The Effect of Evening Technology Use on Objective Sleep in Older Adults: Protocol for a Crossover Randomized Controlled Trial.

Background: Evening technology use (ETU) has been associated with sleep disturbances, often attributed to blue light exposure and cognitive arousal. However, most of the existing evidence focuses on younger populations and relies primarily on subjective measures. As older adults increasingly engage with both passive and active technology use, it is important to investigate how ETU impacts objective sleep. Currently, there is also a limited understanding of how particular evening digital activities, especially active versus passive engagement, affect objective sleep in older adults. Objective: This study aims to investigate the impact of exposure to ETU on both objective and subjective sleep outcomes in older adults. Methods: This is a randomized crossover trial involving approximately 55 adults aged 60-75 years from the ongoing Swedish National Study on Aging and Care - Blekinge. Each participant will undergo 3 one-week intervention periods: active ETU, passive ETU, and a nondigital activity (book reading), with one-week washout periods in between. The order of interventions will be randomized. Sleep will be assessed using a home-based electroencephalography device (MUSE headband) and daily self-reports. Primary outcomes are sleep onset latency and wake after sleep onset. Secondary outcomes include objective measures such as total sleep time, sleep efficiency, and time spent in REM, deep, and light sleep, subjective sleep quality, adherence, and perception of the intervention and comfort of using the objective measurement tool, that is, the electroencephalography headband. Linear mixed-effects models (with fixed effects for condition and period and a random participant intercept) were used to analyze crossover effects on sleep outcomes. Results: Participant recruitment and data collection began in the fall of 2025 and will continue through summer 2026 or until the target sample size is reached. Data collection is scheduled to be completed by spring 2027. Results will include participant flow, baseline characteristics, adherence data, and comparative analyses of the 3 intervention conditions. Within-subject statistical models will be used to evaluate differences in sleep outcomes and investigate the associations between ETU and sleep quality. Conclusions: This crossover study will clarify how active and passive ETU, compared with a nondigital activity, relate to objective sleep in older adults. Findings will inform simple, practical recommendations for technology use before bed in late life.