Version 10

Two trained qualitative analysts reviewed the interview transcripts to develop a codebook for categorizing participants’ rationales for preferring one letter versus another and for particular sections/phrasings of text within the individual letters. A random sample of 10% of the transcripts were reviewed in duplicate by the first author; disagreements in coding were resolved through discussion with the coders. The participants’ rationale for sticker placement was then layered onto this coding to foster rapid comparison across the three letters. After the completion of the coding of all the transcripts and passages, the codes were independently reviewed by two of the authors (SWE and SLS), who identified general themes to characterize participants’ beliefs and preferences with respect to the letters and to the optimal communication of the DXA results. These themes were compared, refined, and synthesized to develop a final letter reflecting participant preference and comprehension. Interviews were coded using qualitative data analysis software (MAXQDA Version 10, VERBI Software GmbH, Marburg, Germany).

The conventional content analysis method was used to analyze the data according to the steps which were proposed by Graneheim and Lundman (25 (link)). In this method, each of the recorded interviews would be transcribed word by word, and the interviews were reviewed several times meticulously. The transcribed interviews were initially reviewed as a whole in order for the researchers to be acquainted with the texts. The actual analysis began with looking for the semantic units which were related to different aspects of barriers and facilitators of early rehabilitation. These units were then condensed, abstracted, and then labeled, provided that their original meaning is retained. Given the similarities and differences, the codes were used to form the subcategories. Finally, the subcategories were re-read and then further categorized based on the similarities and their relationship with the other subcategories. Eventually, the main theme was extracted. Preliminary analyses were performed by the leading researcher (ME) and were then evaluated and finalized by the other authors. Since the researchers did not observe any new code after conducting the twenty-three interviews, it can be confirmed that data saturation has been achieved. MAXQDA version 10 was used for data analysis.

All the interviews were immediately transcribed verbatim. The transcripts were read by the authors several times to get insight into the participants’ experiences. Thereafter, they were analyzed using conventional content analysis according to the technique described by Hsieh and Shannon (14 (link)). Data were coded, and related codes were finally grouped under certain categories by using the constant comparative analysis. The MAXQDA (Version 10) was used to organize, code, and manage the data.