Data analysis

A conventional content analysis with an inductive approach was used to analyze the verbatim transcript data. This approach is appropriate when existing theory or research literature on a phenomenon is limited, allowing researchers to immerse themselves in the data to allow new insights to emerge. The process is also described as inductive category development [21]. Decisions about further sampling, data collection, and coding were guided by a goal of achieving data and thematic saturation, when no new data or themes emerged from the discussions. Saturation in this study was considered as a point at which no new codes occurred in the data and additional data did not lead to any new emergent themes [22].

Analysis occurred in four phases following the guided analytic cycles of qualitative data analysis [23]. In the first phase, the first and second authors (RD and OZ) quantitatively inspected the data and independently coded the transcripts using open coding and then met to discuss their individual codes, identify areas of disagreement, and reach consensus after discussing meanings to establish inter-coder agreement. In the second phase, the coded experiences and opinions of all the practitioners were grouped and categories were drawn out to derive a comprehensive perspective on healthy aging. In the third phase, all researchers employed a member-checking strategy that involved summarizing information to attendees (including original focus group participants) at a gerontological professionals network meeting, obtaining their input, and thus affirming the accuracy and completeness of our findings to enhance the credibility of the findings and validate responses. In the final analysis phase, a conceptual framework (Fig. 1) of healthy aging was developed synthesizing and corroborating findings that emerged from the data analysis.

Conceptual framework of the perspectives of community-based practitioners’ on healthy aging