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Predicting circadian misalignment with wearable technology: validation of wrist-worn actigraphy and photometry in night shift workers

Authors :
Philip Cheng
Helen J Burgess
Christopher L. Drake
Yitong Huang
Thomas Roth
Caleb Mayer
Olivia J. Walch
Chaewon Sagong
Andrea Cuamatzi Castelan
Daniel B. Forger
Source :
Sleep
Publication Year :
2020
Publisher :
Oxford University Press (OUP), 2020.

Abstract

Study ObjectivesA critical barrier to successful treatment of circadian misalignment in shift workers is determining circadian phase in a clinical or field setting. Light and movement data collected passively from wrist actigraphy can generate predictions of circadian phase via mathematical models; however, these models have largely been tested in non-shift working adults. This study tested the feasibility and accuracy of actigraphy in predicting dim light melatonin onset (DLMO) in fixed night shift workers.MethodsA sample of 45 night shift workers wore wrist actigraphs before completing DLMO in the laboratory (17.0 days ± 10.3 SD). DLMO was assessed via 24 hourly saliva samples in dim light (ResultsModel predictions of DLMO showed good concordance with in-lab DLMO, with Lin’s concordance coefficient of 0.70, which was twice as high as agreement using average sleep timing as a proxy of DLMO. The absolute mean error of the predictions was 2.88 h, with 76% and 91% of the predictions falling with 2 and 4 h, respectively.ConclusionThis study is the first to demonstrate the use of wrist actigraphy-based estimates of circadian phase as a clinically useful and valid alternative to in-lab measurement of DLMO in fixed night shift workers. Future research should explore how additional predictors may impact accuracy.

Details

ISSN :
15509109 and 01618105
Volume :
44
Database :
OpenAIRE
Journal :
Sleep
Accession number :
edsair.doi.dedup.....1d6101e3abfb3251ed5dd8e7dc91e466
Full Text :
https://doi.org/10.1093/sleep/zsaa180