Beyond the divide: Comparing and contrasting aspects of qualitativeand quantitative research approaches

J. CHEEK1, M. ONSLOW2, & A. CREAM2

1Hawke Research Institute for Sustainable Societies, University of South Australia, Adelaide, Australia, and 2Australian

Stuttering Research Centre, The University of Sydney, Sydney, Australia

AbstractAs an introduction to this journal issue devoted to qualitative research methods in stuttering research, the present paperprovides an overview of some of the underlying questions and issues arising from the use of qualitative approaches inresearch. The overview is written mindful of the historical domination of quantitative approaches to stuttering research andthe likelihood that many readers of the present issue will have long experience and familiarity with quantitative approaches asopposed to qualitative ones. Consequently, qualitative research approaches are overviewed with particular reference to whathave been, in our experiences, recurring queries about those methods from within the quantitative perspective. A broaddefinition of the inductive methods of qualitative approaches is offered and contrasted with the deductive methods ofquantitative research. Subsequently, the issue of ‘‘bias’’ in qualitative approaches is considered, along with insights into waysof determining the quality of such approaches. It is concluded that there is no future in trying to understand or conceptualiseeither quantitative or qualitative research approaches using understandings transported from the other. Such anunproductive polemic or ‘‘paradigm clash’’ (Ingham, 1984) must be avoided as qualitative approaches to stutteringresearch grow in influence.

Keywords: stuttering, research, qualitative, quantitative.

Introduction

As many of the following pages in this journal issue

attest, the field of stuttering research has been

dominated historically by quantitative approaches

to research. It is likely, then, that many who come

across this edition of Advances in Speech-Language

Pathology, which is devoted to qualitative approaches

to stuttering research, will find such approaches a

new experience to contemplate. Given this, the

purpose of this paper is to provide for those with a

quantitative orientation a brief introduction, before

tackling this issue, to this different research ap-

proach. Rather than merely providing a general

overview of qualitative methods—for there are many

such overviews in existence—this paper is written

mindful of the queries about qualitative approaches

that, in our experience, those with a quantitative

background commonly present. We are also mindful

of the need to avoid inflaming another of the

historical polemics that have affected the field of

stuttering enquiry, by urging harmony between

quantitative and qualitative sources of information.

As is the case with quantitative enquiry, quali-

tative enquiry is a long-standing, sophisticated

field, with a complex interconnected family of

terms, concepts and assumptions. Indeed it can be

argued that the extent to which qualitative and

quantitative methodologies are different ‘‘reflects

their divergent philosophical starting points, espe-

cially with respect to facticity and observability’’

(Fenton & Charsley, 2000, p. 404). Qualitative

research is not unique to any one discipline, and

has a long history in some disciplines such as

anthropology and sociology, and has also been

around for some time in disciplines such as

psychology, education, history, political science,

business, medicine, nursing, social work and

communications. There are a number of qualitative

approaches and methods, each one different in

theoretical traditions and origins. As Rice and Ezzy

(1999) note,

qualitative research cannot be described in terms of a set

of theories and techniques that always apply. Rather,

qualitative research draws on a variety of theoretical

perspectives and practical techniques, including theories

Correspondence: Julianne Cheek, University of South Australia, School of Nursing and Midwifery, Centenary Building, City East Campus, Nth Terrace,

Adelaide, SA. 5000, Australia. Tel: (08) 8302-2675; E-mail: Julianne.Cheek@unisa.edu.au

Advances in Speech–Language Pathology, Vol. 6, No. 3, September 2004, pp. 147 – 152

ISSN 1441-7049 print/ISSN 1742-9528 online # The Speech Pathology Association of Australia Limited

Published by Taylor & Francis Ltd

DOI: 10.1080/14417040412331282995

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such as phenomenology, symbolic interactionism, cul-

tural studies, psychology and feminism, and techniques

such as interviewing, narrative analysis, ethnography,

and focus groups. (p.1)

In what follows, then, the terms ‘‘qualitative’’ and

‘‘quantitative’’ research are convenient labels, not

meant to imply that either is a single or unified

approach that can be reduced to a single set of

understandings. Indeed, it is a common error for

those attempting to come to grips with a new

paradigm to conceptualise that paradigm monolithi-

cally, as occurred, for example, with attempts to

understand behaviourism (Zuriff, 1985).

Qualitative research as ‘‘situated’’ research

In qualitative research there is not an objective reality

that exists waiting to be discovered. The researcher

does not assume truth is fixed and attempts to

identify variables to control in order to test a

hypothesis as a means to access that truth. Rather

than trying to reduce or simplify the world in order to

measure it, a characteristic of qualitative research is

that it is located in the world of the participants of

that research—its subjects, to use the analogous

quantitative term. In other words, qualitative re-

search is contextualised research. Whilst qualitative

research involves many different approaches and

theoretical positions, they all have a commitment to

being naturalistic and interpretive. Qualitative re-

search seeks in-depth understandings of what is

going on in the world.

One of the problems with the current popular use

of the terms ‘‘quantitative’’ and ‘‘qualitative’’ is that

they contain an implicit definition; that qualitative

research methods are all research methods that are

not quantitative. However, this definition has the

effect of positioning qualitative approaches in rela-

tion to quantitative approaches; in other words, in

terms of what they are not when compared to

quantitative approaches, rather than what they are

in their own right.

Qualitative research is ‘‘a situated activity that

locates the observer in the world’’ (Denzin &

Lincoln, 2000, p. 3) and makes aspects of that world

visible. Speaking of sociology, Fenton and Charsley

(2000) note that qualitative sociology ‘‘demonstrates

a complexity and connectedness in the texture and

meanings of social life that it is difficult to reproduce

in quantitative methodologies’’ (p. 404). In so doing,

qualitative research makes the world that is being

researched visible in a particular contextualised way.

This process often challenges taken-for-granted

assumptions about that world and the people who

live and interact in it, and produces new and/or

different insights that transform existing understand-

ings of it. This means that the assumptions and

emphases of the research are quite different from

those underpinning quantitative research. Karp’s

(1996) study of depression illustrates this point. He

wrote,

I’m not primarily interested in explaining what causes

depression or how to cure it . . . Instead, I’m interested in

how depressed individuals make sense of an inherently

ambiguous life situation . . . how people think about

psychiatry and medications, and how they deal with

family and friends (Karp, 1996, p. 189).

Types of insights afforded by qualitative

approaches

Qualitative data is intended to provide insights into

the lives, experiences and understandings of the

research participants. But like any form of research,

it can only ever provide partial understandings of

such situations. Such an approach to research cannot

be removed from the context in which the data are

collected or the participants from whom the in-

formation is obtained. It is impossible for the

researcher or the analysis to remain detached or

removed from what is being studied. In Denzin’s

(1978) words, this involves the researcher viewing

‘‘human conduct from the point of view of those they

are studying and is part of a studied commitment to

actively enter the worlds of interacting individuals’’

(pp. 8 – 9). This is part of the drive for richness and

in-depth information in both the study approach and

findings of qualitative data. As we shall consider

below, this may raise issues of bias in those with

quantitative research backgrounds.

In qualitative analysis, patterns and themes emerge

from the data, which may include, to give just three

examples, interview transcripts, field work observa-

tions, or documents of some kind. However, as is the

case with quantitative research, in order to under-

stand qualitative research it is necessary to know

more than its core methods of enquiry. Although

qualitative methods often involve interviews, for

example, simply interviewing someone is not quali-

tative research. A better fundamental approach to

understanding qualitative research emerges if an

answer is obtained to Rice and Ezzy’s (1999)

question about any qualitative study: ‘‘What is the

theoretical framework within which the study is being

conducted’’ (p. 10). Examples of such theoretical

frameworks include phenomenology, critical dis-

course analysis, and grounded theory.

Often the theoretical framework that needs to

guide the research is overlooked and results in

shallow and largely descriptive findings limited in

terms of what they can contribute to our under-

standings of the issue in question. ‘‘The general

theoretical framework fundamentally shapes the sorts

of things that the research focuses on and therefore

fundamentally shapes the method and techniques

required for the research’’ (Rice & Ezzy, 1999, p.

11).

With this in mind, consider a dataset from a

questionnaire that has within it some open or even

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free responses from participants along with closed

question responses. It will be impossible to push the

analysis of these responses beyond the descriptive

unless the study is situated in a theoretical frame or

context that allows for this. Whilst there is no

question about the usefulness of data from a well

constructed questionnaire, such text does not repre-

sent qualitative research: the findings are

decontextualised. There is no theoretical context

underpinning that research. There is no capacity for

the in-depth exploration of the complex nature of the

issue/situation. A theoretical context provides a

means to interact with those who provide the answers

to the questions, and a means to knowing what the

participants actually meant by their answers, and why

they gave them. Without such a context, such

questionnaire research perhaps is better described

as the application of qualitative data within a

quantitative study.

A matter of bias?

In our experience, researchers familiar with quanti-

tative paradigms who contemplate qualitative

research for the first time can be concerned that

their findings constitute a quite biased view of the

world of the participants. Such a response is

understandable considering the inseparableness of

the researcher from the research, as outlined above,

and also because bias is thought to be the scourge

of reductionist scientific method. However, the

concept of bias in quantitative research cannot

simply be transferred to qualitative research, be-

cause the nature of the knowledge in question is

different. In qualitative research the role of the

researcher, including any inherent biases, is ac-

knowledged at all points of the research process.

For example, Coffey (1999) notes that ethnographic

fieldwork is impossible to undertake without inter-

acting with others. She suggests ‘‘we should not

even think about undertaking qualitative fieldwork

without being prepared to become part of the

interactions of the setting’’ (p. 159) noting that

everyday life is enacted through social interaction

and it is easy to lose sight of the ‘‘fact that those

relations and interactions implicitly include the

researcher, as well as the researched’’ (p. 159). In

qualitative approaches the role of the researcher is

made visible and the position adopted by the

researcher in terms of choice of approach or

analytical decision making is made explicit. This

form of reflexivity is as much a part of the research

as are the findings. Cheek and Rudge (1994) even

went to the extent, in presenting their findings, of

explicating the thinking and questions that they

posed for themselves during the analyses, using a

separate font and layout to set this material apart

from their findings.

Thus in qualitative research, rather than claiming

to have ‘‘removed’’ bias, the effect of the researcher

on all parts of the research process is acknowledged;

from the questions asked to the approaches

employed, the analyses done, and the way the

findings are reported. In contrast to quantitative

methods, in qualitative research there is no meaning

to the idea of an independent person, removed from

the context of the research objectively verifying the

findings, because the notion of a person indepen-

dent of the data has no meaning. In our experiences

this can constitute an affront to the fundamental of

science from a quantitative perspective: that it is a

public forum. However, it might well be argued that

an advantage of qualitative approaches is that any

‘‘biases’’ that are introduced—or what might better

be termed ‘‘subjective choices’’ in light of the

foregoing discussion—are transparent. The preced-

ing discussion highlights the need for clear

articulation of the reasons for the choices the

researcher has made at all points of the research

process in a way that can be understood by those

reading that research. They are there for all who

consume the research to see. This expectation of

transparency contributes to the credibility of the

findings so there is not a concern that ‘‘hidden

bias’’ might have threatened the integrity of the

results, unbeknown to its consuming public. Such

transparency applies as much to decisions about

choice of approach and research technique as to

decisions about topic and analyses done. The

interpretive process is at the centre of the practice

of qualitative methods (Rice & Ezzy, 1999) and that

includes the choice of those methods in the first

place.

The foregoing discussion might create a percep-

tion that qualitative research is a private event for the

researcher. In the present context a straw argument

may be useful, so it is worth a challenge to any notion

at all of an absolute unassailable public science that is

beyond reproach; a challenge to the idea that if

results are replicated by an independent observer

those data better describe the world. Consider the

quantitative mechanism of mathematical algorithms

that underlie what is the process of perceived

objectivity in quantitative research. Can those algo-

rithms be made to speak the same message to a

researcher, regardless of the identity of the research-

er? Is it the case that a data set is either significant or

it is not significant, regardless of who analyses it? The

answer is no, because statistical inference depends

on underlying mathematical algorithms working

correctly. To give a crude example, one statistician

may conduct a t-test and pronounce two groups to

not differ significantly. However, another statistician

may look at the same data set, and decide that it does

not meet the assumption of normality that is

necessary for the algorithm to work. That statistician

may then log-transform the data to make it appear

normally distributed, and conduct a t-test on the

transformed data, and declare that the two groups

indeed do differ significantly. This crude example

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amounts to the fact that the two scenarios of

statistical analysis contain an example of relative

bias: Or, in the appropriate jargon, one scenario is

biased toward a significant finding because of

spurious mathematical elevation of the alpha level.

It is arguable that, on most occasions, the robustness

of the underlying quantitative mathematical algo-

rithm is non-transparent, as shown by Stonehouse

and Forrester (1998). In short, they made an

engaging demonstration that straightforward statis-

tical models, such as the Student’s t-test and the

Mann-Whitney U-test, may provide biased results

under various sampling conditions. As noted pre-

viously, quantitative research methods are a complex

and diverse set of concepts and procedures. It is

somewhat sobering to contemplate the unknown

biases that may be lurking within more complicated

mathematical models of statistical inference, such as

confirmatory factor analysis or structural equation

modelling.

Determining quality

The quality of research is a concern to all who do it

and who use or read it. In quantitative science,

concepts such as reliability, validity, and generalisa-

bility are recurring themes. For the topic of stuttering

that is the focus of this issue, they can be seen to

recur, for example, in the setting of the standards of

evidence to determine whether or not treatments for

stuttering are effective (e.g., Bloodstein, 1995;

Ingham & Riley, 1998).

However, as a prelude to any consideration of the

matter of quality in qualitative research, it should be

noted that there has been recent debate in the

qualitative literature about whether the concepts of

validity and reliability apply in qualitative research

(Denzin & Lincoln, 2000; Rice & Ezzy, 1999;

Silverman, 2001). This debate is about whether the

same terms can mean different things in quantitative

and qualitative research, or whether completely

different terms should be applied when focussing

on rigour in qualitative research design. Advocates of

the latter position (e.g., Agar, 1986) suggest that

because terms such as validity and reliability are

derived from quantitative assumptions they are

difficult to apply to qualitative research.

How, then, might the inherent integrity of

qualitative research be determined? In answering

that question, again the caveat is offered that there

are many different viewpoints about this. What

follows is a beginning discussion of some of the

facets that can contribute to the overall quality of the

qualitative research undertaken. It is not meant to be

prescriptive in the sense of suggesting that qualitative

research that does not address or incorporate these

ideas is necessarily poor research. There are debates

on research quality within the qualitative paradigm,

just as there are such debates within the quantitative

paradigm.

Selection of participants, study sites, and texts

There have to be clear reasons given for the sampling

employed in a qualitative study. The aim in

qualitative research is to choose information-rich

participants, study sites, or texts for analysis; in other

words, ‘‘those from which one can learn a great deal

about issues of central importance to the purpose of

the inquiry’’ (Patton, 2002, p. 230). It is imperative

that the sample selected is in keeping with this logic

and able to be clearly justified and articulated. For

example, Patton outlines 16 types of purposeful (in

the sense of information rich) sampling, none of

which are necessarily mutually exclusive but all of

which serve different purposes. Which is employed in

any study at any time must be made explicit, as must

why.

Confirmability and trustworthiness of results

The criterion of confirmability might include getting

feedback or comment from participants about

analyses or findings developed by the researcher.

Silverman (2001) notes that ‘‘good research goes

back to the subjects with tentative results, and refines

them in the light of the subjects’ reactions’’ (p. 235).

However, this is contestable and not necessarily a set

criterion for good qualitative research. Confirmabil-

ity can also include ensuring that several members of

a research team compare analyses looking for

consistencies and inconsistencies and either resolve

these by consensus, or state where consensus was not

able to be achieved. Having a trail of what decisions

were made during the research, and why, with

respect to both data collection and its analysis, is

another way that trustworthiness in the findings can

be increased.

Triangulation

Triangulation refers to the use of any or all of various

combinations of methods, researchers, data sources

and theories in a research project. As Patton’s (2002)

benchmark text on qualitative approaches notes, four

kinds of triangulation can contribute to verification

and rigour of qualitative design and analysis. They

are as follows: Methods triangulation is the checking

out consistency of findings generated by different

data collection methods. For example a study might

use combinations of interviews, focus groups, nom-

inal groups and workshops. Triangulation of sources

within the same method is when different information

sources are be used in a study. Rice and Ezzy (1999),

for example, note that Goffman’s (1961) classic

study of mental asylums obtained information from

medical staff, patients, administrators, and written

documents. Analyst triangulation using multiple ana-

lysts to review findings is when all researchers will be

involved in independent review of data and this will

then be constantly compared. Theory/perspective

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triangulation using multiple perspectives or theories to

interpret the data has the purpose of not only looking

for points of agreement, but to test consistency.

Hence, researchers search for consistencies and

inconsistencies in findings across different types of

data and settings. Understanding these patterns is

enlightening and important in qualitative research.

Extrapolation of findings

Generalisability of findings is appropriate for evalu-

ating quantitative studies, but not appropriately

applied to qualitative projects which aim to gain in-

depth and detailed contextual understanding of the

area being studied. The nearest concept in qualita-

tive research to the quantitative concept of

generalisability is ‘‘extrapolation.’’ This is because

qualitative approaches, as already noted, seek to

understand not only consistencies, but also incon-

sistencies in findings across different types of data

and settings; it is as concerned with inconsistency as

much as consistency. Inconsistencies, or failure to

attain consistent findings across settings, is of value

itself, and can gell us much about the area of research

interest (see Finn & Felsenfeld, 2004).

Understanding such inconsistencies is illuminative

and important in qualitative research, rather than

being seen as a source of untrustworthiness of data.

By building in the multiple kinds of triangulation

outlined above, qualitative study design permits

extrapolation (Cronbach & Associates, 1980).

As Patton (2002) explains:

Extrapolations are modest speculations on the likely

applicability of findings to other situations under similar,

but not identical, conditions [and] are logical, thought-

ful, case derived, and problem oriented rather than

statistical and probabilistic. Extrapolations can be

particularly useful when based on information-rich

samples and designs, that is, studies that produce

relevant information carefully targeted to specific con-

cerns about both the present and the future. (p. 584)

In quantitative research, the randomness of subject

sampling is intrinsically bound up with the notion of

the extent to which findings can be applied to

populations not sampled in the research. In qualita-

tive research, however, generalisability is not the

issue, no more than it is with the discovery of a new

planet. The discovery of Pluto, for example, was not

limited in astronomic importance because it was not

generalisable. Qualitative projects aim to gain in-

depth and detailed contextual understanding of the

area/reality being studied. As noted previously, they

search for and try to understand consistencies and

inconsistencies in findings across different types of

data and settings. In short, then, the standards for

rigour of qualitative research are somewhat different

from quantitative research. However, the term

‘‘premise’’ rather than ‘‘standard’’ might be more

appropriate, for as soon as we start taking about

different standards we are in the bind of qualitative

research always being defined in terms of its

differences to quantitative research. If we speak of

different standards it is inevitable that at some stage

these different ‘‘standards’’ will be viewed as lesser

by some.

Moving beyond the divide: some concluding

thoughts

It is true that the concepts, assumptions, procedures

and methods familiar to those with backgrounds in

the quantitative paradigm are different in the

qualitative paradigm. Perhaps one way of summaris-

ing the differences is that the quantitative scientific

method is essentially deductive, but the qualitative

paradigm is essentially inductive. The use of the term

‘‘paradigm’’ here is not in the broad Kuhnian sense

(Kuhn, 1962), but in the more narrow sense in which

it may be applied to the history of the study of

stuttering (Ingham, 1984). For in that field, the

divisive potential arising from competing approaches

to research have not been productive, as illustrated

by the history of conflict between behavioural and

non-behavioural approaches to treatment (for an

overview, see Ingham, 1984). Perhaps nowhere was

this unproductive divide more apparent than in

Joseph Sheehan’s end of career pronouncement that

the efforts of the behaviour therapists with stuttering

amounted to an ‘‘indecent scramble’’ (Sheehan &

Sheehan, 1984, p. 250). Surely, such a repeat of our

polemic history is to be avoided at all costs as the

potential of the qualitative paradigm for opening up

new ways of looking at and thinking about stuttering

research is increasingly recognised. One way to

ensure that a repeat of that history does not occur

is to accept that there is no future in trying to

understand or conceptualise either quantitative or

qualitative research approaches using understandings

transported from the other.

It is hoped that the reader of this issue will be

rewarded with clarification about how the outputs of

qualitative and quantitative research can be comple-

mentary, to the extent that they inform each other,

but in different ways, about the disorder of stuttering

and its treatment. Either can be a precursor to the

other, but not necessarily so, because together they

have the potential to guide a research program in

tandem, or inform different dimensions of the aspect

of stuttering under scrutiny. As Fenton and Charsley

(2000, p. 404) note ‘‘with some shifts towards

accommodation, divergent methodologies may live

not only in peaceful coexistence: by recognizing the

other’s strengths, they may create a lively symbiosis.’’

In the articles to follow, it is hoped that the reader

will find there is a wealth of information about how

this might be achieved, plentiful signs of progress

toward it being achieved, and few sources of jeopardy

that it will be achieved.

Beyond the divide? 151

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