letter to the editor about a published article DOI: 10.2196/mhealth.8458 - Johan Goris (2017)
Background Background: Shift work disorder and insufficient sleep are prevalent among nurses, leading to fatigue, reduced well-being, and potential safety concerns. Increasing use of wearable sleep-tracking devices presents an opportunity to evaluate nurses' sleep quality objectively. Objective Objective: The primary objective was to evaluate the feasibility of wearable-based sleep monitoring and to obtain preliminary evidence of agreement with validated actigraphy among nurses. The secondary objective was to describe nurses' sleep characteristics and examine exploratory associations between sociodemographic characteristics, shift patterns, sleep hygiene, and sleep parameters. Methods Methods: A two-phase feasibility observational cohort study was conducted in a tertiary hospital in Singapore. In Phase 1, five nurses concurrently wore a consumer-grade wrist-worn wearable Apple Watch Series 10 and a validated actigraph (GENEActiv®) for two weeks. Preliminary agreement between Apple Watch and GENEActiv® was examined using intraclass correlation coefficients (ICC). Feasibility was determined via wear compliance and completeness of data. In Phase 2, 50 nurses working rotating or single shifts completed demographic and work-related questionnaires and Sleep Hygiene Index. Multiple linear regression analyses were performed to examine exploratory associations between selected covariates and sleep parameters, with adjustment for age, sex, Body Mass Index (BMI), parental status, workplace, total length of service, and sleep hygiene. Results Results: Apple Watch showed preliminary evidence of agreement with GENEActiv® for total sleep time, in-bed wake time, and sleep efficiency (ICC= 0.95, 0.72, and 0.69, respectively), with high wear compliance and minimal missing data, supporting feasibility for sleep monitoring. Mean total sleep time was 381 ± 55 min, and mean sleep efficiency was 94.8%. Shift nurses reported poorer sleep hygiene than non-shift nurses; however, shift work status was not independently associated with sleep outcomes after adjustment. Higher BMI was associated with shorter total sleep time (B = -3.76 minutes per kg/m², p = 0.01), reduced rapid eye movement sleep (B = -1.18 minutes, p = 0.03), shorter core sleep (B = -2.72 minutes, p = 0.02) and reduced time in bed (B = -4.05 minutes, p < 0.01). Age was negatively associated with deep sleep duration, with older age associated with less deep sleep (B = -1.00 minutes per year, p < 0.01). Conclusions Conclusion: Apple Watch-based monitoring was feasible and showed preliminary agreement with actigraphy. Nurses obtained less sleep than recommended, and BMI and age were associated with sleep outcomes in exploratory analyses. These findings support larger studies and workplace strategies to improve sleep opportunity and healthy sleep behaviours. Clinicaltrial Not applicable.