Evidence map›Paper›PMID 39922927›Full record

ReviewEuropean journal of applied physiology2025

The effects, mechanisms and strategies of daytime napping on athletes: a narrative review.

Haitong Yu, Chengbo Yang, Chuanming Xu, Yan Zhuang

Abstract readReview
PubMed Publisher
In one paragraph

Review in European journal of applied physiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Trial
  2. Review
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

4 authors.

Haitong YuSchool of Sports Training, Chengdu Sport University, Chengdu, China. yht522@163.com.ORCID http://orcid.org/0009-0009-8648-9196
Chengbo YangSchool of Sports Training, Chengdu Sport University, Chengdu, China.
Chuanming XuChengdu College of University of Electronic Science and Technology of China, Chengdu, China.
Yan ZhuangSchool of Sports, Southwest University, Chongqing, China.

Funding

Sichuan Province Science and Technology Support Program 2023YFS0452
6 · The paper itself

Abstract

Athletes generally suffer from insufficient sleep duration, lower sleep efficiency, and a high overall prevalence of insomnia. Daytime napping has been demonstrated to supplement nighttime sleep in athletes; however, recent controversial findings warrant further consideration. This review synthesized existing studies on the effects of daytime naps on athletes, explored potential mechanisms of daytime napping, and analyzed instances of ineffective interventions or negative outcomes. Daytime napping functions as a restorative strategy to counteract sleep deprivation or the post-lunch dip, assisting athletes in recovering anaerobic capacity, agility, reaction time, and alertness, with potential mechanisms including the reduction of sleepiness through adherence to circadian rhythms, decreased subjective soreness and fatigue attributed to autonomic functioning, and improved respiratory performance. The optimal nap period occurs between 13:00 and 15:00, with a 5-6 h interval between morning awakening and nap initiation. Depending on the athlete's nighttime sleep, opt for a 20 ~ 40 or 60 ~ 90 min nap with at least 60 min between the nap and subsequent exercise to reduce sleep inertia. The intervention efficacy of daytime napping was correlated with exercise intensity. A nap program must be developed based on the specific athletic demands of the sport in practical application.

Indexed as

AthletesAthletic PerformanceCircadian RhythmSleepExerciseHumansSleep DeprivationAthletesDaytime nappingDaytime recoverySports performance

Identifiers

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.