Data Analysis

Data analysis began following each completed interview and continued throughout the data collection process. After the interviews were completed, they were transcribed by one transcriptionist who noted the participants’ filler words and emotional content and redacted the interviewer’s filler words and any identifying information. The participants’ contextual data were summarized using frequencies and percent to account for their personal and practice contexts during data description and interpretation. The first author analyzed the interview transcripts, the field notes, and the reflective content, using reflexive thematic analysis with the support of NVivo12. Inductive coding and constant comparative analysis occurred across the entire data set while reflecting on SCT and Ruggiero’s approach to moral dilemmas and decision-making. These initial patterns of meaning were developed and presented to the participants for member checking and the coauthors before the final data interpretation. Member checking allowed the participants to provide additional reflections, comment whether the data descriptions were realistic and whether the preliminary patterns of meaning were fair (Creswell, 2005), and provided a reflective space for participants (Candela, 2019) as they contemplated their subsequent interview experiences. Two participants responded to the aggregate finding email; no additional data to analyze were provided through this process. These initial patterns of meaning underwent combining, refining, and eventual interpretation and theming (Braun & Clarke, 2019) and were presented to the doctoral committee. The resultant themes were collated with theme definitions and supporting participant data, which formulated the findings’ structure. These documents were cross-checked by the coauthors and presented to the doctoral committee as part of an expert panel analysis check (Thorne, 2016).