Thematic analysis : a practical guide to understanding and doing / Virginia Braun, Victoria Clarke.

Enhanced descriptions from Syndetics:

**Winner of the 2022 British Psychological Society Book Award - Textbook Category**Developed and adapted by the authors of this book, thematic analysis (TA) is one of the most popular qualitative data analytic techniques in psychology and the social and health sciences.Building on the success of Braun & Clarke′s 2006 paper first outlining their approach - which has over 100,000 citations on Google Scholar - this book is the definitive guide to TA, covering:- Contextualisation of TA- Developing themes- Writing TA reports- Reflexive TAIt addresses the common questions surrounding TA as well as developments in the field, offering a highly accessible and practical discussion of doing TA situated within a clear understanding of the wider terrain of qualitative research.Virginia Braun is a Professor in the School of Psychology at The University of Auckland, Aotearoa New Zealand.Victoria Clarke is an Associate Professor in Qualitative and Critical Psychology in the Department of Social Sciences at the University of the West of England (UWE), Bristol.

Table of contents provided by Syndetics

• Before the Adventure... (p. xvii)
• About the authors and contributors (p. xix)
• Acknowledgements (p. xxiii)
• Scene setting: What Thematic analysis: A practical guide offers you, and how to navigate your way through it (p. xxv)
• Chapter overview (p. xxv)
• Setting the scene for Thematic analysis: A practical guide (p. xxvi)
• Baking, adventures and maps: Is this a recipe book, a guidebook, or what? (p. xxvi)
• Navigating language and imagining the reader (p. xxvii)
• This is our mapping... (p. xxviii)
• Learning through doing: A practice-first approach to learning thematic analysis (p. xxix)
• Who is the book for? (p. xxx)
• A book of two parts (p. xxx)
• Mapped adventure pathways: Navigating your way through the book (p. xxxi)
• Helpful things to support your adventure: The pedagogical features (p. xxxii)
• The companion website: An abundance of teaching and learning resources (p. xxxiii)
• Section I Venturing Forth! Doing Reflexive Thematic Analysis (p. 1)
• 1 It's almost time to depart: Getting ready for your thematic analysis adventure (p. 3)
• Chapter One overview (p. 3)
• Let us introduce you to thematic analysis (p. 4)
• What is reflexive TA? (p. 5)
• Table 1.1 Overview of some key differences between qualitative and quantitative research paradigms (p. 6)
• Can we provide a simple overview of reflexive TA? (p. 6)
• A qualitative sensibility for reflexive TA (p. 7)
• Box 1.1 Ten core assumptions of reflexive TA (p. 8)
• But wait, there's more: Variation within reflexive TA (p. 9)
• Table 1.2 The variations of reflexive TA (p. 10)
• Reflexive TA offers guidelines, not rules, but a clear process (p. 10)
• Mentally preparing yourself to tackle your TA journey: Becoming comfortable with uncertainty and discomfort (p. 11)
• Subjectivity is at the heart of reflexive TA practice (p. 12)
• Reflexivity: The most important companion for your adventure (p. 13)
• Doing reflexivity for reflexive TA (p. 14)
• Box 1.2 Your values and politics in qualitative research (p. 14)
• The time to start reflexivity is ... Now (p. 15)
• Activity pause: A task to get reflexivity started... (p. 16)
• Reflective and reflexive journals (p. 19)
• Box 1.3 What might reflexive journal entries look like? (p. 20)
• Chapter summary (p. 22)
• Want to learn more about...? (p. 23)
• Activities for student readers (p. 23)
• Before analysis: A brief design interlude (p. 25)
• Getting into design thinking... A guided activity (p. 29)
• Some readings to take you further into design thinking (p. 30)
• 2 Taking an initial lay off the land: Introducing our worked example dataset and doing familiarisation (p. 33)
• Chapter Two overview (p. 33)
• Today's the day! (p. 34)
• The process of reflexive TA (p. 34)
• Box 2.1 Introducing six phases of reflexive thematic analysis (p. 35)
• Introducing and contextualising our worked example dataset (p. 37)
• Researcher reflection - Box 2.2: Situating myself in relation to these data (Ginny) (p. 38)
• Researcher reflection - Box 2.3: Situating myself in relation to these data (Victoria) (p. 39)
• Table 2.1 Anonymised but otherwise unedited comments from Seven Sharp Facebook post about "being childfree" (p. 40)
• What's my purpose here? Settling on a research question (p. 41)
• Familiarisation (Phase one) (p. 42)
• Activity pause: Familiarisation (p. 45)
• Meaning, the dataset and the analytic process: A brief note on language (p. 45)
• Note-making for familiarisation (p. 45)
• Figure 2.1 Familiarisation Doodle for participant 'Franz' (p. 46)
• Figure 2.2 Familiarisation Doodle for participant 'Frank' (p. 47)
• Box 2.4 Ginny's overall dataset familiarisation notes (p. 48)
• Chapter summary (p. 49)
• Want to learn more about...? (p. 49)
• Activities for student readers (p. 50)
• 3 Exploring this world in detail: Doing coding (p. 51)
• Chapter Three overview (p. 51)
• Preparing for coding (p. 52)
• Box 3.1 Coding, codes and code labels in reflexive TA - a quick guide (p. 53)
• Coding is a systematic process (p. 53)
• Coding is organic, evolving and subjective (p. 54)
• Inductive and deductive orientations to data coding (p. 55)
• Semantic to latent coding (p. 57)
• Table 3.1 Dispelling some misconceptions about semantic and latent coding (p. 58)
• General guidelines for codes and code labels in reflexive TA (p. 58)
• Doing coding (Phase two) (p. 59)
• Table 3.2 Some general guidelines for developing code labels (p. 60)
• Activity pause: Before coding (p. 60)
• Box 3.2 A selection of six extracts from childfree dataset (p. 61)
• Table 3.3 A selection of childfree comments data with Code labels (p. 63)
• Actually wrangling data and codes: Technologies of coding (p. 65)
• Box 3.3 Is using QDAS better than coding in other ways? (p. 66)
• Researcher reflection - Box 3.4: Thematic analysis and QDAS (p. 67)
• Researcher reflection - Box 3.5: On Using NVivo (p. 68)
• Evolving your coding (p. 69)
• Box 3.6 Codes as building blocks for analysis (p. 69)
• Refining your coding through multiple rounds (p. 70)
• Can I stop coding yet? (p. 71)
• Chapter summary (p. 72)
• Want to learn more about... (p. 72)
• Activities for student readers (p. 73)
• 4 Finding, losing, then finding your way again: Developing your themes (p. 75)
• Chapter Four overview (p. 75)
• Understanding the key concept: What is this thing called a theme? (p. 76)
• In reflexive TA, a topic summary is not a theme (p. 77)
• In reflexive TA, a theme captures shared meaning, united by a central organising concept (p. 77)
• Generating initial themes (Phase three) (p. 78)
• Developing initial themes 2 from your codes (p. 79)
• Figure 4.1 Coding and initial theme development with a cup of coffee (p. 80)
• Table 4.1 A selection of code labels and collated data extracts (p. 82)
• Using visual mapping for theme generation, development and review (p. 85)
• Figure 4.2 An initial mapping of patterns across childfree dataset (p. 86)
• Box 4.1 Theme levels in reflexive TA (p. 87)
• Five key things to keep in mind in the early stages of theme development (p. 88)
• Figure 4.3a & 4.3b: A dandelion head - fully connected seeds (4.3a) and partially dispersed seeds (4.3b) (p. 90)
• Box 4.2 How many themes? Some guiding considerations for theme development and review (p. 91)
• I quite like it here, should 1 stay longer? Tackling time management in (initial) theme development (p. 92)
• I'm struggling a bit, to be honest: Managing anxiety in the TA process (p. 92)
• Researcher reflection - Box 4.3: Facing the battle of anxiety and OCD when undertaking TA for the first time (p. 93)
• Researcher reflection - Box 4.4: Doing TA when you've got ADHD and anxiety: Reflections and strategies (p. 95)
• Developing and reviewing themes 10 (Phase four) (p. 97)
• Figure 4.4 "Data says no" (p. 98)
• Theme development and revision with coded extracts (p. 98)
• Figure 4.5 Theme development as wrestling a sea-monster? (p. 100)
• Theme development and revision with the fall dataset (p. 100)
• Box 4.5 Can my analysis be based on part of the dataset? (p. 101)
• What's the point of this part of my adventure? (p. 102)
• Figure 4.6 Refined thematic map for 'gains and losses' analysis (p. 103)
• Figure 4.7 Refined (finalised) thematic map for 'choice matters' analysis (p. 104)
• Okay so how would a topic summary be different from a shared meaning theme? (p. 104)
• Box 4.6 Illustrative 'topic summary': Reasons for being childfree (p. 105)
• But what about contradiction? (p. 107)
• Precision matters: Refining, defining and naming themes (Phase five) (p. 108)
• Box 4.7 The 'contradictory' theme Good and Bad Parents [extract] (p. 109)
• Box 4.8 Definition of the theme 'deficient personhood' (p. 111)
• Naming themes (p. 111)
• Box 4.9 Naming themes related to 'choice' in the childfree dataset (p. 113)
• Chapter summary (p. 115)
• Want to learn more about...? (p. 115)
• Activities for student readers (p. 116)
• 5 Arriving home and telling a story about your adventure: Writing your thematic analysis report (p. 117)
• Chapter Five overview (p. 117)
• Writing matters for analysis (Phase six) (p. 118)
• Setting the scene of your story (the introduction or literature review) (p. 119)
• Describing how you approached your adventure (the method/ology section) (p. 121)
• Explaining your choice of TA and what it offers (p. 122)
• Table 5.1 Is my rationale for TA strong enough? (p. 123)
• Table 5.2 Examples of rationales for (reflexive) TA from published research (p. 124)
• Describing what you actually did during analysis (p. 124)
• Box 5.1 Should I explain why I used TA and not a similar method? (p. 125)
• Box 5.2 An example of a student analysis process write-up (p. 126)
• Telling your analytic story (the results and discussion section) (p. 128)
• Box 5.3 How we'd briefly write the analysis part of a methodology section, related to the overarching theme around 'choice' (p. 129)
• Introducing the analysis (p. 129)
• Table 5.3 Example of a theme summary table (p. 130)
• Structuring the analysis section (p. 131)
• Box 5.4 Writing separate results and discussion sections (p. 132)
• Selecting data extracts (p. 133)
• Data extracts and your analytic narrative (p. 135)
• Box 5.5 Illustrative and analytic treatment of data extracts in reporting a theme (p. 136)
• Traps to easily avoid when reporting your analysis in reflexive TA (p. 138)
• Box 5.6 Don't try this at home - paraphrasing your data (p. 139)
• Is 'thick description' something I should be aiming for? (p. 140)
• The flow of the story (p. 140)
• Should I use numbers to report theme 'frequency'? (p. 141)
• Should I claim generalisability in reporting my TA? (p. 142)
• Table 5.4 Different types of qualitative generalisability (p. 144)
• Drawing conclusions (p. 146)
• Reflection and evaluation in your write-up (p. 148)
• Telling your story well: The value of the edit (p. 149)
• Chapter summary (p. 149)
• Want to learn more about...? (p. 150)
• Activities for student readers (p. 151)
• Section II Going Deeper for Tip-Top Reflexive Thematic Analysis: Theory, Interpretation, and Quality Matters (p. 153)
• 6 A not-so-scary theory chapter: Conceptually locating reflexive thematic analysis (p. 155)
• Chapter Six overview (p. 155)
• There's no such thing as atheoretical TA! (p. 157)
• What sorts of theory are we discussing? (p. 157)
• Key basic starting points for TA and theory (p. 158)
• The diversity of qualitative research: Revisiting some important conceptual divisions (p. 158)
• Figure 6.1 It's all connected: Qualitative orientation, theory, questions and methods (p. 159)
• Researcher reflection - Box 6.1: An example of experiential TA: African Caribbean women 'staying strong'? (p. 161)
• Researcher reflection - Box 6.2: An example of critical TA research: Onward Gay Christian Soldiers? (p. 162)
• Let's get theoretical! (p. 163)
• What do we think language does? Three theories of language (p. 163)
• Box 6.3 Theories of language applied to data (p. 165)
• Introducing the 'ologies: The big scary theory (p. 166)
• Theories of reality: Ontologies (p. 167)
• Realism (p. 168)
• Critical realism (p. 169)
• Box 6.4 Some of the complexity of critical realism (p. 170)
• Researcher reflection - Box 6.5: Coming to critical realism (p. 172)
• Relativism (p. 173)
• Do I really have to think about ontology for TA? (p. 175)
• Theories of knowledge: Epistemologies (p. 175)
• Table 6.1 Realist and relativist TA: An overview comparison (p. 176)
• (Post)positivism (p. 177)
• Contextualism (p. 178)
• Constructionism (p. 179)
• Researcher reflection - Box 6.6: Beyond western ontologies and epistemologies: Using TA in the context of Indigenous knowledge frameworks (p. 181)
• Box 6.7 Is constructivism just a different name for constructionism? (p. 183)
• Checking out the view from the houses of epistemology (p. 184)
• Back to the confusion... Big Theory is contested terrain (p. 186)
• Theory as it's used: Some TA examples (p. 189)
• Table 6.2 Some varied use of theory in published TA research (p. 189)
• Chapter summary (p. 191)
• Want to learn more about...? (p. 191)
• Activities for student readers (p. 193)
• 7 So what? The importance of interpretation in reflexive thematic analysis (p. 195)
• Chapter Seven overview (p. 195)
• Doing interpretation during theme development (p. 197)
• What is interpretation? (p. 199)
• Interpretation needs to be defensible! (p. 201)
• Different modes of interpretation for reflexive TA (p. 203)
• From more descriptive to more interpretative modes of analysis (p. 203)
• Experiential to critical orientations in interpretation of data patterns (p. 204)
• Box 7.1 Shifting from an experiential to critical orientation to build analytic depth (p. 206)
• A deductive orientation: Working with existing theoretical concepts in doing interpretation (p. 208)
• Box 7.2 Explanatory theory in reflexive TA (p. 209)
• Locating data within the wider context (p. 211)
• Minimising harm in interpretation: Ethics, politics and representation (p. 214)
• Box 7.3 Interpretation across difference; Power, privilege and positioning (p. 216)
• Chapter Summary (p. 220)
• Want to learn more about...? (p. 220)
• Activities for student readers (p. 221)
• 8 One big happy family? Understanding similarities and differences between reflexive thematic analysis and its methodological siblings and cousins (p. 223)
• Chapter Eight overview (p. 223)
• A brief and partial history of 'thematic analysis' (p. 224)
• Table 8.1 Don't believe everything you hear! 10 claims about TA that are actually wrong (p. 225)
• Variation across TA approaches: Core concepts (p. 228)
• Coding: Process and/or output? (p. 229)
• What is a theme? (p. 229)
• Table 8.2 Shared-meaning themes vs. topic summaries (p. 231)
• Researcher subjectivity (reflexivity) (p. 232)
• A process of theme development or identification? (p. 232)
• Box 8.1 How do I get my themes in TA? Two different conceptualisations of the process (p. 233)
• Figure 8.1 Themes do not emerge! (p. 234)
• Mapping the main members of the TA family: Our tripartite clustering (p. 234)
• Table 8.3 Comparing TA: A quick overview of different forms of TA (p. 236)
• Coding reliability approaches: Small q thematic analysis (p. 237)
• What do we think is problematic about coding reliability approaches to TA? (p. 238)
• Codebook approaches to TA (medium q) (p. 242)
• Template analysis (p. 242)
• Do we perceive any problems with template analysis? (p. 244)
• Framework analysis (p. 244)
• Do we perceive any problems with framework analysis? (p. 246)
• Challenges with using codebook approaches in general (p. 246)
• So is reflexive TA the best approach to TA? (p. 247)
• But wait... there's even more? Other approaches to thematic analysis (p. 247)
• Table 8.4 A quick summary of advantages and challenges for different forms of TA (p. 248)
• Box 8.2 Thematic coding (p. 248)
• The use of TA for qualitative evidence synthesis (p. 250)
• Box 8.3 Polytextual TA for visual data analysis (p. 251)
• Researcher reflection - Box 8.4: How I use TA on visual data (p. 252)
• Figure 8.2 Image of Inverness Castle with white grid lines overlay (p. 252)
• Figure 8.3 Initial analysis of photograph (p. 253)
• 'Off-label' TA: Combining thematic analysis with other approaches (p. 254)
• Researcher reflection - Box 8.5: Combining TA and discourse analysis (p. 255)
• Chapter summary (p. 256)
• Want to learn more about...? (p. 256)
• Activities for student readers (p. 257)
• 9 Getting your own house in order: Understanding what makes good reflexive thematic analysis to ensure quality (p. 259)
• Chapter Nine overview (p. 259)
• They did what? Common problems we encounter in TA work (p. 260)
• Table 9.1 Strengths and limitations of reflexive TA (p. 261)
• Figure 9.1 Reflexive TA bingo (p. 262)
• Table 9.2 Common problems and good practice in (reflexive) TA research (p. 263)
• Premature closure of the analysis (p. 266)
• Strategies for ensuring quality in your TA research (p. 268)
• Table 9.3 Our 15-point checklist for good reflexive TA - version 2022 (p. 269)
• Reflexive journaling (p. 270)
• Box 9.1 Check yourself! Avoiding 'positivism creep' by developing a qualitative sensibility (p. 270)
• Talking about your data and analysis with others (p. 271)
• Allowing time for your analytic insights to fully develop (p. 272)
• Working with an experienced supervisor, mentor or co-researcher (p. 273)
• Making sure themes are themes, and naming them carefully (p. 274)
• Drawing inspiration from excellent examples of published research (p. 274)
• Demonstrating quality through an electronic or paper trail (p. 275)
• Managing quality during the publication process (p. 275)
• Are generic qualitative quality criteria and strategies useful in TA research? (p. 277)
• Chapter summary (p. 279)
• Want to learn more about...? (p. 279)
• Activities for student readers (p. 280)
• Fare-well! Becoming a bold adventurer in the world of reflexive TA (p. 281)
• Glossary (p. 283)
• References (p. 299)
• Index (p. 331)

Author notes provided by Syndetics