0468 Predictors of Response to Digital CBTI in a Randomized Controlled Trial of Middle Aged and Older Adults with Insomnia

Abstract

Abstract Introduction Digital CBTI (dCBTI) may serve as a good initial intervention in a stepped-care approach to treat insomnia. Understanding who is likely to respond to dCBTI can guide triaging of care, thus shortening wait times for those who most need to meet with an insomnia therapist. The purpose of this study was to examine baseline predictors of response to a dCBTI program after two months of access. Methods Participants were 173 middle aged and older adults with insomnia (M age=63.56 [SD=8.43], 76% female) who received the dCBTI SleepioTM for two months in the RCT of the Effectiveness of Stepped-Care Sleep Therapy in General Practice (RESTING) study. Baseline predictors included the Epworth Sleepiness Scale (ESS), Dysfunctional Beliefs and Attitudes about Sleep (DBAS), preference for treatment (digital vs. therapist-delivered), and comfort with technology. At baseline and two-month follow-up, participants completed outcome measures, including the Insomnia Severity Index (ISI) and the PROMIS-Sleep Related Impairment (PROMIS-SRI). Multilevel modeling was used. Results In the full sample, no predictors were associated with change on the ISI. Among our predictors, only higher DBAS scores were associated with a smaller reduction in PROMIS-SRI scores from baseline to two-month follow-up (Beta=-0.88, SE=0.35, p=0.01 , 95% CI=-1.57, -0.19). Among those who preferred digital CBTI (n=52), none of the predictors were associated with the ISI or PROMIS-SRI. Among those who preferred therapist-led CBTI (n=66), greater comfort with technology was associated with greater reduction on the ISI (Beta=-1.77, S =0.78, p=0.02 , 95% CI=-3.30, -0.24) and higher DBAS scores were associated with a smaller reduction on the PROMIS-SRI (Beta=-1.63, S =0.56, p<0.01 , 95% CI=-2.73, -0.53). Conclusion The results highlight the importance of targeting dysfunctional beliefs and attitudes, which is consistent with research examining the DBAS in CBTI. Results also indicate that patient preference is an important factor to consider when triaging patients to insomnia care. While additional predictors should be examined, these preliminary findings indicate that dCBTI may be a good initial treatment option for those with high level of comfort using technology and lacking a preference for therapist-led CBTI. Support (If Any) R01AG057500 and T32MH019938