CAPÍTULO IV: DE LA CURATELA

Data analysis was undertaken only after all data was collected. While the data collection

was held in Nepal, data analysis was undertaken in the UK using NVivo 10 software.

Data were analysed using thematic analysis. The following is a brief description of

thematic analysis and a more detailed account of the steps used in the data analysis.

4.9.1 Introduction to thematic analysis

Thematic analysis was used to interpret the data. Thematic analysis is a method for

identifying, analysing, and reporting patterns or themes (Braun and Clarke, 2006). This

method is often used in qualitative data analysis and requires coding to categorise the

data (Bowling and Ebrahim, 2005, p.524). The essence of thematic method is its ability

to identify and recognise the underlying themes as well as the visible ones in the data.

82 (Section 4.9.2.1) (Vaismoradi et al., 2013). Thematic analysis allowed me to identify

and analyse the themes within the context of data collected (Joffe and Yardley, 2003).

4.9.2 Steps in analysis

All data were collected in Nepal before main analysis. The data analysis

consisted of the following steps: a) preliminary analysis- generating initial codes,

b) use of a data management tool, c) generating codes, d) generating themes and

e) selecting themes.

4.9.2.1 Preliminary analysis- generating initial codes

Health workers Women

Figure 5 Interrelationship among health workers, FCHVs and women

The focus of the study was to obtain detailed accounts (Snape and Spencer, 2003) of the FCHVs’ functioning in MHSs from the multiple perspectives of FCHVs, their potential users and paid health workers. Therefore, thorough and careful reading and re-reading

of the transcripts was conducted in a systematic way to recognize recurring themes

(Pope et al., 2006) or to locate certain patterns in the data according to the research

questions (Joffe and Yardley, 2003). In the beginning, an inductive approach to analysis

83 was used where all the data were coded. This is also the most fundamental method of

developing a code and themes (Keenan et al., 2005). An attempt was made to stay

connected with the research questions while allowing new themes to emerge throughout

the analysis.

At the beginning of the analysis, coding was carried out in a Word document without

trying to fit the data into a pre-existing frame. After the first few interviews had been

coded, one of my supervisors (EvT) independently coded them. This helped me to

clarify the emerging sub-themes across the data set and agreements were reached during

the supervision meetings. This was done in order to include an element of inter-rater

reliability (Section 4.10.3). Data coding was iterative throughout the data collection.

Moreover, keeping personal memos and a journal about the coding process helped to

ensure reliability of the findings.

4.9.2.2 Use of a data management tool

Data were managed using the NVivo 10 Software package (QSR International, 2015 ).

For the use of the NVivo software, basic and advanced training was obtained from the

University of Sheffield. I also used YouTube videos to gain additional information and

the learning took upwards of 40 hours. Using NVivo allowed more transparent ways of

data analysis and helped to quantify emerging themes from the textual data (Welsh,

2002), but the software is often criticised for the fragmentation of the text. This is

because the coding of the data may sometimes cause loss of context, which is especially

important for data from FGDs where the interaction between the participants might be

lost (Richards, 1999). However, my familiarity with the study context and my

involvement throughout the data collection, translation and analysis enabled me to have

84 4.9.2.3 Generating codes

The second step in thematic analysis involved systematically producing lists of codes

from the data set (identification of nodes in NVivo) that have a repetitive pattern in the

Nvivo software. Overarching points were noted first, which helped the coding - a “process whereby data are broken down into component parts, which are given names” (Bryman, 2012, p.710). The transcripts were coded using open coding and the

preliminary codes were named using terminology used by the participants themselves.

After coding of the five interviews, the codes were arranged according to the research

questions (Appendix 2) and any new codes emerging from the dataset were also

assimilated.

In my reflective journal, I maintained a record of the emerging codes and the new

codes. This record was a reference point for me while I was interviewing and also

helped me in the data analysis prompting me to understand how the codes would be

incorporated into the final analysis. Each data item was carefully coded in order to

identify any overlooked repeated patterns. At first, the data from women and health

workers were coded in separate NVivo files, whilst the codes from FGDs were

combined with codes from interviews of FCHVs, because they were both volunteers

and themes emerging from the data sets were similar. Then, the coded data for health

workers and women were merged together with the data for FCHVs, because the overall

aim of the study was to explore the role of FCHVs in MHS provision.

The coding process was undertaken repetitively to refine the codes by adding,

removing, merging or splitting potential codes. Coding for as many themes as possible

and coding individual aspects of the data was cumbersome but the process was useful to

85 themes as follows.

4.9.2.4 Generating themes

Themes were generated by reading and rereading the coded empirical materials, and

combining and splitting initial codes according to the meaning of the content in the text.

The coding process was not a linear process, but a cyclical one in which codes emerged

throughout the data analysis. This cyclical process involved going back and forth

between the steps of data analysis until final themes were decided (Ritchie and Lewis,

2003). Themes and subthemes were allowed to emerge from the textual data so that any

new ideas could be identified within the data (Bryman, 2012). Subthemes were

combined to form the major themes. By repeated readings of the subthemes, themes

were identified thus drawing an overall picture for this thesis (Perakyla, 2013).

4.9.2.5 Theme selection

Themes were chosen in order to provide more understanding of the research questions

in this study. Once the themes were defined, connections amongst themes were

established in the final thesis in order to assist the reader to understand how decisions

were made regarding the themes’ selection. Sometimes, aspects of meaning appearing

few times in the text were of a higher priority than those appearing more often

(Kracauer 1952 cited in Schreier, 2012 , p.13). For example, FCHVs provided different

types of medicines or assisted in deliveries in remote places, which was reported merely

a few times, but were of high importance due to its direct health implications (Section

86 4.9.2.6 Data integration and triangulation

Data were integrated in the data analysis step known as “technical integration” (Mason, 2002, p.35). Similar themes emerging from the different data sets were put together and

comparisons were made among different groups. Views of service users and paid health

workers were compared with those of FCHVs. While keeping FCHVs’ perspectives at

the centre, findings are presented according to themes (Chapter Five and Six). To

understand the theme within the context and to convey the meaning of the particular

themes I used quotes (Ritchie and Lewis, 2003).