Cargando…

Soccer, Sleep, Repeat: Effects of Training Characteristics on Sleep Quantity and Sleep Architecture

Due to the high demands of competitive sports, the sleep architecture of adolescent athletes may be influenced by their regular training. To date, there is no clear evidence on how training characteristics (intensity, time of day, number of sessions) influence sleep quality and quantity. 53 male soc...

Descripción completa

Detalles Bibliográficos
Autores principales: Frytz, Patricia, Heib, Dominik P. J., Hoedlmoser, Kerstin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10455405/
https://www.ncbi.nlm.nih.gov/pubmed/37629536
http://dx.doi.org/10.3390/life13081679
_version_ 1785096443093057536
author Frytz, Patricia
Heib, Dominik P. J.
Hoedlmoser, Kerstin
author_facet Frytz, Patricia
Heib, Dominik P. J.
Hoedlmoser, Kerstin
author_sort Frytz, Patricia
collection PubMed
description Due to the high demands of competitive sports, the sleep architecture of adolescent athletes may be influenced by their regular training. To date, there is no clear evidence on how training characteristics (intensity, time of day, number of sessions) influence sleep quality and quantity. 53 male soccer players (M = 14.36 years, SD = 0.55) of Austrian U15 (n = 45) and U16 elite teams (n = 8) were tested on at least three consecutive days following their habitual training schedules. Participants completed daily sleep protocols (7 a.m., 8 p.m.) and questionnaires assessing sleep quality (PSQI), chronotype (D-MEQ), competition anxiety (WAI-T), and stress/recovery (RESTQ). Electrocardiography (ECG) and actigraphy devices measured sleep. Using sleep protocols and an ECG-based multi-resolution convolutional neural network (MCNN), we found that higher training intensity leads to more wake time, that later training causes longer sleep duration, and that one training session per day was most advantageous for sleep quality. In addition, somatic complaints assessed by the WAI-T negatively affected adolescent athletes’ sleep. Individual training loads and longer recovery times after late training sessions during the day should be considered in training schedules, especially for adolescent athletes. MCNN modeling based on ECG data seems promising for efficient sleep analysis in athletes.
format Online
Article
Text
id pubmed-10455405
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-104554052023-08-26 Soccer, Sleep, Repeat: Effects of Training Characteristics on Sleep Quantity and Sleep Architecture Frytz, Patricia Heib, Dominik P. J. Hoedlmoser, Kerstin Life (Basel) Article Due to the high demands of competitive sports, the sleep architecture of adolescent athletes may be influenced by their regular training. To date, there is no clear evidence on how training characteristics (intensity, time of day, number of sessions) influence sleep quality and quantity. 53 male soccer players (M = 14.36 years, SD = 0.55) of Austrian U15 (n = 45) and U16 elite teams (n = 8) were tested on at least three consecutive days following their habitual training schedules. Participants completed daily sleep protocols (7 a.m., 8 p.m.) and questionnaires assessing sleep quality (PSQI), chronotype (D-MEQ), competition anxiety (WAI-T), and stress/recovery (RESTQ). Electrocardiography (ECG) and actigraphy devices measured sleep. Using sleep protocols and an ECG-based multi-resolution convolutional neural network (MCNN), we found that higher training intensity leads to more wake time, that later training causes longer sleep duration, and that one training session per day was most advantageous for sleep quality. In addition, somatic complaints assessed by the WAI-T negatively affected adolescent athletes’ sleep. Individual training loads and longer recovery times after late training sessions during the day should be considered in training schedules, especially for adolescent athletes. MCNN modeling based on ECG data seems promising for efficient sleep analysis in athletes. MDPI 2023-08-02 /pmc/articles/PMC10455405/ /pubmed/37629536 http://dx.doi.org/10.3390/life13081679 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Frytz, Patricia
Heib, Dominik P. J.
Hoedlmoser, Kerstin
Soccer, Sleep, Repeat: Effects of Training Characteristics on Sleep Quantity and Sleep Architecture
title Soccer, Sleep, Repeat: Effects of Training Characteristics on Sleep Quantity and Sleep Architecture
title_full Soccer, Sleep, Repeat: Effects of Training Characteristics on Sleep Quantity and Sleep Architecture
title_fullStr Soccer, Sleep, Repeat: Effects of Training Characteristics on Sleep Quantity and Sleep Architecture
title_full_unstemmed Soccer, Sleep, Repeat: Effects of Training Characteristics on Sleep Quantity and Sleep Architecture
title_short Soccer, Sleep, Repeat: Effects of Training Characteristics on Sleep Quantity and Sleep Architecture
title_sort soccer, sleep, repeat: effects of training characteristics on sleep quantity and sleep architecture
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10455405/
https://www.ncbi.nlm.nih.gov/pubmed/37629536
http://dx.doi.org/10.3390/life13081679
work_keys_str_mv AT frytzpatricia soccersleeprepeateffectsoftrainingcharacteristicsonsleepquantityandsleeparchitecture
AT heibdominikpj soccersleeprepeateffectsoftrainingcharacteristicsonsleepquantityandsleeparchitecture
AT hoedlmoserkerstin soccersleeprepeateffectsoftrainingcharacteristicsonsleepquantityandsleeparchitecture