universe becomes. Sample universe
homogeneity can be sought along a variety of parameters, such as demographic homogeneity,
geographical homogeneity, physical homogeneity, psychological homogeneity or life history
homogeneity (see Table 2 for descriptions of these). The addition of exclusion or inclusion criteria in
these different domains increases sample homogeneity.

Qualitative Research in Psychology, in press
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One of these forms of homogeneity - psychological homogeneity - is established if a criterion for
case inclusion is a particular mental ability, attitude or trait. In order to make case selection possible
based on this kind of criterion, quantitative data from questionnaires or tests can be used as a
sampling tool (Coleman, Williams & Martin, 1996). For example, Querstret and Robinson (2013)
gained quantitative data on the extent to which individuals self-report having a personality that
varies across different social contexts, and used this data to select individuals who were one
standard deviation or more above the mean for ‘cross-context variability’. These persons were then
interviewed for a qualitative study about the motivations for, and experiences of, varying behaviour
and personality according to social context.
(Insert Table 2)
The extent of sample universe homogeneity that a research study aims at is influenced by both
theoretical and practical factors. Theoretically, certain qualitative methods have a preference for
homogenous samples; for example Interpretative Phenomenological Analysis is explicit that
homogenous samples work best in conjunction with its philosophical foundations and analytical
processes (Smith, Flowers & Larkin, 2009). By maintaining a measure of sample homogeneity, IPA
studies remain contextualised within a defined setting, and any generalisation from the study is
made cautiously to that localised sample universe, and not beyond at any more speculative or
abstract level.
Conversely, there are approaches that aim to gain samples that are intentionally heterogeneous, for
example the variation sampling technique of Grounded Theory (Strauss and Corbin, 1998), or the
cross-contextual approach described by Mason (2002). The rationale for gaining a heterogeneous
sample is that any commonality found across a diverse group of cases is more likely to be a widely
generalizable phenomenon than a commonality found in a homogenous group of cases. Therefore,
heterogeneity of sample helps provide evidence that findings are not solely the preserve a particular
group, time or place, which can help establish whether a theory developed within one particular
context applies to other contexts (Mason, 2002).
Cross-cultural qualitative research is another instance where a demographically and geographically
heterogeneous sample may be called for. Such research selects individuals from different cultures in
order to compare them and search for similarities and differences (see Table 2). An example of
qualitative research conducted at such a scale was the EUROCARE study – the sample universe was
comprised of persons caring for co-resident spouses with Alzheimer’s in 14 European countries
(Murray, Schneider, Banerjee, & Mann, 1999; Schneider, Murrary, Banerjee, & Mann, 1999). This

Qualitative Research in Psychology, in press
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influential piece of research shows that cross-cultural qualitative research can be successfully
conducted with a culturally heterogeneous sample universe, if resources are available.
There are however challenges inherent in using a heterogeneous sample. The first is that findings
will be relatively removed from real-life settings, and the second is that the sheer diversity of data
may lessen the likelihood meaningful core cross-case themes being found during analysis. Therefore,
all researchers must consider the homogeneity/heterogeneity trade-off for themselves and
delineate a sample universe that is coherent with their research aims and questions, and with the
amount of research resources they have at their disposal.
The sample universe is not only a practical boundary that aids the process of sampling, it also
provides an important theoretical role in the analysis and interpretation process, by specifying what
a sample is a sample of, and thus defining who or what a study is about. The level of generality to
which a study’s findings is relevant and logically inferable is the sample universe (Mason, 2002), thus
the more clearly and explicitly a sample universe is described, the more valid and transparent any
generalisation can be. If a study does not define a sample universe, or makes claims beyond its own
sample universe, this undermines its credibility and coherence.
Point 2: Deciding on a sample size
The size of a sample used for a qualitative project is influenced by both theoretical and practical
considerations. The practical reality of research is that most studies require a provisional decision on
sample size at the initial design stage. Without a provisional number at the design stage, the
duration and required resource-allocation of the project cannot be ascertained, that makes planning
all but impossible. However a priori sample specification need not imply inflexibility – instead of a
fixed number, an approximate sample size range can be given, with a minimum and a maximum.
Interview studies that have a nomothetic aim to develop or test general theory are to a degree
reliant on sample size to generalise (Robinson, 2012). Sample size is by no means the only factor
influencing generalisability, but it is part of the picture. O’Connor and Wolfe’s grounded theory of
midlife transition, which was based on interviews with a sample of 64 adults between the ages of 35
and 50 (O’Connor and Wolfe, 1987) Illustrates this point. A way of working with larger sample sizes
in qualitative research, which prevents analytical overload, is to combine separate studies together
into larger syntheses. For example, I recently combined findings from a series of three studies on the
topic of early adult crisis into a single analytical synthesis and single article. One contributing study
had a sample of 16 cases, the second had a sample of 8 cases, and the third employed a sample of

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26 cases. These were analysed and reported as separate studies originally, before being combined
into the synthesis paper with a total sample of N=50 (Robinson, Wright & Smith, 2013).
Very large-scale qualitative interview projects include hundreds of individuals in their sample. For
example the aforementioned EUROCARE project employed a sample size of approximately 280 (20
persons of for each of 14 countries) (Murray, Schneider, Banerjee, & Mann, 1999), and the MIDUS
study (The Midlife in the United States Study) is a study that has involved over 700 structured
interviews (Wethington, 2000). While such projects do require time, money, many researchers and a
robust purposive sampling strategy (see below), they are achieved by breaking up the research into
smaller sub-studies that are initially analysed on their own terms before being aggregated together.
Interview research that has an idiographic aim typically seeks a sample size that is sufficiently small
for individual cases to have a locatable voice within the study, and for an intensive analysis of each
case to be conducted. For these reasons, researchers using Interpretative Phenomenological
Analysis are given a guideline of 3 to 16 participants for a single study, with the lower end of that
spectrum suggested for undergraduate projects and the upper end for larger-scale funded projects
(Smith, Flowers & Larkin, 2009). This sample size range provides scope for developing cross-case
generalities, while preventing the researcher being bogged down in data, and permitting individuals
within the sample to be given a defined identity, rather than being subsumed into an anonymous
part of a larger whole (Robinson & Smith, 2010).
Case study design is often referred to as a distinct kind of method that is separable from standard
qualitative method (e.g. Yin, 2009). In relation to interview-based case-studies, a more integrative
view is taken here, in which the decision to do a N=1 case study is a sample size decision to be taken
as part of the four-point rubric set out in this guide. The resulting case study can then be analysed
using an idiographic interview-focused method such as IPA. There are a number of different reasons
for choosing a sample size of 1, and Table 3 lists six of these; psychobiography, theoretical or
hermeneutic insight, theory-testing or construct-problematising, demonstration of possibility,
illustration of best practice and theory-exemplification. All of these warrant a sample size of 1 and
also require associated sample strategies, which are discussed later in this article.
These case study objectives are not mutually exclusive. An example of a paper that evidences
multiple aims is Sparke’s narrative analysis of the autobiography of cyclist Lance Armstrong (Sparkes,
2004). It includes aspects of psychobiography, hermeneutic insight and construct problematizing.
(Insert Table 3)

Frequently asked questions

Q1. What contributions have the authors mentioned in the paper "Qualitative research in psychology, in press" ?

Sampling is central to the practice of qualitative methods, but compared with data collection and analysis, its processes are discussed relatively little. A four-point approach to sampling in qualitative interview-based research is presented and critically discussed in this article, which integrates theory and process for the following: ( 1 ) Defining a sample universe, by way of specifying inclusion and exclusion criteria for potential participation ; ( 2 ) Deciding upon a sample size, through the conjoint consideration of epistemological and practical concerns ; ( 3 ) Selecting a sampling strategy, such as random sampling, convenience sampling, stratified sampling, cell sampling, quota sampling or a single-case selection strategy ; and ( 4 ) Sample sourcing, which includes matters of advertising, incentivising, avoidance of bias, and ethical concerns pertaining to informed consent. The extent to which these four concerns are met and made explicit in a qualitative study has implications for its coherence, transparency, impact and trustworthiness. 

Q2. What is a form of incentive for recruiting others into the study?

Respondent-driven sampling is a form of snowball sampling that gives financial incentives for recruiting others into the study (Heckathorn, 1997; Johnston & Sabin, 2010; Wang et al., 2005). 

Q3. What is the way to justify the use of convenience samples in qualitative research?

The best way of justifying the use of convenience samples in qualitative research is by defining the sample universe as demographically and geographically local and thus restricting generalisation to that local level, rather than attempting decontextualized abstract claims. 

Q4. What is the way to work with larger sample sizes in qualitative research?

A way of working with larger sample sizes in qualitative research, which prevents analytical overload, is to combine separate studies together into larger syntheses. 

Q5. What is the key decision that a researcher must make when recruiting people into an interview study?

When recruiting people into an interview study, the question of whether to offer them a financial incentive for participation is a key decision that the researcher must make. 

Q6. What is the main emphasis of Grounded Theory?

Of all qualitative methodologies, Grounded Theory puts most emphasis on being flexible about sample size as a project progresses (Glaser, 1978). 

Q7. What is the problem of using convenience sampling in quantitative research?

The problem of using this approach in quantitative research is that statistics function on the basis that samples are random, when they are typically not. 

Q8. What is the third criterion for enhancing the validity of a qualitative study?

The third criterion, ‘transparency’, is enhanced by being explicit in a final research report as to how all four points – sample universe, sample size, sample strategy and sample sourcing – were met. 

Q9. What is the way to counteract the female bias in interviews?

This female bias can be easily counteracted in a mixedgender purposive sampling frame that ensures male and female representation, but more subtle systematic biases in differences between participants and non-participants are harder to deal with. 

Q10. What are the key decisions to enhance rigour?

Key decisions to enhance rigour are the relationship of the sample to the sample universe, the appropriate choice of sampling strategy, the robustness of the sample sourcing approach, and the overall fit between research questions and total sample strategy. 

Q11. What is the importance of sampling to qualitative research?

The importance of sampling to qualitative research validityAddressing the four sampling issues that have been outlined in this article is central to enhancing the validity of any particular interview study. 

Q12. What is the process of re-structuring a sample?

The process involves either (a) locating cases from new groups of participants (for example a ‘comparison’ group to provideheterogeneity into the sample, or (b) re-structuring an already-gathered sample into a new set of categories that have emerged from analysis, and replacing any stratification/cells/quotas that were chosen a-priori (Draucker, Martsolf, Ross & Rusk, 2007).