Physical performance was significantly higher in the afternoon than in the morning across all menstrual phases (CMJ: p < 0.001, η² = 0.836).
Cognitive function was better in the afternoon, as indicated by improved performance on the Stroop test (p < 0.001, η² = 0.910).
Mood disturbances increased after competition, particularly in the morning and during the luteal phase (p < 0.001, η² = 0.961).
Fatigue levels were higher in the morning, especially after competitions, with a significant correlation to menstrual phases (Hooper score: p < 0.001, η² = 0.754).
Sleep quality was poorer in the morning following competition, as measured by the Pittsburgh Sleep Quality Index (PSQI: p < 0.001, η² = 0.627).
significantly influenced physical performance, cognitive function, mood, and sleep parameters.
Simplified
BACKGROUND: The influence of and on athletic performance and psychological responses is critical for optimizing training and competition strategies for female athletes. This study aimed to investigate the effects of time of day and menstrual cycle phases on the physical performance and psychological responses of elite female Tunisian volleyball players.
METHODS: Thirteen elite female volleyball players were assessed during three different phases of their menstrual cycle (menstrual, follicular, and luteal) and at two different times of day (morning and evening). Physical performance was evaluated using the Modified Agility Test (MAT), Reactive Agility Test (RAT), and Repeated Sprint Ability (RSA) Test. Psychological responses were measured using the Profile of Mood States (POMS), Hooper's Questionnaire, Pittsburgh Sleep Quality Index, Epworth Sleepiness Scale, Vis-Morgen Questionnaire, and Spiegel Questionnaire.
RESULTS: Significant effects of menstrual cycle, time of day, and competition on physical performance, cognitive function, mood, and sleep parameters were found. Physical performance, including the Countermovement Jump (CMJ), the Modified Agility T-test (MAT) and the Reactive Agility test (RAT), was higher in the afternoon than in the morning across all menstrual phases (CMJ: p < 0.001, η² = 0.836; MAT: p < 0.001, η² = 0.777; RAT: p < 0.001, η² = 0.859). After the competition, performance decreased significantly, especially in the follicular and luteal phases. As measured by the Stroop test, cognitive function showed significant diurnal effects (p < 0.001, η² = 0.910), with pre-competition performance being better in the afternoon. Mood disturbances (POMS) increased after the competition, especially in the morning and during the luteal phase (p < 0.001, η² = 0.961). Sleep parameters were significantly influenced by time and menstrual cycle, with higher fatigue (Hooper score: p < 0.001, η² = 0.754) and poorer sleep quality (PSQI: p < 0.001, η² = 0.627) in the morning, especially after the competition.
CONCLUSION: Our results suggest that aligning high-intensity training and competitions with afternoon circadian peaks may enhance physical and cognitive performance in elite female athletes. Recovery strategies and workload adjustments should account for menstrual phases, particularly reducing morning demands during the luteal phase to mitigate fatigue and mood disruptions. Integrating circadian timing with menstrual cycle monitoring offers a practical, evidence-based approach to optimize athlete readiness and resilience.
Key numbers
1.262
CMJ Performance Increase
Mean difference in CMJ performance between afternoon and morning sessions.
4.154
Mood Disturbance Increase
Mean difference in POMS scores post-competition during the luteal phase.
2.615
Fatigue Score Increase
Mean difference in HOOPER scores during the luteal phase post-competition.
Full Text
We can’t show the full text here under this license.
Declarations. Human ethics and consent to participate: This study was conducted in accordance with the Declaration of Helsinki guidelines and was approved by the Research Ethics Committee of the ISSEP Sfax prior to the start of the study. Written informed consent was obtained from all participants after a thorough explanation of the study’s objectives, procedures, benefits, and potential risks. Informed consent: Participants gave written informed consent to participate in the present study and to its publication. Consent for publication: Not Applicable. In preparing this paper, the authors used ChatGPT model 4 on November 11, 2024, to revise some passages of the manuscript, to double-check for any grammar mistakes or improve academic English only [93, 94]. After using this tool, the authors have reviewed and edited the content as necessary and take full responsibility for the content of the publication. Competing interests: The authors declare no competing interests.
