Assessment of sleep health in collegiate athletes using the Athlete Sleep Screening Questionnaire

Irregular sleep/wake patterns in student-athletes exposed to early morning training

This study aimed to examine the sleep parameters and sleep/wake regularity of a cohort of student-athletes who start training between 06:30 and 07:00. Twenty-one male Rugby Union players, aged 21 ± 2 years and competing at a national level, were assessed using actigraphy over two weeks, and the Athlete Sleep Screening Questionnaire (ASSQ). Sleep/wake regularity was calculated using the Sleep Regularity Index (SRI). Wilcoxon signed-rank tests showed that nocturnal sleep preceding morning training had a significantly shorter sleep duration (1.8 hr, r = .67), and advanced sleep onset (0.9 hr, r = .50) and sleep offset times (3.2 hr, r = .85) compared to nocturnal sleep preceding free days. The variability of training demands resulted in an inconsistent sleep pattern between consecutive days, resulting in a median SRI score of 67.0 (interquartile range: 17.0). Pearson correlations revealed that lower SRI was significantly associated with a higher daily sleep duration including naps (r = -.62), delayed sleep onset (r = -.50) and sleep offset (r = -.60), and a later chronotype assessed using the ASSQ (r = .52). These findings indicate that early morning training is a factor contributing to irregular sleep/wake patterns in student-athletes, and where feasible should be scheduled at an alternative time.

Sleep Status and Chronotype in University Athletes with and without Chronic Low Back Pain: A Cross-Sectional Study

Objective  This study aimed to evaluate the status of sleep, chronotype, and related variables of university athletes with and without chronic low back pain (CLBP), to find the correlation between CLBP, sleep difficulty score (SDS), and chronotype, and to determine if SDS and chronotype predict CLBP. Methods  Ninety-two university athletes [46 with CLBP (Age: 22.08±2.74 years) and 46 healthy athletes (Age: 22.32±3.11 years) completed the athlete sleep screening questionnaire (ASSQ), also, their demographic, anxiety, depression, and sports-related details were collected. A Pearson correlation and logistic regression models (univariate and multivariate) were used for the statistical analysis. Results  The results demonstrated a higher SDS and evening type preference in CLBP athletes, a significant negative correlation between CLBP and chronotype (r = -0.40, p <0.01), a significant correlation between SDS and CLBP (r = 0.25, p  = 0.01). SDS and chronotype were not found to be significant independent predictors of CLBP. Conclusion  This study concludes that there exists a correlation of CLBP, SDS, and chronotype However, despite the relationship, SDS and chronotype cannot predict CLBP.

Snooze it or Lose it: Understanding Sleep Disturbance and Injuries in Soccer and Basketball Student-Athletes

OBJECTIVES

To assess the sleep characteristics of collegiate soccer and basketball student-athletes and explore the associations between sleep and injury risk.

DESIGN

Cohort study.

SETTING

NCAA D1 and NAIA Tier 1.

PARTICIPANTS

One hundred eighty-one collegiate soccer and basketball student-athletes (42% female; mean age: 20.0 ± 1.7 years).

INDEPENDENT VARIABLES

Questionnaires were administered during the 2020/2021 and 2021/2022 preseason, collecting demographic, injury history, medical history, and sleep information, including sleep difficulty category scores of 0 to 4 (none), 5 to 7 (mild), and ≥8 (moderate/severe) and other sleep disturbance measures derived from the Athlete Sleep Screening Questionnaire (ASSQ), including insufficient sleep duration (<7 hours of sleep) and poor subjective sleep quality.

MAIN OUTCOME MEASURES

All-complaint knee and ankle injuries.

RESULTS

According to the ASSQ, 25.4% (95% confidence interval [CI], 17.9-34.3) of the student-athletes had mild sleep difficulty and 12.7% (95% CI, 7.3-20.1) had moderate/severe sleep difficulty. 36.1% (95% CI, 29.1-43.6) had insufficient sleep duration. 17.1% (95% CI, 11.7-23.7) were not satisfied with the quality of their sleep (poor sleep quality), and 13.8% (95% CI, 9.1-19.7) had an "eveningness" chronotype. Based on multivariable logistic regression models, student-athletes with poor sleep quality had significantly higher odds for injury (OR: 2.2, 95% CI, 1.04-4.79, P = 0.039).

CONCLUSIONS

Clinically relevant dysfunctional sleep patterns are prevalent among collegiate soccer and basketball student-athletes. Poor sleep quality was significantly associated with injury risk among student-athletes. Findings suggest a substantial sleep problem in collegiate soccer and basketball student-athletes and warrant that student-athletes are regularly screened and timely interventions applied.

Sex Differences in Mental Health Symptoms in Elite Athletes: A Systematic Review and Meta-analysis

CONTEXT

Mental health is a growing area of concern for elite athletes.

OBJECTIVE

To determine the sex differences in mental health symptoms in elite athletes.

DATA SOURCES

PubMed, EMBASE, and Cochrane Library databases were used.

STUDY SELECTION

Included studies included comparisons of mental health symptoms of athletes by sex.

STUDY DESIGN

Systematic review and meta-analysis were conducted following the PRISMA guidelines.

LEVEL OF EVIDENCE

Level 2a.

DATA EXTRACTION

The rate ratio (RR) was calculated as the rates in female and male athletes. Data were pooled using a random-effects model.

RESULTS

Of 1945 articles identified, 60 articles were included. Male athletes reported higher alcohol misuse (RR, 0.74; CI, 0.68-0.80), illicit drug abuse (RR, 0.82; CI, 0.75-0.89), and gambling problems (RR, 0.14; CI, 0.08-0.25). Female athletes reported higher overall anxiety (RR, 1.17; CI, 1.08-1.27), depression (RR, 1.42; CI, 1.31-1.54), distress (RR, 1.98; CI, 1.40-2.81), and disordered eating (RR, 2.19; CI, 1.58-3.02). Sleep disturbances were reported at similar rates in male and female athletes (RR, 1.13; CI, 0.98-1.30).

CONCLUSION

Female and male athletes have significant differences in reported mental health symptoms. Female athletes are more likely to report anxiety, depression, distress, and disordered eating, while male athletes report more alcohol misuse, illicit drug abuse, and gambling. Monitoring and evaluation of mental health is a necessary part of any sport, including access to resources. Longitudinal studies following athletes over time to determine the development and causation for mental health symptoms should be included in future research directions.

Baseline Sleep Characteristics in NCAA Division I Collegiate Athletes

OBJECTIVE

The authors report no conflicts of interest.To determine baseline sleep characteristics of male/female student-athletes across multiple sports using objective and subjective measures.

DESIGN

Prospective study.

SETTING

Division I college.

PARTICIPANTS

Eighty-two male and female Division I student-athletes.

INTERVENTIONS

Participants completed 2 validated sleep questionnaires (Epworth Sleepiness Scale [ESS] and Single-Item Sleep Quality Scale [SISQS]) to assess subjective sleep. They also wore a validated sleep monitoring device (WHOOP 4.0 band) for at least 14 nights to collect objective data on total sleep time (TST) and sleep architecture.

MAIN OUTCOME MEASURES

Overnight sleep variables, including TST, time spent awake in bed after falling asleep, time spent in light sleep, rapid eye movement (REM) sleep, and slow-wave sleep (SWS) cycles. Sleep quality and daytime sleepiness were also assessed.

RESULTS

There were no statistical differences between male and female student-athletes in average TST, sleep architecture, sleep consistency, SISQS, and ESS scores. The average TST was 409.2 ± 36.3 minutes. Sleep architecture consisted of 25.6% REM, 19.9% SWS, and 54.4% light sleep. The average sleep consistency was 61.6% ± 8.9%. The average SISQS score was 6.48 ± 1.71, and the average ESS score was 7.57 ± 3.82. A significant difference was found in average wake time between males and females (55.0 vs 43.7 min, P = 0.020), with an overall average of 50.2 ± 16.2 minutes.

CONCLUSIONS

College student-athletes do not typically obtain the recommended amount of sleep. Optimizing sleep can positively affect academic and athletic performance.

Sleep Difficulties in Swiss Elite Athletes

For athletes, sleep is essential for recovery and performance. Yet, up to two-thirds of athletes report poor sleep quality. Comprehensive data across all sports disciplines on the underlying causes of sleep problems are missing. We reanalyzed a data set of N = 1004 Swiss top athletes across an extensive array of 88 sports to gain knowledge on the specific deficits in sleep health with respect to gender, sport classes, sport-related factors, and well-being. We found that 18% of athletes were affected by at least two out of five high-risk sleep factors: 9% of athletes slept less than 6 h per day, 30% were dissatisfied with their sleep, 17% showed problems falling asleep within 30 min, 18% of athletes reported difficulty maintaining sleep more than three times a week, and 6% of athletes used sleeping pills more than once a week. We found sleep health strongly linked to overall well-being and mental health (22% showed at least moderate symptoms of either depression or anxiety). Therefore, screening and treating sleep disorders might effectively improve mental health and general well-being as well as performance among athletes around the globe.

Health status of university football athletes through multidimensional screening

OBJECTIVE

Adequate conditioning results from various physical, environmental, and psychological factors in sports activities. In this study, we aimed to clarify the concurrence and relevance of injuries, psychological problems, and sleep disturbance in university football (soccer) players. Biomechanical characteristics and risk factors for those injuries were also investigated.

METHODS

Overall, 1,084 university football players participated in this cross-sectional study using a web-based health history questionnaire. Assessments were made via the presence of injuries for physical problems, the Athlete Psychological Strain Questionnaire (APSQ) for psychological problems, and the Athlete Sleep Screening Questionnaire (ASSQ) for sleep difficulties.

RESULTS

There were 200 (19%) athletes with injuries; 413 (38%) of these were APSQ-positive, 246 (23%) were ASSQ-positive, and 468 (43%) athletes had no physical, psychological, or sleep problems. APSQ-positive respondents were significantly more likely to have a current injury than those who were APSQ-negative. No significant difference was observed between the number of ASSQ-positive and -negative respondents and current injuries. Those with sleep problems were significantly more likely to have psychological problems.

CONCLUSION

More than 60% of university football players had one or more physical, psychological, or sleep problems. Players may have co-occurring problems, and it is important to address them for these athletes to reach peak performance.

The validity and reliability of the Persian version of the Athlete Sleep Screening Questionnaire

Background

Sleep as a biological phenomenon is effective in the performance and recovery of athletes. Questionnaires can be used as a cost-effective initial assessment tool for sleep. The Athlete Sleep Screening Questionnaire (ASSQ) demonstrated a clinically valid instrument for screening relevant sleep issues in athletic populations. Due to the lack of validated tools for adequate screening for sleep difficulties in the Iranian athlete population, the present study was conducted to evaluate the validity and reliability of the Persian version of the ASSQ.

Materials and Methods

The translation process was performed using instructions by Beaton et al. Content validity was assessed by a panel of experts. Exploratory and confirmatory factor analysis was performed for two 5-item sleep difficulty scores (SDS) and a 4-item chronotype score. Internal consistency based on Cronbach's alpha and McDonald's omega and stability reliability were used to evaluate reliability.

Results

The ASSQ achieved conceptual and semantic equivalence with the original scale. The item-level content validity index (I-CVI) of each item ranged from 0.87 to 1, and the averaging scale-level CVI/average was 0.95. In factor analysis, one factor for SDS and one factor for chronotype score were identified and confirmed. The internal consistency of the SDS scale (α =0.77, Ω =0.83) and chronotype (α =0.74, Ω =0.77) was acceptable. Stability reliability was confirmed for SDS scale (intra-class correlation [ICC] =0.87) and for chronotype (ICC = 0.83).

Conclusion

Persian ASSQ has acceptable psychometric measurement properties as a screening tool to assess sleep in Iranian athletes.

Chronotype characteristics of professional athletes in China: a comprehensive descriptive study

BACKGROUND

Chronotype has gained recognition as a significant factor in enhancing athletic performance. This study aimed to deepen our understanding of athletes' sleep chronotypes and provide a foundation for developing evidence-based training and competition programs. By comprehensively describing and analyzing the chronotype characteristics of Chinese professional athletes, considering individual and sports factors, sleep quality and habits, and mental energy, this research aimed to contribute valuable insights to the field.

METHODS

A sample of 1069 professional athletes from sports teams in Shanghai completed the Athlete Sleep Screening Questionnaire and the Athlete Mental Energy Scale to assess chronotype, sleep quality, sleep-influencing habits, and mental energy.

RESULTS

Among athletes, sleep typology fell within the intermediate range, slightly leaning toward morningness. Male athletes and those who engaged in static sports displayed a greater propensity for morningness. Age correlated with a preference for eveningness. High-level athletes exhibited a stronger inclination toward eveningness. Sleep quality issues were associated with an inclination toward eveningness. Daily caffeine intake and the habit of using electronic devices before bedtime are also linked to eveningness. Chronotype demonstrated the ability to predict various dimensions of athletes' mental energy. It was the strongest predictor of vigor, but the loadings were smaller than those of sleep quality.

CONCLUSION

Chinese athletes' chronotypes primarily exhibit distinct characteristics related to individual factors such as gender, sports discipline, and ranking, as well as habits like caffeine consumption and electronic device use. Moreover, these sleep patterns demonstrate predictive capabilities across all dimensions of athletes' mental energy. This study sheds light on Chinese athletes' unique sleep chronotype attributes, enriching our understanding of sleep patterns among professional athletes under various systems. These insights offer an initial basis for enhancing the effectiveness of athlete scheduling and training management.

Reliability and validity of the Chinese version of the Athens insomnia scale for non-clinical application in Chinese athletes

Purpose

This study aimed to revise and examine the reliability and validity of the Chinese version of the Athens Insomnia Scale for Non-clinical Application (AIS-NCA) among Chinese athletes. Additionally, the study tested the scale in non-athlete individuals with similar sleep management practices to further analyze its cultural specificity among Chinese athletes and make preliminary inferences about its applicability in other Chinese populations.

Methods

Four hundred twenty-six Chinese professional athletes and 779 high school students participated in this research. Both athletes and students were divided into two parallel groups for exploratory and confirmatory factor analyses. Additionally, three athlete samples and one student sample were established for reliability and validity assessments. Among athletes, the Pittsburgh Sleep Quality Index, the Epworth Sleepiness Scale, the Athlete Sleep Screening Questionnaire, and the Warwick-Edinburgh Mental Well-Being Scale were employed to evaluate convergent and discriminant validity. Re-test reliability was evaluated at intervals of 1 and 2 weeks. In the case of students, convergent and discriminant validity were tested using the Pittsburgh Sleep Quality Index and the General Self-Efficacy Scale, with re-test reliability assessed at two-week intervals.

Results

The Chinese version of the AIS-NCA consists of six items, categorized into two dimensions: sleep problems and daytime functioning. This structure explained 65.08% (athletes) and 66.22% (students) of the variance. Confirmatory factor analysis revealed good model fit, with values of χ2/df = 2.217, CFI = 0.975, AGFI = 0.929, TLI = 0.953, and RMSEA = 0.076 among athletes, and χ2/df = 3.037, CFI = 0.979, AGFI = 0.947, TLI = 0.961, and RMSEA = 0.072 among students. The scale demonstrated a reasonable degree of measurement invariance. The overall scale and two subscales exhibited strong reliability and validity among athletes. Similar results in terms of reliability and validity were also observed within the student sample.

Conclusion

The Chinese version of the AIS-NCA shows promise as an assessment tool for evaluating the sleep quality of Chinese athletes. It effectively captures both sleep-related concerns and daytime functionality within the athlete population. The scale demonstrates solid reliability and validity in professional athletes and holds potential for application across various other demographic groups in China.

Examination of clinical sleep difficulties in college student-athletes

BACKGROUND

Due to the rising concern of inadequate sleep, critical analysis is needed for the presence of sleep problems in diverse populations. Research has shown that college athletes may be one such population at risk for sleep disturbances. Poor sleep may lead to physiological, psychological, and cognitive deficits that can impact college athletes academically and athletically. This investigation was performed to examine the relationship of age, sex, and history of concussion on sleep disturbance in college athletes.

METHODS

A total of 191 collegiate athletes between the ages of 18-26 from a single academic NCAA institution in the Rocky Mountain region of the USA, consented to participate in the study. Participants completed a demographic questionnaire and the Athlete Sleep Screening Questionnaire (ASSQ). Results were analyzed using SPSS Version 27.

RESULTS

Primary results revealed that female athletes reported higher sleep disturbance scores when compared to males (U=3643.0, P=0.016). Self-reported sleep disturbances when traveling for sport were higher for females (<inf>X</inf>(1) = 23.800, P<0.001). Males were also less likely to report daytime dysfunction when traveling for sport (<inf>X</inf>(1) =22.988, P<0.001). Sleep disturbance had a significant association with age (<inf>X</inf>(1) =4.145, P=0.042), with older participants (20+ years of age) reporting greater sleep disturbance. Concussion history did not associate with sleep disturbance in the present study.

CONCLUSIONS

Results suggest that sophomore or older female may be at higher risk for sleep disturbances. Clarifying sex-specific sleep health and understanding the role of age and academic class is crucial to enhance and personalize interventions.

Implementation of the International Olympic Committee Sport Mental Health Assessment Tool 1: Screening for Mental Health Symptoms in a Canadian Multisport University Program

OBJECTIVE

To apply the International Olympic Committee Sport Mental Health Assessment Tool 1 (SMHAT-1) to determine the prevalence of mental health symptoms in a cohort of university student athletes over an academic year. A secondary objective was to explore the internal consistency of the screening tools from the SMHAT-1.

DESIGN

Cross-sectional design with 3 repeated measurements over an academic year.

SETTING

A large university multisport program.

PARTICIPANTS

Five hundred forty-two university-level student athletes from 17 sports.

INTERVENTION

N/A.

MAIN OUTCOME MEASURES

On 3 occasions, the participants completed the SMHAT-1, which consists of the Athlete Psychological Strain Questionnaire. If an athlete's score was above the threshold (≥17), the athlete completed step 2, consisting of (1) Generalized Anxiety Disorder-7; (2) Patient Health Questionnaire-9; (3) Athlete Sleep Screening Questionnaire; (4) Alcohol Use Disorders Identification Test Consumption; (5) Cutting Down, Annoyance by Criticism, Guilty Feeling, and Eye-openers Adapted to Include Drugs; and (6) Brief Eating Disorder in Athletes Questionnaire. Internal consistency of the SMHAT-1 was also measured.

RESULTS

Participants reported mental health symptoms with prevalence of 24% to 40% for distress, 15% to 30% for anxiety, 19% to 26% for depression, 23% to 39% for sleep disturbance, 49% to 55% for alcohol misuse, 5% to 10% for substance use, and 72% to 83% for disordered eating. Female athletes were more likely to suffer psychological strain, depression, and sleep disturbance; male athletes were more likely to report substance use.

CONCLUSIONS

The SMHAT-1 was feasible to implement with good internal consistency. University-level athletes suffer from a variety of mental health symptoms underscoring the necessity for team physicians to have the clinical competence to recognize and treat mental health symptoms.

The effects of sleep disturbance and chronotype on baseline vestibular/ ocular motor screening in collegiate athletes

BACKGROUND

The vestibular/ocular motor screening (VOMS) is a clinically validated screening tool for concussion management. Multiple factors have been known to influence VOMS performance such as preexisting migraine and mood disorders. Poor sleep is an another important variable that warrants investigation as a modifier on the VOMS that may need to be considered during administration.

AIM

This study aims to examine whether self-reported sleep difficulties significantly modify baseline VOMS symptom provocation in collegiate athletes.

METHODS

A total of 191 collegiate student-athletes completed a pre-season baseline VOMS and the 16-item Athlete Sleep Screening Questionnaire (ASSQ) before the start of their respective sport season. The ASSQ was used to establish sleep health variables consisting of hours of sleep per night, sleep difficulties when traveling for sport, chronotype (e.g., morning or evening person), and a sleep disturbance score (SDS) category of none, mild, and moderate + severe.

RESULTS

Those who reported sleep disturbances when traveling for sport on that respective ASSQ item had higher pre-test VOMS symptoms (P < 0.001) and symptom provocation on convergence (P = 0.015), horizontal vestibular ocular reflex (VOR) (P = 0.008), and vertical VOR (P = 0.039). There were worse pre-test symptoms (P = 0.015) and provocation on horizontal VOR (P = 0.046) in the moderate + severe SDS group than no SDS. The moderate + severe SDS group reported worse symptom provocation on the horizontal (P = 0.018) and vertical VOR (P = 0.010), and VMS (P = 0.017). No differences were found on VOMS symptom provocation for hours of sleep or chronotype.

CONCLUSIONS

These results show agreement with previous symptom and neurocognitive data in that sleep difficulties among collegiate athletes may have an important role in the interpretation of baseline concussion testing. It may be beneficial to utilize sleep assessments with baseline concussion testing when using the VOMS as the clinical concussion measurement modality.

RELEVANCE FOR PATIENTS

The addition of sleep assessment may aid sports medicine practitioners in properly interpreting baseline VOMS scores. Pre-season baseline testing may need to be delayed if athletes report with poor sleep in the acute period prior.

Sleep Quality and Sleep Behaviors in Varsity Athletes: A Pilot Study

Sleep hygiene practices may hinder university athletes from obtaining quality sleep to support health and performance. We sought to provide a comprehensive evaluation of sleep quality and behaviors in varsity athletes using validated sleep questionnaires: the Athlete Sleep Screening Questionnaire (ASSQ) and the Athlete Sleep Behavior Questionnaire (ASBQ). Sixty-four (n = 64) athletes participated (54% female; 71% Caucasian). The mean age was 20.3 ± 1.7 years and the mean BMI was 23.3 ± 3.3. Fifty-one percent met the threshold for adequate sleep (7+ h) and 54% reported being somewhat/very satisfied with sleep quality. Global scores for ASSQ Sleep Difficulty and ASBQ sleep behaviors were significantly correlated (r = 0.31; p = 0.014) and not significantly different across age, academic year, or residence. According to the ASSQ, 11% and 24% were classified as having severe or moderate sleep problems, respectively. The ASBQ categorized 62% as having "poor" sleep behaviors. Notable sleep-influencing factors included a high frequency of emotional/cognitive processing of sport-performance issues (46.9%), frequent use of light-emitting devices before bed (90%), training after 7 pm (65%), and the use of sleep medication (19%). Half of the university athletes did not meet the thresholds for adequate sleep, and some may require a referral for clinical sleep issues. The majority of these athletes' sleep behaviors do not promote adequate sleep. The ASSQ shows utility to assess gradations in clinical sleep difficulty; the ASBQ could be used in concert with the ASSQ to discern "cognitive and physiological arousal" targets for use in educational workshops designed to promote optimal sleep hygiene in university athletes.

Assessment of sleep disturbances with the athlete sleep screening Questionnaire in Chinese athletes

This study investigated the factors that are associated with sleep disturbances among Chinese athletes. Sleep quality and associated factors were assessed by the Athlete Sleep Screening Questionnaire (ASSQ, n ​= ​394, aged 18–32 years, 47.6% female). Sleep difficulty score (SDS) and level of sleep problem (none, mild, moderate, or severe) were used to classify participants' sleep quality. Categorical variables were analyzed by Chi-square or fisher's exact tests. An ordinal logistic regression analysis was used to explore factors with poor sleep (SDS ≥8).

Approximately 14.2% of participants had moderate to severe sleep problem (SDS ≥8). Fifty-nine percent of the athletes reported sleep disturbance during travel, while 43.3% experienced daytime dysfunction when travelling for competition. No significant difference was found in the SDS category between gender, sports level and events. Athletes with evening chronotype were more likely to report worse sleep than athletes with morning and intermediate chronotype (OR, 2.25; 95%CI, 1.44–3.52; p ​< ​0.001). For each additional year of age, there was an increase of odds ratio for poor sleep quality (OR, 1.15; 95%CI, 1.04–1.26; p ​= ​0.004), while each additional year of training reduced the odds ratio (OR, 0.95; 95%CI, 0.91–0.99; p ​= ​0.044). To improve sleep health in athletes, chronotype, travel-related issues, age and years of training should be taken into consideration.

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Sleep problems in athletes have been noticed in recent years. By using the clinically validated questionnaire (ASSQ) in Chinese athletes, we found that 14.2% of Chinese athletes had sleep disturbance.

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By using a multivariate ordinal logistic regression model, we were able to detect chronotype, travel-related issues, age and years of training were important influencing factors on poor sleep quality in Chinese athletes.

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The novel findings observed in this study shed new light on the current sleep health and possible factors affecting sleep disturbances of Chinese athletes and provide a new perspective for Chinese athletes to optimize their sleep strategies that improve sleep quality.

Sleep, health, and well-being in elite athletes from different sports, before, during, and after international competition

Objectives: Limited research has been conducted on sleep problems in elite athletes at international competition, and how this relates to their general health and well-being. Methods: Sixty-five elite international athletes (37 males, 28 females, 21.8 ± 2.1 years) from different sports completed validated sleep (Athlete Sleep Screening Questionnaire), health (Subjective Health Complaints Inventory) and well-being (Sports Profile of Mood States) questionnaires; 1 month pre-competition, at the end of international competition, and 1 month post-competition. Results: Twenty-three percent of the elite athletes were identified as having a moderate or severe clinically significant sleep problem during competition, with 82% reporting less than 8 h of sleep per night. Athletes with a moderate or severe clinically significant sleep problem during competition had significantly greater general health complaints (p = 0.002), mood disturbance (p = 0.001) and poorer sleep hygiene (p = 0.002). Swimmers had more sleep difficulty pre and during competition compared to athletics and soccer (p = 0.009). Conclusion: Sleep disturbance during international competition is common and associated with poorer health and lower mood. Swimmers may be more at risk of sleep difficulty pre and during competition compared to those competing in athletics and soccer. Sleep services may be required to support elite athletes at international competition.

Exploring the Relationship Between Sleep Quality, Sleep Hygiene, and Psychological Distress in a Sample of Canadian Varsity Athletes

Student athletes balance academic, social, and athletic demands, often leading to increased levels of stress and poor sleep. This study explores the relationship between sleep quality, sleep hygiene, and psychological distress in a sample of student athletes. Ninety-four student athletes completed the six-item Kessler Psychological Distress Scale (K6), Sleep Hygiene Practice Scale, and four components from the Pittsburgh Sleep Quality Index. Age, gender, and sport were also collected. The Pittsburgh Sleep Quality Index revealed that 44.7% of student athletes received ≥6.5 hr of sleep each night; 31% of athletes showed signs of severe mental illness according to the K6. Stepwise regression predicted K6 scores with the Pittsburgh Sleep Quality Index and the Sleep Hygiene Practice Scale scores as independent variables. A significant model accounting for 26% of the variation in K6 scores emerged; sleep schedule and sleep disturbances were significant predictors. Athletic staff should highlight the importance of sleep for mental health; suggestions on how to help athletes are provided.