thematic analysis


  • Both coding reliability and code book approaches typically involve early theme development – with all or some themes developed prior to coding, often following some data familiarisation
    (reading and re-reading data to become intimately familiar with its contents).

  • The popularity of this paper exemplifies the growing interest in thematic analysis as a distinct method (although some have questioned whether it is a distinct method or simply
    a generic set of analytic procedures[11]).

  • Once themes have been developed the code book is created – this might involve some initial analysis of a portion of or all of the data.

  • [1] Phase 4: Reviewing themes[edit] This phase requires the researchers to check their initial themes against the coded data and the entire data-set – this is to ensure the
    analysis hasn’t drifted too far from the data and provides a compelling account of the data relevant to the research question.

  • This aspect of data coding is important because during this stage researchers should be attaching codes to the data to allow the researcher to think about the data in different

  • [24] For some thematic analysis proponents, including Braun and Clarke, themes are conceptualised as patterns of shared meaning across data items, underpinned or united by
    a central concept, which are important to the understanding of a phenomenon and are relevant to the research question.

  • The logging of ideas for future analysis can aid in getting thoughts and reflections written down and may serve as a reference for potential coding ideas as one progresses
    from one phase to the next in the thematic analysis process.

  • [1] Researchers conducting thematic analysis should attempt to go beyond surface meanings of the data to make sense of the data and tell a rich and compelling story about
    what the data means.

  • [45] Coding is a process of breaking data up through analytical ways and in order to produce questions about the data, providing temporary answers about relationships within
    and among the data.

  • At this point, researchers have a list of themes and begin to focus on broader patterns in the data, combining coded data with proposed themes.

  • [17] This form of analysis tends to be more interpretative because analysis is explicitly shaped and informed by pre-existing theory and concepts (ideally cited for transparency
    in the shared learning).

  • [13] Code book approaches like framework analysis,[5] template analysis[6] and matrix analysis[7] centre on the use of structured code books but – unlike coding reliability
    approaches – emphasise to a greater or lesser extent qualitative research values.

  • [3] For others (including most coding reliability and code book proponents), themes are simply summaries of information related to a particular topic or data domain; there
    is no requirement for shared meaning organised around a central concept, just a shared topic.

  • Deductive approaches can involve seeking to identify themes identified in other research in the data-set or using existing theory as a lens through which to organise, code
    and interpret the data.

  • [3] Topic summary themes are typically developed prior to data coding and often reflect data collection questions.

  • [45] Phase 3: Generating initial themes[edit] Searching for themes and considering what works and what does not work within themes enables the researcher to begin the analysis
    of potential codes.

  • Some coding reliability and code book proponents provide guidance for determining sample size in advance of data analysis – focusing on the concept of saturation or information
    redundancy (no new information, codes or themes are evident in the data).

  • [14] Throughout the coding process researchers should have detailed records of the development of each of their codes and potential themes.

  • Data complication serves as a means of providing new contexts for the way data is viewed and analyzed.

  • [18] Different approaches to thematic analysis Coding reliability[4][2] approaches have the longest history and are often little different from qualitative content analysis.

  • This systematic way of organizing and identifying meaningful parts of data as it relates to the research question is called coding.

  • [35] There are numerous critiques of the concept of data saturation – many argue it is embedded within a realist conception of fixed meaning and in a qualitative paradigm
    there is always potential for new understandings because of the researcher’s role in interpreting meaning.

  • [4] In some thematic analysis approaches coding follows theme development and is a deductive process of allocating data to pre-identified themes (this approach is common in
    coding reliability and code book approaches), in other approaches – notably Braun and Clarke’s reflexive approach – coding precedes theme development and themes are built from codes.

  • Coding as inclusively as possible is important – coding individual aspects of the data that may seem irrelevant can potentially be crucial later in the analysis process.

  • Such questions are generally asked throughout all cycles of the coding process and the data analysis.

  • The complication of data is used to expand on data to create new questions and interpretation of the data.

  • “[28] Methodological issues Reflexivity journals[edit] Given that qualitative work is inherently interpretive research, the positionings, values, and judgments of the researchers
    need to be explicitly acknowledged so they are taken into account in making sense of the final report and judging its quality.

  • Leading thematic analysis proponents, psychologists Virginia Braun and Victoria Clarke[3] distinguish between three main types of thematic analysis: coding reliability approaches
    (examples include the approaches developed by Richard Boyatzis[4] and Greg Guest and colleagues[2]), code book approaches (these includes approaches like framework analysis,[5] template analysis[6] and matrix analysis[7]) and reflexive approaches.

  • In this stage of data analysis the analyst must focus on the identification of a more simple way of organizing data.

  • Themes are typically evident across the data set, but a higher frequency does not necessarily mean that the theme is more important to understanding the data.

  • In approaches that make a clear distinction between codes and themes, the code is the label that is given to particular pieces of the data that contributes to a theme.

  • Other approaches to thematic analysis don’t make such a clear distinction between codes and themes – several texts recommend that researchers “code for themes”.

  • Description Thematic analysis is used in qualitative research and focuses on examining themes or patterns of meaning within data.

  • Connections between overlapping themes may serve as important sources of information and can alert researchers to the possibility of new patterns and issues in the data.

  • [1][13] After this stage, the researcher should feel familiar with the content of the data and should be able to start to identify overt patterns or repeating issues the data.

  • [13] Thematic analysis can be used to analyse most types of qualitative data including qualitative data collected from interviews, focus groups, surveys, solicited diaries,
    visual methods, observation and field research, action research, memory work, vignettes, story completion and secondary sources.

  • [1] Coding sets the stage for detailed analysis later by allowing the researcher to reorganize the data according to the ideas that have been obtained throughout the process.

  • [45] Coding can not be viewed as strictly data reduction, data complication can be used as a way to open up the data to examine further.

  • Sometimes deductive approaches are misunderstood as coding driven by a research question or the data collection questions.

  • In addition, changes made to themes and connections between themes can be discussed in the final report to assist the reader in understanding decisions that were made throughout
    the coding process.

  • Thematic analysis is sometimes claimed to be compatible with phenomenology in that it can focus on participants’ subjective experiences and sense-making;[2] there is a long
    tradition of using thematic analysis in phenomenological research.

  • [1] The procedures associated with other thematic analysis approaches are rather different.

  • [3] Reflexive approaches centre organic and flexible coding processes – there is no code book, coding can be undertaken by one researcher, if multiple researchers are involved
    in coding this is conceptualised as a collaborative process rather than one that should lead to consensus.

  • [14] Sample size considerations[edit] There is no straightforward answer to questions of sample size in thematic analysis; just as there is no straightforward answer to sample
    size in qualitative research more broadly (the classic answer is ‘it depends’ – on the scope of the study, the research question and topic, the method or methods of data collection, the richness of individual data items, the analytic approach[33]).

  • Shared meaning themes that are underpinned by a central concept or idea[22] cannot be developed prior to coding (because they are built from codes), so are the output of a
    thorough and systematic coding process.

  • [4] This means that the process of coding occurs without trying to fit the data into pre-existing theory or framework.

  • This approach allows the respondents to discuss the topic in their own words, free of constraints from fixed-response questions found in quantitative studies.

  • Data complication can be described as going beyond the data and asking questions about the data to generate frameworks and theories.

  • These approaches are a form of qualitative positivism or small q qualitative research,[19] which combine the use of qualitative data with data analysis processes and procedures
    based on the research values and assumptions of (quantitative) positivism – emphasising the importance of establishing coding reliability and viewing researcher subjectivity or ‘bias’ as a potential threat to coding reliability that must be
    contained and ‘controlled for’ to avoiding confounding the ‘results’ (with the presence and active influence of the researcher).

  • Thematic analysis is best thought of as an umbrella term for a variety of different approaches, rather than a singular method.

  • In other approaches, prior to reading the data, researchers may create a “start list” of potential codes.

  • [2] Phase 2: Generating codes[edit] The second step in reflexive thematic analysis is tagging items of interest in the data with a label (a few words or a short phrase).

  • In this phase, it is important to begin by examining how codes combine to form over-reaching themes in the data.

  • Coding involves allocating data to the pre-determined themes using the code book as a guide.

  • [44] As Braun and Clarke’s approach is intended to focus on the data and not the researcher’s prior conceptions they only recommend developing codes prior to familiarisation
    in deductive approaches where coding is guided by pre-existing theory.

  • However, Braun and Clarke urge researchers to look beyond a sole focus on description and summary and engage interpretatively with data – exploring both overt (semantic) and
    implicit (latent) meaning.

  • [31] The reflexivity process can be described as the researcher reflecting on and documenting how their values, positionings, choices and research practices influenced and
    shaped the study and the final analysis of the data.

  • Gender, Support) or titles like ‘Benefits of…’, ‘Barriers to…’ signalling the focus on summarising everything participants said, or the main points raised, in relation
    to a particular topic or data domain.

  • As the name suggests they prioritise the measurement of coding reliability through the use of structured and fixed code books, the use of multiple coders who work independently
    to apply the code book to the data, the measurement of inter-rater reliability or inter-coder agreement (typically using Cohen’s Kappa) and the determination of final coding through consensus or agreement between coders.

  • [45] Tesch defined data complication as the process of reconceptualizing the data giving new contexts for the data segments.

  • Braun and Clarke are critical of this language because they argue it positions themes as entities that exist fully formed in data – the researcher is simply a passive witness
    to the themes ’emerging’ from the data.

  • [45] Reduction of codes is initiated by assigning tags or labels to the data set based on the research question(s).

  • [1] Thematic analysis is often used in mixed-method designs – the theoretical flexibility of TA makes it a more straightforward choice than approaches with specific embedded
    theoretical assumptions.

  • Reflexivity journals are somewhat similar to the use of analytic memos or memo writing in grounded theory, which can be useful for reflecting on the developing analysis and
    potential patterns, themes and concepts.

  • Reflexivity journal entries for new codes serve as a reference point to the participant and their data section, reminding the researcher to understand why and where they will
    include these codes in the final analysis.

  • This description of Braun and Clarke’s six phase process also includes some discussion of the contrasting insights provided by other thematic analysis proponents.

  • [2] Throughout the coding process, full and equal attention needs to be paid to each data item because it will help in the identification of otherwise unnoticed repeated patterns.

  • [14] conclusion of this phase should yield many candidate themes collected throughout the data process.


Works Cited

[‘Braun, Virginia; Clarke, Victoria (2006). “Using thematic analysis in psychology”. Qualitative Research in Psychology. 3 (2): 77–101. doi:10.1191/1478088706qp063oa. hdl:10125/42031. S2CID 10075179.
• ^ Jump up to:a b c d e f g h i j k l m n o p q
r s t Guest, Greg; MacQueen, Kathleen; Namey, Emily (2012). Applied thematic analysis. Thousand Oaks, California: SAGE Publications. p. 11.
• ^ Jump up to:a b c d e f Braun, Virginia; Clarke, Victoria (2019). “Thematic Analysis”. Handbook of Research
Methods in Health Social Sciences. Hoboken, New Jersey: Springer. pp. 843–860. doi:10.1007/978-981-10-5251-4_103. ISBN 978-981-10-5250-7. S2CID 239210796.
• ^ Jump up to:a b c d e f Boyatzis, Richard (1998). Transforming qualitative information:
Thematic analysis and code development. Thousand Oaks, CA: Sage.
• ^ Jump up to:a b Gale, Nicola; Heath, Gemma (2013). “Using the framework method for the analysis of qualitative data in multi-disciplinary health research”. BMC Medical Research
Methodology. 13: 117. doi:10.1186/1471-2288-13-117. PMC 3848812. PMID 24047204.
• ^ Jump up to:a b King, Nigel; Brooks, Joanna (2016). Template analysis for business and management students. Sage.
• ^ Jump up to:a b Groenland, Edward (2014). “Employing
the Matrix Method as a Tool for the Analysis of Qualitative Research Data in the Business Domain”. SSRN. doi:10.2139/ssrn.2495330. S2CID 59826786. SSRN 2495330.
• ^ Langdridge, Darren (2004). Introduction to research methods and data analysis in
psychology. The Open University.
• ^ Hayes, Nicky (2000). Doing psychological research. Open University Press.
• ^ Braun, Virginia; Clarke, Victoria (2019). “Reflecting on reflexive thematic analysis”. Qualitative Research in Sport, Exercise and
Health. 11 (4): 589–597. doi:10.1080/2159676x.2019.1628806. S2CID 197748828.
• ^ Willig, Carla (2013). Introducing qualitative research in psychology. Open University Press.
• ^ Daly, Jeanne; Kellehear, Allan; Gliksman, Michael (1997). The public
health researcher: A methodological approach. Melbourne, Australia: Oxford University Press. pp. 611–618. ISBN 978-0195540758.
• ^ Jump up to:a b c d e f g Braun, Virginia; Clarke, Victoria (2013). Successful qualitative research: A practical guide
for beginners. Sage.
• ^ Jump up to:a b c d e f g h Saldana, Johnny (2009). The Coding Manual for Qualitative Researchers. Thousand Oaks, California: Sage.
• ^ Dapkus, Marilyn (1985). “A thematic analysis of the experience of time”. Journal of
Personality and Social Psychology. 49 (2): 408–419. doi:10.1037/0022-3514.49.2.408. PMID 4032226.
• ^ Clarke, Victoria; Braun, Virginia (2014). “Thematic Analysis”. Encyclopedia of Critical Psychology. Springer. pp. 1947–1952. doi:10.1007/978-1-4614-5583-7_311.
ISBN 978-1-4614-5582-0.
• ^ Crabtree, B (1999). Doing Qualitative Research. Newbury Park, CA: Sage.
• ^ Huang, H., Jefferson, E. R., Gotink, M., Sinclair, C., Mercer, S. W., & Guthrie, B. (2021). Collaborative improvement in Scottish GP clusters
after the Quality and Outcomes Framework: a qualitative study. British Journal of General Practice, 71(710), e719-e727.
• ^ Kidder, Louise; Fine, Michelle (1987). “Qualitative and quantitative methods: When stories converge”. New Directions for
Program Evaluation. 1987 (Fall) (35): 57–75. doi:10.1002/ev.1459.
• ^ Morse, Janice (1997). “”Perfectly Healthy, but Dead”: The Myth of Inter-Rater Reliability”. Qualitative Health Research. 7 (4): 445–447. doi:10.1177/104973239700700401.
• ^
Yardley, Lucy (2008). “Demonstrating validity in qualitative psychology”. Qualitative Psychology: A Practical Guide to Research Methods. Sage: 235–251.
• ^ Jump up to:a b Braun, Virginia; Clarke, Victoria (2014). “How to use thematic analysis with
interview data”. The Counselling and Psychotherapy Research Handbook: 183–197.
• ^ Terry, Gareth; Hayfield, Nikki; Clarke, Victoria; Braun, Virginia (2017). “Thematic analysis”. The Sage Handbook of Qualitative Research in Psychology: 17–36. doi:10.4135/9781526405555.
ISBN 9781473925212.
• ^ DeSantis, Lydia; Ugarriza, Doris (2000). “The concept of theme as used in qualitative nursing research”. Western Journal of Nursing Research. 22 (3): 351–372. doi:10.1177/019394590002200308. PMID 10804897. S2CID 37545647.
• ^
Clarke, Victoria; Braun, Virginia (2018). “Using thematic analysis in counselling and psychotherapy research: A critical reflection”. Counselling and Psychotherapy Research. 18 (2): 107–110. doi:10.1002/capr.12165.
• ^ Connelly, Lynne; Peltzer,
Jill (2016). “Underdeveloped Themes in Qualitative Research: Relationship With Interviews and Analysis”. Clinical Nurse Specialist. 30 (1): 52–57. doi:10.1097/nur.0000000000000173. PMID 26626748. S2CID 5942773.
• ^ Sandelowski; Leeman, Jennifer
(2012). “Writing using qualitative health research findings”. Qualitative Health Research. 22 (10): 1404–1413. doi:10.1177/1049732312450368. PMID 22745362. S2CID 26196750.
• ^ Jump up to:a b Saldana, Johnny (2009). The Coding Manual for Qualitative
Researchers. Thousand Oaks, California: Sage. p. 13.
• ^ Creswell, John (1994). Research Design: Qualitative & Quantitative Approaches. Thousand Oaks, CA: Sage Publications, Inc. pp. 147.
• ^ Locke, L.F. (1987). Proposals that work: A guide for
planning dissertations and grant proposals. Newbury Park, CA: Sage Publications, Inc.
• ^ Creswell, John (2007). Qualitative Inquiry & Research Design: Choosing Among Five Approaches. Thousand Oaks, CA: Sage Publications, Inc. pp. 178–180.
• ^
Lincoln; Guba (1995). “Criteria For Rigor in Qualitative research”. {{cite journal}}: Cite journal requires |journal= (help)
• ^ Malterud, Kirsti (2016). “Sample Size in Qualitative Interview Studies: Guided by Information Power”. Qualitative Health
Research. 26 (13): 1753–1760. doi:10.1177/1049732315617444. PMID 26613970. S2CID 34180494.
• ^ Guest, Greg; Bunce, Arwen; Johnson, Laura (2006). “How Many Interviews Are Enough?: An Experiment with Data Saturation and Variability”. Field Methods.
18 (1): 59–82. doi:10.1177/1525822×05279903. S2CID 62237589.
• ^ Hennink, Monique; Kaiser, Bonnie (2016). “Code Saturation Versus Meaning Saturation: How Many Interviews Are Enough?”. Qualitative Health Research. 27 (4): 591–608. doi:10.1177/1049732316665344.
PMC 9359070. PMID 27670770. S2CID 4904155.
• ^ Low, Jacqueline (2019). “A Pragmatic Definition of the Concept of Theoretical Saturation”. Sociological Focus. 52 (2): 131–139. doi:10.1080/00380237.2018.1544514. S2CID 149641663.
• ^ Fugard AJ, Potts
HW (10 February 2015). “Supporting thinking on sample sizes for thematic analyses: A quantitative tool”. International Journal of Social Research Methodology. 18 (6): 669–684. doi:10.1080/13645579.2015.1005453.
• ^ Lowe, Andrew; Norris, Anthony
C.; Farris, A. Jane; Babbage, Duncan R. (2018). “Quantifying Thematic Saturation in Qualitative Data Analysis”. Field Methods. 30 (3): 191–207. doi:10.1177/1525822X17749386. ISSN 1525-822X. S2CID 148824883.
• ^ Braun, Virginia; Clarke, Victoria
(2016). “(Mis)conceptualising themes, thematic analysis, and other problems with Fugard and Potts’ (2015) sample-size tool for thematic analysis” (PDF). International Journal of Social Research Methodology. 19 (6): 739–743. doi:10.1080/13645579.2016.1195588.
S2CID 148370177.
• ^ Hammersley, Martyn (2015). “Sampling and thematic analysis: a response to Fugard and Potts”. International Journal of Social Research Methodology. 18 (6): 687–688. doi:10.1080/13645579.2015.1005456. S2CID 143933992.
• ^ Byrne,
David (2015). “Response to Fugard and Potts: supporting thinking on sample sizes for thematic analyses: a quantitative tool”. International Journal of Social Research Methodology. 16 (6): 689–691. doi:10.1080/13645579.2015.1005455. S2CID 144817485.
• ^
Emmel, Nick (2015). “Themes, variables, and the limits to calculating sample size in qualitative research: a response to Fugard and Potts” (PDF). International Journal of Social Research Methodology. 18 (6): 685–686. doi:10.1080/13645579.2015.1005457.
S2CID 55615136.
• ^ Braun, Virginia; Clarke, Victoria (2012). “Thematic analysis”. APA Handbook of Research Methods in Psychology. Vol. 2. pp. 57–71. doi:10.1037/13620-004. ISBN 978-1-4338-1005-3.
• ^ Jump up to:a b c Miles, M.B. (1994). Qualitative
data analysis: An expanded sourcebook. Thousand Oaks, California: Sage. ISBN 9780803955400.
• ^ Jump up to:a b c d e f g h i j k l Coffey, Amanda; Atkinson, Paul (1996). Making Sense of Qualitative Data. Sage. p. 30.
• ^ Clarke, Victoria; Braun,
Virginia (2016). “Thematic analysis”. Analysing Qualitative Data in Psychology. Sage: 84–103.
Photo credit:’]