using computer software to analyze qualitative data...
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Using computer software to analyze qualitative data:
Accounting versus other disciplines
Tjerk Budding*
VU University Amsterdam, the Netherlands
Martine Cools
Lessius - KU Leuven, Belgium
& Rotterdam School of Management, the Netherlands
DRAFT November 2008
Please do not circulate or quote without the permission of the authors
*Corresponding author:
Tjerk Budding, VU University Amsterdam, Faculty of Economics and Business Administration,
ARCA, De Boelelaan 1105, room 2E-43, 1081 HV Amsterdam, The Netherlands, Tel
+31/20/598.60.40, Fax +31/20/598.98.70, email: [email protected]
Martine Cools, Lessius – KU Leuven, Korte Nieuwstraat 33, 2000, Antwerpen, Belgium, Tel:
+32/3/201.18.75, Fax: +32/3/201.18.42, email: [email protected]
The authors like to thank Pursey Heugens, the participants of the Accounting research seminar at
Rotterdam School of Management, the EIASM conference on new directions in management
accounting in Brussels, the EAA Conference in Lisbon and the ENROAC-MACORG Conference in
Paris for their comments on earlier drafts of this paper.
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Using computer software to analyze qualitative data:
Accounting versus other disciplines
Abstract The aim of this paper is to investigate the use of Computer Assisted Qualitative Data Analysis
Software (CAQDAS). In order to get insights in its current use and further potential for accounting
researchers, we review the accounting literature in comparison to other disciplines until December
2007. Our analysis framework takes into account the diverse functions CAQDAS offers, as well as the
extent of analysis activities undertaken through CAQDAS. Related to the CAQDAS functions,
researchers can use CAQDAS just for organizing their data (‘code and retrieve’), or for undertaking a
‘gentle’ or ‘far-reaching’ analysis within the software package (Lee & Fielding 1995, Seale 2005).
Related to analysis quality, researchers can give an indication of whether they find CAQDAS
important to enhance the ‘validity’, ‘reliability’ and/or ‘theoretical sophistication’ of their work
(Silverman 2005). A thorough search through the contents of ten accounting journals identified 26
published articles using CAQDAS before January 2008. Atals/ti, NUDIST-Nvivo and The Ethnograph
are used most. A search for academic papers using these packages in three online databases (from their
existence until December 2007) led us to identify about 1150 published papers in journals with a JCR
impact score. Our initial analysis compares accounting to sociology. We find that accounting
researchers make use of CAQDAS to an extensive degree, in a comparable way to what sociology
researchers do. Accounting researchers especially mention the advantages of reliability and validity,
appearing more apologetic about their use of qualitative data than sociology researchers. Further, the
sociology journals seem to streamline more the way in which authors report about their analysis
process based on CAQDAS. We conclude that readers could get better insights in the research process
when authors clearly and concisely indicate what they actually did with CADQDAS. Apart from the
lessons learned by comparing CAQDAS use in accounting to other disciplines, we want to make sure
future CAQDAS users embark on software analysis projects with reasonable expectations: how far-
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reaching (or not) the options offered, CAQDAS cannot provide a substitute for continuing to think
critically about the meaning of data.
Keywords: Computer Assisted Qualitative Data Analysis Software (CAQDAS), research method,
qualitative data analysis
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1. Introduction
This paper investigates the use of Computer Assisted Qualitative Data Analysis Software
(CAQDAS) in the accounting domain. In order to get insights in its current use and further potential,
we review the accounting literature in comparison to other disciplines until December 2007 to identify
the papers supported by CAQDAS. Over recent years, an increasing number of published accounting
articles have used CAQDAS. Table 1 provides a chronological overview of the 26 relevant accounting
publications. The first accounting article using CAQDAS was published in 1999. The main software
packages used in the accounting literature are Atlas/ti and NUDIST – later Nvivo. The Ethnograph
was used twice, while one study used the less known package OCP and another one TACT.
Table 1: The use of CAQDAS in the extant accounting literature1 1999 2000 2001 2002 2004 2005 2006 2007 Widener & Selto (JMAR Atlas/ti
Smith & Taffler (AAAJ, OCP)
Anderson- Gough, Grey & Robson (AOS Ethnograph) Malina & Selto (JMAR Atlas/ti)
Lillis (AOS NUDIST) Willman, Fenton-O’Creevy, Nicholson & Soane (AOS Nvivo)
Budding (MAR NUDIST) Empson (AOS NUDIST) Malina & Selto (MAR Atlas/ti) Sweeney & Pierce (AAAJ NUDIST)
Abernethy, Horne, Lillis, Malina & Selto (MAR Atlas/ti) Anderson-Gough, Grey & Robson (AOS Ethnograph) Fogarty & Rogers (AOS NUDIST & Diction 5.0)
Breton & Côté (AAAJ TACT) Dixon, Ritchie & Siwale (AAAJ Nvivo) Donada & Nogatchewsky (MAR Nvivo) Irvine & Gaffikin (AAAJ NUDIST) Neu, Ocampo Gomez, Graham & Heincke (AOS Atlas/ti) Sian (AOS Atlas/ti) Sweeney & Pierce (AAAJ NUDIST)
Cuganesan, Boedker & Guthrie (AAAJ Nvivo) Dambrin, Lambert & Sponem (MAR Nvivo) Durocher, Fortin & Côté (AOS Nvivo) Ezzamel, Robson, Stapleton & McLean (MAR Ethnograph) Neu & Ocampo (CPA Atlas/ti) Rahaman, Everett & Neu (AAAJ Atlas/ti)
1 1 2 2 4 3 7 6
1 The articles were published in Accounting, Auditing, Accountability Journal (AAAJ), Accounting, Organizations and Society (AOS), Critical Perspectives on Accounting (CPA), Journal of Accounting Research (JAR), Journal of Management Accounting Research (JMAR) and Management Accounting Research (MAR).
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The increasing popularity of CAQDAS in the accounting literature is not an isolated
phenomenon. As will become clear from our review further on in this paper, CAQDAS has been used
more frequently in the broader field of ‘Business and Management’, as well as in ‘Education’,
‘Nursing and Medicine’, ‘Psychology’ and ‘Social and Political Sciences’. Our aim here is to discuss
the use of CAQDAS by accounting researchers by comparing it to the applications of Atlas/ti,
NUDIST – Nvivo and The Ethnograph in other research disciplines. To undertake the literature
review, we set up a framework focusing on the CAQDAS functions used and the research quality
considerations mentioned in the publications. In terms of the CAQDAS functions, we analyze whether
the authors use CAQDAS just for organizing their data (‘code and retrieve’), or whether they
undertake a ‘gentle’ or even a ‘far-reaching’ analysis within the software package (Lee & Fielding
1995, Seale 2005). In terms of analysis quality, we investigate whether CAQDAS was indicated as
being important for the researchers to enhance the ‘validity’, ‘reliability’ and/or ‘theoretical
sophistication’ of their work (Silverman 2005).
In a recent call for modeling management accounting phenomena with greater real-world
complexity, Luft & Shields (2003) emphasize the need for rigorously undertaken qualitative research.
Also Scapens and Bromwich (2001) call for greater refinement in research methods used in case
studies and fieldwork with more explicit attention to the validity of evidence used. This paper aims at
contributing to the debate on the problems versus benefits of undertaking qualitative studies
(Eisenhardt 1989, Gephart 2004, Yin 1994). Authors like Lillis & Mundy (2005) and Modell (2005)
tried to find an answer in calling for multi-method approaches. Our paper aims at promoting the use of
CAQDAS with realistic expectations to improve the quality of analysis when qualitative data come in,
although the advantages and disadvantages of a purely manual versus a CAQDAS-sustained analysis
need to be evaluated for every research study separately. CAQDAS packages offer useful tools and
complement the traditional manual analysis but can never substitute for continuing to think critically
about the meaning of data.
The remainder of this paper is organized as follows. Section 2 provides an overview of the
analysis functions of CAQDAS, which are incorporated as the first part of our analysis framework.
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Section 3 discusses how the use of CAQDAS can enhance the quality of qualitative data analysis and
will also mention potential pitfalls of relying on the software. These quality issues are important for
the second part of our analysis framework. Section 4 details the set-up of our literature review and
analysis protocol. Section 5 discusses the use of CAQDAS in the accounting versus other disciplines.
At the current stage of our analysis, we focus on the results for the sociology literature. Section 6
concludes with a discussion and advice for future research.
2. Analysis functions of CAQDAS
The use of computers for basic content analysis of text became popular in the 1960s. In
literature studies, academics started to use large mainframe computers for counting the number of
times particular words occurred in a text. The introduction of the personal computer in the 1980s
enhanced the possibilities, leading to a steady increase of computer use for qualitative research in the
social sciences from that time onwards (Fielding & Lee 1998, Seale 2000). Appendix A provides an
overview of the different functions CAQDAS packages can undertake (Miles & Huberman 1994,
Miles & Weitzman 1994). Appendix A also provides an overview of the different software families
reflecting the functions offered by the different packages (Miles & Weitzman, 1994). While activities
like writing and editing field notes, memos and reports at various stages, and searching and retrieving
can be undertaken with a simple word processor, more complex qualitative data handling functions
will become slow or even impossible without specific CAQDAS support. Especially sophisticated
organization of the data, data linking and display, content analysis, conclusion drawing and
verification, theory building and graphic mapping can be handled rather easily using the right
CAQDAS packages (Miles & Huberman 1994).
The first aim of our analysis framework is to provide insights in the degree to which different
research disciplines make use of the various functions of CAQDAS and to situate the current state of
management accounting studies in this context. We therefore distinguish between the following three
categories of CAQDAS use:
- The use of CAQDAS as a storage tool refers to the use of CAQDAS
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o to store information
o and for simple coding, searching along codes and retrieval of coded data.
- The use of CAQDAS as a gentle analysis tool refers to
o its functions for data linking, developing categories, clusters and networks of
information, preparing the road for further analysis and theory development through
the investigation of the relationships between the concepts.
o its possibilities for memoing and annotation, inviting the researcher to write down his
reflective commentaries and think thoroughly about the data.
o the possibilities to count the frequencies with which words, phrases or codes occur,
hereby providing indications of the relative importance of concepts or the importance
of certain verbal expressions by the interviewees.
o its more advanced possibilities for coding, in the sense that autocoding can be
instructed, and that codes can be flexibly rearranged in the coding hierarchy. The
advanced use of code and retrieve functions also facilitates data display.
- The use of CAQDAS as a far-reaching analysis tool refers to
o its use for developing conceptual maps, often aided by the graphic mapping functions
of the packages
o its use for theory building by investigating relationships among concepts within the
CAQDAS package.
o theory testing using the data, being the most advanced use of the code and retrieve
functions. Specific queries can be inserted and the results can be nicely displayed.
We also wonder which advantages and disadvantages are mentioned by the authors when
describing their experience with CAQDAS. The main advantages of CAQDAS versus working with
the familiar word processor for qualitative field research can be summarized in the following way:
- CAQDAS packages can assist in carrying out the mechanical tasks involved in interpretative
analysis, especially in terms of the management of data material. Qualitative research
processes are known for generating huge amounts of unstructured textual data, such as
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interview transcripts, protocols, field notes and personal documents. Proper data management
is required to avoid ‘data overload’ (Kelle, 1995).
- CAQDAS increases the speed of handling large quantities of data. Coding will go faster, better
and can be done with more precision when using CAQDAS. Also storing and retrieving
relevant chunks of text will be much quicker and easier. Especially in the initial stages of
analysis, the rapidity with which CAQDAS can identify patterns in large volumes of text can
be useful. In this way, computer-aided analysis can reduce analysis time and consequently cut
out much drudgery (Miles & Huberman 1994, Seale 2005, Tesch 1989).
- CAQDAS helps researchers demonstrate that their conclusions are based on rigorous analysis
and enhances the trust placed in research texts by readers. Helpful activities, easily executed
using CAQDAS, are counting the number of times things occur as well as demonstrating that
the researchers have searched for negative instances by examining the whole corpus of data
rather than selecting only anecdotes supporting their interpretation. Further, CAQDAS
encourages researchers to maximize the consistency of their coding and is also found helpful
in relation to sampling issues, serving representativeness or theory development. The rapid
retrieval, enabled by CAQDAS, can help in dealing with larger samples, so enhancing
confidence with which empirical generalizations are made (Seale 2005). Still, one should not
overlook that theoretical sampling in qualitative research has a different purpose from random
sampling: the aim is not so much to create empirical generalizations through large
representative samples, but to develop theory (Kelle & Laurie in Kelle 1995).
- Furthermore, the software can help in keeping track of emerging ideas, arguments and
theoretical concepts. This is important in qualitative research, because here data analysis and
theory construction are more closely interlinked than in other kinds of enquiry (Kelle 1995).
- CAQDAS also facilitates team research. In collaborative projects, researchers need to agree
on the meaning of codes and assess inter-rater reliability. This matter is easier to ignore
without the discipline imposed by the use of computers (Seale 2005).
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Although CAQDAS packages can be of great help for researchers, they also have a number of
disadvantages.
- The most important concern is that researchers risk taking a narrowly exclusive approach if
they stick too much to the computer analysis when interpreting the data. In this way, they
could become alienated from the data (Cannon 1998, Lee & Fielding 1995, Seale 2005).
- A more practical consideration is whether the advantages of using CAQDAS outweigh the
time invested in learning to use the package, especially if the researcher would mainly use the
functions of CAQDAS packages that might as well be carried out by a good word processor.
Seale (2005) discusses the use of CAQDAS in the context of small data extracts: there is no
point in spending time entering data if things can be worked out more quickly by hand.
In 1995, Lee & Fielding noticed that most researchers using CAQDAS confined their use to
coding and retrieval of text segments, using the computer as an electronic filing cabinet. Theory
building is generally done in the mind or with the aid of paper (Seale 2005). Seale (2005) discusses the
attraction of applying the new analytic possibilities of several (revised) CAQDAS packages for
researchers to come close to what has traditionally been the domain of quantitative research: counting,
theory development and theory testing. Several CAQDAS packages support theorizing by offering the
capacity to map out ideas in diagrams or conceptual networks (e.g. Atlas/ti, NVivo, or specific
conceptual mapping software). ‘Links between concepts can be visually represented in a variety of
forms, so that one type of link can mean ‘X causes Y’, another ‘X is associated with Y’, or ‘X loves
Y’, ‘X depends on Y’, ‘X is a property of Y’ and so on. Since the network is linked to coded segments
of data, instances of X and instances of Y, or instances of X where Y also occurs, or instances of Y
where X is not present (and so on) can be generated by the application of Boolean search statements’
(Seale 2005, 202). For theory-testing, Seale (2005) recommends to distinguish between two broad
categories of codes: heuristic and factual codes. Heuristic codes usually reflect the researcher’s
theoretical concepts (indicating: this chunk of text is ‘about research method’, or ‘about validity’).
They are used to retrieve segments of data which can then be further analyzed, sub-categorized etc.
Factual codes represent facts (e.g. this is a quote from Seale, or this is a paper from the management
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accounting literature). Rigorous hypothesis testing supported by CAQDAS needs factual coding,
because it allows the researcher to test whether something occurs related to certain antecedent
conditions (Seale 2005).
Coffey et al. (1996) make use of the hypertext link. It allows the analyst of data or the reader of a
report to click on a highlighted word or icon, which brings them instantly to some link which has been
previously made2. Instead of retrieving the relevant segment, hypertext links present the segment in its
original context and further allow the analyst to attach explanations, interpretations and memos to
particular links3. Certain CAQDAS packages promote hypertext links as a way to avoid the
decontextualization of data, caused by simple code-and-retrieve approaches. The sophisticated options
offered by these CAQDAS packages fuelled the methodological debate on the dominant grounded
theory approach, its limitations, and ‘post-modern’ alternatives (Kelle 1997).
Opponents of CAQDAS fear that computer technology will be used uncritically for data
analysis. Still, experienced qualitative, as well as quantitative, researchers stay aware of the need to
treat computers as instruments for pursuing arguments about data, rather than limiting thought to what
the computer can offer (Seale 2005).
3. Using computer software to enhance field study quality
‘Deciding to do qualitative research is not a soft option. Such research demands theoretical
sophistication and methodological rigour’ (Silverman 2005, 209).
The requirement of methodological rigor involves that qualitative researchers need to
demonstrate their methodological awareness to the reader: researchers should be committed to show
the procedures and evidence that have led to particular conclusions, and stay open to the possibility
that conclusions may need to be revised in the light of new evidence (Seale 1999). CAQDAS can play
an important role in this process, and our discussion will focus on validity and reliability, two criteria
2 cf. the use of Internet 3 The reader of the research report will then interact with the computer/CD-ROM rather than with a research report published on paper (Seale 2005).
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traditionally used to judge the quality of empirical research. In addition, we will pay attention to
theoretical sophistication, linking it to creativeness during the field study process.
3.1. Validity
Validity is the extent to which the data are in some sense a ‘true’ reflection of the real world
(Silverman 2005). It is ‘interpreted as the extent to which an account accurately represents the social
phenomena to which it refers’ (Hammersley 1990, 57). Validity deals with the way in which field
researchers manage to analyze the often large volumes of qualitative data in order to reach credible
results (Eisenhardt 1989). Lukka & Kasanen (1995) state that high quality case studies may produce
credibly generalizable results. By paying attention to the real (business) context and to the deeper
general structural relationships, a way is provided to move from isolated observations to results of a
more general status. Miles and Huberman (1998) use the concepts ‘internal validity’, ‘credibility’ and
‘authenticity’ as synonyms. They emphasize that qualitative researchers should critically question
whether their findings make sense and whether they are credible to the people studied as well as the
readers. The assumption of the existence of an ‘objective reality’ has to be judged in the right context:
reality is socially constructed, which means that some researchers find the idea of an external objective
reality hard to sustain (Ryan et al. 2002). But the main message is that it is important to handle
upcoming conclusions with care by engaging in a continuous process of checking, questioning and
theorizing (Miles & Huberman 1998).
The validity of an explanation can become doubtful when the researcher makes no attempt to
deal with contrary cases (Silverman 2005). Mehan (1979) commented on the anecdotalism he
observed in ethnographic field studies. Some research reports seemed to include just a few exemplary
instances of the behavior under study. Further, a majority of researchers did not mention the criteria or
grounds for including certain instances and not others, which makes it hard to judge the
representativeness of the instances and findings generated from them. Another observation by Mehan
(1979) was that the presentation of summarized research results in tabular form did not preserve the
original materials upon which the analysis was conducted. It becomes consequently impossible to
enable alternative interpretations of the same materials.
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Triangulation4 has been a common response to anecdotalism, and is formulated by Yin (1994,
p. 92) in the following way: ‘Any finding or conclusion in a case study is likely to be much more
convincing and accurate if it is based on several different sources of information, following a
corroboratory mode’. Working with CAQDAS facilitates different kinds of triangulation, especially
data triangulation and researcher triangulation. CAQDAS allows data triangulation by providing tools
to create and manage different sorts of data, like interview transcripts and archival documents. Further,
CAQDAS packages are usually also designed to facilitate researcher triangulation (Weston et al.
2001). The manual of NUDIST N5, for example, describes how NUDIST supports teamwork by three
instruments (Richards 2000a). One is called ‘within-project co-operation’. It means that two or more
researchers can work together on the same database (they can easily identify different bodies of data,
or different categories for thinking about phenomena by having a node for each researcher and coding
what they contribute at their node, storing their ideas in a memo at their node, etc.). A second sort of
collaboration allows ‘merging projects’, whereby two or more NUDIST projects can be easily merged.
The third option is referred to as ‘viewing a project in no-save mode’. It implies that one researcher
can ‘save a project in no-save mode’, so that it can be opened, explored and discussed by colleagues
working with a no-save viewer.
Silverman (2005) calls for prudence in terms of overly relying on triangulation in order to
increase validity. He points at the difficulties for novice researchers and the analytical limitations.
Instead, also in the tradition of Yin, he promotes a number of interrelated techniques that press
researchers for high-quality research and force them to continue to think critically about their
qualitative data:
- The data analysis should be demonstrated to be comprehensive, relying on all relevant
evidence. An analytic strategy to deal with this issue is constantly comparing data: attempting
4 Most authors (Eisenhardt 1989, Ferreira and Merchant 1992, Miles and Huberman 1998, Ryan et al. 2002) use Denzin’s (1978) terminology of the different kinds of triangulation: ‘data triangulation’ refers to collecting multiple sources of evidence on a particular issue; ‘method triangulation’ means that different research methods (e.g. observations, interviewing) can be used to collect data; ‘researcher triangulation’ refers to the use of several researchers. Working in teams can prevent an individual researcher’s bias from being brought into the study; ‘theory triangulation’ means that alternative theories are used to study a specific case.
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to find another case through which to test out a provisional hypothesis, until all parts of the
data are inspected and analyzed (Yin 1994, Silverman 2005, Tesch 1989).
- This involves that the analysis should include all major rival interpretations. The researcher
should seek to refute his initial assumptions about his data in order to achieve objectivity, and
should actively seek out and address anomalies or deviant cases (Yin 1994, Silverman 2005).
- Where appropriate, qualitative researchers can use tabulations: ‘Simple counting techniques,
theoretically derived and ideally based on members’ own categories, can offer a means to
survey the whole corpus of data ordinarily lost in intensive, qualitative research. Instead of
taking the researcher’s word for it, the reader has a chance to gain a sense of the flavor of the
data as a whole. In turn, researchers are able to test and revise their generalizations, removing
nagging doubts about the accuracy of their impressions about the data’ (Silverman 2005 p.
220).
While we acknowledge that validity ultimately requires researchers to expose their findings to the
confirmation of outsiders, CAQDAS offers a number of ways to improve the ‘content’ aspect of
validity. The data management functions of CAQDAS packages enable researchers to take into
account all case material in the analysis. CAQDAS provides instruments to search in the complete data
set for specific words, codes, phrases etc. and makes it easy to go back to the complete database when
a specific research step needs to be carried out or repeated. It means that the software provides
evidence that no occurrence has been overlooked. In addition, CAQDAS can help to handle large
volumes of data while it still allows the researcher to stay focused. It provides facilities to search
systematically and thoroughly for occurrences of codes (Kelle & Laurie 1995). The easily manageable
search and retrieve instruments allow a complete analysis that can always be refined (Tesch 1989).
Also counting and the presentation of the counted numbers in tables become easy tasks using
CAQDAS.
The newest options offered by CAQDAS packages, such as hypertext links, can clearly
address the problem of anecdotalism: presenting a research report to the reader in a CD-ROM format
will convey a lot of information and will allow the ‘readers’ to fully examine the corpus of data on
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which conclusions are based. One should however not ignore that this leads to an exhaustive task for
the readers of the report: ‘it is likely that the single-paragraph abstract of findings will retain a greater
appeal for readers concerned to survey a range of studies in order to extract the major research findings
of a particular field’ (Seale 2005, 206).
The possibilities CAQDAS offers for complete and refined research on large volumes of
different sorts of data, has disadvantages. Kelle & Laurie (1995) observe a paradox concerning
computer use in qualitative analysis: while the technology facilitates the clerical handling of
voluminous textual material, the analysis process does not necessarily become quicker or easier. The
sheer volume of information that can be taken into account when using a CAQDAS package can
become overwhelming for researchers. An important aspect is that the potential benefits of a larger
sample size may be outweighed by the extra costs in time and effort required for data preparation and
data entry. In the context of technically easy data retrieval and coding instruments, researchers should
be careful not to develop a ‘fascination with volume’. Instead, the decisions about which and how
much data to use should depend on the research aims (Seidel 1991).
3.2. Reliability
Reliability is the extent to which evidence is independent of a person using it. This expression
implies that the investigator has to adopt an independent and impersonal point of view (Yin 1994).
Reliability refers to consistency of the research process and to its reasonable stability over time and
across researchers and methods. Miles & Huberman (1998) refer to reliability as a synonym for
dependability or auditability. They stress the importance of ‘quality control’ by investigating whether
the analysis process has been executed with reasonable care. Some researchers, as Ryan et al. (2002),
remark that the focus on reliability is difficult to realize and even undesirable for field studies, because
the interpretations of the researcher and his/her relation to the subject matter are essential elements of
the explanations of the case. They therefore prefer the term ‘procedural reliability’ (Ryan et al. 2002),
whereby they insist on having all evidence recorded in a coherent set of field notes and fully
documenting the case analysis. In other words, the researcher is asked ‘to leave an audit trail’ (cf.
Miles and Huberman 1998).
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In the context of improving the reliability of qualitative studies, a number of researchers are
calling for ‘low-inference descriptors’: detailed data presentations which make minimal inferences are
always preferable to researchers’ presentation of their own (high-inference) summaries of their data.
This means researchers are stimulated to include verbatim accounts of what people say rather than
present researchers’ reconstructions of the general sense of what a person said (Seale 1999, Silverman
2005). This request is closely related to Mehan’s (1979) unease with presentations of summarized
research results in tabular form – although his stress was on the problematic consequences in terms of
validity.
Using CAQDAS allows researchers to demonstrate that their conclusions are based on
consistent analysis:
- CAQDAS packages enable a thorough and full documentation of the analysis process. They
encourage systematization and largely are self-documenting (Fielding & Lee 1998). NUDIST,
for instance, registers whether codes have been merged with other nodes, have been moved
within the hierarchical tree of nodes, etc. (Richards 2000a). In addition, CAQDAS packages
stimulate researchers to keep track of emerging ideas, arguments and theoretical concepts, by
offering electronic memoing facilities.
- A related fact is that CAQDAS forces users to make explicit choices during the analysis
process. In manual analyses, such decisions often remain implicit. The most obvious example
is that the computerized system requires the researcher to make clear from the start which
items he is interested in (Fielding & Lee 1998, Tesch 1989). Miles & Huberman (998) stress
the importance of undertaking research that is relatively neutral and reasonably free from
unacknowledged researcher biases. By asking for clear instructions, CAQDAS forces
researchers to be explicit about inevitable biases.
- By making analysis choices explicit and by thoroughly documenting the research process,
CAQDAS allows researchers to follow a consistent and systematic research path, and to
increase the stability of the research over time, across researchers and methods (Fielding &
Lee 1998, Tesch 1989).
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The prospect of being able to work with CAQDAS also has a major disadvantage. In general, field
studies should be sufficiently prepared in terms of the field study design and the analysis protocol (Yin
1994, Miles & Huberman 1998, Ryan et al. 2002). Although CAQDAS encourages researchers to pay
attention to these issues, a number of CAQDAS researchers warn for the following potential danger.
The prospect of using the software could tempt researchers to prepare insufficiently, because they
quickly want to start working with the package. Insufficient preparation could lead them to base the
analysis on a kind of ‘trial and error’ procedures when going through the case material, instead of
basing the analysis on a thoroughly prepared research design (Russell & Gregory 1993, Fielding &
Lee 1998). These potential pitfalls of case study research cannot be prevented by the CAQDAS
package itself. Instead, avoiding theme remains to be the researchers’ own responsibility.
3.3. Theoretical sophistication and creativeness
Apart from discussing validity and reliability, theoretical sophistication deserves to be
discussed when evaluating the potential of CAQDAS for management accounting field research.
‘Good-quality research thinks theoretically through and with the data’ (Silverman 2005, 242), and
therefore the theorizing process and the creativeness this requires, are important topics.
Working with CAQDAS has the following advantages:
- As the presentation of the analysis functions offered by CAQDAS indicates, it is clear that
CAQDAS can take over a lot of – often dull – routine tasks. CAQDAS allows, for example, a
quick and easy search through the complete database. Consequently, the researcher can
concentrate on essential design and analysis tasks (Tesch 1989). An example of traceable and
confirmable research procedures are the Node Searches in NUDIST (Richards 2000b). The
facility ‘Node Search’ consists of a set of tools for automatically finding relationships between
the coding of two or more nodes. Examples are ‘union’ (creating a new node merging the
coding under two previously separate nodes), ‘overlap’, ‘intersection’ and ‘followed by’. In
the context of such facilities, CAQDAS packages make it easy to re-ask the same question
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about something different and allow storing the answer to a question as coding at a new node,
which can be used for further investigation.
- CAQDAS packages keep track of emerging ideas, arguments and theoretical concepts.
Depending on the specific software package used, the researcher can add his comments in
separate memos that are easily retrievable. Such options stimulate the researcher to keep on
critically evaluating his data during the theorizing process.
- CAQDAS at the same time enables analytic reassessment of the research, because it permits a
far-reaching flexibility and revision of analysis procedures (Tesch 1989).
- The newest features offered by CAQDAS packages include hypertext links. Apart from
dealing with the traditional validity and related reliability concerns, since they make the link
between the original data and the final presentation extremely explicit, working with hypertext
links can also lead to useful and creative theorizing approaches: researchers can benefit from
the possibility to intimately link data, analysis and interpretation (Seale 2005).
A disadvantage of using CAQDAS is that researchers – busy with the CAQDAS package and
learning about all possible/new options - could be tempted to stick to their initial coding scheme, and
forget to relate other interesting phenomena to the analysis. It means that they could take a narrow
approach to the data (Eisenhardt 1989). While CAQDAS has to potential to aggravate this potential
pitfall, the software packages all offer instruments to overcome this problem. The memoing
instruments have been discussed, and there is also the possibility to add ‘free nodes’. These nodes,
indicating previously unmentioned issues, can be added after the initial hierarchy of codes has been set
up. Free nodes are useful to capture new themes that emerge during the analysis process and can help
the researcher to develop a new perspective on the research topic. The opposite danger is that case
study researchers end up with a theory that is overly complex (Eisenhardt 1989). This is a problem that
cannot be avoided by the use of a software package, and of which all qualitative researchers should be
aware at any stage of their analysis. To conclude, the discussion of the three quality criteria is
summarized in Table 2.
18
Table 2: The impact of using CAQDAS for the quality of qualitative research
Quality criteria
VALIDITY RELIABILITY CREATIVENESS
CAQDAS advantages
Triangulation (data, researcher) Completeness and refinement Counting techniques
Ease to retrieve low-inference descriptors Thorough and full documentation of the research process Analytic choices made explicit Stable research path over time, across researchers and methods
Concentration on essential design and analysis tasks Keeping track of emerging ideas, arguments, theoretical concepts, enabling analytic reassessment of the research Flexibility and revising options Intimate link between data, analysis and interpretation (e.g. hyperlinks)
CAQDAS disadvantages
Danger for researchers to become overwhelmed by large sample size: need for careful selection of data and careful examination of extra costs in terms of time/effort required for data preparation/entry
Researchers potentially tempted to prepare insufficiently in their eagerness to embark on using the CAQDAS package
Danger that researchers have a narrow view on the data Too many nodes might end up in an overly complex theory
4. Approach
The previous two sections reviewed the research method literature related to our analysis
framework: we will pay attention to the functions offered by CAQDAS and crucial quality issues to
review the CAQDAS-based qualitative literature. This framework guides our analysis of the extent to
which CAQDAS packages are actually used in different research disciplines. In this section, we
explain the set-up of the literature review and the analysis protocol.
The identification of the accounting articles using CAQDAS was different from the selection
of the publications in other disciplines. To identify the relevant accounting publications, we searched
through the following journals for the period January 1994 till December 2007: 1. Accounting,
Auditing, Accountability Journal (AAAJ), 2. Journal of Accounting Research (JAR), 3. Journal of
Accounting & Economics (JAE), 4. The Accounting Review (TAR), 5. Contemporary Accounting
Research (CAR), 6. Journal of Management Accounting Research (JMAR), 7) Accounting,
Organizations and Society (AOS), 8. Management Accounting Research (MAR), 9. The European
Accounting Review (EAR) and 10. Critical Perspectives on Accounting (CPA). Table 1 provides an
overview of the articles actually using CAQDAS to perform their analysis and indicates the packages
involved. We exclude articles referring to CAQDAS in general without applying it to a specific
19
research project5. As Table 1 shows, the number of papers relying on CAQDAS is overall growing.
Only in five of the ten selected journals (9 in AOS, 8 in AAAJ, 1 in CPA, 2 in JMAR and 6 in MAR)
papers have used CAQDAS, which is not a coincidence given that these are the journals publishing
most of the field research in accounting.
Given the large amount of hits encountered after a first search in the databases, we used a
stricter procedure to select the published articles from other disciplines. First, we confined our search
to three databases that have an extensive content of scientific papers: 1) Wiley Interscience, 2) ABI
Inform and 3) Sciencedirect. We searched all scientific publications in these databases from their
existence until December 2007 for their use of Atlas/ti, NUDIST – Nvivo and The Ethnograph, the
packages most frequently used in accounting. Our search was therefore directed by the following
keywords:
- CAQDAS; Computer assisted qualitative data analysis software
- NUDIST software; nudist
- N-Vivo; N-VIVO; NVivo
- Atlas/ti; atlas.ti; atlasti
- Ethnograph
Searching the full document text produced approximately 1.700 papers. In order to focus on the
highest quality publications, we selected only those papers that were published in journals mentioned
in the Journal Citation Report (JCR) of the ISI Web of Science. To determine the disciplines in which
the CAQDAS papers were published as well as to know the ranking of the journals, we used the
categorization of disciplines and the ranking of journals as indicated by the JCR Social Science
Edition (SSE) and the JCR Science Edition (SCE). Both the SCE and the SSE distinguish a rather
great number of categories that express the (sub)discipline of journals. In order to get a better
overview, we constructed 31 groups of disciplines as indicated in the table in Appendix B. For 21 of
these groups we found papers that reported the use of CAQDAS.
5 The accounting article by Irvine and Gaffiking (2006) was included because it discusses methodological issues based on a concrete research project.
20
Several checks were undertaken in order to make sure that only relevant publications were
added to our database, e.g. by removing the papers that were dealing with ‘nudists’ or referred to the
medical term ‘nvivo’. Further, we checked to make sure that every paper was only included once, so
more hits per paper were excluded. Given that we only analyzed the papers in the journals that were
ranked in the JCR list, our final research sample contained 1150 publications. However, some journals
belong to several discipline groups.
We are currently analyzing the social science papers that will be used for more in-depth
analysis. In order to determine an appropriate research sample, we use a stratified sampling method.
Step one consists of including only the discipline groups providing ten or more relevant publications.
Step two consists of randomly selecting a number of papers. This number depends on the total number
of papers found per group: for the groups having less than 50 papers we selected 10 papers randomly,
for the groups with 50 to 100 papers we selected 20 papers, and for the groups with more than 100
papers we keep 30 papers in our sample.
The selected papers are categorized (along discipline group, CAQDAS package used etc.) in
SPSS. For the literature review and analysis, we use NVivo7. This CAQDAS package allows us to
manage the large number of papers involved, fastens our coding and retrieval processes and facilitates
the display of the results. CAQDAS ensures our analysis takes into account the complete coding
scheme. Further, it facilitates the researcher triangulation we are able to benefit from. Both researchers
compared and discussed the coding of the first three accounting papers, before the rest of the
accounting papers were analyzed. After this was done, both researchers again compared their coding
and made sure they came to an agreement about every aspect of the coding scheme. Based on this
experience, coding of the papers from other disciplines can be divided among both researchers.
During several coding rounds the original coding scheme, heavily based on the research
methods literature discussed above, has been refined. The resulting coding scheme is presented in
Appendix C.
21
5. Analysis of field research using CAQDAS
This section presents the preliminary outcomes of the analysis. In the first place, we give an
overview of the use of CAQDAS in the different research disciplines excluding the accounting papers
reviewed. Second, we compare Accounting and Sociology in terms of our framework on the functions
of CAQDAS used and the quality items.
5.1. A descriptive analysis of the use of CAQDAS in the academic literature
Table 3 provides a chronological overview of the academic articles found through the
selection procedure described above. The table reveals a remarkable increase in the use of CAQDAS
based on the packages Atlas/ti, NUDIST and Nvivo, and the Ethnograph over the last decade. The
discipline groups that stand out in terms of published papers using these packages are Nursing and
Medicine (38% of the total number of CAQDAS papers), Social and Political Sciences (19%),
Business and Management excluding Accounting (10%), Psychology (9%), Computer science (5%),
Education (4%) and Information Science and Library Science (3%).
Table 4 describes the use of the different CAQDAS packages in the literature. Nvivo is the
most widely used package (used in 47% of the selected papers), closely followed by Atlas/ti (38%).
While Accounting papers have only recently shifted towards using Nvivo instead of NUDIST, the use
of NUDIST in the other disciplines is relatively low (8%). The Ethnograph is only used in 7% of the
selected papers. The dominance of Atlas/ti and Nvivo seems to be present in most of the science
domains.
22
Table 3: The use of Atlas/ti, NUDIST – Nvivo and The Ethnograph over time
1991 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 Total % Anthropology 2 1 2 1 2 1 4 13 1.13% Business & Man. 1 2 2 3 1 7 12 12 10 12 12 18 26 119 10.35% Education 1 2 1 1 1 3 1 7 7 12 13 49 4.26% Nursing and Medicine 1 2 1 1 2 2 8 5 6 7 13 21 45 71 104 147 436 37.91% Public Administration 1 1 1 2 5 10 0.87% Psychology 5 1 4 1 6 3 10 23 14 32 99 8.61%
Social and political sciences 2 1 9 1 6 5 6 14 18 35 50 74 221 19.22%
Geography related studies 3 1 8 12 1.04% Communication 1 3 1 5 0.43% Law 1 1 1 3 0.26% Environmental studies 1 1 1 2 2 2 3 4 9 25 2.17% Ethics 1 1 1 3 4 10 0.87% History 1 1 0.09%
Information Science & Library science 1 1 2 2 5 8 3 15 37 3.22% Planning & development 1 3 1 2 4 5 16 1.39% Biology 1 3 4 1 5 14 1.22% Engineering 1 3 1 4 9 0.78% Computer Science 1 1 2 1 3 7 12 8 25 60 5.22% Agricultural 1 1 0.09%
Geology / Physical Geography 4 1 5 0.43% Miscellaneous 1 3 1 5 0.43% Total 1 3 9 4 3 4 29 9 32 30 50 61 113 187 234 380 1150 100.00%
23
Table 4: The use of Atlas/ti, NUDIST – Nvivo and The Ethnograph in the academic literature
Atlas/ti Ethnograph NUDIST Nvivo Total Anthropology 6 3 0 4 13Business & Man. 32 15 27 42 116Education 13 4 4 27 48Nursing and Medicine 180 28 17 209 434Public Administration 3 3 1 3 10Psychology 46 7 5 40 98Social and political sciences 90 11 21 98 220Geography related studies 4 0 0 8 12Communication 1 2 0 2 5Law 1 0 1 1 3Environmental studies 9 0 4 12 25Ethics 2 1 3 4 10History 0 0 1 0 1Information Science & Library science 10 1 4 22 37Planning & development 4 0 1 11 16Biology 3 0 0 11 14Engineering 4 0 0 5 9Computer Science 20 0 3 35 58Agricultural 0 0 0 0 0Geology / Physical Geography 4 0 0 1 5Miscellaneous 2 0 1 2 5Total 434 75 93 537 1139Percentages 38% 7% 8% 47% 100%
5.2. A first look at Accounting versus Sociology
As the tables above reveal, our analysis is not only aiming at comparing Accounting with
Sociology, but our goal is also to place Accounting CAQDAS use in the context of other research
disciplines. The analysis is still in full process. In order to avoid providing an incomplete picture by
comparing all disciplines at this stage, we here present our first insights about the use of CAQDAS in
Accounting as compared to its use in Sociology, one of the fields known for a high level of qualitative
24
research. Appendix D lists all Accounting papers indicating the use of CAQDAS. Appendix E gives an
overview of the Sociology articles included so far in this analysis. Note that the sociology articles in
Appendix E have been found by searching the databases until April 2005 only, for the following key
words: CAQDAS; Computer assisted qualitative data analysis software; NUDIST software; nudist; N-
Vivo - N-VIVO; Atlas/ti. The analysis of the more recent papers and of the papers using ‘The
Ethnograph’ is in full process at this moment.
Table 5 gives an overview of the number of papers discussed. As indicated in the section above,
the selection of the sociology papers (only articles published in journals with a JCR impact score) has
been more severe than for the accounting papers. In addition, the Sociology papers included date until
April 2005.
Table 5: Articles using CAQDAS in Accounting and Sociology along year of publication
1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 Total
Accounting 0 1 1 2 2 0 4 3 7 6 26
Sociology 1 0 1 3 5 4 7 9 0 0 30
Table 6 details the different packages used in Accounting and Sociology along our original search
criteria. All Accounting papers are included in this analysis. The Sociology papers brought in here do
not reflect the complete sample, since they include only the Atlas/ti and NUDIST –Nvivo papers until
April 2005.
Table 6: Use of different packages in Accounting versus Sociology according to the original search criteria
Ethnograph Nudist Nvivo Atlas.ti TACT NUDIST and
Diction 5 OCP
Accounting 3 6 7 8 1 1 1
Sociology Not yet included 6 0 24 0 0 0
The first part of our analysis framework guides us towards the extent of CAQDAS use in the
different disciplines. Table 7 summarizes the use of CAQDAS, as it has been reported by the authors
in the published article. Three categories are distinguished:
- the use of CAQDAS as code and retrieve (a data storage) tool
- the use of CAQDAS as a ‘gentle analysis tool’
25
- the use of CAQDAS as a far-reaching analysis tool: it means CAQDAS is used for developing
conceptual maps, and for building and testing theory using the data.
Table 7: Degree of CAQDAS use in Accounting versus Sociology
code and retrieve gentle analysis far reaching analysis
Accounting 19 19 7
Sociology 4 17 4
In contrast to what we had expected beforehand, the number of Accounting papers making advanced
use of the theorizing tools of CAQDAS does not seem to have to underdo for the Sociology papers.
Most far-reaching in their use of CAQDAS are Malina & Selto (JMAR 2001), Malina & Selto (MAR
2004) and Abernethy et al. (MAR 2005). These authors rely a lot more on CAQDAS than any of the
Sociology papers involved in the preliminary analysis.
Table 8: Different techniques used in CAQDAS in Accounting versus Sociology
Accounting Sociology autocoding in CAQDAS 0 1
constructing conceptual maps 2 1 content analysis 6 4 frequency counts 9 3
creating categories for further analysis and investigating inter relationships 4 10
memoing in CAQDAS 0 3 purposive coding in CAQDAS 0 1
theory development 3 2 theory testing 2 2
Table 8 provides an overview of the different techniques used within CAQDAS. Both fields
have a different emphasis. Accounting papers relatively make more use CAQDAS for content analysis
and frequency counts, while the Sociology papers indicate more often to use CAQDAS to create
categories for further analysis and to investigate the inter-relationships between these categories. A
large number of these papers indicate the use of CAQDAS in the context of their grounded theory
approach. In future research, we will link the use of CAQDAS to the intended goal of the paper in
terms of description, theory development or theory testing.
26
Table 9: Advantages of using CAQDAS, mentioned in Accounting and Sociology
Accounting Sociology ease to go back to context 2 3
facilitate teamwork 7 9 increase speed 2 1
use CAQDAS retrievals for data display 8 10 ascertain prevalence and substance of a
theme 1 2
measuring intercoder reliability 3 1 rigor of analysis 6 3
Table 9 presents the major advantages mentioned in the two fields when using CAQDAS. The
retrieval of data for display and the facilitation of teamwork are indicated as appreciated features when
using CAQDAS. In addition, the Accounting authors seem more concerned about the reliability of
their analysis, expressed by using CAQDAS. They aim at proving that their work is undertaken in a
strict way. When reading the CAQDAS-based papers, we observe that the Sociology papers account
for the use of CAQDAS in a different way than the Accounting papers. The Sociology papers seem to
follow a more standardized, predictable way to discuss their use of the CAQDAS functions. The
references to CAQDAS in the Accounting papers are made in a much more loose and diverse way.
Accounting papers go from the extreme of providing detailed information on the use of CAQDAS in
Journals like AAAJ and MAR to the other extreme of only mentioning the use of CAQDAS in a
footnote (e.g. Sian 2006 in AOS). When further refining our analysis in the future, we want to
incorporate how much attention is paid in each paper to explaining the use of CAQDAS.
5.3. Detailed analysis of the Accounting papers
In this paragraph we analyze the Accounting papers in more detail along the coding scheme (Appendix
C). The following tables represent how the Accounting papers report about the degree of analysis they
undertake using CAQDAS packages.
Table 10: Degree of analysis
Code and retrieve Gentle analysis Far-reaching analysis Accounting 19 16 7
27
Most papers stick to the basic code and retrieve functions, and recur to gentle analysis methods.
Almost 3% of the Accounting papers use CAQDAS in a more advanced way. The table below shows
the ‘gentle’ or soft use of CAQDAS these Accounting papers are actually mentioning.
Table 11: Different techniques used in CAQDAS in Accounting – Gentle analysis
Creating categories
Frequency counts
Autocoding in CAQDAS
Memoing in CAQDAS
Query functions
used Accounting 6 9 0 0 9
Most papers make use of CAQDAS for frequency counts. While in some cases words and phrases are
counted, other papers count the number of times a certain node has appeared (as we actually apply in
this paper). The reference to query functions indicates that quite some authors use CADQAS’ query
functions and use the resulting retrieval to fill in data matrices, like the thematic conceptual matrices
suggested by Miles & Huberman (1998). Further, the use of CAQDAS to refine conceptual categories
has been mentioned in several papers. We now look at what authors indicate in their papers when they
use CAQDAS in an advanced way.
Table 12: Different techniques used in CAQDAS in Accounting – Far reaching analysis
Theory development
Investigating interrelationships
Theory testing
calculation of probabilities that a
word collocates with another
CAQDAS identifying semantic
tonalities of passages of text
Accounting 5 6 2 1 1
Five papers indicated the use of CAQDAS for theory development, and all of them referred to the far-
reaching use of the computer to investigate interrelationships between concepts. Only two papers
indicated the use of CAQDAS for theory testing. Interestingly, one paper indicated the use of the
package to calculate the probability that a word collocates with another. And one paper let the package
DICTION automatically identify the semantic tonalities of passages of text.
Table 13: Advantages of using CAQDAS, mentioned in Accounting
Accounting
28
Flexibility 4 Ease to go back to context 2
Facilitate teamwork 3 Measure intercoder
reliability 3
Use CAQDAS retrievals for data display
2
Justification Ascertain prevalence and
substance of a theme 1
Negative/contrary cases 1 Prove rigor of analysis 6 Prove validity 4
Leave audit trail 3 Increase speed 3
Table 13 displays the advantages the authors of the papers mentioned about the use of CAQDAS. It
shows that the researchers especially appreciate CAQDAS for its flexibility and to prove its rigor as
well as the validity of the analysis. The table below indicates that few accounting papers give
information about the experienced disadvantages when using CAQDAS for their analysis.
Table 14: Disadvantages of using CAQDAS, mentioned in Accounting
Time spent Narrow analysis Too many categories Accounting 0 1 0
Only one paper (Abernethy et al 2005) mentioned the possibility to end up with a narrow analysis
when recurring too much to the software and forgetting to analyze the data yourself.
Table 15: Information processed in CAQDAS accounting papers
Interviews Other documents Newspaper articles
Field notes
Accounting 22 7 1 2
Table 15 gives an overview of the type of information processed in CAQDAS accounting
papers. About 85% of the papers use CAQDAS with interview transcripts. Other documents (like
annual reports, chairmen’s statements etc.) are mentioned, and one paper analyses newspaper articles
29
using CAQDAS. Table 16 displays the amount of detail provided in the paper about the use of
CAQDAS.
Table 16: CAQDAS detail
Accounting In footnote only 1 In research method section only 16 In analysis section only 1 In appendix only 0 In results section only 0 In discussion section only 0 In methods section and conclusion 0 In research method and footnote 3 In research method, results, analysis, discussion section, and foodnote
1
In research method and discussion 1 In research method, footnotes, appendix, and results
1
In research method, footnotes, and results
1
In research method, discussion, and footnotes
1
It shows that most papers report the use of CAQDAS in the research method section, 24 out of the 26
papers explain the way they used CAQDAS in this section. 8 of these 22 papers also pay attention to
CAQDAS in another part of the paper. In one paper, the author only reports the use of CAQDAS in a
footnote. In another paper, the use of CAQDAS is discussed in the analysis section.
6. Preliminary discussion and conclusions
The purpose of this paper is to provide an overview of the use of CAQDAS to analyze
qualitative accounting data: are we in accounting benefiting from CAQDAS to its full potential? In
order to find an answer we are reviewing the accounting papers referring to CAQDAS use in
comparison to the use of CAQDAS in other research disciplines. Our analysis is guided by a
framework focusing on the CAQDAS functions used and the research quality considerations
mentioned in the publications. Related to the CAQDAS functions, researchers can use CAQDAS just
for organizing their data (‘code and retrieve’), or for undertaking a ‘gentle’ or ‘far-reaching’ analysis
30
within the software package (Lee & Fielding 1995, Seale 2005). Related to analysis quality,
researchers can give an indication of whether they find CAQDAS important to enhance the ‘validity’,
‘reliability’ and/or ‘theoretical sophistication’ of their work (Silverman 2005). A thorough search
through the contents of ten accounting journals identified 26 published articles using CAQDAS before
January 2008. Atals/ti, NUDIST-Nvivo and The Ethnograph are used most. A search for academic
papers using these packages in three online databases (from their existence until December 2007) led
us to identify about 1150 published papers in journals with a JCR impact score. A sample of each
discipline containing more than ten CAQDAS papers is currently being analyzed based on our coding
protocol.
What can we conclude from our preliminary analysis comparing all Accounting papers using
CAQDAS with a limited set of Sociology CAQDAS papers? Accounting – and especially
management accounting - researchers use a wide variety of CAQDAS functions, so Accounting does
not seem to underdo for Sociology. Authors like Abernethy et al. (2005) and Malina and Selto (2001,
2004) make use of the most advanced functions of ATLAS/ti for theory development and testing,
while most researchers stick to the code-and-retrieve and the more gentle analysis options offered by
CAQDAS. The advantages of using CAQDAS at all degrees are clear: researcher as well as data
triangulation becomes easier. Further, ‘low-inference descriptors’ (Seale 1999, Silverman 2005) can be
easily traced back. Since CAQDAS requires researchers to make explicit choices and in this way
stimulates researchers towards an explicitly systematic and rigorous analysis, researchers can enhance
the trust of readers in the validity and reliability of the final conclusions.
That CAQDAS use proves the rigor of the analysis is indicated more often by Accounting than
by Sociology researchers. It seems that Accounting researchers are even more apologetic about their
use of qualitative data, which might be the main reason why they use CAQDAS to a more extreme
degree than Sociology researchers (by going over to theory testing, visual mapping etc.). While
Accounting researchers focus on the use of CAQDAS to enhance the validity and reliability of their
study, the sociologists indicate to use CAQDAS often for its possibilities in terms of creativity and
theoretical sophistication. A lot of Sociology researchers describe how CAQDAS is used for creating
31
categories for theory development, aided by the memoing functions provided by CAQDAS. In
contrast, qualitative Accounting researchers often seem to prefer to rather avoid this option because it
makes them feel alienated from the interpretive freedom they have in the qualitative research process.
We observe that the extent of reporting and explanation of how CAQDAS has been used is
more diverse in the Accounting than in the Sociology literature. Accounts on CAQDAS use appeared
more streamlined and uniform in the Sociology papers. One striking aspect was the place of
mentioning CAQDAS in the article. A extreme is an Accounting paper only mentioning the use of
CAQDAS in a footnote, while the paper does not reveal in any other way how CAQDAS was used.
Another aspect is that some Accounting papers do not report what CAQDAS is used for. Just
mentioning that ‘we analyzed our interview material using CAQDAS’ does not provide satisfactory
information about the analysis undertaken. We conclude that readers could get better insights in the
research process when authors clearly and concisely indicate what they actually did with CADQDAS.
In terms of the reports on CAQDAS use in both disciplines, we find that a lot depends on the
journal. Two extremes are the Journal of Social Science and Medicine (providing a highly streamlined
account of the research process) versus Accounting, Organizations and Society (characterized by a
high diversity in reporting on CAQDAS use). At a first glance, AOS seems to publish more articles
that mention marginally that CAQDAS was used, without providing particular details or proving the
value for validity and reliability in the paper. In contrast, MAR and AAAJ articles sometimes go so far
in their explanation of how CAQDAS improved the rigor of analysis, that they become quite
apologetic about the choice for qualitative data.
One avenue for future research would be to link these observations back to the methods
textbooks that have been used in both fields. Further, the current analysis only captures how
researchers mention the use of CAQDAS in their published article. Another idea for future research is
to involve these authors in a survey about their use of CAQDAS. This approach would enable us to get
better insights into the degree to which the various CAQDAS options were tested out and actually
used.
32
To conclude, apart from the lessons learned from CAQDAS publications in other disciplines,
we want to make sure future CAQDAS users embark on software analysis projects with reasonable
expectations: how far-reaching (or not) the options offered, CAQDAS cannot provide a substitute for
continuing to think critically about the meaning of data.
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Appendix A. CAQDAS functions
Today, CAQDAS packages are used in various ways in qualitative studies (Miles & Huberman 1994, Miles & Weitzman 1994):
- to make notes in the field, - to write up or transcribe field notes, - to edit, i.e. to correct, extend or revise field notes, - to code, meaning to attach key words or tags to segments of text to permit later retrieval, - to store information, i.e. to keep text in an organized database, - for search and retrieval, referring to locating relevant segments of text and making them
available for inspection, - for data ‘linking’, i.e. to connect relevant data segments with each other, forming categories,
clusters or networks of information, - for memoing and annotation, i.e. to write reflective commentaries on some aspect of the data,
as a basis for deeper analysis, - for content analysis, in other words counting frequencies, determining sequence or locations of
words and phrases, - for data display, i.e. to place selected or reduced data in a condensed, organized format, such
as a matrix or network, for inspection, - for conclusion drawing and verification, aiding the analyst to interpret displayed data and to
test or confirm findings, - for conceptual/ theory development, namely to develop systematic, conceptually coherent
explanations of findings, or to test hypotheses, through providing rule-based or logical approaches and through building semantic networks,
- for graphic mapping, i.e. to create diagrams that depict findings or theories and - to prepare interim and final reports.
One of the most recent trends consists of the increasing possibilities to collect, store, manage and analyze digital data (e.g. by using digital camcorders and computers). In addition, analogue data can now easily be digitized (Brown 2002). Spoken text on a tape recorder, for example, can be transcribed and imported into a computer by using voice recognition software. Another development is ‘direct transcription software’, where speech is recorded on a CD-ROM. Data analysis software then evolves to the application of codes to the sound segments instead of to transcribed text (Fielding & Lee 1998). CAQDAS software packages can be divided in the following families, reflecting the functions they provide (Miles and Weitzman, 1994):
Word processors These tools are basically designed for the production and revision of text, and thus are helpful for taking, transcribing, writing down, or editing field notes, for memoing, for preparing files for coding and analysis, and for writing report text. Word retrievers These specialize in finding all instances of words, phrases, and combinations of these you are interested in locating, in one or several files. Some have content-analytic capabilities as well: counting, displaying words in their context, and creating word lists and concordances (organized lists of all words and phrases in their context). Text base managers The programs organize text systematically. They search for and retrieve various combinations of words, phrases, coded segments, memos, or other material. Code-and-retrieve programs These programs help you to divide text into segments or chunks, attach codes to the chunks, and find and display all instances of coded chunks (or combinations of coded chunks). Theory builders These programs include code-and-retrieve capabilities. They also allow you to make connections between codes (categories of information); to develop higher-order classifications and categories; to formulate propositions or assertions, implying a conceptual structure that fits the data; and/or to test
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such propositions to determine whether they apply. They are often organized around a system of rules, or are based on formal logic. Conceptual network builders These also help you build and test theory, but you work with systematically-built graphic networks. You can see your variables as nodes, linked with other nodes by specified relationships. The networks are not just casually hand-drawn, but are real “semantic networks” that develop from your data and your concepts and the connections you see among them.
Appendix B: Groups of disciplines used6
Group Original SSE – SCE reference Anthropology (d=1 ANT) SSE 01, Anthropology
SSE 15 Ethnic Studies; SSE 16 Family Studies; SSE 54 Women’s Studies
Business & Management (d=2 BM)
SSE 04, Business SSE 05, Business, finance SSE 27, Management SCE 122 Operations Research & Management Science
Education (d=3) SSE 10, Education SSE 11 Education, Special SSE 44 Rehabilitation SCE 148 Rehabilitation SCE 45 Education, Scientific Disciplines;
Nursing and Medicine (d=4)
SSE 28, Nursing SSE 13 Ergonomics; SSE 18 Gerontology SSE 31 Psychiatry SCE 144 Psychiatry SSE 43 Public, Environmental & Occupational Health; SCE 118, Nursing SSE 19 Health Policy & Services SSE 51 Substance Abuse SCE 11 Anesthesiology; SCE 30 Clinical Neurology; SCE 39 Critical Care Medicine; SCE 41 Dentistry, Oral Surgery & Medicine; SCE 42 Dermatology; SCE 47 Emergency Medicine; SCE 48 Endocrinology & Metabolism; SCE 70 Gastroenterology & Hepatology; SCE 71 Genetics and Heredity
SCE 76 Geriatrics & Gerontology;
SCE 77 Health Care & Services; SCE 78 Hematology; SCE 82 Immunology; SCE 83 Infectious Diseases; SCE 85 Integrative & Complementary Medicine; SCE 100 Medical Ethics; SCE 101 Medical Informatics; SCE 102 Medical Laboratory Technology; SCE 103 Medicine, General & Internal;
6 Although the discipline codes go until 33, we ended up with 31 categories after reorganizing the original categories 15 and 27.
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SCE 104 Medicine, Legal; SCE 105 Medicine, Research & Experimental; SCE 116 Neuroscience SCE 118 Nursing; SCE 119 Nutrition & Dietetics; SCE 120 Obstetrics & Gynecology; SCE 123 Ophthalmology; SCE 124 Optics; Ornithology; SCE 125 Orthopedics SCE 126 Otorhinolaryngology; SCE 129 Pathology; SCE 130 Pediatrics; SCE 131 Peripheral Vascular Disease; SCE 132 Pharmacology & Pharmacy; SCE 145 Psychology; SCE 146 Public, Environmental & Occupational Health; SCE 147 Radiology, Nuclear Medicine & Medical Imaging; SCE 152 Rheumatology; SCE 158 Surgery; SCE 162 Transplantation; SCE 164 Tropical Medicine; SCE 165 Urology & Nephrology; SCE 173 Oncology; SCE 157 Substance abuse
Public Administration (d=5) SSE 42, Public administration Psychology (d=6)
SSE 32, Psychology applied SSE 33 Psychology, Biological SSE 34, Psychology clinical SSE 35, Psychology developmental SSE 36, Psychology educational SSE 37, Psychology experimental SSE 38, Psychology, Mathematical; SSE 39, Psychology multidisciplinary SSE 41, Psychology social SCE 145, Psychology
Social and political Sciences (d=7) SSE 30 Political Science SSE 45, Social issues SSE 46, Social sciences, biochemical SSE 47, Social sciences, interdisciplinary SSE 48 Social sciences, mathematic meth. SSE 49, Social work SSE 50, Sociology SSE 25 International Relations
Linguistics (d=8) SSE 02 Applied Linguistics; SSE 55 Linguistics
Geography related studies (d=9) SSE 03 Area Studies; SSE 08 Demography; SSE 17 Geography SSE 52 Transportation; SSE 53 Urban Studies; SCE 164 Transportation Science & Technology
Communication (d=10) SSE 06 Communication;
Law (d=11) SSE 07 Criminology & Penology; Law SSE 26 Law
Economics (d=12) SSE09 Economics;
Environmental studies (d=13) SSE012 Environmental Studies; SCE65 Environmental Sciences
Ethics (d=14) SSE 14 Ethics;
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History (d= 16) SSE 20 History; His SSE 21 History & Philosophy of Science; His SSE 22 History of Social Sciences; His
Information Science & Library
Science (d=17)
SSE 24 Information Science & Library Science;
Planning & Development (d=18) SSE 29 Planning & Development;
Biology (d=19) SCE 15 Biochemical Research Methods; SCE 16 Biochemistry & Molecular Biology; SCE 17 Biodiversity Conservation; SCE 18 Biology; SCE 19 Biophysics; SCE 20 Biotechnology & Applied Microbiology; SCE 21 Cardiac & Cardiovascular Systems; SCE 22 Cell Biology; SCE 43 Developmental Biology; SCE 66 Evolutionary Biology; SCE 69 Forestry
SCE 87 Marine & Freshwater Biology; SCE 108 Microbiology; SEC 109 Microscopy; SCE 142 Plant Sciences; SCE 150 Reproductive Biology; SCE 161 Toxicology; SCE 167 Virology SCE 169 Zoology
SCE 172 Mathematical & Computational Biology; Chemistry (d=20) SCE 23 Chemistry, Analytical;
SCE 24 Chemistry, Applied; SCE 25 Chemistry, Inorganic & Nuclear; SCE 26 Chemistry, Medicinal; SCE 27 Chemistry, Multidisciplinary; SCE 28 Chemistry, Organic; SCE 29 Chemistry, Physical; SCE 46 Electrochemistry;
Engineering (d=21)
SCE 50 Engineering, Aerospace; SCE 51 Engineering, Biomedical; SCE 52 Engineering, Chemical; SCE 53 Engineering, Civil; SCE 54 Engineering, Electrical & Electronic; SCE 55 Engineering, Environmental; SCE 56 Engineering, Geological; SCE 57 Engineering, Industrial; SCE 58 Engineering, Manufacturing; SCE 59 Engineering, Marine; SCE 60 Engineering, Mechanical; SCE 61 Engineering, Multidisciplinary; SCE 62 Engineering, Ocean; SCE 63 Engineering, Petroleum;
Computer Science (d=22)
SCE 31 Computer Science, Artificial Intelligence; SCE 32 Computer Science, Cybernetics; SCE 33 Computer Science, Hardware & Architecture; SCE 34 Computer Science, Information Systems; SCE 35 Computer Science, Interdisciplinary Applications; SCE 36 Computer Science, Software Engineering; SCE 37 Computer Science, Theory & Methods; SCE 159 Telecommunications;
Materials Science (d=23)
SCE 88 Materials Science, Biomaterials; SCE 89 Materials Science, Ceramics; SCE 90 Materials Science, Characterization & Testing; SCE 91 Materials Science, Coatings & Films;
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SCE 92 Materials Science, Composites; SCE 93 Materials Science, Multidisciplinary; SCE 94 Materials Science, Paper & Wood; SCE 95 Materials Science, Textiles;
Physics (d=24)
SCE 133 Physics, Applied; SCE 134 Physics, Atomic, Molecular & Chemical; SCE 135 Physics, Condensed Matter; SCE 136 Physics, Fluids & Plasmas; SCE 137 Physics, Mathematical; SCE 138 Physics, Multidisciplinary; SCE 139 Physics, Nuclear; SCE 140 Physics, Particles & Fields
Agricultural (d=25)
SCE 02 Agricultural Economics & Policy; SCE 03 Agricultural Engineering; SCE 04 Agriculture, Dairy & Animal Science; SCE 05 Agriculture, Multidisciplinary SCE 06 Agriculture, Soil Science SCE 171 Soil Science;
Mathematics (d=26)
SCE 96 Mathematics; SCE 97 Mathematics, Applied; SCE 98 Mathematics, Interdisciplinary Applications;
Geology/Physical Geography (d=28)
SCE 74 Geology; SCE 86 Limnology; SCE 110 Mineralogy; SCE 111 Mining & Mineral Processing; SCE 121 Oceanography; SCE 149 Remote Sensing; SCE 168 Water Resources;
Astronomy & Astrophysics (d=29) SCE 12 Astronomy & Astrophysics
History & Philosophy of Science
(d=30)
SCE 79 History & Philosophy of Science
Multidisciplinary Sciences (d=31) SCE 112 Multidisciplinary Sciences
Industrial Relations & Labor (d=32) SSE 23 Industrial Relations & Labor?;
Miscellaneous (d=33) SCE 155 Sport Science
SCE 68 Food Science and Technology
Appendix C: Refined coding scheme Note: We code in a conservative way: an article is only coded along the nodes in the scheme when the authors explicitly mention these elements. Nodes used for coding within the articles ADVANTAGES
- data display - data management - ensure complete coding - facilitate teamwork
o measure intercoder reliability - flexibility
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o ease of context (ease to go back to context explicitly mentioned) - justification
o ascertain prevalence and substance of theoretical concept o negative/contrary cases (demonstrate search for negative instances/contrary cases) o prove rigour of analysis o prove validity
- leave audit trail - speed
AIM (overall aim by the researchers, not necessarily done with CAQDAS)
- Descriptive study - Theory development - Theory testing
ANALYSIS METHOD (analysis method by the researchers, not necessarily all with CAQDAS)
- Cognitive mapping - Counting and testing in stats (counting and testing meaning of the numbers using statistical
packages) - Grounded theory - Others
CAQDAS detail (Amount of detail provided in the paper about the use of CAQDAS)
- CAQDAS in appendix only - CAQDAS in discussion section only - CAQDAS in Research method section only - CAQDAS in results only - In footnote only - in the Analysis section only - for any combinations: we create a new, specific node
DEGREE OF ANALYSIS (here we indicate all possible aspects as indicated in the papers)
- Code and retrieve (called: use as electronic filing cabinet, Fielding & Lee) - Soft analysis
o Autocoding in CAQDAS o Creating categories (for further analysis…) o Frequency counts o memoing in CAQDAS o Query functions used
- Far-reaching analysis o Theory development
Investigating interrelationships (mapping out ideas in diagrams or conceptual networks: visual representation of links between concepts
o Theory testing Testing propositions
o Calculation of probabilities that word collocates with another o CAQDAS identifying semantic tonalities of passages of text
DISADVANTAGES (disadvantages experienced when using CAQDAS)
o Narrow analysis (Only reporting causal links representing the queries made) o Time spent (Exaggerated time spent on CAQDAS) o Too many categories (Ending up with too many categories/nodes)
INFORMATION (types of information used in CAQDAS)
- interviews (only if inserted in CAQDAS)
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- newspaper articles - field notes - other documents (only indicated if inserted in CAQDAS
Attributes of the cases to be included
- CAQDAS package used o NVivo o Nudist o Atlas/ti o TACT o WORDS o DICTION o Ethnograph o Any combinations need to be inserted separately in Nvivo
- Number of authors involved in Coding
o 1 o 2 o 3 or more o not indicated
- Sciencefield
o Accounting o Broader disciplines: see discipline numbers
- Year of publication
o 1997 … 2006 - Journal name (only for the accounting papers)
o AAAJ, AOS, CPA, JMAR, MAR Appendix D: ‘Accounting’ papers using CAQDAS Abernethy, M.A., Horne, M., Lillis, A.M., Malina, M.A., Selto, F.H., 2005. A Multi-Method Approach to Building Causal Performance Maps from Expert Knowledge. Management Accounting Research 16, 135-155. Anderson-Gough, F., C. Grey, Robson, K., 2001. Tests of time: organizational time-reckoning and the making of accountants in two multi-national accounting firms. Accounting, Organizations and Society, 26(2), 99-122. Anderson-Gough, F., Grey, C., Robson, K., 2005. "Helping them to forget..": the organizational embedding of gender relations in public audit firms. Accounting, Organizations and Society 30(5), 469- 490. Breton, G., Côté, L., 2006. Profit and the legitimacy of the Canadian banking industry. Accounting, Auditing & Accountability Journal 19(4), 512-539. Budding, G.T., 2004. Accountability, Uncertainty and Government Performance: Evidence on Dutch Municipalities. Management Accounting Research, 15(3), 285-304. Cuganesan S., C. Boedker, J. Guthrie, 2007. Enrolling discourse consumers to affect material intellectual capital practice. Accounting, Auditing & Accountability Journal, 20 (6), 883-911. Dambrin C., C. Lambert, S. Sponem, 2007. Control and change – Analysing the process of institutionalisation. Management Accounting Research, 18, 172-208. Dixon, R., Ritchie, J., Siwale, J., 2006. Microfinance: accountability from the grassroots. Accounting, Auditing & Accountability Journal 19(3), 3, 405-427
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Donada, C., Nogatchewsky, G., 2006. Vassal or lord buyers: How to exert management control in asymmetric interfirm transactional relationships? Management Accounting Research 17(3), 259-287. Durocher S., A. Fortin, L. Côté, 2007. Users’ participation in the accounting standard-setting process: A theory-building study. Accounting, Organizations and Society 32, 29-59. Empson L., 2004. Organizational identity change: managerial regulation and member identification in an accounting firm acquisition. Accounting, Organizations and Society 29(8), 759-781. Ezzamel M., K. Robson, P. Stapleton, C. McLean, 2007. Discourse and institutional change: ‘Giving accounts’ and accountability. Management Accounting Research 18, 150-171. Fogarty T.J., Rogers, R.K., 2005. Financial analysts' reports: an extended institutional theory evaluation. Accounting, Organizations and Society 30, 331-356. Irvine, H., Gaffikin, M., 2006. Getting in, getting on and getting out: reflections on a qualitative research project. Accounting, Auditing & Accountability Journal 19(1), 115-145. Lillis, A.M., 2002. Managing multiple dimensions of manufacturing performance - an exploratory study. Accounting, Organizations and Society, 27(6), 497-529. Malina, M.A., Selto, F.H., 2001. Communicating and Controlling Strategy: An Empirical Study of the Effectiveness of the Balanced Scorecard. Journal of Management Accounting Research 13, 47-90. Malina, M.A., Selto, F.H., 2004. Choice and Change of Measures in Performance Measurement Models. Management Accounting Research, 15, 441-469. Neu, D., Ocampo Gomez, E., Graham, C., Heincke, M., 2006. “Informing” technologies and the World Bank. Accounting, Organizations and Society 31(7), 635-662. Neu, D., E. Ocampo, 2007. Doing missionary work: the World Bank and the diffusion of financial practices. Critical Accounting Perspectives 18, 363-389. Rahaman A.S., J. Everett, D. Neu, 2007. Accounting and the movie to privatize water services in Africa. Accounting, Auditing & Accountability Journal 20(5), 637-670. Sian S., 2006. Inclusion, exclusion and control: the case of the Kenyan accounting professionalisation project. Accounting, Organizations and Society 31, 295-322. Smith, M., Taffler, R.J., 2000. The chairman's statement - A content analysis of discretionary narrative disclosures. Accounting, Auditing & Accountability Journal 13(5), 624-646. Sweeney, B., Pierce, B., 2004. Management control in audit firms – a qualitative examination. Accounting, Auditing & Accountability Journal 17(5), 779-812. Sweeney, B., Pierce, B., 2006. Good hours, bad hours and auditors’ defence mechanisms in audit firms. Accounting, Auditing & Accountability Journal 19(6), 858-892. Widener S.K., Selto F.H., 1999. Management control systems and the boundaries of the firm: why do firms outsource internal auditing activities? Journal of Management Accounting Research 11, 45-73 Willman, P., Fenton-O'Creevy, M., Nicholson, N., Soane, E., 2002. Traders, managers and loss aversion in investment banking: a field study. Accounting, Organizations and Society 27(1-2), 85-98. Appendix E: ‘Sociology’ papers using NUDIST/NVIVO and Atlas.ti till April 2005 Barry, C.A., Stevenson, F.A., Britten, N., Barber, N., Bradley, C.P., 2001. Giving voice to the lifeworld. More humane, more effective medical care? A qualitative study of doctor-patient communication in general practice. Social Science & Medicine 53(4), 487-505. Bryant, L.L., Corbett, K.K., Kutner, J.S., 2001. In their own words: a model of healthy aging. Social Science & Medicine 53(7), 927-941. DelVecchio Good, M.-J., Gadmer, N.M., Ruopp, P., Lakoma, M., Sullivan, A.M., Redinbaugh, E., Arnold, R.M., Block, S.D., 2004. Narrative nuances on good and bad deaths: internists' tales from high-technology work places. Social Science & Medicine 58(5), 939-953. Deschepper, R., Vander Stichele, R.H., Haaijer-Ruskamp, F.M., 2002. Cross-cultural differences in lay attitudes and utilisation of antibiotics in a Belgian and a Dutch city. Patient Education and Counseling 48(2), 161-169. Eilbert, K.W., Lafronza, V., 2005. Working together for community health--a model and case studies. Evaluation and Program Planning 28(2), 185-199.
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Fitzpatrick, J., 2000. Dialogue with David Fetterman. The American Journal of Evaluation 21(2), 242-259. Gooberman-Hill, R., Ayis, S., Ebrahim, S., 2003 Understanding long-standing illness among older people. Social Science & Medicine 56(12), 2555-2564. Hallowell, N., , Murton, F., 1998. The value of written summaries of genetic consultations. Patient Education and Counseling 35(1), 27-34. Hutchinson, S.L, Baldwin, C.K., Caldwell, L.L., 2003. Differentiating Parent Practices Related to Adolescent Behavior in the Free Time Context. Journal of Leisure Research 35(4), 396-422. Joffe, H., Haarhoff, G., 2002. Representations of far-flung illnesses: the case of Ebola in Britain. Social Science & Medicine 54(6), 955-969. Kagee, A., 2004. Present concerns of survivors of human rights violations in South Africa. Social Science & Medicine 59(3), 625-635. Kyle, G., Chick, G., 2002. The social nature of leisure involvement. Journal of Leisure Research 34(4), 426-448. Li, S., 2005. Doing criticism in 'symbiotic niceness': a study of palliative care nurses' talk. Social Science & Medicine 60(9), 1949-1959. Lowton, K., 2003. 'Double or quits': perceptions and management of organ transplantation by adults with cystic fibrosis. Social Science & Medicine 56(6), 1355-1367. Manderson, L., Markovic, M., Quinn, M., 2006. "Like roulette": Australian women's explanations of gynecological cancers. Social Science & Medicine 61(2), 323-332. Menkes, D.B., Davison, M.P., Costello, S.A., Jaye, C., 2005. Stereotactic radiosurgery: the patient's experience. Social Science & Medicine 60(11), 2561-2573. Miles, A., Curran, H.V., Pearce, S. Allan, L., 2005. Managing constraint: the experience of people with chronic pain. Social Science & Medicine 61(2), 431-441. Milligan, C., Gatrell, A., Bingley, A., 2004. 'Cultivating health': therapeutic landscapes and older people in northern England. Social Science & Medicine 58(9), 1781-1793. Molnar, B.E., Roberts, A.L., Browne, A., Gardener, H., Buka, S.L., 2005. What girls need: recommendations for preventing violence among urban girls in the US. Social Science & Medicine 60(10), 2191-2204. Moreira, T., 2005. Diversity in clinical guidelines: the role of repertoires of evaluation. Social Science & Medicine 60(9), 1975-1985. Pelto, P.J., 2002. Building social sciences and health research: A decade of technical assistance in South Asia. Human Organization 61(3), 189-209. Raskoff, S.A., Sundeen, R.A., 2001. Cultural diversity and high school community service: The relationships between ethnicity and students' perceptions. Nonprofit and Voluntary Sector Quarterly 30(4), 720-746. Rousseau, C.C., Rufagari, M.-C., Bagilishya, D., Measham, T., 2004. Remaking family life: strategies for re-establishing continuity among Congolese refugees during the family reunification process. Social Science & Medicine 59(5), 1095-1108. Sommerfield, J., Sanon, M., Kouyate, B.A., Sauerborn, R., 2002. Perceptions of risk, vulnerability, and disease prevention in rural Burkina Faso: Implications for community-based health care and insurance. Human Organization 61(2), 139-146. Thomas, C., Morris, S.M., Clark, D., 2004, Place of death: preferences among cancer patients and their carers. Social Science & Medicine 58(12), 2431-2444. Vanheule, S., Lievrouw, A., Verhaeghe, P., 2003. Burnout and intersubjectivity: A psychoanalytical study from a Lacanian perspective. Human Relations 56(3), 321-338. Vanheule, S., Verhaeghe, P., 2004. Powerlessness and impossibility in special education: A qualitative study on professional burnout from a Lacanian perspective. Human Relations 57(4), 497-519. Ware, N.C., Wyatt, M.A., Tugenberg, T., 2005. Adherence, stereotyping and unequal HIV treatment for active users of illegal drugs. Social Science & Medicine 61(3), 565-576. Waring, J.J., 2005. Beyond blame: cultural barriers to medical incident reporting. Social Science & Medicine 60(9), 1927-1935. Washer, P., 2004. Representations of SARS in the British newspapers. Social Science & Medicine 59(12), 2561-2571.