Ninety-three percent identify as gay or lesbian, while 7% are bisexual or queer

Ninety-three percent identify as gay or lesbian, while 7% are bisexual or queer

Because older LGB adults are a hard-to-reach population, I relied on non-probability sampling methods (e.g., convenience, snowball) to recruit the participants; this method is consistent with most studies of this population ( Fredriksen-Goldsen & Kim, 2017). I also relied on a feature of respondent-driven sampling methods, wherein participants are asked to have their peers contact me directly if they desired to participate in the study (see Heckathorn, 1997).

Finally, integrative memos were written as part of the analysis process, a practice used to record reflective thoughts about themes that are emerging in the data (Emerson et al

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Most interviews were conducted in person or by phone in the Southeast and Midwest. Flyers containing study information were also hung at houses of worship, coffee shops, bars, etc. in a Southeastern state to recruit a diverse array of people. In addition, I recruited from social spaces from the LGB community, including online, community-based organizations, LGBTQ centers, senior centers, and retirement communities that specifically serve older LGBTQ people. I also identified gatekeepers for the study at local organizations, who helped recruit participants.

Consistent with qualitative research practices, all interviews were transcribed verbatim; participants were also assigned a pseudonym to ensure anonymity. Data were coded with ATLAS.ti, a qualitative software program. Using an interpretivist approach, I sought to discern how older LGB adults make sense of late-life plans. In doing so, my goal was to uncover meaning-making processes in the lives of participants, including motivations behind attitudes and behaviors (Krauss, 2005). In addition, I took detailed notes during and after interviews, which allowed me to enter the coding process with ideas about themes that had emerged across the interviews. I use line-by-line coding to identify patterns in the data that are not yet apparent and focused coding to collapse some of the overlapping themes into more general categories (Charmaz, 2002; Emerson et al., 1995). , 1995). More