Nearly 50% of older adults complain of poor habitual sleep, and in many cases the underlying reason remains undiagnosed or unknown. Meanwhile, observational data suggest that bedroom temperature significantly influences sleep quality in community-dwelling older adults, including those without financial constraints that limit the use of heating and cooling. These individuals often struggle to maintain an optimal bedroom temperature, either due to impaired motor function and cognitive abilities, and/or a lack of awareness about how temperature affects their sleep. Therefore, for a non-trivial portion of older adults, optimizing the bedroom temperature presents an exciting and untapped opportunity to improve sleep without substantial cost, burden, and side effects. The intervention, biologically adaptive control of bedroom temperature, uses wearable health trackers (e.g., a Garmin watch) and smart thermostats to automate and personalize bedroom temperature control, tailoring it to each person's unique physiology and context. Initially, individuals will be monitored in their home to determine each person's specific temperature range that promotes sleep quality, as measured by the wearable device. After the initial monitoring, the smart thermostat will maintain bedroom temperature within the optimal range for sleep for as long as the individual uses the intervention. The primary purpose of this project is to test the feasibility of biologically adaptive control of bedroom temperature as an intervention to improve sleep in older adults and gather preliminary data to facilitate sample size calculations for a definitive trial. 20 Older adults, aged 65 and above, will be enrolled and their bedrooms bedrooms will be equipped with smart thermostats. The first aim focuses on assessing the feasibility of the intervention. This includes evaluating participant recruitment and retention, the acceptability of temperature adjustments (tracked through the number of temperature overrides by participants), and the self-reported likelihood of future use. The second aim involves analyzing the mean and variance of sleep outcomes during observation and intervention phases (separately for each group), examining the degree to which they vary with temperature variations and behavioral adaptations.
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Sleep Efficiency Assessed by Actigraphy
Timeframe: up to 8 weeks