a) The broad methodological approach

Overview of the Vutivi study research design of primary data collection

Figure 15 illustrates the methods used in data collection (Stage 2 of the research design).

Figure 15. Research design summarising the methods and design used in Stage 2 of data collection

Stage 1: Initial pilot observations in healthcare facilities and community Stage 2: Qualitative data collection Transcriptions Formulation of coding framework Stage 2:

Qualitative data collection methods using case study design:

 Ethnography and non-participant observations including informal interviews

 In-depth semi-structured formal interviews with seven participant groups:

-Vutivi chronic patients -Nkateko hypertensive patients -Pregnant women

-Nurses and doctors

-Health-workers (additional) -Community members -Policy-makers

-eHealth and mHealth experts

 Focus groups discussions -Pregnant women

Quantitative secondary data:

 Descriptive statistics of demographics and three census variables

Stage 3: Analysis and synthesis of qualitative data Secondary quantitative data analysis

qualitative methods integrated in-depth interviews, focus group discussions and a prolonged engagement in non-participant observations in clinics and within the community as indicated in Stage 2 of the research design (Figure 15). The choice of qualitative methodology was crucial in allowing the research to focus on participant’s experiences (Colaizzi, 1978) to understand more about a new phenomenon (Tesch, 2013). Data was triangulated during thematic and comparative analysis (Gilson et al., 2011; Denzin, 1970).

In addition, a secondary quantitative data analysis of the Agincourt HDSS census data, aided the contextualisation and interpretation of the qualitative findings by describing descriptive statistics of relevant variables.

Analysis of primary qualitative and secondary quantitative data, synthesis of theory and policy discussion was then integrated into the overall findings. The theoretical-conceptual framework (Figure 2) guided the development of the research design.

To address Research Questions 2-4, data was collected from n=231 multiple key informants from distinct participant groups: patients with chronic diseases (Vutivi and Nkateko), pregnant women, nurses and doctors, additional health-workers, policy-makers and eHealth and mHealth experts. Interviews were undertaken to explore the experience of healthcare, meanings, dynamics, current and potential uses of technologies within in the

clinics and local community. Each data collection phase informed the next phase and so on.

Epistemological commitments

The epistemological ‘positionality’ taken is that of realism. This was discussed in Chapters 1 and 3. Emmel (2013:157) suggests that ‘social reality is not simply captured by descriptions of events and experiences; it is far richer and deeper within a social system’. The realist researcher must always seek to explain ‘what works, for whom, in what circumstances and why’ (Pawson & Tilley, 1997). The qualitative methods used in this study aim to address this realist question by working out the relationship between ideas and evidence, between insiders’ perspectives and experiences of events and outsiders’ understandings of the causal mechanisms that bring about change (Emmel, 2013:6).

Case study design

The study uses case study design (Yin, 2013). South Africa as the single case study and embedded within that, a case study on the Agincourt HDSS. Case study research is in line with realist principles. Realists are concerned with understanding how each case contributes to the interpretation and explanation

open social system’ with the purpose of describing what is going on in a particular setting (Emmel, 2013:107). Yin (2013:141) suggests that cases can make a significant contribution to ‘theory building’ and knowledge. This research provides a representative case, capturing circumstances (patients and health-workers in rural health facilities using eHealth and mHealth), likely to be typical of other rural settings.

The case study design was used to allow an in-depth investigation of the interrelated factors underlying the participant’s experiences (Neuman & Kreuger, 2003). The shortcomings of the case approach include the researcher’s own subjective bias, difficulty of replication, and non- representative and time-consuming cases (Hammersley & Atkinson, 2007). These have been recognised as issues that could arise in any qualitative design.

Description of methods used in the empirical data collection

Justification of multiple data collection methods

The choice of multiple methods is appropriate since focus group discussions, in-depth interviews and ethnographic observations enable the investigation of attitudes, meanings, experiences and behaviours from many participant’s perspectives. Creditability of the findings was enhanced through iterative data collection. Interviews and observations occurred on the same day enabling an overall representation of the research environment. Gilson (2012) endorsed

that to ensure rigour in qualitative data collection, prolonged engagement with the subject of enquiry is paramount. Data was collected over a continuous twelve-month period (September 2013-2014).

Ethnography and observations in the community and healthcare facilities

A pivotal mode of ethnography was non-participant observation and interviews. The ethnographer’s gaze demands two things: ‘being able to locate the mundane features of extraordinary situations and to identify what is remarkable in everyday life’ (Silverman, 2007:23). Ethnography allows for the observation of ordinary practices that cannot always be detected in interviews. The strength of ethnography is the potential for rigorous and authentic stories from the perspective of local people (Fetterman, 2010). In ethnography, the primary ‘research instrument’ is the researcher (Hammersley & Atkinson, 2007:19). It is therefore crucial that researchers locate themselves within the research environment and try to explicitly reflect on how personal subjectivities affect research and research relationships, such as the researcher’s ethnicity, language and appearance. ‘Researchers bring prejudices, prejudgements, theories, frames of references and concepts to their choices’ (Emmel, 2013:158).

implementation and be able ‘to reflect on their challenges’. In this study, we aimed to get both emic (from the perspective of the observer, for example the policy-makers) and etic (from the perspective of the subject, for example the patients) responses. Petersen et al. (2005:1237) describe this process as ‘the participant’s view of what is happening, with the researcher interpreting the emic data from their etic perspective which the researcher brings to bear on the data’.

Informal interviews

Informal interviews or ‘natural conversations’ (Green & Thorogood, 2013) occurred spontaneously and fortuitously in the field. This data was gathered opportunistically and played an important role in developing an overall account of people’s perceptions to healthcare topics and technology use. These conversations provided the ‘backbone’ to the formal interviews.

Formal interviews

Formal interviews with each participant group were selected on the grounds that they provided unique and different information. Interviews increased the understanding of social phenomena (Bowling, 2014:144). All interviews were semi-structured and guided by an interview schedule.

There are a number of actors, each playing a role at the micro-, meso- and macro-levels within the health system. Interviews were undertaken with ‘actors’ at each level. Each actor’s perspectives about their role within the healthcare system and where eHealth and mHealth can fit were discussed to generate data on beliefs and behaviours (Green & Thorogood, 2013).

Focus group discussions

The purpose of conducting focus group discussions (FGDs) with pregnant women, in addition to interviews was to elicit ideas in a group environment. Bowling (2014:410) suggests that FGDs ‘create a space to stimulate discussion, gain insights and generate ideas in order to pursue topics in greater depths’. A period of time lapsed between the interviews and FGDs allowing for discussion around topics that had arisen in the interviews where more detailed explanations were needed.

Data saturation

Data saturation was interpreted when new ideas relating to the study aim ceased to emerge from the data (Creswell & Clark, 2007). The term saturation point (Glaser & Strauss, 1967) or data sufficiency (Suri, 2011) is in line with realist methodology that seeks to test theories until data saturation (Wong et

diversity of participants who were demographically different within each group.

Documentary analysis

A documentary analysis of policies, strategies, parliamentary speeches and clinical guidelines publically available from the NDOH’s website, were also analysed. Sampling of documents was based on relevancy to eHealth and mHealth and those mentioned by interview participants. These documents have been discussed as contextual background in Chapter 2 and to follow in Chapter 7.

Preparation and familiarisation

Access into the study site was only made possible due to the long-standing engagement between Warwick and Wits and the established and venerable engagement that the Agincourt Research Unit has with the community: Shangaan chiefs, known as the Indunas, community leaders and members and the healthcare facilities. The Learning, Information Dissemination and Networking with the Community (LINC) team facilitated access into the field site. This was useful because often researchers enter as ‘strangers’ (Hammersley & Traianou, 2012:54).

It was a concern that interviewing within study site clinics could be hampered by the participants’ ‘general fatigue’ from the research process (Clark, 2008:953). This was overcome, as the research topic was relevant to everyone, as generally mobile phones are peoples’ prised possession. There was no direct incentive to take part other than good will and perhaps intrigue.

Mixed-methods research design

A ‘dominant-less-dominant’ design of QUAL/quant was used, also known as ‘an exploratory design’ (Ivankova et al., 2006:3). This sequential design gives priority to the qualitative over the quantitative method. It was important to make use of ‘the richness of differing methodological traditions’ by integrating them (Kelle & Erzberger, 2004:158). This was appropriate for this study’s complex research questions (Dixon-Woods et al., 2004).

The rational to use a mixed-method approach was made in the attempt to counteract the biases that are associated with mono-method studies (Gilson, 2012). Green and Thorogood (2013) propose that researchers should ‘appeal to the deficit model’ of traditional clinical and epidemiological research, as qualitative methods ‘reach the parts other methods cannot reach’. There is also the opportunity for complementarity of results. The secondary quantitative data analysis allowed for expansion of the findings by adding