Evidence map›Paper›PMID 32918087›Full record

ArticleSleep2021

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

Philip Cheng, Olivia Walch, Yitong Huang, Caleb Mayer, Chaewon Sagong, Andrea Cuamatzi Castelan, Helen J Burgess, Thomas Roth, Daniel B Forger, Christopher L Drake

Open access · bronzeAbstract read
In one paragraph

Article in Sleep, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
43citing papers in PubMed, 1 pooled it
8.0field-weighted citation impact, top 2% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

43 citing papers in PubMed, 1 synthesis or guideline pooled it, 85 citations in OpenAlex.

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  18. The relationship between sleep and circadian-sleep phase angles based on dim light melatonin onset predicted from light and activity data.Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine · 2025
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 2 institutions in 1 country.

Philip ChengSleep Disorders and Research Center, Henry Ford Health System, Detroit, MI.
Olivia WalchDepartment of Mathematics, University of Michigan, Ann Arbor, MI.
Yitong HuangDepartment of Mathematics, University of Michigan, Ann Arbor, MI.
Caleb MayerDepartment of Mathematics, University of Michigan, Ann Arbor, MI.
Chaewon SagongSleep Disorders and Research Center, Henry Ford Health System, Detroit, MI.
Andrea Cuamatzi CastelanSleep Disorders and Research Center, Henry Ford Health System, Detroit, MI.
Helen J BurgessDepartment of Mathematics, University of Michigan, Ann Arbor, MI.
Thomas RothSleep Disorders and Research Center, Henry Ford Health System, Detroit, MI.
Daniel B ForgerDepartment of Mathematics, University of Michigan, Ann Arbor, MI.
Christopher L DrakeSleep Disorders and Research Center, Henry Ford Health System, Detroit, MI.
Henry Ford Health System · USUniversity of Michigan · US

Funding

Clinical translation of phenotypes of shift work disorderK23HL138166 · NHLBI · HENRY FORD HEALTH SYSTEM · PI CHENG, PHILIP · 2017 to 2021
$761k
NHLBI NIH HHS K23 HL138166
6 · The paper itself

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 (<10 lux). Data from actigraphy were provided as input to a mathematical model to generate predictions of circadian phase. Agreement was assessed and compared to average sleep timing on non-workdays as a proxy of DLMO. Model code and an open-source prototype assessment tool are available (www.predictDLMO.com).

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.

Indexed as

MelatoninWearable Electronic DevicesActigraphyAdultCircadian RhythmHumansLightPhotometrySleepWristMelatoninactigraphycircadian rhythmmathematical modelnight shift work

Identifiers

PMID32918087
PMCPMC8240654
OpenAlexW3085362956

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.