Evidence map›Paper›PMID 39639100›Full record

ArticleNPJ digital medicine2024

The real-world association between digital markers of circadian disruption and mental health risks.

Minki P Lee, Dae Wook Kim, Yu Fang, Ruby Kim, Amy S B Bohnert, Srijan Sen, Daniel B Forger

Abstract read
In one paragraph

Article in NPJ digital medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
–field-weighted citation impact
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

13 citing papers in PubMed.

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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

7 authors.

Minki P Lee *Department of Mathematics, University of Michigan, Ann Arbor, MI, 48109, USA.ORCID http://orcid.org/0009-0007-0976-8285
Dae Wook Kim *Department of Mathematics, University of Michigan, Ann Arbor, MI, 48109, USA. daewook@kaist.ac.kr.ORCID http://orcid.org/0000-0003-1060-891X
Yu FangMichigan Neuroscience Institute, University of Michigan, Ann Arbor, MI, 48109, USA.ORCID http://orcid.org/0000-0002-2810-806X
Ruby KimDepartment of Mathematics, University of Michigan, Ann Arbor, MI, 48109, USA.
Amy S B BohnertDepartment of Psychiatry, University of Michigan, Ann Arbor, MI, 48109, USA.
Srijan SenMichigan Neuroscience Institute, University of Michigan, Ann Arbor, MI, 48109, USA.ORCID http://orcid.org/0000-0003-4495-495X
Daniel B ForgerDepartment of Mathematics, University of Michigan, Ann Arbor, MI, 48109, USA. forger@umich.edu.ORCID http://orcid.org/0000-0001-7581-4031

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

While circadian disruption is recognized as a potential driver of depression, its real-world impact is poorly understood. A critical step to addressing this is the noninvasive collection of physiological time-series data outside laboratory settings in large populations. Digital tools offer promise in this endeavor. Here, using wearable data, we first quantify the degrees of circadian disruption, both between different internal rhythms and between each internal rhythm and the sleep-wake cycle. Our analysis, based on over 50,000 days of data from over 800 first-year training physicians, reveals bidirectional links between digital markers of circadian disruption and mood both before and after they began shift work, while accounting for confounders such as demographic and geographic variables. We further validate this by finding clinically relevant changes in the 9-item Patient Health Questionnaire score. Our findings validate a scalable digital measure of circadian disruption that could serve as a marker for psychiatric intervention.

Identifiers

PMID39639100
PMCPMC11621392

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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.