Evaluating the Feasibility and Acceptability of Internet-Based Cognitive Behavioral Therapy for Insomnia in Rural Women

Abstract

Background: Insomnia, one of the most common sleep disorders among women in midlife, is associated with multiple negative health outcomes. Rural Appalachian women are disproportionately affected by insufficient sleep, but their barriers to care ( e.g., health care shortages, cultural norms) may prevent intervention. This study assessed the feasibility and acceptability of Sleep Healthy Using the Internet (SHUTi) an Internet-based version of cognitive behavioral therapy for insomnia in Appalachian women ages 45+ years.

Materials and Methods: We used mixed methods to assess feasibility (through summaries of recruitment and retention data) and acceptability (quantitatively through online survey scales and qualitatively through interviews). Subject-level responses for satisfaction, adherence, and helpfulness scales were averaged over the multiple response domains and reported as percentages. Interviews were transcribed and coded using a multistage coding process.

Results: Forty-six women (average age 55 years) enrolled; 38 completed the SHUTi program (retention = 82.6%). The majority of participants (61%) indicated that SHUTi made things “somewhat better” or “a lot better.” Seventy-six percent reported that they followed the SHUTi protocol “most of the time” or “consistently.” Most participants (84%) ranked SHUTi as “moderately” or “very” helpful. Participants expressed enthusiasm about SHUTi and offered minor suggestions for improvement.

Conclusions: This study was the first to asses SHUTi in the health disparity population of Appalachian women. Rich insights gained through quantitative and qualitative data suggest that SHUTi was feasible and acceptable for middle-aged Appalachian women. Given rural Appalachian women's documented barriers to utilizing technology, these results hold promise for SHUTi's utility in other rural populations. Future research should incorporate a randomized case–control design within a larger sample and consider participants' suggestions for improvement.