The prevalence of menstrual cycle symptoms and their association with mental health and sleep in German exercising women and athletes.

OBJECTIVES: Menstrual cycle symptoms are very common in female athletes. However, more evidence about the association between menstrual cycle characteristics and symptoms with sleep and mental health in athletes needs to be gathered. This study aimed to examine this association in German exercising women and athletes. DESIGN: 322 women (mean age: 23.13 ±â€¯4.36) participated in a cross-sectional study. The survey included the Menstrual Symptom index (MSi), the Depression Anxiety Stress Scales (DASS-21), the Pittsburgh Sleep Quality Index (PSQI), and the Athletes Sleep Behavior Questionnaire (ASBQ). Additionally, demographic, sport-specific data and further menstrual cycle characteristics were examined. Multiple regression models were used for the statistical analyses. RESULTS: The MSi score demonstrated a highly significant (p < 0.001) positive association with Depression, Anxiety, Stress, PSQI, and ASBQ. The most prevalent menstrual cycle symptoms were cravings/increased appetite, mood changes/anxiety, and tiredness/fatigue. A difference between individual and team sport athletes could not be found. Moreover, there was no association between the constructs and menses length, irregularity, or heaviness of bleeding. CONCLUSIONS: Menstrual cycle symptoms occur very frequently in female athletes. In this study, they were related to mental health, sleep quality, and sleep behavior, regardless of the cycle phase. This evidence demonstrates the relevance of considering the menstrual cycle and menstrual symptoms in future studies with female athletes and in sport practice.

Effects of sleep self-monitoring via app on subjective sleep markers in student athletes.

As sleep problems are highly prevalent among university students and competitive athletes, and the application of commercial sleep technologies may be either useful or harmful, this study investigated the effects of a 2-week sleep self-monitoring on the sleep of physically active university students (n = 98, 21 ± 1.7 years). Two intervention groups used a free sleep app (Sleep Score; SleepScore Labs™, Carlsbad, CA, USA: n = 20 or Sleep Cycle; Sleep Cycle AB, Gothenburg, Sweden: n = 24) while answering online sleep diaries. They used the app analysis function in week 1 and the 'smart alarm' additionally in week 2. As controls, one group answered the online sleep diary without intervention (n = 21) and another the pre-post questionnaires only (n = 33). Facets of subjective sleep behaviour and the role of bedtime procrastination were analysed. Multilevel models did not show significant interactions, indicating intervention effects equal for both app groups. Sleep Cycle users showed trends toward negative changes in sleep behaviour, while the online sleep diary group showed more, tendentially positive, developments. Bedtime procrastination was a significant predictor of several variables of sleep behaviour and quality. The results indicate neither benefits nor negative effects of app-based sleep self-tracking. Thus, student athletes do not seem to be as susceptible to non-validated sleep technologies as expected. However, bedtime procrastination was correlated with poor sleep quality and should be addressed in sleep intervention programmes.

Spirometry has added value over electrodermal activity as a physiological marker of mental load in male subjects.

The objective distinction of different types of mental demands as well as their intensity is relevant for research and practical application but poses a challenge for established physiological methods. We investigated whether respiratory gases (oxygen uptake and carbon dioxide output) are suitable to distinguish between emotional stress and cognitive load. To this end, we compared the application of spirometry with an established procedure, namely electrodermal activity (EDA). Our results indicate that electrodermal activity shows a strong responsivity to emotional stress induction, which was highly correlated with its responsivity to cognitive load. Respiratory gases were both sensitive and specific to cognitive load and had the advantage of being predictive for cognitive performance as well as self-reported emotional state. These results support the notion that respiratory gases are a valuable complement to common physiological procedures in the detection and discrimination of different mental demands.