Self-Determined Motivation and Competitive Anxiety in Athletes/Students: A Probabilistic Study Using Bayesian Networks

Abstract

This study attempts to analyze the relationship between two key psychological variables associated with performance in sports – Self-Determined Motivation and Competitive Anxiety – through Bayesian Networks (BN) analysis. We analyzed 674 university students that are athletes from 44 universities that competed at the University Games in Mexico, with an average age of 21 years (SD = 2.07) and with a mean of 8.61 years’ (SD = 5.15) experience in sports. Methods: Regarding the data analysis, firstly, classification using the CHAID algorithm was carried out to determine the dependence links between variables; Secondly, a BN was developed to reduce the uncertainty in the relationships between the two key psychological variables. The validation of the BN revealed AUC values ranging from 0.5 to 0.92. Subsequently, various instantiations were performed with hypothetical values applied to the “bottom” variables. Results showed two probability trees that have extrinsic motivation and amotivation at the top, while the anxiety/activation due to worries about performance was at the bottom of the probabilities. The instantiations carried out support the existence of these probabilistic relationships, demonstrating their scarce influence on anxiety about competition generated by the intrinsic motivation, and the complex probabilistic effect of introjected and identified regulation regarding the appearance of anxiety due to worry about performance.

The Influence of the Trainer’s Social Behaviors on the Resilience, Anxiety, Stress, Depression and Eating Habits of Athletes

“…Different studies in the field of sport have shown that anxiety is negatively related to sports performance [33], concentration [34], social relations [35] and self-confidence [36]. In contrast, anxiety has been positively related to stress [37], amotivation [38], dropout [39], depression [40] and mental rumination [34].…”

Competitive Anxiety, and Guilt and Shame Proneness From Perspective Type D and Non-type D Football Players

“…Currently, there are only a few studies dealing with type D personalities in the sports context (Borkoles et al, 2018). Also, only a few studies deal with competitive anxiety in individual and team sports (Verdaguer et al, 2016;Cho et al, 2019;Ponseti et al, 2019;González-Hernández et al, 2020;Reigal et al, 2020;Vila et al, 2020) and guilt and shame proneness of athletes, which plays a key role in creating mental blocks from a failed performance (Murrar et al, 2019). As we consider the examination of this connection to be justified, and currently there is no research of this type, we decided to formulate the following research questions in the presented study: (1) Are there statistically significant differences in competitive anxiety, and guilt and shame proneness between type D football players and non-type D?…”

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

“…Based on the above results, it was decided to explore, as in previous studies [ 48 , 66 , 70 ], the changes in the probabilities of occurrence of antecedent variables when hypothetical values are “injected” into bottom or consequent variables. To be more precise, and also considering the meaning of the variables, the instantiations that have been carried out are as follows: Social support, passing to 0% HIGH; DOSPERT-S, Social/Safety, passing to 100% HIGH; Depression, passing to 100% HIGH; The union of the three above, simultaneously.…”

“…The graphical representation of BNs captures the compositional structure of the relations and the general aspects of all probability distributions that are factorised according to that structure. They have proven to be a promising tool for discovering relationships between negative features in sport [ 44 ], and in many other sport-related studies, such as cooperative teamwork, motivation and types of sporting cooperation among players in competing teams, motivational climate and competitive anxiety, psychological variables related to athlete injuries [ 45 ], the relative effect of age [ 46 , 47 , 48 , 49 ], and the relation between sport and educational performance [ 50 ]. In line with our study, a number of papers have recently been published that use a new approach, called dynamic BNs, which strives to predict and then mitigate the probability of injuries occurring in athletes [ 51 ].…”