Sampling for qualitative research

Family Practice

Vol.

13, No. 6

Printed in Great Britain

Martin N Marshall

Marshall,

MN. Sampling for qualitative research. Family Practice 1996; 13: 522-525.

The probability sampling techniques used for quantitative studies are rarely appropriate

when conducting qualitative research. This article considers and explains the differences

between the two approaches and describes three broad categories of naturalistic sampling:

convenience, judgement and theoretical models. The principles are illustrated with practical

examples from the author's own research.

Keyword. Qualitative sampling.

Introduction

The benefits of a qualitative approach to health care

research are becoming increasingly recognized by both

academics and clinicians, but misunderstandings about

the philosophical basis and the methodological approach

remain. The impression is sometimes given that

qualitative research differs from the hypothetico-

deductive model simply in terms of the way that data

is collected. The process of sampling is one of

the

prin-

cipal areas of confusion, a problem not helped by the

inadequate way that it is covered in the literature, where

there is little agreement on definitions and authors fre-

quently invent new and complex terms which cloud

simple fundamental issues. In this article I will describe

both quantitative and qualitative methods of sampling

and consider the basic differences between the two

approaches in order to explain why the sampling tech-

niques used are not transferable. I will consider issues

relating to sample size and selection in qualitative

research and illustrate the principles with practical

examples.

Quantitative sampling

Choosing a study sample is an important step in any

research project since it is rarely practical, efficient or

ethical to study whole populations. The aim of all quan-

titative sampling approaches is to draw a representative

sample from the population, so that the results of

studying the sample can then be generalized back to

the population. The selection of an appropriate method

depends upon the aim of the study. Sometimes less

rigorous methods may be acceptable, such as incidental

or quota samples, but these methods do not guarantee

Received 30 May 1996; Accepted 15 July 1996.

Institute of General Practice, University of Exeter, Postgraduate

Medical School, Barrack Road, Exeter EX2 5DW, UK.

a representative sample. The most common approach

is to use random, or probability samples. In a random

sample the nature of the population is defined and all

members have an equal chance of selection. Stratified

random sampling and area sampling are variants of

random sampling, which allow subgroups to be studied

in greater detail.

The size of the sample is determined by the optimum

number necessary to enable valid inferences to be made

about the population. The larger the sample size, the

smaller the chance of a random sampling error, but since

the sampling error is inversely proportional to the square

root of the sample size, there is usually little to be gained

from studying very large samples. The optimum sample

size depends upon the parameters of the phenomenon

under study, for example the rarity of the event or the

expected size of differences in outcome between the in-

tervention and control groups.

Comparing the quantitative and

qualitative

approaches

The choice between quantitative and qualitative research

methods should be determined by the research ques-

tion, not by the preference of the researcher. It would

be just as inappropriate to use a clinical trial to examine

behavioural differences in the implementation of clinical

guidelines as it would be to use participant observation

to determine the efficacy of antibiotics for upper respira-

tory tract infections. The aim of the quantitative ap-

proach is to test ore-determined hypotheses and produce

generalizable

results.

Such studies are useful for answer-

ing more mechanistic 'what?' questions. Qualitative

studies aim to provide illumination and understanding

of complex psychosocial issues and are most useful

for answering humanistic 'why?' and 'how?' questions.

The principal fundamental differences in both the

philosophical foundation of and the methodological

approach to the two disciplines are summarized in

Table 1.

522

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Sampling for qualitative research

523

Why is random sampling inappropriate for

qualitative studies?

The process of selecting a random sample is well defined

and rigorous, so why can the same technique not be

used for naturalistic studies? The answer lies in the aim

of the study; studying a random sample provides the

best opportunity to generalize the results to the popula-

tion but is not the most effective way of developing an

understanding of complex issues relating to human

behaviour. There are both theoretical and practical

reasons for this.

First, samples for qualitative investigations tend to

be small, for reasons explained later in this article. Even

if a representative sample was desirable, the sampling

error of such a small sample is likely to be so large that

biases are inevitable. Secondly, for a true random sam-

ple to be selected, the characteristics under study of the

whole population should be known; this is rarely pos-

sible in a complex qualitative study. Thirdly, random

sampling of a population is likely to produce a represen-

tative sample only if the research characteristics are nor-

mally distributed within the population. There is no

evidence that the values, beliefs and attitudes that form

the core of qualitative investigation are normally

distributed, making the probability approach inappro-

priate. Fourthly, it is well recognized by sociologists

that people are not equally good at observing, understan-

ding and interpreting their own and other people's

behaviour. Qualitative researchers recognize that some

informants are 'richer' than others and that these people

are more likely to provide insight and understanding

for the researcher. Choosing someone at random to

answer a qualitative question would be analogous to ran-

domly asking a passer-by how to repair a broken down

car, rather than asking a garage mechanic—the former

might have a good stab, but asking the latter is likely

to be more productive.

Sample size

Quantitative researchers often fail to understand the

usefulness of studying small samples. This is related

to the misapprehension that generalizability is the

ultimate goal of all good research and is the principal

reason for some otherwise sound published qualitative

studies containing inappropriate sampling techniques.

An appropriate sample size for a qualitative study is

one that adequately answers the research question. For

simple questions or very detailed studies, this might be

in single figures; for complex questions large samples

and a variety of sampling techniques might be

necessary. In practice, the number of required subjects

usually becomes obvious as the study progresses, as

new categories, themes or explanations stop emerging

from the data (data saturation). Clearly this requires

a flexible research design and an iterative, cyclical

approach to sampling, data collection, analysis and in-

terpretation. This contrasts with the stepwise design of

quantitative studies and makes accurate prediction of

sample size difficult when submitting protocols to

funding bodies.

Sample strategies

There are three broad approaches to selecting a sample

for a qualitative study.

Convenience sample

This is the least rigorous technique, involving the selec-

tion of the most accessible subjects. It is the least costly

to the researcher, in terms of

time,

effort and money,

but may result in poor quality data and lacks intellec-

tual credibility. There is an element of convenience

sampling in many qualitative studies, but a more

thoughtful approach to selection of a sample is usually

justified.

Judgement sample

Also known as purposeful sample, this is the most com-

mon sampling technique. The researcher actively selects

the most productive sample to answer the research ques-

tion. This can involve developing a framework of the

variables that might influence an individual's contribu-

tion and will be based on the researcher's practical

knowledge of the research area, the available literature

and evidence from the study

itself.

This is a more in-

tellectual strategy than the simple demographic

stratification of epidemiological studies, though age,

gender and social class might be important variables.

If the subjects are known to the researcher, they may

be stratified according to known public attitudes or

beliefs. It may be advantageous to study a broad range

of subjects (maximum variation sample), outliers

(deviant sample), subjects who have specific experiences

(critical case sample

) or subjects with special exper-

tise (key informant sample). Subjects may be able to

recommend useful potential candidates for study

(snowball sample). During interpretation of

the

data it

is important to consider subjects who support emerg-

ing explanations and, perhaps more importantly, sub-

jects who disagree (confirming and disconfirming

samples).

Theoretical sample

The iterative process of qualitative study design means

that samples are usually theory driven to a greater or

lesser extent. Theoretical sampling necessitates building

interpretative theories from the emerging data and

selecting a new sample to examine and elaborate on this

theory. It is the principal strategy for the grounded

theoretical approach

but will be used in some form

in most qualitative investigations necessitating

interpretation.

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524

Family Practice—an international journal

TABLE

1 Comparison of quantitative and qualitative methods

Philosophical

foundation

Aim

Study plan

Position of

researcher

Assessing quality

of outcomes

Measures of

utility of results

Quantitative

Deductive,

reducdonalist

To test pre-set

hypothesis

Step-wise,

predetermined

Aims to be detached

and objective

Direct tests of

validity and reliabi-

lity using statistics

Generalizability

Qualitative

Inductive, holistic

To explore complex

human issues

Iterative, flexible

Integral part of

research process

Indirect quality

assurance methods of

trustworthiness

Transferability

It is apparent from the above description that there

is considerable overlap even between these three broad

categories. The relative balance will depend upon the

research question and the chosen style of data analysis

and interpretation. It is important to recognize that

the essence of the qualitative approach is that it is

naturalistic—studying real people in natural settings

rather than in artificial isolation. Sampling therefore

has to take account not only of the individual's

characteristics but also temporal, spatial and situational

influences, that is, the context of the study. The re-

searcher should consider the broader

picture:

would this

individual express a different opinion if they were in-

terviewed next week or next month? Would they feel

differently if they were interviewed at home or at work?

Should I study mem when they are under stress or re-

laxed? There is no correct answer to these questions,

just as there is no perfect way to sample, but the in-

fluence that these factors might have on the trustwor-

thiness of the results should be acknowledged.

A practical example of sampling strategy

In practice, qualitative sampling usually requires a flex-

ible,

pragmatic approach. This may be illustrated by

my own study of the professional relationship between

GPs and specialists (in progress).

The way that the two branches of the medical

profession work together is a key component of the

primary-secondary care interface, which, in terms of

sociological interaction, is largely unresearched. The

study aims to describe the current relationship, com-

pare this with the historical literature, and elucidate the

principal factors causing a change in the interaction be-

tween the two main branches of the medical profession.

Four methods of data collection have been used, each

of which view the interaction from differing perspectives

and each of which have required different sampling

strategies.

The first stage involved the use of key informant

interviews,

an anthropological technique utilizing rich

information sources, which has defined sample selec-

tion criteria.

A sample of 10 national figures in posi-

tions of leadership and responsibility within the

profession were chosen. Since the total population of

possible key informants is small, this was necessarily

a convenience sample, though there was an element of

a judgement approach, since efforts were made to ensure

that participants came from a range of clinical,

academic, managerial and political backgrounds. The

advantage of this approach lies in its simplicity but it

was difficult to determine at the sampling stage whether

the informants fulfilled the published selection criteria.

The second stage involved in-depth interviews with

practising clinicians throughout the South and West

Region. The aim was to develop an understanding and

an interpretative framework of the process of interaction

between specialists and GPs. I started with a judgement

sample framework including variables such as time since

qualification, gender, geographical location, rurality,

fundholding status and teaching hospital status. As the

data was collected and analysed, an interpretative

framework was constructed, so the sampling strategy

changed from largely judgement to largely theoretical,

in order to build on the developing theory. New themes

stopped emerging after about 15 interviews and an ac-

ceptable interpretative framework was constructed after

24 interviews—the stage of thematic and theoretical

saturation.

The third stage of the study brought GPs and

specialists together in focus groups to collect the dif-

ferent level of data produced by personal interaction.

For pragmatic reasons, this had to be conducted in my

own locality, and it was important for the study that

the participants were able to interact in a productive,

rather than dysfunctional way. I was able to use my

local knowledge to satisfy these sampling requirements

using a combination of convenience and purposive

techniques.

The three qualitative stages of the study will form

the basis of

Likert survey to test out emergent themes

and which will be distributed to a stratified random

sample of the whole population of clinicians work-

ing in the Region. This will represent a different, not

necessarily a stronger, perspective of the professional

relationship.

Conclusion

Sampling for qualitative research is an area of con-

siderable confusion for researchers experienced in the

hypothetico-deductive model. This largely relates to

misunderstanding about the aims of the qualitative

approach, where improved understanding of complex

human issues is more important than generalizability

of results. This basic issue explains why probabilis-

tic sampling is neither productive nor efficient for

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Sampling for qualitative research

525

qualitative studies and why alternative strategies are

used. Three broad categories of naturalistic sampling

techniques have been described—convenience, judge-

ment and theoretical sampling—though in practice there

is often considerable overlap between these approaches.

Acknowledgements

I would like to thank Ms Nicky Britten for her com-

ments on this paper. The study of the professional rela-

tionship between specialists and GPs is funded by a

Research and Training Fellowship from the Research

and Development Directorate of the South and West

Regional Health Authority.

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