Evidence map›Paper›PMID 35713743›Full record

ArticleSports medicine - open2022

Sleep Regularity and Predictors of Sleep Efficiency and Sleep Duration in Elite Team Sport Athletes.

Shona L Halson, Rich D Johnston, Laura Piromalli, Benita J Lalor, Stuart Cormack, Gregory D Roach, Charli Sargent

Open access · goldAbstract read
In one paragraph

Article in Sports medicine - open, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
5.9field-weighted citation impact, top 3% 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

16 citing papers in PubMed, 33 citations in OpenAlex.

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  15. Sleep and Performance in Professional Athletes.Current sleep medicine reports · 2023
    Review
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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 at 3 institutions in 2 countries.

Shona L HalsonSchool of Behavioural and Health Sciences, Australian Catholic University, McAuley at Banyo, Brisbane, Australia. shona.halson@acu.edu.au.ORCID http://orcid.org/0000-0002-1047-3878
Rich D JohnstonSchool of Behavioural and Health Sciences, Australian Catholic University, McAuley at Banyo, Brisbane, Australia.
Laura PiromalliWestern Australia Institute of Sport, Mt Claremont, Australia.
Benita J LalorSchool of Behavioural and Health Sciences, Australian Catholic University, Melbourne, Australia.
Stuart CormackSports Performance, Recovery, Injury and New Technologies (SPRINT) Research Centre, Australian Catholic University, Brisbane, QLD, Australia.
Gregory D RoachAppleton Institute for Behavioural Science, Central Queensland University, Wayville, Australia.
Charli SargentAppleton Institute for Behavioural Science, Central Queensland University, Wayville, Australia.
Australian Catholic University · AUCentral Queensland University · AULeeds Beckett University · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMany elite athletes have suboptimal sleep duration and efficiency, potentially due to factors that may impact sleep onset and offset times. Variability in sleep onset and offset may negatively influence sleep. The sleep regularity index (SRI) is a novel metric for sleep regularity, however there are no published descriptions of SRI in elite athletes. Further, contributors to sleep efficiency and duration in elite athletes using objective measures have not been explored.

methodsSleep was monitored over a minimum of seven consecutive days (7 to 43)-in 203 elite team sport athletes (age range = 19-36 years; female, n = 79; male, n = 124, total sleep nights = 1975) using activity monitoring and sleep diaries. The sleep regularity index (SRI) was calculated to reflect the night-to-night shifts in sleep by accounting for changes in sleep onset and sleep offset. Sleep characteristics were compared between regular and irregular sleepers and important contributors to sleep efficiency and total sleep time were assessed using multiple linear regression models.

resultsThe median sleep regularity index and interquartile range were 85.1 (81.4 to 88.8). When compared to irregular sleepers, regular sleepers demonstrated (1) significantly greater sleep efficiency (p = 0.006; 0.31 medium effect size [ES]), (2) significantly less variability in total sleep time (- p ≤ 0.001; - 0.69, large ES) and sleep efficiency (- 0.34, small ES), (3) similar total sleep time and (4) significantly less variation in sleep onset (p ≤ 0.001; - 0.73, large ES) and offset (p ≤ 0.001; - 0.74, large ES) times. Sleep characteristics explained 73% and 22% of the variance in total sleep time and sleep efficiency, respectively. The most important contributor to total sleep time was a later sleep offset time, while the most important contributors to sleep efficiency were an earlier bedtime and less variable sleep onset times.

conclusionsBedtime and a consistent sleep onset time are important factors associated with sleep efficiency in athletes, while sleep offset is an important factor for total sleep time. Coaches and staff can assist their athletes by providing training schedules that allow for both regularity and sufficiency of time in bed where possible.

Indexed as

AthleteSleep regularity indexTeam sportVariability

Identifiers

PMID35713743
PMCPMC9206056
OpenAlexW4283013862

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.