Data analysis

The previous subsection discussed the use of in-depth interviews to collect the data that informed the present study. This subsection focuses on data analysis using Strauss and Corbin’s (1990) cyclic three-step analysis guidelines. The aim of data analysis was to develop better understanding about how members of the theoretical population managed living in families in which the man was HIV-positive. The researcher strove to keep in the foreground participants’ concerns, and to minimize the researcher effect, as discussed under reflexivity and relationality. As outlined below, analysis eventually focused on the issue of communicating HIV-positive status.

Data analysis began with open coding, the inductive identification of codes, short descriptor statements used to group data items (Wuest, 2012) in terms of their overall meaning (Sbaraini et al., 2011) in a process herein called coding. During the coding process, more than one code could be assigned to identified units of meaning, as discussed below. The researcher used constant comparison and questioning techniques to make theoretical comparisons (Cranely, 2009), as

102

described above. Once the codes and concepts, the conceptual labels assigned to discrete instances of the subject under investigation (Strauss & Corbin, 1990), emerged from the analysis, they were compared and contrasted to check their relevance to the developing theory. Ultimately, codes were grouped into abstract categories that highlighted the realm of the study, albeit descriptively. The researcher also referred to the literature to check for similarities and differences between the literature and the emerging theory. For example, the researcher briefly reviewed literature on multiple illnesses as an emerging category, to compare the kinds of illnesses reported in the literature with those reported by the present participants, such as diabetes, sexual dysfunction and liver and kidney problems. In cases where the findings were unclear or the researcher could not fully understand the participant’s views, follow-up phone calls were made to solicit clarification. For example, when housing emerged as a relevant category, the researcher phoned back several participants to find out about any issues associated with their tenancy arrangements. In the subsection that follows, the researcher describes the process of open coding as the first stage of the cyclical three-stage data analysis approach used in the present study.

2.4.8.1 Open coding

Open coding refers to the “process of breaking down, examining, comparing, conceptualizing and categorizing data” (Strauss & Corbin, 1990, p. 61). The aim of using open coding here was to break up the data into small analytical chunks which could then be grouped, compared and contrasted.

The researcher began the process of open coding by listening to the audio files from the interviews repeatedly, to develop a mental map of the data. After each transcription, he read through the transcripts several times in order to develop a broader picture of the interview, identify key issues (Wuest, 2012) and enhance theoretical sensitivity (Strauss & Corbin, 1990, 1998). The researcher broke the data into small chunks containing a unit of meaning and attached a brief description to each, summarizing what was being said. Related items were grouped together in open-coding categories. Appendix 13 provides an example of the open coding

103

process carried out in the present study. Through constant questioning and constant comparison, the researcher acknowledged and strove to minimize the researcher effect on the data. As Strauss and Corbin noted, “fracturing data forces preconceived notions and ideas to be examined against the data themselves. A researcher may inadvertently place data in a category where they do not analytically belong, but by means of systematic comparison, the errors will eventually be located and the data and concepts arranged in appropriate classifications” (Strauss &

Corbin, 1990, p. 13). Open coding gradually developed into axial and then selective coding, although these analytical processes overlapped. Details on how the researcher carried out axial coding are discussed next.

2.4.8.2 Axial coding

According to Strauss and Corbin (1990), axial coding refers to procedures through which data broken down during open coding are reconstituted in new ways by making connections between and within categories and exploring their dimensional ranges. This form of coding is called ‘axial’ because coding takes place around the

‘axis’ of a category (Strauss & Corbin, 1998). In the present study, the researcher developed many categories, for example alcohol use, medication issues, culture, communication with children, HIV-positive status disclosure and gender relations.

The researcher began to link categories and to notice variations within categories, for instance between public and selective disclosure. In adherence to Strauss and Corbin’s (1990, p. 99) model on axial coding, the researcher asked of the data questions such as why, how or what were the outcomes of the action or interaction involved and in what context did the happening occur? He drew upon his previous experience and knowledge of HIV and its impact on the family in developing the categories further. The identified relationships between categories and their dimensional ranges were noted in memos.

During axial coding, the researcher moved back and forth between inductive and deductive interpretations. For example, the researcher noted from the data that most of the participants had not disclosed their HIV status to their children. The hypothesis on concealment from children was then deductively verified by the

104

literature. Appendix 14 illustrates how the process of axial coding was applied in the present study.

2.4.8.3 Selective coding

This was the most abstract stage of coding. Strauss and Corbin (1990, p. 116) defined selective coding as “the process of selecting the core category, systematically relating it to other categories, validating those relationships, and filling in categories that needed further refinement and development”. The core category relates to a storyline concerning the central issue around which other identified categories are integrated (Walker & Myrick, 2006). As Strauss and Corbin (1990) argued, making a commitment to a storyline is particularly difficult because the researcher becomes so immersed in the data that everything begins to appear important. Data analyses identified communication about HIV status as the core category around which three important subcategories – HIV status disclosure, exposure and concealment - were organized as shown in Figure 0.1 presented in the Introduction to the thesis. These subcategories were related to other emergent categories, such as the social contexts of disclosure, concealment and exposure, and multiple stigmatization.

The issue of communication about HIV-positive status could be identified throughout the data. Participants’ narratives contained many references to whom they told and did not tell and who might or might not have found out about their condition; about their reasons for deciding whom they should tell; and about the consequences, as they saw them, of disclosure, concealment and exposure of their HIV-positive status. Communication regarding HIV status also influenced participant’s access to and use of HIV-related services, as will be discussed in the findings chapters.