Evidence map›Paper›PMID 40258391›Full record

ArticleJournal of sleep research2025

Predictors of Sleep Latency From the Multiple Sleep Latency Test: A Random Forest Investigation in a Community Sample.

Jesse D Cook, Filipe Barata, David T Plante, Steve Woodward, Jamie M Zeitzer, Renske Lok

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of sleep research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

6 authors.

Jesse D CookDepartment of Psychiatry, University of Wisconsin-Madison, Madison, Wisconsin, USA.ORCID 0000-0003-1905-0262
Filipe BarataETH Zurich, Center for Digital Health Interventions, Zürich, Switzerland.
David T PlanteDepartment of Psychiatry, University of Wisconsin-Madison, Madison, Wisconsin, USA.
Steve WoodwardNational Center for PTSD, Veterans Affairs Palo Alto Health Care System, Palo Alto, California, USA.
Jamie M ZeitzerMental Illness Research Education and Clinical Center, Veterans Affairs Palo Alto Health Care System, Palo Alto, California, USA.
Renske LokDepartment of Psychiatry and Behavioral Sciences, Stanford University, Stanford, California, USA.ORCID 0000-0003-1684-5625

Funding

University of Wisconsin Institute for Clinical and Translational ResearchUL1TR002373 · NCATS · UNIVERSITY OF WISCONSIN-MADISON · PI ELIZABETH S BURNSIDE, Allan R. Brasier · 2017 to 2026
$75.9M
INSTITUTIONAL CTSA (UW-MADISON): CLINICAL TRIALSUL1RR025011 · NCRR · UNIVERSITY OF WISCONSIN-MADISON · PI DREZNER, MARC KENNETH · 2007 to 2011
$29.5M
EPIDEMIOLOGY OF SLEEP-DISORDERED BREATHING IN ADULTSR01HL062252 · NHLBI · UNIVERSITY OF WISCONSIN-MADISON · PI PEPPARD, PAUL E · 1999 to 2013
$14.1M
National Sleep Research Resource (NSRR)R24HL114473 · NHLBI · BRIGHAM AND WOMEN'S HOSPITAL · PI REDLINE, SUSAN S., ZHANG, GUO-QIANG · 2013 to 2017
$7.5M
Longitudinal Associations of Midlife Sleep Duration and Quality with Later Life Cognitive and Physical Functioning DeclineR01AG058680 · NIA · UNIVERSITY OF WISCONSIN-MADISON · PI HAGEN, ERIKA W · 2018 to 2021
$2.6M
The REST Study: A Longitudinal, Bidirectional Examination of Retirement And SleepR01AG036838 · NIA · UNIVERSITY OF WISCONSIN-MADISON · PI PEPPARD, PAUL E · 2010 to 2014
$2.5M
Application of precision medicine to phototherapy: a stepped care approach to consolidate sleep and slow cognitive decline in older adultsK99AG084846 · NIA · STANFORD UNIVERSITY · PI LOK, RENSKE · 2024 to 2025
$262k
NCATS NIH HHS UL1 TR002373NCRR NIH HHS 1UL1RR025011NCRR NIH HHS UL1 RR025011NHLBI NIH HHS 75N92019R002NHLBI NIH HHS R01 HL062252NHLBI NIH HHS R01HL62252NHLBI NIH HHS R24 HL114473NIA NIH HHS K99AG08484NIA NIH HHS K99 AG084846NIA NIH HHS R01 AG036838NIA NIH HHS R01AG036838NIA NIH HHS R01 AG058680NIA NIH HHS R01AG058680U.S. National Institutes of Health
6 · The paper itself

Abstract

This study aimed to advance the understanding of factors that predict mean sleep latency (MSL) on the multiple sleep latency test (MSLT) by applying machine learning methodology on a high-dimensional dataset from a large community sample. A cross-sectional analytic dataset of first visit clinical-protocol MSLTs (without shift workers) was developed from the Wisconsin Sleep Cohort Study, a community-based longitudinal study of middle-aged to older adults in Wisconsin, USA. Fifty predictors captured demographics, medical and psychiatric health, sleep (diary; polysomnography [PSG]) and circadian characteristics. The random forest (RF) algorithm identified the 10 most important predictors, which underwent subsequent regression analyses. Primary analyses focused on MSLT MSL, whereas secondary analyses centred on nap-specific sleep latencies. Post hoc analyses further explored the relationship between circadian preference and MSLT MSL. The primary sample (n = 301) of middle-aged adults (mean age = 57.5 ± 7.71 years) was predominantly non-Hispanic White (97%) and nearly equal across sexes (percentage female = 51.8%). RF model showed low explanatory value for MSLT MSL (R

Indexed as

Machine LearningSleep LatencyAgedCircadian RhythmCross-Sectional StudiesFemaleHumansLongitudinal StudiesMaleMiddle AgedPolysomnographyRandom ForestWisconsincircadian preferencedaytime sleepinessmachine learningmean sleep latencymultiple sleep latency testrandom forest

Identifiers

PMID40258391
PMCPMC12320902

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.