Identifying Factors Associated with Sleep Disorders and Treatment Avoidance among Collegiate Student-Athletes

Introduction: Mental health concerns among collegiate students-athletes are exacerbated by poor sleep, and this population experiences elevated risk for irregular sleep patterns and associated sleep disorders. Interventions aimed at early identification of student-athletes experiencing sleep disorders and guiding them to treatment can contribute to improved mental health in this group. The present study’s objective was to clarify risk-factors associated with increased likelihood of sleep disorders and treatment avoidance in student-athletes. Methods: Data were self-reported survey responses related to sleep disorders, from US college/university varsity athletes (n=51,882) completing the 2011-2019 National College Health Assessments (NCHA). Outcomes: The primary outcomes that we examined were feeling exhausted, sleep disorder diagnoses, and the secondary outcome we examined was related treatment. Risk factors: The primary risk factors that we examined were year in school, gender, sexual orientation, race/ethnicity, school type, international student status, history of mental health treatment, receiving information on sleep disorders, and poor sleep impeding academic performance. Results: Over 75% of student-athletes reported feeling exhausted in the past year, whereas 3.8% reported a sleep disorder diagnosis, and only 2.2% received treatment. Gender, sexual orientation, race/ethnicity, school type, and history of mental health treatment were significant predictors of the symptom and of sleep disorder diagnoses, but only history of mental health treatment was a predictor of receiving concurrent sleep disorder treatment. Discussion: While the majority of student-athletes reported feeling exhausted, few were diagnosed with sleep disorders and even fewer received treatment. Several factors affected risk for poor sleep or probability of receiving treatment. Healthcare professionals working with student-athletes can apply this information to screen for, and help treat, individuals at elevated risk for disordered sleep.