RESEARCH DESIGN AND METHODS
2.5 DATA ANALYSIS
The purpose of data analysis is to organise, provide structure to, and elicit meaning from data (Polit & Beck 2012:556). In analysing qualitative data, I tried to establish how participants make meaning of the RPL phenomenon by analysing their perceptions, attitudes, understanding, knowledge, values, feelings and experiences in an attempt to approximate their construction of the phenomenon (Nieuwenhuis in Maree 2013:99). Qualitative data analysis entails organising and preparing the data, coding the data, and developing a description and thematic analysis from the codes (Creswell, 2014:212). Data is categorised, summarised and described in more meaningful terms.
2.5.1 Organising the data
Qualitative data collected from individual interviews and field notes and personal notes was found to be very lengthy and required intensive examination, understanding and reading (Nieuwenhuis in Maree 2013:104). An appropriate method to organise data was used to ensure easy retrieval when necessary. In this way data was converted to smaller manageable segments (Polit & Beck 2012:562).
Files were used to store the same batch of data and identification numbers were attached to each file.
2.5.2 Transcribing the data
Audio taped data were transcribed verbatim (rewritten word for word). I involved a professional transcriber following an agreement as to how data should be transcribed and how confidentiality would be maintained. The accuracy of the transcribed data was checked and continuous communication with the transcriber was maintained telephonically and via emails.
2.5.3 Coding the data
This was best achieved by beginning with a full description of my own experience of the phenomenon in an attempt to set aside my personal experiences so that the focus could be directed to the participants. Lists of significant statements were developed. Each statement was treated as having equal worth and worked to develop a list of non-repetitive, non-overlapping statements. Composite descriptions of the experience were written, which investigated how the studied phenomenon was experienced by participants. I then looked at all possible alternative meanings and different perspectives. Significant statements were taken and then grouped into larger units of information, called ‘meaning’ units or themes.
All data, including interview transcripts, field and reflective notes, were analysed using the descriptive analysis technique by Tesch (in Creswell, 2014:198). Tesch’s approach proposes eight steps to engage a researcher in a systematic process of analysing textual data:
1. The researcher obtains a sense of the whole by reading through transcriptions carefully. Ideas that come to mind may be jotted down.
2. The researcher selects one interview, for example the shortest one, the one at the top of the pile or the most interesting one, and goes through it asking: “What is this about?”
3. When the researcher has completed this task for several respondents, a list is made of all the topics. Similar topics are clustered together and formed into columns that might be arranged into major topics, unique topics and leftovers. 4. The researcher now takes the list and returns to the data. The topics are
abbreviated as codes and the codes are written next to the appropriate segments of the text. The researcher tries out this preliminary organising scheme to see whether new categories and codes emerge.
5. The researcher finds the most descriptive wording for the topics and turns them into categories. The researcher endeavours to reduce the total list of categories by grouping together topics that are related to each other. Lines are drawn between categories to show interrelationships.
6. The researcher makes a final decision on the abbreviations for each category and alphabetises the codes.
7. The data belonging to each category is assembled in one place and a preliminary analysis is performed.
8. If necessary, existing data is coded by the researcher.
A set of clean data were provided to an independent coder who has experience in qualitative data analysis. After the independent coder and I had completed the data analysis, we met for a consensus discussion. The findings, as agreed by both myself and the independent coder, are fully disclosed in Chapter 3 of this research study.
2.6 MEASURES OF TRUSTWORTHINESS
Lincoln and Guba (in Polit & Beck 2012:584) suggests four criteria for developing the trustworthiness of a qualitative inquiry: credibility, dependability, confirmability, and transferability.
2.6.1 Credibility
Credibility refers to confidence in the truth of the data and the interpretations thereof (Polit & Beck 2012:585). Data quality was enhanced by practising intensive listening and concentration during individual face-to-face interviews. Sufficient time was allocated for data collection so as to obtain an in-depth view of participants regarding
their experience and also to improve the relationship with participants (prolonged engagement). The total time of the recorded interviews was 405 minutes, 95 seconds.
To demonstrate reflexivity, I used a reflective diary to reflect on potential biases that may influence data collection, analysis and interpretation. Frequent debriefing sessions (Maritz & Jooste 2011:972) between myself and my supervisor were maintained. I used this opportunity to discuss ideas and interpretations related to the study.
A peer review process was applied to evaluate the quality of the study. Individual interviews, naïve sketches, field and reflective notes (Data triangulation) were used in this study. Member checking was applied by conducting a follow-up interview with participants and providing them with an opportunity to comment on the findings (Creswell 2014:202).
2.6.2 Dependability
Dependability refers to the stability of data over time and over conditions (Polit & Beck 2012:539). To enhance dependability, the research was audited by checking the accuracy of transcriptions and the relationship between the research questions and the data (Creswell 2014:203). Thick, rich descriptions of the methodology were provided.
2.6.3 Confirmability
Confirmability is maintained if there is objectivity or congruency between two or more independent people’s data in relation to accuracy, relevance or meaning (Polit & Beck 2012:585). The researcher ensured that the whole research project was reviewed by an independent objective auditor. This was an expert in qualitative
research with a qualification in nursing and experienced in qualitative research.
The participants’ interviews were tape recorded with their permission. This data were transcribed verbatim (Annexure D), analysed and coded. It was then handed to an
independent co-coder who was a qualified and experienced qualitative researcher for co-coding.
I ensured that accurate and thorough record keeping was maintained. This included all material and documentation used during data collection, including field and reflective notes and transcripts. These records were kept safely and could be made available should they be requested at a later stage.
2.6.4 Transferability
Transferability refers to the generalisability of the data, that is, the extent to which the findings can be transferred to or have applicability in other settings or groups (Polit & Beck 2012:585). The research findings cannot be generalised, however, thick descriptions will be provided of the methodology in order to assist in the possible transferability of the findings to other contexts.
2.7 SUMMARY
In this chapter all the research design components, which included the research methods, data collection, data analysis and measures of trustworthiness were discussed. As previously stated, the chosen research design and procedures enabled the researcher to explore the lived experiences of nursing RPL candidates. An exploratory, descriptive and contextual qualitative research design was employed. During data collection, triangulation was ensured as multiple means of data collection were used to collect data and two people analysed the data. The research results of the experiences of nursing RPL candidates are discussed in Chapter 3.