DATA ANALYSIS PROCEDURE AND DISCUSSION OF NASCENT FINDINGS
Step 2: Generating initial codes
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never been to school and they are only in their early teenage years or their 20s (R. Page, Interview, 6 March 2018).
This insight prompted the revision of questions in the research guides that were too technical and/or pitched at too high an academic level and, therefore, inaccessible to the ‘typical’ vulnerable young women with MDR-TB in eThekwini Metro as described in Chapter Four. The possibility that unnecessarily complicated language would alienate participants and affect participation was considered. This led to contemplation that nuances in MDR-TB biomedical and technical terms in English would not translate well into isiZulu and that I, a non-isiZulu-speaking researcher, would struggle to expound unclear questions without interpretation during focus group discussions.
Some questions were consequently simplified to abridge and elucidate lines of enquiry in the research guides. Furthermore, questions deemed superfluous to the task of gathering sufficient information to address the research questions were excluded altogether at this stage.
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iii. people or groups with most influence in terms of communicating health information to young women with MDR-TB for behaviour change; and iv. media programmes/content/messages identified.
Over many months of the research, an iterative process to code and identify themes, often in tandem with data collection was adopted. While engaging with the data, instances where participants used words and phrases that highlighted issues of importance to the research often became clear (Ke and Wenglensky 2010); this also happened during data collection. These axioms were noted verbatim or as paraphrased sentences and associated with a code (Ke and Wenglensky 2010; Allan 2003). It was common for more than one code to be derived from the same text (Allan 2003). Interesting or unfamiliar terms were included in anticipation that they could result in unique analytical categories appearing later in the process (Pope et al.
2000). Some inimitable findings identified through this process and how they influenced changes in the research approach are discussed in this chapter. Identified themes were examined against content in new transcripts following each data collection event to ensure their continued utility and representativeness and interminably added codes to the table.
From this process, the shortened phrases that emerged were considered codes and listed as such in the table in Appendix 12, which presents how all data collected and exhaustively interpreted was organised and coded. Table 4 is an abridged version of Appendix 12. As discussed later, thematic analysis in this research did not involve the mere counting of analogous words or phrases in transcripts and presenting the most ubiquitous information as fact. Instead, data coded in Step 2 was analysed further using an interpretive lens to identify latent themes and lay the foundation for deeper analysis in Step 3, where the approach allowed for tentative linkages to be made, as explained in the next section.
168 Table 4: Coding for initial themes
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Extensive literature reviewed in Chapters Three and Four explains why people may fail to adhere to MDR-TB treatment. It was clear while analysing data at the beginning of fieldwork that this research needed to ask questions differently to avoid regurgitating what was already known and instead contribute new knowledge specific to the researched case study and context. Advancing new or novel findings to understanding of the complexities that impact a defined vulnerable population’s suboptimal adherence to MDR-TB treatment was dependent on the questions research participants were asked, and the links and meanings made in the findings during data analysis. Adjustments to the research tools and expansion of the key respondent list as described earlier was undertaken to further improve the quality of information collected.
It is important to clarify here that many of the broad themes that emerged from the preliminary analysis of data in the early stages were discussed in the literature review chapters of this thesis. Indeed, in line with conclusions reached in Chapter Four, one of the first key participants interviewed was clear that:
We know why people default, that information is out there. People default for a lot of reasons and we know what those reasons are. A lot of those reasons are out of the Department of Health’s control. For example, people’s socioeconomic backgrounds, where they are living, who they are living with, the poverty, those are all socioeconomic things that cause a person to default.
We know that (R. Page, Interview, 6 March 2018).
Reading of data to make meanings from it in this phase of analysis was not undertaken in a vacuum. My experiences working in and knowledge of the TB management field in South Africa ineluctably influenced how I interpreted findings. Furthermore, five significant factors in 2017 and 2018 and my involvement in each must be considered in relation to their potential influence on the meanings made from the data. As discussed in Chapter Six, two studies published in 2016 and 2017 established the growing challenge of primary transmission of DR-TB in eThekwini Metro, and influenced the design of this study. Indeed, findings in the study by Shah et al. (2017) sparked policy makers, practitioners (including me through my employment) and those in the health fraternity to intensify efforts to assuage the crisis in KwaZulu-Natal through multi-sectoral interventions during 2017 in a process discussed in Chapter Five.
In 2018, however, these same stakeholders, led by the National Department of Health, shifted attention to ‘finding missing TB patients’ nationally, resulting in reduced momentum on DR-TB infection prevention and treatment efforts in eThekwini. The
‘finding missing patients’ initiative was launched in reaction to the WHO’s (2016)
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‘Global tuberculosis report’, which estimated that 154,000 people with TB in South Africa were undiagnosed or not receiving care. Once ‘found’, the initiative emphasised ensuring that people with confirmed TB were initiated on treatment and their contacts screened for symptoms of the disease. This was the first factor.
Secondly, at a press briefing in Johannesburg on 30 August, Tamaryn Green, recently crowned Miss South Africa 2018, disclosed that she was TB survivor and launched her
#BeatTheStigma social media campaign, which aimed to contribute to alleviating negative effects of TB infection and treatment on children and women specifically. I shared the stage with Miss South and a representative of the Department of Health as a speaker in a panel discussion at the event. The third initiative was topical in September, when the country launched the South Africa Chapter of the Global Tuberculosis Caucus of Parliamentarians. The initiative was formally debated in Parliament in Cape Town on 4 September and the motion to constitute the caucus passed by all political parties. I was present at both the debate and the launch in my professional capacity. The fourth factor is that on 21 September the United Nations convened the first-ever High-Level Meeting on Tuberculosis held in New York, United States of America. An indication of how important the last event was to global and national efforts to end TB is that while this was the first high-level meeting on TB, there had already been three such assemblies convened to discuss the HIV epidemic, in 2008, 2011 and again in 2016.
Fifthly, but not insignificantly, South Africa launched its maiden TB prevalence survey in KwaZulu-Natal province in August 2017; the survey was ongoing nationally at the time of data collection and was scheduled to conclude in June 2019 in Western Cape province. It serves this study to briefly discuss the survey. Many potential participants’
responses to the national survey were lukewarm, for various reasons. Besides lack of knowledge about the scientific impetus and national interest in establishing the prevalence of TB in the country and the importance of broad participation, low communication and public awareness about the survey process affected enrolment.
Additionally, insufficient public knowledge about how TB is transmitted and the scale of the challenge in South Africa led to many participants who felt their risk of TB infection was low refusing to consent to participate. This was despite that the survey aimed to establish prevalence, not incidence of TB. Low participation in the survey was common in affluent neighbourhoods and areas where the majority of residents were not Black.
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The events in 2017 and 2018 discussed above were significant to this study because they contributed to higher than usual coverage of TB in mass media for a year between August 2017 and September 2018. The events also illustrate the multiple and oft- changing priorities of TB stakeholders in South Africa during this period. This study was conceptualised in 2017 when addressing MDR-TB in eThekwini was an urgent priority of the NTP, sparked by Shah et al.’s (2017) study, but data was collected in 2018 when national attention had shifted back to TB broadly, and was divided among the four enterprises (excluding Miss South Africa’s campaign) discussed above and others. I use this explanation to sign-post that external events had bearing on how I approached the analysis of data for this research.