It Is Not Just Stress: A Bayesian Approach to the Shape of the Negative Psychological Features Associated with Sport Injuries

Abstract

The main objective of this study is to extend the stress and injury model of Andersen and Williams to other “negative” psychological variables, such as anxiety and depression, encompassed in the conceptual model of Olmedilla and García-Mas. The relationship is studied of this psychological macro-variable with two other variables related to sports injuries: the search for social support and the search for connections between risk and the environment of athletes. A combination of classic methods and probabilistic approaches through Bayesian networks is used. The study samples comprised 455 traditional and indoor football players (323 male and 132 female) of an average age of 21.66 years (±4.46). An ad hoc questionnaire was used for the corresponding sociodemographic data and data relating to injuries. The variables measured were the emotional states of: stress, depression and anxiety, the attitude towards risk-taking in different areas, and the evaluation of the perception of social support. The results indicate that the probabilistic analysis conducted gives a boost to the classic model focused on stress, as well as the conceptual planning derived from the Global Model of Sports Injuries (GMSI), supporting the possibility of extending the stress model to other variables, such as anxiety and depression (“negative” triad).

The bright side of sports: a systematic review on well-being, positive emotions and performance

“…In recent decades, research in the psychology of sport and physical exercise has focused on the analysis of psychological variables that could have a disturbing, unfavourable or detrimental role, including emotions that are considered 'negative' , such as anxiety/stress, sadness or anger, concentrating on their unfavourable relationship with sports performance [1][2][3][4], sports injuries [5][6][7] or, more generally, damage to the athlete's health [8][9][10]. The study of 'positive' emotions such as happiness or, more broadly, psychological well-being, has been postponed at this time, although in recent years this has seen an increase that reveals a field of study of great interest to researchers and professionals [11][12][13] including physiological, psychological, moral and social beneficial effects of the physical activity in comic book heroes such as Tintin, a team leader, which can serve as a model for promoting healthy lifestyles, or seeking 'eternal youth' [14].…”

Bayesian Network Analysis for Prediction of Unplanned Hospital Readmissions of Cancer Patients with Breakthrough Cancer Pain and Complex Care Needs

“…There is an increased interest in Bayesian statistical inference in public health and medical research. Many applications are in the field of cancer prediction and prognosis [ 17 ], but several pieces of research have been conducted in palliative care [ 18 ] as well as in other clinical settings and scenarios [ 19 , 20 , 21 ]. Interestingly, in large cohort of inpatients ( n = 198,972), Roth et al [ 22 ] investigated HRAs from all causes using Bayesian data-driven analytical methods.…”

“…In other words, a Bayesian approach allows a robust estimate based on the data but also exploits the information (e.g., correlations) on considered elements. The assumption is that although models must offer predictive results with excellent performance, often there is the need to provide an accurate estimate of the uncertainty of the prediction [ 20 ]. Thus, these Bayesian approaches are also increasingly used for predictive analysis in machine learning and artificial intelligence [ 17 , 24 ].…”

Load Monitoring and Its Relationship with Healthcare in Sports

“…Other negative psychological variables, such as stress, injury, anxiety, and depression in adult soccer players, were also analyzed [ 32 ]. In this regard, one study applied a mindfulness program to address levels of impulsivity, mood, and pre-competition anxiety in samples of athletics, tennis, swimming, basketball, handball, volleyball, and soccer athletes [ 33 ].…”