Sleep. 2023 Jun 9:zsad167. doi: 10.1093/sleep/zsad167. Online ahead of print.

ABSTRACT

STUDY OBJECTIVES: Insomnia is a disorder diagnosed based on self-reported sleep complaints. Differences between self-reported and sensor-based sleep parameters (sleep-wake state discrepancy) are common but not well-understood in individuals with insomnia. This two-arm, parallel-group, single-blind, superiority randomised controlled trial examined whether monitoring sleep using wearable devices and providing support for interpretation of sensor-based sleep data improved insomnia symptoms or impacted sleep-wake state discrepancy.

METHODS: 113 (age M=47.53; SD=14.37, 64.9% female) individuals with significant insomnia symptoms (Insomnia Severity Index >=10; ISI) from the community were randomised 1:1 (permuted block randomization) to receive 5-week (a) Intervention (n=57): feedback about sensor-based sleep (Fitbit and EEG headband) with guidance for data interpretation and ongoing monitoring; (b) Control (n=56): sleep education and hygiene. Both groups received one individual session and two check-in calls. The ISI (primary outcome), Sleep Disturbance (SDis), Sleep-Related Impairment (SRI), Depression, and Anxiety were assessed at baseline and post-intervention.

RESULTS: 103 (91.2%) participants completed the study. Intention-to-treat multiple regression with multiple imputations showed that after controlling for baseline values, compared to the Control group (n=51), the Intervention group (n=52) had lower ISI (p=.011, d=0.51) and SDis (p=.036, d=0.42) post-intervention, but differences in SRI, Depression, Anxiety, and sleep-wake state discrepancy parameters (TST, SOL, WASO) were not meaningful (p-values>.40).

CONCLUSIONS: Providing feedback and guidance about sensor-based sleep parameters reduced insomnia severity and sleep disturbance but did not alter sleep-wake state discrepancy in individuals with insomnia more than sleep hygiene and education. The role of sleep wearable devices among individuals with insomnia require further research.

PMID:37294865 | DOI:10.1093/sleep/zsad167