Evidence map›Paper›PMID 37759947›Full record

ArticleBrain sciences2023

Sleep Health, Individual Characteristics, Lifestyle Factors, and Marathon Completion Time in Marathon Runners: A Retrospective Investigation of the 2016 London Marathon.

Jesse D Cook, Matt K P Gratton, Amy M Bender, Penny Werthner, Doug Lawson, Charles R Pedlar, Courtney Kipps, Celyne H Bastien, Charles H Samuels, Jonathan Charest

Abstract read
In one paragraph

Article in Brain sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Trial
  2. Article
  3. Review
  4. 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

10 authors.

Jesse D CookDepartment of Psychiatry, University of Wisconsin-Madison, Madison, WI 53706, USA.
Matt K P GrattonDivision of Medical Informatics, Department of Internal Medicine, University of Kansas Medical Center, Kansas City, MO 66160, USA.
Amy M BenderFaculty of Kinesiology, University of Calgary, Calgary, AB T2N 1N4, Canada.ORCID 0000-0002-4086-2882
Penny WerthnerFaculty of Kinesiology, University of Calgary, Calgary, AB T2N 1N4, Canada.
Doug LawsonCentre for Sleep and Human Performance, Calgary, AB T2X 3V4, Canada.
Charles R PedlarFaculty of Sport, Allied Health, and Performance Science, Twickenham, St Mary's University, London TW1 4SX, UK.ORCID 0000-0002-3075-9101
Courtney KippsInstitute of Sport, Exercise and Health, University College London, London WC1E 6JB, UK.ORCID 0000-0002-5087-9602
Celyne H BastienÉcole de Psychologie, Université Laval, Québec City, QC G1V 0A6, Canada.
Charles H SamuelsFaculty of Kinesiology, University of Calgary, Calgary, AB T2N 1N4, Canada.
Jonathan CharestFaculty of Kinesiology, University of Calgary, Calgary, AB T2N 1N4, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Despite sleep health being critically important for athlete performance and well-being, sleep health in marathoners is understudied. This foundational study explored relations between sleep health, individual characteristics, lifestyle factors, and marathon completion time. Data were obtained from the 2016 London Marathon participants. Participants completed the Athlete Sleep Screening Questionnaire (ASSQ) along with a brief survey capturing individual characteristics and lifestyle factors. Sleep health focused on the ASSQ sleep difficulty score (SDS) and its components. Linear regression computed relations among sleep, individual, lifestyle, and marathon variables. The analytic sample (N = 943) was mostly male (64.5%) and young adults (66.5%). A total of 23.5% of the sample reported sleep difficulties (SDS ≥ 8) at a severity warranting follow-up with a trained sleep provider. Middle-aged adults generally reported significantly worse sleep health characteristics, relative to young adults, except young adults reported significantly longer sleep onset latency (SOL). Sleep tracker users reported worse sleep satisfaction. Pre-bedtime electronic device use was associated with longer SOL and longer marathon completion time, while increasing SOL was also associated with longer marathon completion. Our results suggest a deleterious influence of pre-bedtime electronic device use and sleep tracker use on sleep health in marathoners. Orthosomnia may be a relevant factor in the relationship between sleep tracking and sleep health for marathoners.

Indexed as

electronic device usemarathonorthosomniasleep healthsleep tracker

Identifiers

PMID37759947
PMCPMC10527296

What Socratic holds

Textmetadata
LicenceCC BY
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 Socratic graph.