Cédric Leduc1, Jason Tee1,2, Jonathon Weakley1,3, Carlos Ramirez1,4, Ben Jones1,4,5,6,7,8. 1. Carnegie Applied Rugby Research (CARR) Centre, Institute for Sport, Physical Activity and Leisure, Carnegie School of Sport, Leeds Beckett University, Leeds, UK. 2. Department of Sport Studies, Faculty of Applied Sciences, Durban University of Technology, Durban, South Africa. 3. School of Behavioral and Health Sciences, Australian Catholic University, Brisbane, Queensland, Australia. 4. Yorkshire Carnegie Rugby Union Football Club, Leeds, UK. 5. Leeds Rhinos Rugby League Club, Leeds, UK. 6. England Performance Unit, The Rugby Football League, Leeds, UK. 7. School of Science and Technology, University of New England, Armidale, New South Wales, Australia. 8. Division of Exercise Science and Sports Medicine, Department of Human Biology, Faculty of Health Sciences, the University of Cape Town and the Sports Science Institute of South Africa, Cape Town, South Africa.
Abstract
BACKGROUND: Student-athletes are subject to significant demands due to their concurrent sporting and academic commitments, which may affect their sleep. This study aimed to compare the self-reported sleep quality, quantity, and intraindividual variability (IIV) of students and student-athletes through an online survey. HYPOTHESIS: Student-athletes will have a poorer sleep quality and quantity and experience more IIV. STUDY DESIGN: Case-control study. LEVEL OF EVIDENCE: Level 4. METHODS: Sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI), while sleep quantity and IIV were assessed using the Consensus Sleep Diary. Initially, the PSQI and additional questions regarding sport participation habits were completed by 138 participants (65 students, 73 student-athletes). From within this sample, 44 participants were recruited to complete the sleep diary for a period of 14 days. RESULTS: The mean PSQI score was 6.89 ± 3.03, with 65% of the sample identified as poor sleepers, but no difference was observed between students and student-athletes. Analysis of sleep patterns showed only possibly to likely small differences in sleep schedule, sleep onset latency, and subjective sleep quality between groups. IIV analysis showed likely moderate to possibly small differences between groups, suggesting more variable sleep patterns among student-athletes. CONCLUSION: This study highlights that sleep issues are prevalent within the university student population and that student-athletes may be at greater risk due to more variable sleep patterns. CLINICAL RELEVANCE: University coaches should consider these results to optimize sleep habits of their student-athletes.
BACKGROUND: Student-athletes are subject to significant demands due to their concurrent sporting and academic commitments, which may affect their sleep. This study aimed to compare the self-reported sleep quality, quantity, and intraindividual variability (IIV) of students and student-athletes through an online survey. HYPOTHESIS: Student-athletes will have a poorer sleep quality and quantity and experience more IIV. STUDY DESIGN: Case-control study. LEVEL OF EVIDENCE: Level 4. METHODS: Sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI), while sleep quantity and IIV were assessed using the Consensus Sleep Diary. Initially, the PSQI and additional questions regarding sport participation habits were completed by 138 participants (65 students, 73 student-athletes). From within this sample, 44 participants were recruited to complete the sleep diary for a period of 14 days. RESULTS: The mean PSQI score was 6.89 ± 3.03, with 65% of the sample identified as poor sleepers, but no difference was observed between students and student-athletes. Analysis of sleep patterns showed only possibly to likely small differences in sleep schedule, sleep onset latency, and subjective sleep quality between groups. IIV analysis showed likely moderate to possibly small differences between groups, suggesting more variable sleep patterns among student-athletes. CONCLUSION: This study highlights that sleep issues are prevalent within the university student population and that student-athletes may be at greater risk due to more variable sleep patterns. CLINICAL RELEVANCE: University coaches should consider these results to optimize sleep habits of their student-athletes.
Entities:
Keywords:
collegiate athlete; recovery; sport; training load
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