Early morning sport scheduling is associated with poorer subjective sleep characteristics in British student-athletes.

This study presents the sleep characteristics of British student-athletes and examines the relationships between sport scheduling and time demands on sleep outcomes. Student-athletes (n = 157, 51% male) completed the Pittsburgh Sleep Quality Index (PSQI), Epworth Sleepiness Scale (ESS), and the Sleep Hygiene Index (SHI). Self-reported sleep characteristics on weekdays and weekends, weekly frequencies of early morning and late evening sport sessions, and academic-related and sport-related time demands were also collected. Questionnaires revealed a high prevalence of undesired sleep characteristics including poor sleep quality (global PSQI >5 in 49.0%) and low sleep durations on weekdays (25% reporting <7 h). Paired t-tests revealed significant differences in bedtime, waketime, sleep duration, and sleep onset latency between weekdays and weekends (all p < 0.01). Hierarchical regression analyses indicated that early morning sport frequency was a significant predictor of PSQI (ß = 0.30) and SHI (ß = 0.24) global scores, weekday waketimes (ß = -0.17), and weekday sleep durations (ß = -0.25; all p < 0.05) in models adjusted for participant characteristics. Late evening sport frequency, and academic-related and sport-related time demands, were not significant predictors of any sleep outcome. Adjusting sport scheduling to avoid early start times could provide a means to improve sleep outcomes and may improve sporting performance and academic attainment.

Behavioral interventions and behavior change techniques used to improve sleep outcomes in athlete populations: A scoping review.

BACKGROUND: Athletes display a high prevalence of undesired sleep characteristics that may affect both performance and wellbeing. OBJECTIVES: This scoping review aimed to identify and map the existing evidence of behavioral sleep interventions and their effects on sleep outcomes in athletes, and retrospectively code the behavior change techniques (BCTs) implemented using the Behavior Change Technique Taxonomy (BCTTv1). METHODS: Conducted following the JBI methodology for scoping reviews, four online databases were used to identify prospective interventions with at least one behavioral component in competitive athletes, and reporting a sleep outcome pre- and post-intervention. RESULTS: Thirty-three studies met the inclusion criteria, encompassing 892 participants with a median age of 23. Five intervention categories were identified (education, mind-body practices, direct, multi-component, and other), with each demonstrating mixed efficacy but the potential to improve sleep outcomes. The BCTs varied in type and frequency between each category, with only 18 unique BCTs identified across all studies. CONCLUSIONS: The varied efficacy of previous studies at improving sleep outcomes may be attributed to the lack of behavior change theory applied during intervention development. Designing interventions following a targeted specification of the behavioral problem, and the integration of corresponding BCTs should be considered in future research.