Doing thematic analysis: step-by-step guide

Some of the phases of thematic analysis aresimilar to the phases of other qualitativeresearch, so these stages are not necessarilyall unique to thematic analysis. The processstarts when the analyst begins to notice,and look for, patterns of meaning andissues of potential interest in the data /this may be during data collection. Theendpoint is the reporting of the contentand meaning of patterns (themes) in thedata, where themes are abstract (and oftenfuzzy) constructs the investigators identify[sic] before, during, and after analysis(Ryan and Bernard, 2000: 780). Analysisinvolves a constant moving back and forwardbetween the entire data set, the codedextracts of data that you are analysing, andthe analysis of the data that you are producing.Writing is an integral part of analysis,not something that takes place at the end, asit does with statistical analyses. Therefore,writing should begin in phase one, with thejotting down of ideas and potential codingschemes, and continue right through theentire coding/analysis process.There are different positions regardingwhen you should engage with the literaturerelevant to your analysis / with somearguing that early reading can narrow youranalytic field of vision, leading you to focuson some aspects of the data at the expenseof other potentially crucial aspects. Othersargue that engagement with the literaturecan enhance your analysis by sensitizingyou to more subtle features of the data(Tuckett, 2005). Therefore, there is no oneright way to proceed with reading for thematicanalysis, although a more inductiveapproach would be enhanced by not engagingwith literature in the early stages ofanalysis, whereas a theoretical approachrequires engagement with the literatureprior to analysis.We provide an outline guide through thesix phases of analysis, and offer examples todemonstrate the process.7 The differentphases are summarized in Table 1. It isimportant to recognize that qualitative analysisguidelines are exactly that / they arenot rules, and, following the basic precepts,will need to be applied flexibly to fit theresearch questions and data (Patton, 1990).Moreover, analysis is not a linear process ofsimply moving from one phase to the next.Instead, it is more recursive process, wheremovement is back and forth as needed,throughout the phases. It is also a process86 V Braun and V Clarkethat develops over time (Ely et al., 1997),and should not be rushed.Phase 1: familiarizing yourself with yourdataWhen you engage in analysis, you may havecollected the data yourself, or they may havebeen given to you. If you collected themthrough interactive means, you will come tothe analysis with some prior knowledge ofthe data, and possibly some initial analyticinterests or thoughts. Regardless, it is vitalthat you immerse yourself in the data to theextent that you are familiar with the depthand breadth of the content. Immersionusually involves repeated reading of thedata, and reading the data in an active way /searching for meanings, patterns and so on.It is ideal to read through the entire data setat least once before you begin your coding,as ideas and identification of possible patternswill be shaped as you read through.Whether or not you are aiming for anoverall or detailed analysis, are searchingfor latent or semantic themes, or are data- ortheoretically-driven will inform how thereading proceeds. Regardless, it is importantto be familiar with all aspects of yourdata. At this phase, one of the reasons whyqualitative research tends to use far smallersamples than, for example, questionnaireresearch will become apparent / the readingand re-reading of data is time-consuming.It is, therefore, tempting to skip overthis phase, or be selective. We wouldstrongly advise against this, as this phaseprovides the bedrock for the rest of theanalysis.During this phase, it is a good idea to starttaking notes or marking ideas for codingthat you will then go back to in subsequentphases. Once you have done this, you areready to begin, the more formal codingprocess. In essence, coding continues to bedeveloped and defined throughout the entireanalysis.Transcription of verbal dataIf you are working with verbal data, such asinterviews, television programmes or politicalspeeches, the data will need to betranscribed into written form in order toconduct a thematic analysis. The process oftranscription, while it may seen time-consuming,frustrating, and at times boring, canbe an excellent way to start familiarizingyourself with the data (Riessman, 1993).Further, some researchers even argueit should be seen as a key phase ofdata analysis within interpretative qualitativemethodology (Bird, 2005: 227), andrecognized as an interpretative act, whereTable 1 Phases of thematic analysisPhase Description of the process Familiarizing yourselfwith your data:Transcribing data (if necessary), reading and re-reading the data, noting downinitial ideas.Generating initial codes: Coding interesting features of the data in a systematic fashion across the entiredata set, collating data relevant to each code.Searching for themes: Collating codes into potential themes, gathering all data relevant to eachpotential theme.Reviewing themes: Checking if the themes work in relation to the coded extracts (Level 1) and theentire data set (Level 2), generating a thematic map of the analysis.Defining and namingthemes:Ongoing analysis to refine the specifics of each theme, and the overall story theanalysis tells, generating clear definitions and names for each theme.Producing the report: The final opportunity for analysis. Selection of vivid, compelling extractexamples, final analysis of selected extracts, relating back of the analysis to theresearch question and literature, producing a scholarly report of the analysis.Using thematic analysis in psychology 87meanings are created, rather than simply amechanical act of putting spoken sounds onpaper (Lapadat and Lindsay, 1999).Various conventions exist for transformingspoken texts into written texts (see Edwardsand Lampert, 1993; Lapadat and Lindsay,1999). Some systems of transcription havebeen developed for specific forms of analysis/ such as the Jefferson system for CA (seeAtkinson and Heritage, 1984; Hutchby andWooffitt, 1998). However, thematic analysis,even constructionist thematic analysis, doesnot require the same level of detail in thetranscript as conversation, discourse or evennarrative analysis. As there is no one way toconduct thematic analysis, there is no one setof guidelines to follow when producing atranscript. However, at a minimum it requiresa rigorous and thorough orthographictranscript / a verbatim account ofall verbal (and sometimes nonverbal / eg,coughs) utterances.8 What is important isthat the transcript retains the informationyou need, from the verbal account, and in away which is true to its original nature (eg,punctuation added can alter the meaning ofdata / for example I hate it, you know. I doversus I hate it. You know I do, Poland,2002: 632), and that the transcription conventionis practically suited to the purpose ofanalysis (Edwards, 1993).As we have noted, the time spent intranscription is not wasted, as it informsthe early stages of analysis, and you willdevelop a far more thorough understandingof your data through having transcribed it.Furthermore, the close attention needed totranscribe data may facilitate the close readingand interpretative skills needed to analysethe data (Lapadat and Lindsay, 1999). Ifyour data have already been, or will be,transcribed for you, it is important that youspend more time familiarising yourself withthe data, and also check the transcripts backagainst the original audio recordings foraccuracy (as should always be done).Phase 2: generating initial codesPhase 2 begins when you have read andfamiliarized yourself with the data, and havegenerated an initial list of ideas about whatis in the data and what is interesting aboutthem. This phase then involves the productionof initial codes from the data. Codesidentify a feature of the data (semanticcontent or latent) that appears interestingto the analyst, and refer to the most basicsegment, or element, of the raw data orinformation that can be assessed in a meaningfulway regarding the phenomenon(Boyatzis, 1998: 63). See Figure 1 for anexample of codes applied to a short segmentof data. The process of coding is part ofanalysis (Miles and Huberman, 1994), as youare organising your data into meaningfulgroups (Tuckett, 2005). However, yourcoded data differ from the units of analysis(your themes), which are (often) broader.Your themes, which you start to develop inthe next phase, are where the interpretativeanalysis of the data occurs, and in relation towhich arguments about the phenomenonbeing examined are made (Boyatzis, 1998).Coding will, to some extent, depend onwhether the themes are more data-drivenor theory-driven / in the former, theData extract Coded forits too much like hard work I mean how much paper have you got to signto change a flippin name no I I mean no I no we we have thought about it((inaudible)) half heartedly and thought no no I jus- I cant be bothered,its too much like hard work. (Kate F07a)Talked about with partnerToo much hassle to change nameFigure 1 Data extract, with codes applied (from Clarke et al ., 2006)88 V Braun and V Clarkethemes will depend on the data, but in thelatter, you might approach the data withspecific questions in mind that you wish tocode around. It will also depend on whetheryou are aiming to code the content of theentire data set, or whether you are coding toidentify particular (and possibly limited)features of the data set. Coding can beperformed either manually or through asoftware programme (see, eg, Kelle, 2004;Seale, 2000, for discussion of softwareprogrammes).Work systematically through the entiredata set, giving full and equal attention toeach data item, and identify interestingaspects in the data items that may formthe basis of repeated patterns (themes)across the data set. There are a number ofways of actually coding extracts. If codingmanually, you can code your data by writingnotes on the texts you are analysing,by using highlighters or coloured pens toindicate potential patterns, or by usingpost-it notes to identify segments of data.You may initially identify the codes, andthen match them with data extracts thatdemonstrate that code, but it is important inthis phase to ensure that all actual dataextracts are coded, and then collated togetherwithin each code. This may involvecopying extracts of data from individualtranscripts or photocopying extracts ofprinted data, and collating each code togetherin separate computer files or usingfile cards. If using computer software, youcode by tagging and naming selections oftext within each data item.Key advice for this phase is: (a) code for asmany potential themes/patterns as possible(time permitting) / you never know whatmight be interesting later; (b) code extractsof data inclusively / ie, keep a little of thesurrounding data if relevant, a commoncriticism of coding is that the context islost (Bryman, 2001); and (c) remember thatyou can code individual extracts of data inas many different themes as they fit into /so an extract may be uncoded, coded once,or coded many times, as relevant. Note thatno data set is without contradiction, and asatisfactory thematic map that you willeventually produce / an overall conceptualizationof the data patterns, and relationshipsbetween them9 / does not have tosmooth out or ignore the tensions andinconsistencies within and across dataitems. It is important to retain accountsthat depart from the dominant story in theanalysis, so do not ignore these in yourcoding.

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