Pinning down what interpretative analysis actually entails

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It is difficult to specify exactly what interpretative
analysis actually entails, particularly
as the specifics of it will vary from
study to study. As a first step, we recommend
looking at published examples of
thematic analysis, particularly of the specific
version you are planning to use (this is
made somewhat more difficult in that thematic
analysis is often not a named method,
but you can find examples, eg, Ellis and
Kitzinger, 2002; Kitzinger and Willmott,
2002; Toerien and Wilkinson, 2004). In
order to provide a sense of the sorts of
questions you should be asking of your data,
and the sorts of analytic claims you should
be seeking to make, we will discuss a
particularly good example of an inductive
thematic analysis, which emphasizes understanding
men’s experiences in relation to
the broader social context (see Frith and
Gleeson, 2004).
Frith and Gleeson (2004) aim to explore
how men’s feelings about their
bodies influence their clothing practices,
and they use data gathered in qualitative
questionnaires from 75 men to answer
this question. They report four themes:
practicality of clothing choices; lack of
concern about appearance; use of clothing
to conceal or reveal the body; use of
clothing to fit cultural ideals. Each theme
is clearly linked back to the overall
research question, but each is distinct.
They provide a clear sense of the scope
and diversity of each theme, using a
combination of analyst narrative and
illustrative data extracts. Where relevant,
they broaden their analysis out, moving
from a descriptive to an interpretative
level (often relating their claims to existing
literature). For example, in ‘men
value practicality’, they make sense of
men’s accounts in relation to gender
norms and stereotypes, linking the accounts
individual men provided to the
expectations that men / as members of
society / face. What they do, as analysts,
Using thematic analysis in psychology 93
is relate the patterns of meaning in men’s
responses to an academic analysis of how
gender operates. In so doing, they demonstrate
the dual position that analysts
need to take: as both cultural members
and cultural commentators. Their ‘discussion’
section makes broader analytic
statements about the overall story that
the themes tell us about men’s relationship
with clothing. This story reveals
that men ‘deliberately and strategically
use clothing to manipulate their appearance
to meet cultural ideals of masculinity’
(Frith and Gleeson, 2004: 45), in a
way more traditionally associated with
women. This analysis makes an important
contribution in that it challenges
perceived wisdom about clothing/appearance
and masculinity.
As this example demonstrates, your analytic
claims need to be grounded in, but go
beyond, the ‘surface’ of the data, even for a
‘semantic’ level analysis. The sort of questions
you need to be asking, towards the end
phases of your analysis, include: ‘What does
this theme mean?’ ‘What are the assumptions
underpinning it?’ ‘What are the implications
of this theme?’ ‘What conditions
are likely to have given rise to it?’ ‘Why
do people talk about this thing in this
particular way (as opposed to other
ways)?’ and ‘What is the overall story the
different themes reveal about the topic?’.
These sorts of questions should guide the
analysis once you have a clear sense of your
thematic map.
Potential pitfalls to avoid when doing
thematic analysis
Thematic analysis is a relatively straightforward
form of qualitative analysis, which
does not require the same detailed theoretical
and technical knowledge that approaches
such as DA or CA do. It is
relatively easy to conduct a good thematic
analysis on qualitative data, even when you
are still learning qualitative techniques.
However, there are a number of things that
can result in a poor analysis. In this section
we identify these potential pitfalls, in the
hope that they can be avoided.
The first of these is a failure to actually
analyse the data at all! Thematic analysis is
not just a collection of extracts strung
together with little or no analytic narrative.
Nor is it a selection of extracts with analytic
comment that simply or primarily paraphrases
their content. The extracts in thematic
analysis are illustrative of the analytic
points the researcher makes about the data,
and should be used to illustrate/support an
analysis that goes beyond their specific
content, to make sense of the data, and tell
the reader what it does or might mean / as
discussed above. A second, associated pitfall
is the using of the data collection
questions (such as from an interview schedule)
as the ‘themes’ that are reported. In
such a case, no analytic work has been
carried out to identify themes across the
entire data set, or make sense of the patterning
of responses.
The third is a weak or unconvincing
analysis, where the themes do not appear
to work, where there is too much overlap
between themes, or where the themes are
not internally coherent and consistent. All
aspects of the theme should cohere around a
central idea or concept. This pitfall has
occurred if, depending on what the analysis
is trying to do, it fails adequately to capture
the majority of the data, or fails to provide a
rich description/interpretation of one or
more aspects of the data. A weak or un-
94 V Braun and V Clarke
convincing analysis can also stem from a
failure to provide adequate examples from
the data / for example, only one or two
extracts for a theme. This point is essentially
about the rhetorics of presentation,
and the need for the analysis to be convincing
to someone who has not read the entire
data set: ‘The ‘‘analysis’’ of the material. . . is
a deliberate and self-consciously artful creation
by the researcher, and must be constructed
to persuade the reader of the
plausibility of an argument’ (Foster and
Parker, 1995: 204). In so doing, one avoids
(the appearance of) what Bryman (1988) has
referred to as ‘anecdotalism’ in qualitative
research / where one or a few instances of a
phenomenon are reified into a pattern or
theme, when it or they are actually idiosyncratic.
This is not to say that a few instances
cannot be of interest, or revealing; but it is
important not to misrepresent them as an
overarching theme.
The fourth pitfall is a mismatch between
the data and the analytic claims that are
made about it. In such an (unfounded)
analysis, the claims cannot be supported
by the data, or, in the worst case, the data
extracts presented suggest another analysis
or even contradict the claims. The researcher
needs to make sure that their
interpretations and analytic points are consistent
with the data extracts. A weak
analysis does not appear to consider other
obvious alternative readings of the data, or
fails to consider variation (and even contradiction)
in the account that is produced. A
pattern in data is rarely, if ever, going to be
100% complete and non-contradicted, so an
analysis which suggests that it is, without a
thorough explanation, is open to suspicion.
It is important to pick compelling examples
to demonstrate the themes, so give this
considerable thought.
The fifth involves a mismatch between
theory and analytic claims, or between the
research questions and the form of thematic
analysis used. A good thematic analysis
needs to make sure that the interpretations
of the data are consistent with the theoretical
framework. So, for instance, if you are working
within an experiential framework, you
would typically not make claims about the
social construction of the research topic, and
if you were doing constructionist thematic
analysis, you would not treat people’s talk
of experience as a transparent window on
their world. Finally, even a good and interesting
analysis which fails to spell out
its theoretical assumptions, or clarify how it
was undertaken, and for what purpose, is
lacking crucial information (Holloway and
Todres, 2003), and thus fails in one aspect.
What makes good thematic analysis?
One of the criticisms of qualitative research
from those outside the field is the perception
that ‘anything goes’. For instance, this
sentiment is echoed in the first sentence of
Laubschagne’s (2003) abstract: ‘For many
scientists used to doing quantitative studies
the whole concept of qualitative research is
unclear, almost foreign, or ‘‘airy fairy’’ / not
‘‘real’’ research.’ However, although ‘qualitative’
research cannot be subjected to the
same criteria as ‘quantitative’ approaches, it
does provide methods of analysis that
should be applied rigorously to the data.
Furthermore, criteria for conducting good
qualitative research / both data collection
and analysis / do exist (eg, Elliott et al.,
1999; Parker, 2004; Seale, 1999; Silverman,
2000; Yardley, 2000). The British Psychological
Society offers relatively succinct online
guidelines for assessing quality in qualitative
research (see
Using thematic analysis in psychology 95
cfm). ‘Criteria’ for assessing qualitative
research is a not uncontroversial
topic, with concerns raised about rigid
criteria limiting freedom and stifling methodological
development (Elliott et al., 1999;
Parker, 2004; Reicher, 2000). Reicher (2000)
takes the critique further, by asking whether
the incredibly diverse range of qualitative
approaches can and should be subject to
the same criteria.
Bracketing these critiques off, the issues
raised in many general qualitative research
assessment criteria can be more or less
applied to thematic forms of analysis. As
thematic analysis is a flexible method, you
also need to be clear and explicit about what
you are doing, and what you say you are
doing needs to match up with what you
actually do. In this sense, the theory and
method need to be applied rigorously, and
‘rigour lies in devising a systematic method
whose assumptions are congruent with the
way one conceptualizes the subject matter’
(Reicher and Taylor, 2005: 549). A concise
checklist of criteria to consider when determining
whether you have generated a good
thematic analysis is provided in Table 2.
So what does thematic analysis offer
We now end this paper with some brief
comments on the advantages and disadvantages
of thematic analysis. As we have
shown throughout this paper, thematic analysis
is not a complex method. Indeed, as
you can see from Table 3, its advantages are
many. However, it is not without some
disadvantages, which we will now briefly
consider. Many of the disadvantages depend
more on poorly conducted analyses
or inappropriate research questions than on

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