The concept “data analysis”, as introduced in Chapter 1 (see sub-section 1.10), can further be described as a process giving meaning to data through a continuous process of analytical reflection (Creswell, 2016:183). Royse (2011:42) concurs, adding that data analysis is the organising of collected information/data into groups or themes. Data analysis involves ordering “raw data” into structured, systematic and comparable themes. Words expressed during interviews (raw data) are analysed to come to certain conclusions during the data analysis (Bricki & Green, 2007:4). Bless et al. (2016:341) assert that data analysis begins during data collection, where the researcher is able to note certain themes emerging and recurring. The authors (2016) explain that coding is the process whereby the transcripts of interviews are broken into fragments, which share a common theme.
Data for the study was collected during interviews, recorded on a digital recorder. Thereafter, the interviews were transcribed verbatim. The transcription was formatted in the correct style for coding and data analysis. Additionally, the transcribed interviews were printed out and kept safely. I then followed the steps of
105
qualitative data analysis, as proposed by Tesch (in Creswell, 2014:198). These steps appear on the surface to be in a linear form, but Creswell (2014:196) asserts that the process of data analysis is cyclical in nature. In agreement with Bless et al. (2016:341), as stated above, he proffers that data analysis is an interactive process and develops during the process of qualitative research. Hennink et al. (2011:234) concur that data analysis is a cyclical process, involving the description, comparison, categorising and conceptualisation of the raw data. In the next section, I will indicate how this process of organising and preparing raw data for analysis was conducted.
Organising and preparing the raw data for analysis
I recorded the data and transcribed the raw data as soon as possible after the interviews. During the interviews, I made use of a note pad and pencil to write down possible probing questions or note down certain issues that I wanted to return to in the interview (Moser et al., 2018:15). These authors (2018) are also of the opinion that the researcher should not postpone or wait with the data analysis process, as emerging designs are at the centre of qualitative research, and this entails a process of moving back and forth between sampling, data collection and analysis. Emerging issues/themes should be noted and followed up during the process of interviewing. Moser et al. (2018:16) further indicate that this process guides subsequent sampling decisions. During the interviews, I also made notes of matters that came across as of high importance to the participants. In this way, I started ordering the data early on in the process, and started analysing it informally.
At first I made use of a transcriber, but soon realised the value of doing the transcription myself, as it allowed me to gain more meaning and insight in the information gathered. Only two interviews were transcribed by an outside transcriber. Thereafter, I did all the transcribing myself. I found that transcribing formed part of the process of early analysis of the data. After each transcribed interview, I read through the transcription and made notes on emerging patterns or themes. I made unique abbreviations to identify certain emerging topics as part of coding the data, as indicated in Chapter 1 (sub-section 1.11.4).
106
Once all the interviews had been conducted, I gained a holistic sense of the data collected by reading through each transcribed interview, making notes in the margins, and clustering information together. All ideas/thoughts that came to the fore were noted. I then compiled a draft table where I indicated the emerging themes based on the questions asked in the interview guide and indicated sub-themes next to them. The following process assisted me in conducting the data analysis:
FIGURE 2.2: PROCESS FLOW OF DATA ANALYSIS
I transcribed the audio recordings of the interviews conducted word-for-word. I proceeded to read the transcripts carefully, making notes as I read. I then wrote down ideas and gained a general sense of the content and meaning of the transcripts.
I took the first transcript and reread it carefully, asking myself: What is this about? What is the essence of the information? The purpose was to gain a holistic sense of the interview. I made notes on implied messages and themes that I picked up in the interview and read thoroughly through the transcript.
I repeated this process with the remaining transcripts. In executing this step, I revisited and sorted the topics and then grouped similar topics. For example, “parents’ previous knowledge of LGBTIQA+ matters prior to their child coming out” and then categorised sub-themes, such as “parents had no previous knowledge” or “parents had previous experience/knowledge of LGBTIQA+ matters”.
107
Following the categorising of the topics, I started allocating an abbreviation and finding descriptive words for each of the identified topics. I then returned with the list of topics and their accompanying abbreviations to the data sets and placed the abbreviations next to the segments of data corresponding to the respective topics.
I utilised the cut and paste option to group topics that belonged together under one theme, dividing the material into themes and providing the groundwork to do a preliminary analysis of the information.
When I was satisfied with the categorising and coding of the topics, a final decision was made about the wording of each topic. Each one had to be specific and clear, and then was adopted and/or reworded as a theme.
A final decision was made regarding which themes (topics) and sub-themes should be included (in consultation with the independent coder). The two diagrams in Chapter 3 and Chapter 4 indicate the themes and sub-themes that were eventually deduced and verified at the consensus discussion.
Finally, the existing data were recorded and discussed, as found in Chapter 3 and Chapter 4. During the process of presenting my findings and substantiating my findings with relevant research, I revisited the data several times to check on its correct presentation.
108
An independent coder and I followed the same steps, as indicated above. Following the analysis, my supervisor, the independent coder and I held a discussion panel on 31 October 2019 to finalise the themes and sub-themes that answered the research questions. We found that we, in most instances, had identified the same themes and sub-themes. We agreed on the themes and sub-themes that would be used in the research findings.
In addition, I took note of the verification of the qualitative data to ensure the validity of this study. The aspects that were considered will be discussed in the next section.