Identifying Psychological Difficulties in College 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.

What If Violent Behavior Was a Coping Strategy? Approaching a Model Based on Artificial Neural Networks

The aggressor sets in motion dysfunctional and violent behaviors with others in the dynamic of bullying. These behaviors can be understood as misfit coping strategies in response to environmental demands perceived as stressful, putting at risk the quality of education. The aim of this study was to develop a predictive model based on artificial neural networks (ANN) to forecast a violent coping strategy based on perceived stress, resilience, other coping strategies and various socio-demographic variables. For this purpose, the Stress Coping Questionnaire (SCQ), the Perceived Stress Scale (PSS) and the Brief Resilient Coping Scale (BRCS) were administered to 283 participants from the educational field (71.5% women). The design was cross-sectional. An inferential analysis (multilayer perception ANN) was performed with SPSS version 24. The results showed a predictive model that took into consideration the subject’s stress levels, personal assessment and strategies such as negative self-targeting or avoidance to predict open emotional expression (a coping strategy defined by violent behaviors) in approximately four out of five cases. The conclusions emphasis the need for considering problem solving, stress management and coping skills to prevent school violence and improve the social environment through sustainable psychological measures.

The Comparison of Perfectionism and Commitment between Professional and Amateur Golfers and the Association between Perfectionism and Commitment in the Two Groups

This study investigated differences in perfectionist traits and commitment between professional and amateur golfers, as well as correlations among perfectionist traits, commitment, and golf handicap. Using simple random sampling, 486 professional golfers (mean age = 22.1 ± 3.0, 52.1% female) and 233 amateur golfers (mean age = 44.8 ± 10.2, 55.8% female) were recruited and assessed using the Multidimensional Perfectionism Scale (MPS) and Expansion of Sports Commitment Model (ESCM). An ANCOVA, controlling for age, golf career length, and training time, revealed lower MPS self-oriented scores (10.3%; F = 8.9, p < 0.01; effect size [ES] = 0.498) and higher ESCM-Cognition (12.6%; F = 9.4, p < 0.01; ES = 0.691) and ESCM-Behavior (9.4%; F = 4.6, p = 0.03; ES = 0.479) scores in professional golfers than in amateur golfers. In partial correlations controlling for age, golf career length, and training time, professional golfers' MPS scores were negatively associated with ESCM-Cognition scores (r = -0.30, p < 0.001). Professional golfers' mean golf handicap was positively correlated with MPS total (r = 0.33, p < 0.01). Altogether, golfers seeking to attain high levels of performance must consider the mental aspect of golfing and find ways to maximize commitment levels while minimizing perfectionist traits.