Thematic Analysis Procedure

Each manuscript was transcribed verbatim into a separate identified folder. The digitally recorded focus discussions or individual interviews were re-played many times to ensure the adequate understanding of obtained data. As a standard digital recorder was used, it was possible to minimise the background noise and change the sound tones to maximise the clarity of voices.

The manuscripts were read through frequently, to become familiar with the overall picture of data (deductive analysis). That is, this approach was used to discern an overall and fundamental meaning of experiences (Hall, 2004). Then, line by line a search of manuscripts was undertaken to scan central themes (e.g. how do nurses understand the meaning of health promotion?). This included repeated ideas or statements “that say something” (Brunard, 1991). This process was accompanied by

making notes about each manuscript using different colours for different themes (e.g. green = the meaning of health promotion, red = the meaning of health).

Once again the manuscript was re-read to check that common themes were really common in the manuscripts. Indeed, so doing allowed the current author to become immersed in the data and thus the “life world” of participants (Gillis and Jackson, 2002). Once the current author has become aware of the main issues found, as many headings as necessary were highlighted. Irrelevant materials which are referred to as “dross” (Brunard, 1991) were identified and excluded from the analysis (e.g. talking in a detailed way about the housing prices). Whilst this could involve bias because of the hazard of subjective decisions regarding relevant materials, it aids the

development of data that are specifically of significance to the work objectives (Miles and Huberman, 1994). However, if in doubt about what to exclude from analysis, both relevant literatures together with the current work objectives were examined. Thus, the possibility of subjective decisions, regarding what is relevant or otherwise, was kept to a minimum. Eventually, irrelevant materials were kept in mind at the end of data analysis to see if they fitted in with the overall picture of the data emerging.

Once the main themes were highlighted, a category system was created for each manuscript (e.g. Category One: all themes about the meaning of health and related extracts). Initially, as many categories as possible were generated and materials of relevance were linked accordingly. Then the number of categories was reduced (collapsing stage) i.e. some of the ones that have similar contents (Brunard, 1991). Once the final version of categories was finalised, each of them was examined within the context of each question reported in the interview schedule.

As qualitative analysis is an ongoing and dynamic process, during the writing up phase, if there is some doubt about certain findings, the current author checks the manuscript to ensure the credibility of analysis.

The extent to which certain themes are based on “real data” were re-checked and reinforced by examples. A Jordanian research colleague (PhD student) in the UK was asked to produce another list of categories without seeing the first one (2 transcripts). This introduced the reliability element to the categorisation process.

Given the nature of qualitative data and the complexity of its quantification, an inter- rater reliability coefficient was not computed. Instead, both researchers discussed the given category to examine the level of agreement or otherwise. The discussion was informed by some examples of significance reported by participants. As a result, some changes were made to the category label as well as the related content.

However, in case the discussion between the independent researchers showed a remarkable difference, two interventions were utilised. Firstly, each researcher needed to offer justifications for a certain category by giving extracts from the original manuscript as “live evidence”. Before data were collected, it was anticipated in advance that, if the disagreement has not been resolved, a third

researcher will be involved in analysing specific manuscripts and then all researchers will discuss a debated issue together until a high degree of agreement is reached. In the current study, only the first measure was used as the disagreement was resolved after further information was given about the study’s theoretical background. For example, the PhD student referred to protecting health from disease as a “physical view of health”. The current researcher explained that this will be categorised as a medical view of health in order to minimise the conceptual ambiguity highlighted in Chapter (2).

Whilst measures were undertaken to enhance the credibility of data, it is unwise to claim that bias was entirely eradicated in this work. Arguably, the only way of analysing qualitative materials without manipulation would be to offer the manuscripts whole and unanalysed, so readers themselves could judge them (Brunard, 1991, Miles and Huberman, 1994). However, practically this is not possible given the amount of data created by this research, coupled with difficulties in understanding their contents, particularly those linked to cultural issues.

The above thematic procedure was applied to documentary reviews, interviews (n=4), focus group discussions (n=8) and observational data. However, because of their nature and aims, the data of the latter two methods required further analytical procedures. This is illuminated in the next two sections.

1- Focus Group Discussions

Discussing the debate about analysing the data of focus group discussions, Barbour and Kitzinger (1999) argue that such data could be basically analysed as other qualitative self reported data. Whilst in one respect this could be true, given their qualitative nature, it is crucial to maintain a sense of the whole group within the analysis in this research. That is, it is the group that is the unit of analysis and not individuals within the group (McLafferty 2004). Subsequently, certain strategies were undertaken whilst the discussion was in progress and after the data were collected.

Careful attention was paid to obvious ambiguities, latent disagreement and

“unfinished business” that arose in the course of the group (Barbour and Kitzinger, 1999). In addition to thematic analysis procedure outlined above, the transcript was read through at least three times. This was in order to establish where there was group consensus on an identified issue and to distinguish individual’s opinions expressed supporting or otherwise the group. At the same time, the transcripts were analysed with this in mind and an overview grid was used to provide a synthesis of the emerging themes.

Finally, during analysis, data emanating from group discussions involved examples of the discursive nature of the method by reporting two or more participants in any extracts rather than focusing on an isolated excerpt offered by a certain individual. Although the above strategies are critical for a systematic analysis of focus group discussions (Umaña-Taylor and Bámaca, 2004), earlier qualitative work paid little attention to the above points and offered inadequate descriptions on how the data of

focus group discussions were analysed (See Chapters 2 & 3: Maidwell, 1996, Hjelm et al, 2005). This has raised concerns about the credibility of conclusions generated from such a dynamic research method.