Sleep disorder risk factors among student athletes

A Biopsychosocial Model for Understanding Training Load, Fatigue, and Musculoskeletal Sport Injury in University Athletes: A Scoping Review

ABSTRACT

McClean, ZJ, Pasanen, K, Lun, V, Charest, J, Herzog, W, Werthner, P, Black, A, Vleuten, RV, Lacoste, E, and Jordan, MJ. A biopsychosocial model for understanding training load, fatigue, and musculoskeletal sport injury in university athletes: A scoping review. J Strength Cond Res 38(6): 1177-1188, 2024-The impact of musculoskeletal (MSK) injury on athlete health and performance has been studied extensively in youth sport and elite sport. Current research examining the relationship between training load, injury, and fatigue in university athletes is sparse. Furthermore, a range of contextual factors that influence the training load-fatigue-injury relationship exist, necessitating an integrative biopsychosocial model to address primary and secondary injury prevention research. The objectives of this review were (a) to review the scientific literature examining the relationship between training load, fatigue, and MSK injury in university athletes and (b) to use this review in conjunction with a transdisciplinary research team to identify biopsychosocial factors that influence MSK injury and develop an updated, holistic biopsychosocial model to inform injury prevention research and practice in university sport. Ten articles were identified for inclusion in this review. Key findings were an absence of injury surveillance methodology and contextual factors that can influence the training load-fatigue-MSK injury relationship. We highlight the inclusion of academic load, social load, and mental health load as key variables contributing to a multifactorial, gendered environmental, scientific inquiry on sport injury and reinjury in university sport. An integrative biopsychosocial model for MSK injury in university sport is presented that can be used to study the biological, psychological, and social factors that modulate injury and reinjury risk in university athletes. Finally, we provide an example of how causal inference can be used to maximize the utility of longitudinally collected observational data that is characteristic of sport performance research in university sport.

Computational ensemble expert system classification for the recognition of bruxism using physiological signals

This study aimed to develop an automatic diagnostic scheme for bruxism, a sleep-related disorder characterized by teeth grinding and clenching. The aim was to improve on existing methods, which have been proven to be inefficient and challenging. We utilized a novel hybrid machine learning classifier, facilitated by the Weka tool, to diagnose bruxism from biological signals. The study processed and examined these biological signals by calculating the power spectral density. Data were categorized into normal or bruxism categories based on the EEG channel (C4-A1), and the sleeping phases were classified into wake (w) and rapid eye movement (REM) stages using the ECG channel (ECG1-ECG2). The classification resulted in a maximum specificity of 93% and an accuracy of 95% for the EEG-based diagnosis. The ECG-based classification yielded a supreme specificity of 87% and an accuracy of 96%. Furthermore, combining these phases using the EMG channel (EMG1-EMG2) achieved the highest specificity of 95% and accuracy of 98%. The ensemble Weka tool combined all three physiological signals EMG, ECG, and EEG, to classify the sleep stages and subjects. This integration increased the specificity and accuracy to 97% and 99%, respectively. This indicates that a more precise bruxism diagnosis can be obtained by including all three biological signals. The proposed method significantly improves bruxism diagnosis accuracy, potentially enhancing automatic home monitoring systems for this disorder. Future studies may expand this work by applying it to patients for practical use.

Waking Up to the Issue! Research Inattention and Sex-Related Differences Warrant More Sleep Studies in Female Athletes

Understanding sleep patterns and behaviors of athletes is essential for developing targeted sleep-based interventions for implementation in practice. However, more than double the number of sleep studies have examined male athletes compared with female athletes, making the current understanding of sleep patterns, behaviors, and interventions among athletes disproportionately indicative of men. Consequently, this review demonstrates the need for more female-specific sleep data among athlete populations due to research inattention and sex-related differences. Specifically, this review identifies variations in sleep patterns and behaviors between male and female athletes, as well as physiological and lifestyle factors that potentially affect sleep patterns and behaviors across the lifespan, specifically in female athletes. In this regard, evidence suggests some female athletes experience longer sleep durations and better objective sleep quality, but similar or worse subjective sleep quality compared with male athletes. Additionally, scheduling training in the morning or throughout the day may benefit sleep in some female athletes. Considering sleep disorders, women may be at greater risk for insomnia and restless legs syndrome compared with men, which may be attributed to pregnancy, as well as a higher prevalence of anxiety and depressive symptoms, iron deficiency without anemia, and use of psychotropic medication among women. Finally, the menstrual cycle, menstrual disorders, oral contraceptive use, and the postpartum period have been shown to exert detrimental effects on sleep patterns and behaviors and should theoretically be considered when monitoring and managing sleep in female 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.

What complex factors influence sleep quality in college students? PLS-SEM vs. fsQCA

Introduction

Sleep quality has a significant impact on the health-related quality of life, particularly among college students. This study proposes a framework for identifying factors that influence college students' sleep quality, including stress, self-control, bedtime habits, and neighborhood environment.

Methods

The study employed a cross-sectional analytical approach on a convenience sample of 255 medical students from a private university in China during the 2021/2022 academic year, of which 80.39% (205) were women. Two complementary methodologies, partial least squares-structural equation modeling (PLS-SEM), and fuzzy sets qualitative comparative analysis (fsQCA), were utilized in the study.

Results

The results of the PLS-SEM analysis suggest that Stress and Self-control act as mediating variables in the model, with Bedtime habits and Neighborhood environment influencing sleep quality through these variables. Additionally, the fsQCA analysis reveals that Bedtime habits and Neighborhood environment can combine with Stress and Self-control, respectively, to influence sleep quality.

Discussion

These findings provide insight into how multiple factors, such as Stress, Self-control, Bedtime habits, and Neighborhood environment, can impact college students' sleep quality, and can be used to develop intervention programs aimed at improving it. Moreover, the use of both methodologies enables the expansion of new methodological approaches that can be applied to different contexts.

Prevalence and risk factors of poor subjective sleep quality in elite judo athletes

This study aimed to determine the prevalence and risk factors of poor subjective sleep quality in elite judo athletes. A subjective cross-sectional questionnaire survey was conducted with 106 elite judo athletes who participated in the training camp of the Japanese national team. Eighty-six respondents (men: 52.3%; average age: 22.9 ± 3.1 years) with complete responses were included in the analysis (valid response rate: 81.1%). Subjective sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI). The prevalence of poor sleep quality (PSQI score ≥ 5.5), the mean PSQI score, and subscale scores were investigated. Relationships between poor sleep quality and attributes, lifestyle habits, competition-based activities, and psychological distress were explored using Fisher's exact tests and multivariate logistic regression analysis. Thirty-five respondents (40.7%) reported poor sleep quality. The percentage and subscale scores of the respondents for sleep latency, sleep duration, and daytime dysfunction were higher than those of the population of Japanese national-level athletes. The mean PSQI score of the respondents was similar to that of some elite athlete populations but higher than those of others. Multivariate logistic regression analysis revealed that psychological distress was associated with poor sleep quality. In conclusion, the prevalence of poor subjective sleep quality in elite judo athletes was suggested to be similar or higher among elite athlete population. Sleep latency, sleep duration, and daytime dysfunction status were worse in elite judo athletes than in Japanese national-level athletes. Psychological distress was a risk factor for poor subjective sleep quality in elite judo athletes.

Supplementary Information

The online version contains supplementary material available at 10.1007/s41105-023-00444-6.

Translation and Validation of the Arabic Version of the Athlete Sleep Screening Questionnaire

Sleep improves the cognitive and physical performance of athletes. A detailed questionnaire that detects sleep disruptions is required to identify sleep-deprived athletes. This study evaluates the translated Athlete Sleep Screening Questionnaire (ASSQ), a tool suggested by the International Olympic Committee, among Arabic-speaking athletes. The ASSQ was translated into Arabic and examined for floor or ceiling effects, internal consistency, and validity among Arabic-speaking athletes. The Arabic Pittsburgh Sleep Quality Index (PSQI) was employed to assess convergent validity. Ninety athletes (28.9% women) participated and completed this study's questionnaires. The Cronbach's alpha for the ASSQ-Sleep Difficulty Score (SDS) was 0.435, and that of the ASSQ-chronotype was 0.632. The SDS and chronotype subset of the ASSQ demonstrated excellent test-retest reliability, with intraclass correlation coefficients of 0.84 and 0.938, respectively. The ASSQ-SDS correlated positively with the PSQI (0.734, p = 0.001). The ASSQ-chronotype was inversely associated with the PSQI (p = 0.001). This study's findings can assist clinicians in assessing sleep disorders in sports. The Arabic version of the ASSQ has satisfactory psychometric qualities and can identify clinically relevant sleep problems in athletes.

Daytime Napping Benefits Passing Performance and Scanning Activity in Elite Soccer Players

The present study explored the effect of a daytime napping opportunity on scanning activity, which is an essential component of successful soccer performance. Fourteen male elite collegiate soccer players performed the Trail Making Test (TMT), which was used to assess complex visual attention. In addition, a soccer passing test, modified with reference to the Loughborough Soccer Passing Test, was used to evaluate passing performance as well as scanning activity. A cross-over design was applied to examine nap and no-nap interventions. Participants (N = 14, mean age: 21.6 SD = 0.5 years, height: 1.73 ± 0.06 m, body mass: 67.1 ± 4.5 kg) were randomly allocated to a midday nap (40 minutes) or no-nap group. Subjective sleepiness was measured using the Karolinska Sleepiness Scale, and perceptive fatigue was evaluated by the visual analog scale. There were no significant differences in subjective measurements or TMT between the nap and no-nap groups. However, the performance time for the passing test and scanning activity was significantly shorter (p < 0.001) and scanning activity was significantly more frequent in the nap condition than in the no-nap condition (p < 0.00005). These results suggest that daytime napping is beneficial for soccer-related cognitive function, represented by visuospatial processing and decision-making, and particularly as a potential countermeasure to mental fatigue. Considering that inadequate sleep and residual fatigue are commonly observed in elite soccer, this finding may have practical implications for the preparation of players.

Propiedades psicométricas del índice de calidad de sueño de Pittsburgh en deportistas

El índice de calidad de sueño de Pittsburgh (ICSP) es un instrumento ampliamente utilizado en poblaciones clínicas y no clínicas para la evaluación de la calidad de sueño. El objetivo de este trabajo fue determinar la estructura factorial y consistencia interna del ICSP en deportistas universitarios del sur de Sonora México para la evaluación de las propiedades psicométricas del instrumento. Se realizó un estudio transversal no experimental con 98 deportistas universitarios, 39 mujeres (38,2%), en un rango de 17 a 25 años. Se evaluó la consistencia interna y homogeneidad del instrumento, así como los análisis factorial exploratorio (AFE) y confirmatorio (AFC). Los resultados de confiabilidad indicaron un α de Cronbach de 0,79 eliminando los componentes de uso de medicamentos para dormir y eficiencia habitual del sueño. El AFE identificó un modelo de dos factores y el AFC un modelo unidimensional. Se concluye que la calidad de sueño en esta muestra de deportistas se explica mejor mediante un modelo unidimensional de cinco componentes.

Study on lifestyle habits affecting sleep disorders at the undergraduate education stage in Xuzhou City, China

Background

In China, undergraduate students face both academic and career selection pressures, sleep is an important physiological process for them. Investigate the physical exercise, sleep quality of undergraduate students in the education stage in Xuzhou City, and analyze the factors affecting their sleep quality, to promote the health education and psychological health of undergraduate students.

Materials and methods

The Physical Activity Rating Scale-3 (PARS-3), the Pittsburgh Sleep Quality Index (PSQI), and the demographic information questionnaire were used to survey a whole-group sample of four undergraduate colleges and universities (Xuzhou Institute of Engineering, Xuzhou Medical University, China University of Mining and Technology, Jiangsu Normal University) in Xuzhou by cluster sampling, the general characteristics including gender, grade, height, weight, domicile, race, economic income, etc., were collected, and the data were analyzed and processed using chi-square tests and multi-factor logistic regression.

Results

3,366 valid questionnaires were collected from four undergraduate colleges and universities, including 1,355 males and 2,011 females. The detection rate of exercise in Jiangsu Normal University was lower than that in other universities, and the detection rate of sleep disorders was higher than that in other universities. Xuzhou Medical University, the highest detection rate of large exercise, Xuzhou Institute of Technology, the lowest detection rate of sleep disorders. There were significant differences in the detection rate of large amount of exercise among college students of different genders, grades, body types, and majors (χ2 = 259.172, P < 0.001; χ2 = 34.473, P < 0.001; χ2 = 36.026, P < 0.001; χ2 = 57.908, P < 0.001). There were significant differences in the detection rate of sleep disorders among college students with different gender, grade, family economic status, daily cell phone use time, cell phone purposeless usage, and exercise level (χ2 = 5.806, P = 0.016; χ2 = 47.5, P < 0.001; χ2 = 28.949, P < 0.001; χ2 = 55.866, P < 0.001; χ2 = 147.101, P < 0.001; χ2 = 9.129, P = 0.010). Multivariate logistic regression analysis showed that grade, family economic status, cell phone use time, cell phone purposeless usage is the main influencing factors of sleep disorders in college students.

Conclusion

The sleep problems of undergraduates are serious, especially in Jiangsu Normal University. Scientific and appropriate exercise is an important measure to solve the sleep problems of undergraduates. Colleges and universities should actively carry out health education, college students living habits such as cell phone use should be guided training.

The Impact of Dietary Factors on the Sleep of Athletically Trained Populations: A Systematic Review

Many athletic populations report poor sleep, especially during intensive training and competition periods. Recently, diet has been shown to significantly affect sleep in general populations; however, little is known about the effect diet has on the sleep of athletically trained populations. With sleep critical for optimal recovery and sports performance, this systematic review aimed to evaluate the evidence demonstrating that dietary factors influence the sleep of athletically trained populations. Four electronic databases were searched from inception to May 2022, with primary research articles included if they contained a dietary factor(s), an outcome measure of sleep or sleepiness, and participants could be identified as ‘athletically trained’. Thirty-five studies were included, with 21 studies assessed as positive quality, 13 as neutral, and one as negative. Sleep or sleepiness was measured objectively in 46% of studies (n = 16). The review showed that evening (≥5 p.m.) caffeine intakes >2 mg·kg−1 body mass decreased sleep duration and sleep efficiency, and increased sleep latency and wake after sleep onset. Evening consumption of high glycaemic index carbohydrates and protein high in tryptophan may reduce sleep latency. Although promising, more research is required before the impact of probiotics, cherry juice, and beetroot juice on the sleep of athletes can be resolved. Athletic populations experiencing sleep difficulties should be screened for caffeine use and trial dietary strategies (e.g., evening consumption of high GI carbohydrates) to improve sleep.

A Strategy to Inform Athlete Sleep Support From Questionnaire Data and Its Application in an Elite Athlete Cohort

PURPOSE

Information from the Pittsburgh Sleep Quality Index (PSQI) and Athlete Sleep Behavior Questionnaire (ASBQ) provide the ability to identify the sleep disturbances experienced by athletes and their associated athlete-specific challenges that cause these disturbances. However, determining the appropriate support strategy to optimize the sleep habits and characteristics of large groups of athletes can be time-consuming and resource-intensive. The purpose of this study was to characterize the sleep profiles of elite athletes to optimize sleep-support strategies and present a novel R package, AthSlpBehaviouR, to aid practitioners with athlete sleep monitoring and support efforts.

METHODS

PSQI and ASBQ data were collected from a cohort of 412 elite athletes across 27 sports through an electronic survey. A k-means cluster analysis was employed to characterize the unique sleep-characteristic typologies based on PSQI and ASBQ component scores.

RESULTS

Three unique clusters were identified and qualitatively labeled based on the z scores of the PSQI components and ASBQ components: cluster 1, "high-priority; poor overall sleep characteristics + behavioral-focused support"; cluster 2, "medium-priority, sleep disturbances + routine/environment-focused support"; and cluster 3, "low-priority; acceptable sleep characteristics + general support."

CONCLUSIONS

The findings of this study highlight the practical utility of an unsupervised learning approach to perform clustering on questionnaire data to inform athlete sleep-support recommendations. Practitioners can consider using the AthSlpBehaviouR package to adopt a similar approach in athlete sleep screening and support provision.

Monitoring the Changing Patterns in Perceived Learning Effort, Stress, and Sleep Quality during the Sports Training Period in Elite Collegiate Triathletes: A Preliminary Research

Background: Few studies have examined the mental profiles and academic status of collegiate triathletes during training/competitive periods. We evaluated the changes in sleep quality, physical fatigue, emotional state, and academic stress among collegiate triathletes across training periods. Methods: Thirteen collegiate triathletes (19−26 years old) were recruited in this study. Mood state, sleep quality, degree of daytime sleepiness, subjective fatigue, and academic learning states were measured during the following five training periods: before national competitions for 3 months (3M-Pre Comp), 2 months (2M-Pre Comp), 1 month (1M-Pre Comp), 2 weeks (2wk-Pre Comp), and national competition (Comp) according to their academic/training schedule. Results: The academic stress index in 1M-Pre Comp (Final exam) was significantly higher than that in 3M-Pre Comp in these triathletes. No markedly significant differences were observed in overall mood state, sleep quality, individual degree of sleepiness, and fatigue among these five periods. However, the profiles mood state scale (POMS)-fatigue and -anger were lower in 2wk-Pre Comp than that in 1M-Pre com. The POMS-tension score in Comp was significantly higher than that in 3M-Pre Comp and 2M-Pre Comp. POMS-depression in Comp was lower than that in 1M-Pre Comp. Conclusion: We found that training volume was highest one month before a competition, and the academic stress is greatest during their final term exam period (1M-Pre Comp). After comprehensive assessment through analyzing POMS, PSQI, ESS, and personal fatigue (CIS), we found that the collegiate triathletes exhibited healthy emotional and sleep states (PSQI score < 5) across each training period, and our results suggest that these elite collegiate triathletes had proficient self-discipline, time management, and mental adjustment skills.

Prevalence and Risk Factors of Poor Sleep Quality in Collegiate Athletes during COVID-19 Pandemic: A Cross-Sectional Study

The COVID-19 pandemic has changed our lifestyle, sleep and physical activity habits. This study evaluated the prevalence of poor sleep quality, its disrupters, and the impact of the pandemic in collegiate athletes. We performed a cross-sectional study of collegiate athletes (N = 339, median age: 20 (IQR,19−21) years old, 48.5% female, 47% individual sports) who received a web-based questionnaire in April 2021. This survey included subject characteristics, chronotype, sleep disrupters, the changes due to the pandemic and sleep quality (Pittsburg Sleep Quality Index [PSQI]). A multivariate linear regression was performed to assess the relationship between sleep quality, gender, chronotype, sleep disrupters and the changes to training volume or sleep. Results showed a disrupted sleep quality in 63.7%. One in five students had a total sleep time under 6.5 h per night. Poor sleep quality was significantly correlated with nocturnal concerns related to the pandemic, evening chronotype, female gender, third year of study, caffeine consumption and lack of sleep routine (all p < 0.05). To conclude, poor sleep quality is common in collegiate athletes. Sleep disrupters remain prevalent in the lifestyle habits of this population and may have been exacerbated by changes related to the COVID-19 pandemic. Sleep hygiene should become a major aspect of sports education during the return to post-covid normality.

Exploring the Effect of Long Naps on Handball Performance and Heart Rate Variability

This study explored the effect of long naps on handball-related performance and assessed the role of the cardiac autonomic nervous system in this process. Eleven male collegiate handball players performed a repeated sequential trial consisting of a 20-m consecutive turnaround run, 10-m run with a load, and shooting the ball into a target. Participants were allocated randomly and sequentially to have a short (20 minutes) nap, long (60 minutes) nap, or no nap. The Pittsburgh Sleep Quality Index was used to assess regular sleep quality. Subjective sleepiness before and after napping was measured using the Karolinska Sleepiness Scale. Heart rate variability was recorded to assess cardiac autonomic nervous function during napping. The Pittsburgh Sleep Quality Index score was correlated with shot accuracy only after long naps (ρ=0.636, r=0.048). A negative correlation was observed between the root mean square of successive differences and average load run time (ρ=−0.929, p<0.001). Long napping was associated with a significant benefit on performance in athletes with poor sleep quality, implying a role of the autonomic nervous system in this regard. Our findings indicate the effect of sleep quality on the endurance and resistance of handball players.

Deconstructing athletes' sleep: A systematic review of the influence of age, sex, athletic expertise, sport type, and season on sleep characteristics

PURPOSE

This systematic review aimed to describe objective sleep parameters for athletes under different conditions and address potential sleep issues in this specific population.

METHODS

PubMed and Scopus were searched from inception to April 2019. Included studies measured sleep only via objective evaluation tools such as polysomnography or actigraphy. The modified version of the Newcastle-Ottawa Scale was used for the quality assessment of the studies.

RESULTS

Eighty-one studies were included, of which 56 were classified as medium quality, 5 studies as low quality, and 20 studies as high quality. A total of 1830 athletes were monitored over 18,958 nights. Average values for sleep-related parameters were calculated for all athletes according to sex, age, athletic expertise level, training season, and type of sport. Athletes slept on average 7.2 ± 1.1 h/night (mean ± SD), with 86.3% ± 6.8% sleep efficiency (SE). In all datasets, the athletes' mean total sleep time was <8 h. SE was low for young athletes (80.3% ± 8.8%). Reduced SE was attributed to high wake after sleep onset rather than sleep onset latency. During heavy training periods, sleep duration and SE were on average 36 min and 0.8% less compared to pre-season and 42 min and 3.0% less compared to in-season training periods, respectively.

CONCLUSION

Athletes' sleep duration was found to be short with low SE, in comparison to the general consensus for non-athlete healthy adults. Notable sleep issues were revealed in young athletes. Sleep quality and architecture tend to change across different training periods.

Chronotype and social support among student athletes: impact on depressive symptoms

Previous studies have shown individuals with evening chronotype to have a greater likelihood for depression (self-reported and clinical ratings), especially in young adults. However, the mechanisms for this relationship remain unknown. Low levels of social support may be a plausible mechanism: young adults with evening chronotypes are awake when others are sleeping, which may lead to feelings of isolation or low support. This study examined links between chronotype, depression, and social support in relationship subtypes within a group of university student athletes. Data were obtained from 189 NCAA Division-I student athletes across all sports. Chronotype was assessed with the Circadian Energy Scale and ranged from -2 (definitely morning type) to +2 (definitely evening type). Depressive symptoms were assessed with Center for Epidemiological Studies Depression scale. Social support was assessed with the Multidimensional Scale of Perceived Social Support, which included subscales for Family, Friends, and Significant Other. A subscale for Team was created using the items from the Friends subscale (changing the word "friends" to "teammates"). Regression analyses adjusted for age, sex, and minority status. More evening chronotype was associated with higher reported depressive symptoms (p = .018), lower overall perceived social support (p = .001), and lower perceived social support specifically provided by family (p < .0001), friends (p < .0001), and teammates (p = .014). However, more evening chronotype was associated with higher depressive symptoms for higher, but not lower perceived social support from significant other. Moreover, chronotype-by-support interactions on depressive symptoms were observed; the statistical relationship between chronotype and depression was evident only in those with low (but not high) social support from friends and teammates. These data suggest that having a more evening chronotype may be associated with social isolation, and decreased opportunities for interactions with friends and teammates. This may contribute to the long-standing circadian association seen with depression in college student-athletes. Interventions aimed at increasing university support networks may reduce the impact of depression in students self-identifying with later chronotypes and sleep schedules.

Prevalence and risk factors of sleep disorders in visually impaired athletes

OBJECTIVE

The present study clarified the prevalence and risk factors of sleep disorders in visually impaired athletes.

METHODS

A cross-sectional questionnaire survey was conducted with 99 visually impaired athletes engaged in the following Paralympic sport events: track and field (marathon), goalball, swimming, blind soccer, and judo. Eighty-one respondents (male: 72.8%; average age: 32.5 ± 12.0 years) who completed the survey were chosen for analyses. Survey items were attributes [age, gender, body mass index, and condition of visual impairment (athletic classification and causing time of disability)], lifestyle habits (bedtime, wake-up time, drinking alcohol, meals, and use of electronics after lights out), competition activities (sports time per week, morning and evening practices, and competition stressors), psychological distress, and sleep disorders [recorded using the Pittsburgh Sleep Quality Index (PSQI)]. First, the prevalence of the respondents having sleep disorders (scored 5.5 points or more in the PSQI) was investigated. Then, the relations between attributes, lifestyle habits, competition activities, psychological distress, and sleep disorders were explored using logistic regression analysis.

RESULTS

Twenty-six respondents (32.1%) had sleep disorders. Results of multivariate logistic regression analysis showed that "interpersonal relationship stressors" and "wake-up time" were independently related to sleep disorders.

CONCLUSIONS

Approximately one-third of visually impaired athletes were shown to have sleep disorders. High interpersonal relationship stressors and late wake-up time may be risk factors of their sleep disorders.

A Novel Hybrid Machine Learning Classification for the Detection of Bruxism Patients Using Physiological Signals

Bruxism is a sleep disorder in which the patient clinches and gnashes their teeth. Bruxism detection using traditional methods is time-consuming, cumbersome, and expensive. Therefore, an automatic tool to detect this disorder will alleviate the doctor workload and give valuable help to patients. In this paper, we targeted this goal and designed an automatic method to detect bruxism from the physiological signals using a novel hybrid classifier. We began with data collection. Then, we performed the analysis of the physiological signals and the estimation of the power spectral density. After that, we designed the novel hybrid classifier to enable the detection of bruxism based on these data. The classification of the subjects into “healthy” or “bruxism” from the electroencephalogram channel (C4-A1) obtained a maximum specificity of 92% and an accuracy of 94%. Besides, the classification of the sleep stages such as the wake (w) stage and rapid eye movement (REM) stage from the electrocardiogram channel (ECG1-ECG2) obtained a maximum specificity of 86% and an accuracy of 95%. The combined bruxism classification and the sleep stages classification from the electroencephalogram channel (C4-P4) obtained a maximum specificity of 90% and an accuracy of 97%. The results show that more accurate bruxism detection is achieved by exploiting the electroencephalogram signal (C4-P4). The present work can be applied for home monitoring systems for bruxism detection.

A critical review on sleep assessment methodologies in athletic populations: factors to be considered

A growing body of research focus on athletes' sleep in order to investigate the effects of sleep in sports performance and recovery or the prevalence of sleep disorders in athletes. At the same time, several sleep monitoring tools have been developed and used in athletic populations for fulfilling these purposes. This review aimed to provide critical assessment to the most used by athletes' methodological approaches and compared them with the gold standard approach. Advantages and disadvantages of the various sleep monitoring tools were critically discussed. Literature related to aspects of athletes' sleep was reviewed. From the shortlisted studies, several factors that seem to affect sleep in athletes were identified using objective methods such as polysomnography/electroencephalography and actigraphy. These factors were associated to sleep (eg such as sleep environment, familiarization procedures and napping) and daily habits (eg nutrition, fluid consumption, alcohol and caffeine intake, tobacco use). The selected studies that evaluated sleep objectively were screened according the reporting rates of these variables. The majority of the screened studies were found to underreport these variables. Practical issues were addressed and recommendations about reporting sleep-related factors were made in order to improve studies' quality assessment and allow for more robust comparisons between studies.

Mental Health Status and Related Factors Among Visually Impaired Athletes

Background

A growing body of pieces of evidence suggests that sport activity is of potential importance both for physical and mental health. To date, there is a lack of information and evidence regarding the mental health of visually impaired people playing some extent of sports and recognized as athletes with renowned career track. The present study aims to clarify the mental health status and its related factors in visually impaired athletes.

Methods

The current study was a questionnaire-based cross-sectional investigation. Visually impaired athletes (n = 81; men: 72.8%; average age: 32.8 ± 12.0 years) engaged in Paralympic sports events namely track and field (marathon), goalball, swimming, blind soccer, and judo were the study subjects from leading institutions in Japan. A diverse range of issues were included in a questionnaire survey like attributes, condition of visual impairment, competition activities, competition stressors, social support, and mental health status (recorded through the K6 scale). Logistic regression analyses were performed with mental health status as a dependent variable and other studied parameters as independent variables.

Results

A total of 21.0% of study participants (11.9% of men and 45.5% of women) showed bad mental health condition. Results of multivariate logistic regression analysis showed that “female” (odds ratio (OR) 11.94, 95% confidence interval (CI) 2.60 - 54.76, P = 0.001), “higher evaluation from one’s surroundings for competition stressors” (OR 5.74, 95% CI 1.34 - 24.60, P = 0.019), and “lower social support from family members” (OR 3.97, 95% CI 1.03 - 15.25, P = 0.045) were the risk factors of bad mental health.

Conclusions

The mental health status among visually impaired athletes might be almost the same level as non-visually impaired athletes and general population, and have relation to gender, stress of evaluation from surroundings during competition, and social support from family members. It may be necessary to pay attention especially to women, and improve one’s surroundings of competition stressors and family social support to maintaining the mental health of visually impaired athletes.

The onset of sleep disturbances and their associations with anxiety after acute high-altitude exposure at 3700 m

Sleep disturbances and psychiatric repercussions pose great challenges at high altitude; however, few studies have investigated sleep disturbance and anxiety profiles and their associations after acute exposure in consecutive patients. Thus, we aimed to study the profiles of sleep disturbances in consecutive patients after high-altitude exposure and the association of such disturbances with anxiety. A total of 668 participants were recruited at sea level and 3700 m. The trials were performed at sea level (1 week prior to a 2-h flight to a high-altitude destination) and at 3700 m (24, 72, and 168 h). Sleep disturbances were assessed by self-reported sleep patterns and scores on the Athens Insomnia Scale (AIS). State anxiety was assessed using the Self-Rating Anxiety Scale (SAS). In our study, the incidence of sleep disturbances increased significantly after acute high-altitude exposure (65.3%, 434/668) and then gradually decreased after 72 h (50%, 141/282) and 168 h (44%, 124/282). The sleep assessments AIS [2.0 (4.0) vs. 4.0 (5.0)] and ESS [4.0 (4.0) vs. 5.0 (5.0)] increased significantly (p < 0.05). Also, the SAS increased significantly from 26.25 (3.75) to 28.75 (7.5). The SAS was significantly high in sleep disturbance group [31.25 (7.5) vs. 27.5 (5), p < 0.001] than in the non-sleep- disturbance group. The baseline SAS and AIS scores were significantly higher in participants with sleep disturbances than in those without (p < 0.01). Age, baseline insomnia, sleepiness, fatigue, and higher SAS were predictors of sleep disturbances in univariate regression (all p values < 0.05). However, only an older age (p = 0.045) and a higher baseline SAS (p = 0.018) remained independent predictors of sleep disturbances. Our findings indicated that acute high-altitude exposure triggers the onset of sleep disturbances, which are closely associated with anxiety. Furthermore, baseline state anxiety and age are independent predictors of sleep disturbances at high altitude.

Naps and exercise: reinforcing a range of benefits for elderly health

According to the United Nations, in 2017, people aged 60 or over in the world, comprised 13 per cent of the global population. It is a fact that elderly people are keeping a health lifestyle, such as practicing physical exercises and avoiding excessive dosages of medications. However, this population is also more prone to have injuries while practicing exercises. Sleep architecture is physiologically different among elderly, and naps can be very beneficial to improve their mental and physical health. Thus, in this article, we encourage health professionals to recommend regular naps to this population, which could lead to an improve in their well-being and quality of life.

Mobile Phone Use and Mental Health. A Review of the Research That Takes a Psychological Perspective on Exposure

The purpose of this study was to carry out a review of observational studies that consider links between mobile phone use and mental health from a psychological or behavioral perspective. Systematic literature searches in PubMed and PsycINFO for articles published until 2017 were done. Exclusion criteria included: papers that considered radiofrequency fields, attention, safety, relational consequences, sexual behavior, cyberbullying, and reviews, qualitative, and case or experimental studies. A total of 4738 papers were screened by title and abstract, 404 were retrieved in full text, and 290 were included. Only 5% had any longitudinal design. Self-reporting was the dominating method of measurement. One third of the studies included children or youth. A majority of adult populations consisted of university students and/or self-selected participants. The main research results included associations between frequent mobile phone use and mental health outcomes, such as depressive symptoms and sleep problems. Mobile phone use at bedtime was associated with, e.g., shorter sleep duration and lower sleep quality. "Problematic use" (dependency) was associated with several negative outcomes. In conclusion, associations between mobile phone use and adverse mental health outcomes are found in studies that take a psychological or behavioral perspective on the exposure. However, more studies of high quality are needed in order to draw valid conclusions about the mechanisms and causal directions of associations.

Sleep Quality and Chronotype Differences between Elite Athletes and Non-Athlete Controls

Previous research has found that elite athletes have insufficient sleep, yet the specific kinds of sleep disturbances occurring as compared to a control group are limited. Here we compare the subjective sleep quality and chronotype of elite athletes to a control group of non-athlete good sleepers. Sixty-three winter Canadian National Team athletes (mean age 26.0 ± 0.0; 32% females) completed the Pittsburgh Sleep Quality Index (PSQI) and the Athlete Morningness Eveningness Scale. They were compared to 83 healthy, non-athlete, good-sleeper controls (aged 27.3 ± 3.7; 51% females) who completed the PSQI and the Composite Scale of Morningness. The elite athletes reported poorer sleep quality (PSQI global score 5.0 ± 2.6) relative to the controls (PSQI global score 2.6 ± 1.3), despite there being no group difference in self-reported sleep duration (athletes 8.1 ± 1.0 h; controls 8.0 ± 0.7 h). Further, athletes’ chronotype distribution showed a greater skew toward morningness, despite there being no group differences in self-reported usual bedtime and wake time. These results suggest that a misalignment of sleep times with circadian preference could contribute to poorer sleep quality in elite athletes.

The Clinical Validation of the Athlete Sleep Screening Questionnaire: an Instrument to Identify Athletes that Need Further Sleep Assessment

Background

Previous research has established that general sleep screening questionnaires are not valid and reliable in an athlete population. The Athlete Sleep Screening Questionnaire (ASSQ) was developed to address this need. While the initial validation of the ASSQ has been established, the clinical validity of the ASSQ has yet to be determined. The main objective of the current study was to evaluate the clinical validity of the ASSQ.

Methods

Canadian National Team athletes (N = 199; mean age 24.0 ± 4.2 years, 62% females; from 23 sports) completed the ASSQ. A subset of athletes (N = 46) were randomized to the clinical validation sub-study which required subjects to complete an ASSQ at times 2 and 3 and to have a clinical sleep interview by a sleep medicine physician (SMP) who rated each subjects’ category of clinical sleep problem and provided recommendations to improve sleep. To assess clinical validity, the SMP category of clinical sleep problem was compared to the ASSQ.

Results

The internal consistency (Cronbach’s alpha = 0.74) and test-retest reliability (r = 0.86) of the ASSQ were acceptable. The ASSQ demonstrated good agreement with the SMP (Cohen’s kappa = 0.84) which yielded a diagnostic sensitivity of 81%, specificity of 93%, positive predictive value of 87%, and negative predictive value of 90%. There were 25.1% of athletes identified to have clinically relevant sleep disturbances that required further clinical sleep assessment. Sleep improved from time 1 at baseline to after the recommendations at time 3.

Conclusions

Sleep screening athletes with the ASSQ provides a method of accurately determining which athletes would benefit from preventative measures and which athletes suffer from clinically significant sleep problems. The process of sleep screening athletes and providing recommendations improves sleep and offers a clinical intervention output that is simple and efficient for teams and athletes to implement.

Electronic supplementary material

The online version of this article (10.1186/s40798-018-0140-5) contains supplementary material, which is available to authorized users.