Exploring the use of wearable devices for sleep self-monitoring among nurses: a feasibility observational cohort study (Preprint)

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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 This study aimed to: (i) evaluate sleep quality among nurses and determine the measurement accuracy and feasibility of wearable-based sleep monitoring compared with validated actigraphy; and (ii) examine associations between sociodemographic characteristics, shift patterns, sleep hygiene, and sleep parameters. 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. Measurement accuracy of Apple Watch was established through comparison of total sleep time, in-bed wake time, and sleep efficiency using intraclass correlation coefficients. 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 the Sleep Hygiene Index. Multiple linear regression analyses were performed to identify predictors of sleep parameters, with adjustment for age, sex, Body Mass Index (BMI), parental status, workplace, total length of service, and sleep hygiene. RESULTS Apple Watch demonstrated excellent measurement accuracy for total sleep time (intraclass correlation coefficient = 0.95, p < 0.001), good accuracy for in-bed wake time (intraclass correlation coefficients = 0.72) and sleep efficiency (intraclass correlation coefficients = 0.69), with high wear compliance and minimal missing data, supporting its feasibility for individual 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. However, 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 predicting less deep sleep (B = −1.00 minutes per year, p < 0.01). CONCLUSIONS Behavioural factors, including sleep hygiene and BMI, were more strongly associated with sleep duration than nurses’ shift type, highlighting the need for interventions to improve sleep opportunity and promote healthy sleep behaviours.

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