Student Blog 06: The Association Between Subjective Sleep and Stress in Recreational Athletes

My background: After moving home to Ireland from Canada, I completed my initial qualification in Exercise and Health Fitness (University Limerick) in 2014. In 2015 I began my four year BSc in Sports Coaching and Performance (SETU Waterford). Upon completion of my BSc, I completed my MSc in Applied Sport and Exercise Psychology (SETU Waterford) and then completed a further MSc in Psychology (Northumbria University). I now work as a performance consultant and own and operate Effectus in Waterford City which is a community based fitness and health facility that focuses on developing health through fitness, nutrition and psychology.

My research project was carried out with The Northumbria Centre for Sleep Research, Northumbria University under the supervision of Dr. Greg Elder, Assistant Professor Psychology. The primary aim of the study was to examine the association between subjective sleep quality and subjective stress levels in a population of recreational athletes. The secondary aims of this research study were to examine the association between subjective stress and training load/levels of overtraining and to examine the association between subjective sleep and training load/levels of overtraining.

Sleep has been previously reported as the most important recovery tool at the disposal of elite, sub-elite and recreational athletes (Venter, 2012). The growing body of research literature suggests that sleep is the new frontier in performance enhancement among an athletic population (Leeder et al., 2012). Although participation in regular physical exercise has been associated with better levels of sleep quantity and quality, athletes at varying competitive levels have been found to experience worse sleep quality when compared to measures among the general population (Gupta et al., 2017). It is evident from the current body of literature that athletes consistently report high levels of sleep inadequacy due to sport-specific and lifestyle factors. Such factors explaining this clear sleep inadequacy are high training loads, evening competition and training related early morning start times as well as lifestyle sacrifices in order to complete training. It is likely for these reasons, that athletes may have a higher need for physical and mental recovery than non-active individuals (Walsh et al., 2021).

Subjective sleep and stress are strongly associated, at multiple levels, and the current body of evidence highlights that this association is bidirectional. Previous research has highlighted that issues with sleep can impact on several stress responses. On the other side of this relationship, research highlights that stress-inducing factors can significantly impact sleep. Research is emerging highlighting the bidirectional relationship between subjective sleep and stress among elite and sub elite athletes. The present study examined this association in a sample of recreational athletes, a population that has received little to no research focus in this area.

Recreational athletes have previously been defined as individuals who exercise >4 hours per week for health, fitness, or unofficial competitions (McKinney et al., 2019). Recreational athletes have been shown to have similar demanding training schedules to elite and sub-elite athletes and often compromise their sleep in order to fit their training schedule into their already busy lifestyles. Recreational athletes have double burden life stressors and responsibilities to manage on top of their individual training schedules.

In order to determine the sample size for this study an a priori power analysis was conducted using the software GPower (Faul et al., 2007). 34 Recreational athletes completed an online questionnaire consisting of measures of the Pittsburgh Sleep Quality Index (PSQI) to measure subjective sleep, The Perceived Stress Scale (PSS) to measure subjective stress, The Hospital Anxiety and Depression Scale (HADS) to measure subjective mood, specifically anxiety/depression and The Daily Analysis of Life Demands for Athletes (DALDA) to measure training load and levels of overtraining. A Pearson’s bivariate correlation coefficient test was carried out to examine the associations between variables.

Within the population of recreational athletes, 67.6% (n = 23)  were classified as ‘good sleepers’ and 32.3% (n = 11) were classified as ‘poor sleepers” as per the PSQI classifications. In line with the primary research aim, significant moderate positive correlations were found between subjective sleep and subjective stress. These results indicate that recreational athletes who report better subjective sleep scores also report lower levels of stress. The groups mean scores for anxiety and depression were non cases as per the HADS which highlights that subjective mood did not appear to be a confounding variable and that the association found between subjective sleep and stress was not due to mood, specifically anxiety or depression.

In line with the secondary research aims, significant strong positive correlations were found between subjective stress and training load/levels of overtraining. These results indicate that recreational athletes who report better subjective stress scores also report lower levels of overtraining. There was also significant moderate positive correlations found between subjective sleep and training load/levels of overtraining. These results indicate that recreational athletes who report better subjective sleep scores also report lower levels of overtraining.

The positive association between subjective good sleep and perceived stress and levels of overtraining in this study highlight the importance of consistent quality sleep for recreational athletes. These findings may begin to inform educational content for a group that has previously received little research focus. Individualised sleep hygiene practices tailored to the constraints of recreational athletes who have to balance their training with other life stressors may enhance quality of sleep which is critical for physiological and psychological recovery.

The initial novel findings presented in this study may provide justification for future research in this area. Studies that are longitudinal in their design may be able to explore the bidirectional relationship between sleep, stress, mood and training load over a longer period and include interventions aimed at improving these key health variables. Geynther et al., (2022) carried out a systematic review and meta-analysis of certain sleep interventions for improving sleep, stress, mood and performance in athletes. The researchers found that interventions such as sleep education, sleep hygiene, assisted sleep and sleep extension may bring about positive improvements in sleep, mood and performance outcomes. The reciprocal interaction between these variables is still not fully understood and further research into this area is advocated.

Jay Walsh

jaywalshperformance@gmail.com

LinkedIn: http://linkedin.com/in/jay-walsh-209245224

Instagram: @effectus_fnm

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Practitioner Blog 02: “Raising the bar in Sport Coaching

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Student Blog 05: Investigating the effects of powered exoskeleton-based physical activity in adults with neurological impairments.