Sleep Characteristics in Esport Players and Associations With Game Performance

Residual Dynamic Structural Equation Modeling

Dados Bibliográficos

ID5284752
AutoresFrode Moen (0000-0002-6290-5070, Norwegian University of Science and Technology, autor correspondente), Marte Vatn (Norwegian University of Science and Technology), Maja Olsen (Norwegian University of Science and Technology), Jan Arvid Haugan (0000-0002-5758-7813, Norwegian University of Science and Technology), Věra Skalická (0000-0003-1443-1656, Norwegian University of Science and Technology)
Ano2022
Volume3
Páginas697535-697535
Data de publicação2022-01-13
Peer ReviewedSim
Open AccessSim
TipoARTICLE
PeriódicoFrontiers in Sports and Active Living (JOURNAL)
Identificadores do periódicoISSN: 2624-9367 • E-ISSN: 2624-9367
EditoraFrontiers Media SA (PUBLISHER • CH)
DOI10.3389/fspor.2021.697535
PMID35098116
OpenAlexW4206750323
IdiomaEN
Citações recebidas3
Referências citadas62

The current study aimed to examine sleep characteristics of esport players and the stipulated effects of game performance on consecutive sleep characteristics using residual dynamic structural equation modeling (RDSEM). A sample of 27 Counterstrike players with a mean age of 181⁄2 years participated in the current study. Sleep was detected over a period of 56 days with a Somnofy sleep monitor that utilizes an impulse radio ultra-wideband puls radar and Dopler technology, and weekly game performance was reported by the players. The results showed that esport players' sleep characteristics were in the lower levels of recommended guidelines and that sleep onset started later and sleep offset ended later in the morning compared with athletes from other traditional sports. The esport players displayed stable patterns in sleep onset, sleep offset, time in bed, sleep efficiency and non-REM respiration rates per minute (NREM RPM). On the between-person level, esport players with better game performance spent more time sleeping (r = 0.55) and scored lower on NREM RPM (r = −0.44). Unstandardized within-person cross-lagged paths showed that better game performance predicted subsequent earlier sleep offset. The within-level standardized estimates of the cross-lagged paths revealed that participants with better game performance spent subsequently more time in deep sleep (0.20), less time in light sleep (−0.14), less time in bed (−0.16), and displayed lower NREM RPM (−0.21), earlier sleep offset (−0.21), and onset (−0.09). The findings of better game performance being related to better sleep are discussed in terms of existing knowledge on how stress responses elicitated by poor performance might impact on non-REM respiration rates and sleep

Audiology · Electroencephalography · Non-rapid eye movement sleep · Psychiatry · Simulation · Sleep (system call · Computer Science · Medicine · Physical Activity and Health · Psychology · Sleep and related disorders · Sleep and Wakefulness Research