CHAPTER 3 RESEARCH METHODOLOGY
3.9 DATA ANALYSIS
The mixed-methods data were analysed with a parallel mixed-data analysis. Analysis of the qualitative and quantitative data was done separately. According to Fielding (2012) parallel analysis allows for a more complete and separate qualitative and quantitative understanding before findings of the quantitative analysis are compared and contrasted to the qualitative findings. In the event where qualitative data provided new or meaningful insights into the findings from the quantitative study, these findings are reported (Fielding, 2012). Data integration is a crucial element in mixed methods analysis and conceptualisation. It has three major purposes: illustration, convergent validation (triangulation), and the development of analytic density or ‘‘richness.’’ Statistical data can be dry, and a clip from an interview can bring the issue alive. Equally, qualitative data can be dense, and a statistic can provide focus (Fielding, 2012).
3.9.1 Qualitative data analysis
Qualitative data analysis involves dismantling, segmenting and reassembling data to form meaningful findings in order to draw inferences (Wahyuni, 2012). The research questions and research aim were used to guide the process of cutting the collected texts into pieces and logically recombining them. Analysis of data proceeded with data collection. The researcher did not wait to finish all the interviews before starting to analyse. As the process continued, the researcher analysed an interview that was conducted earlier. Memos that would be included as narratives in the final report were written. The researcher then collated and analysed data using thematic analysis. This is a systematic process of looking at data from different angles, with a view to identifying codes in the transcripts that will assist the researcher in understanding and interpreting raw data. Thematic analysis is an inductive and iterative process in which the researcher looks for similarities and differences in the text that contribute to rich descriptions of, in this study, the extent of participation of nurse leaders in health policy development (Creswell, 2014).
Transcription
The researcher transcribed all audio recordings and notes personally. Listening to the voice recordings and reading of field notes was done over and over again to gain
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understanding of the content before coding (Creswell, 2013). This helped to recall observations and experiences until the researcher became immersed in the data.
Coding
Transcribed data were coded by reading again through each transcript to get a sense of emerging patterns. Data were hand colour coded. The related words, phrases and sentences were identified in the texts and assigned colours. They were highlighted in each interview text as many times as they occurred. Information provided by the participants that was not directly related to the study was omitted. The result of initial coding is the identification of numerous concepts relevant to the subject under study. After initial coding, the researcher tried to summarise and organise the data. This step resulted in refining and revising initial codes, categorising and searching for relationships and patterns in the data.
Establishing themes
The next step was to combine related codes into themes, and each theme was assigned identifying words (Babbie 2010). Themes were derived from words, phrases and sentences related to the research questions emerging from transcripts. A brief description of each theme was written down and outstanding quotes were marked with a coloured highlighter. The whole process was iterative, as the researcher moved back and forth through the data.
3.9.2 Quantitative data analysis
The quantitative data generated in this study came from self-administered questionnaires.
The analysis sought to identify if there were any statistically significant changes in participation of nurse leaders at different stages of the health policy development. The nurse leaders were analysed individually (intra-individual variance) and as a group (inter- individual variance). Data were analysed using the Statistical Package for the Social sciences (SPSS) Version 23. Results were presented using tables, graphs, frequencies and percentages. The processing of data followed these steps:
Editing: The researcher had to ensure that data collected were usable. All questionnaires were examined at the point of collection or receipt for completeness.
Coding: The open-ended responses in the questionnaire were coded in preparation for data entry.
Data entry: Raw data from responses to all questions were entered into the computer using SPSS version 23. Statistical commands for analysis were used to produce frequencies, cross tabulations, graphs and correlation statistics. The data outliers were taken out.
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Sorting: Hard copies of the instrument were grouped according to the facilities where they were collected. Facility instruments were labelled. The data for facilities from the same district were put together and a district batch was created.
3.9.3 Data triangulation
Triangulation of data took place as illustrated in Figure 3.4. Triangulation refers to checking to see whether information from different sources or different data collection techniques correspond or are parallel (Lapan and Quartaroli, 2009). Triangulation provides a wider perspective from participants and supports validity (Tekin and Kotaman, 2013). The two data sets were analysed separately, then compared and converged at interpretation and discussion stages with a view to providing corroborating evidence for the conclusions drawn.
Figure 3.4: Data triangulation (Creswell, 2014)
3.9.4 The capacity-building workshop
The results of the study were shared with the research team for verification. The team brainstormed the interventions. It was agreed that a capacity-building policy workshop for nurse leaders was required based on the findings. The team also agreed on the topics to be covered during the workshop, including developing a policy brief. For cost containment, the workshop was planned to run on the same date as the presentation and verification of data with a larger group of nurse leaders. A consultant working at the Centre for Health Policy Studies at a reputable university was approached to facilitate the workshop.
3.9.4 The
Interpretation Compare
Quantitative data and
analysis
Qualitative data and
analysis
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3.9.4.1 Selection of participants
The planning of the workshop began with a process of selection and preparation of participants. Every effort was made to locate individuals and groups who have a legitimate interest or say in the matter under consideration. All facilities and individuals that had participated in the study were recruited for the workshop. Three nurse leaders were invited per facility. The nurse educators were also invited to the workshop. The invitations were sent via e-mail and telephonically.
3.9.4.2 The workshop programme
The researcher, in consultation with the research team, developed the programme for the workshop. It was informed by the research results, after analysing the gaps in the participation of nurse leaders in health policy development. The programme was emailed to the facilitator to ensure that the critical topics were covered during her presentations.
3.9.4.3 Venue
The workshop took place at Glenmore Pastoral Centre in Durban (KZN). The setting was somewhat retreat-like, permitting the participants to separate themselves from their daily lives briefly and focus intensively on the problem at hand. The researcher had to visit the place prior to the workshop to ensure that it was conducive for the event. The room was large enough for plenary discussions and for the participants to move around freely. The setting also contained ample space for working in small groups. In preparing for the workshop, close cooperation with some of the local participants was important. They assisted in preparing the workshop venue in the morning and were assigned to take notes during the workshop.
3.9.4.4 Equipment
A laptop was used for presentations. The data projector, microphone (to project the sound), flip chart and screen provided by the venue were also used.
3.9.4.5 Data collection
Data were collected during the course of the workshop by taking notes of all the proceedings and discussions. Records were captured using various data sheets (Cano, 2009) such as the registration form, attendance register and evaluation forms.
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3.9.4.6 Data analysis
Grundy and Kemmis (1981) suggested that it is during the reflective stage of the AR cycle that data analysis occurred. This stage provided the researcher with important insights with which to move the process forward. The practitioner is the sole arbiter of interpretation (French, 2009). Consequently, the interpretation of others was vitally important because they provided insights that were not obvious to the researcher. These insights were elicited through discussion or through the deliberation of participants.