1. Effect of Wearables on Sleep in Healthy Individuals: A Randomized Cross-Over Trial and Validation Study
- Author
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Saif Mashaqi, Adam Berryhill, Natalie Provencio-Dean, Lynn B. Gerald, Jerry A. Krishnan, Sairam Parthasarathy, Daniel Combs, Salma I. Patel, Christopher J Morton, Adam Dean, Sarah Berryhill, and Lauren Estep
- Subjects
Sleep Wake Disorders ,Pulmonary and Respiratory Medicine ,medicine.medical_specialty ,Validation study ,Polysomnography ,education ,Wearable computer ,Wearable Electronic Devices ,03 medical and health sciences ,0302 clinical medicine ,Physical medicine and rehabilitation ,medicine ,Humans ,Cross-Over Studies ,Sleep quality ,business.industry ,Scientific Investigations ,Actigraphy ,Crossover study ,Neurology ,Healthy individuals ,Commentary ,Female ,Neurology (clinical) ,Sleep (system call) ,Sleep ,business ,030217 neurology & neurosurgery ,Sleep loss - Abstract
STUDY OBJECTIVES: The purpose of this study was to determine whether a wearable sleep-tracker improves perceived sleep quality in healthy participants and to test whether wearables reliably measure sleep quantity and quality compared with polysomnography. METHODS: This study included a single-center randomized crossover trial of community-based participants without medical conditions or sleep disorders. A wearable device (WHOOP, Inc.) was used that provided feedback regarding sleep information to the participant for 1 week and maintained sleep logs versus 1 week of maintained sleep logs alone. Self-reported daily sleep behaviors were documented in sleep logs. Polysomnography was performed on 1 night when wearing the wearable. The Patient-Reported Outcomes Measurement Information System sleep disturbance sleep scale was measured at baseline, day 7 and day 14 of study participation. RESULTS: In 32 participants (21 women; 23.8 ± 5 years), wearables improved nighttime sleep quality (Patient-Reported Outcomes Measurement Information System sleep disturbance: B = −1.69; 95% confidence interval, −3.11 to −0.27; P = .021) after adjusting for age, sex, baseline, and order effect. There was a small increase in self-reported daytime naps when wearing the device (B = 3.2; SE, 1.4; P = .023), but total daily sleep remained unchanged (P = .43). The wearable had low bias (13.8 minutes) and precision (17.8 minutes) errors for measuring sleep duration and measured dream sleep and slow wave sleep accurately (intraclass coefficient, 0.74 ± 0.28 and 0.85 ± 0.15, respectively). Bias and precision error for heart rate (bias, −0.17%; precision, 1.5%) and respiratory rate (bias, 1.8%; precision, 6.7%) were very low compared with that measured by electrocardiogram and inductance plethysmography during polysomnography. CONCLUSIONS: In healthy people, wearables can improve sleep quality and accurately measure sleep and cardiorespiratory variables. CLINICAL TRIAL REGISTRATION: Registry: ClinicalTrials.gov; Name: Assessment of Sleep by WHOOP in Ambulatory Subjects; Identifier: NCT03692195. CITATION: Berryhill S, Morton CJ, Dean A, et al. Effect of wearables on sleep in health individuals: a randomized crossover trial and validation study. J Clin Sleep Med. 2020;16(5):775–783.
- Published
- 2020