The past, present and future of research on judgment and decision making in sport

Objectives: The study of judgment and decision-making in sports is at least as old as the anniversary of FEPSAC we celebrate with this special issue. It seems therefore appropriate to look into the past, present and future of this topic. Design: For the past, a focus of the review is relating the European perspective of the co-authors into a larger frame of areas in judgment and decision making within the last 50 years and beyond. Method/Results/Conclusions: For the present, scientific current developments will be structured as judgments from the most influential perspectives such as the economical, social cognition, ecological dynamics or cognitive approaches illustrating some milestones in research on judgment and decision-making in sports of today. For the future, potentials of the field will be structured based on theory, methodology and practical applications showcasing challenges for the next decades of research ahead of us

Applications of Sports Data to Study Decision Making

The features and determinants of human decision making, especially under competitive environments, have been a central theme of research in economics and psychology alike. This special issue centers on applying sports data to understand behavior and decision making in competitive environments. In particular, we assemble original research with sports data that provides us with insights into hitherto unanswered questions relating to various strategic and psychological aspects of decision making

Decision-making of English Netball Superleague umpires: Contextual and dispositional influences

Objectives. The decisions made by officials have a direct bearing on the outcomes of competitive sport contests. In an exploratory study, we examine the interrelationships between the decisions made by elite netball umpires, the potential contextual and environmental influences (e.g., crowd size), and the umpires’ dispositional tendencies – specifically, their propensity to deliberate and ruminate on their decisions. Design/Method. Filmed footage from 60 England Netball Superleague matches was coded using performance analysis software. We measured the number of decisions made overall, and for home and away teams; league position; competition round; match quarter; and crowd size. Additionally, 10 umpires who officiated in the matches completed the Decision-Specific Reinvestment Scale (DSRS). Results. Regression analyses predicted that as home teams’ league position improved the number of decisions against away teams increased. A model comprising competition round and average league position of both teams predicted the number of decisions made in matches, but neither variable emerged as a significant predictor. The umpire analyses revealed that greater crowd size was associated with an increase in decisions against away teams. The Decision Rumination factor was strongly negatively related to the number of decisions in Quarters 1 and 3, this relationship was driven by fewer decisions against home teams by umpires who exhibited higher Rumination subscale scores. Conclusions. These findings strengthen our understanding of contextual, environmental, and dispositional influences on umpires’ decision-making behaviour. The tendency to ruminate upon decisions may explain the changes in decision behaviour in relation to the home team advantage effect

Corporeality, equality and education. A biopedagogical perspective

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Application of a stochastic modeling to evaluate tuberculosis onset in patients treated with tumor necrosis factor inhibitors

In this manuscript we apply stochastic modeling to investigate the risk of reactivation of latent mycobacterial infections in patients undergoing treatment with tumor necrosis factor inhibitors. First, we review the perspective proposed by one of the authors in a previous work and which consists in predicting the occurrence of reactivation of latent tuberculosis infection or newly acquired tuberculosis during treatment; this is based on variational procedures on a simple set of parameters (e.g. rate of reactivation of a latent infection). Then, we develop a full analytical study of this approach through a Markov chain analysis and we find an exact solution for the temporal evolution of the number of cases of tuberculosis infection (re)activation. The analytical solution is compared with Monte Carlo simulations and with experimental data, showing overall excellent agreement. The generality of this theoretical framework allows to investigate also the case of non-tuberculous mycobacteria infections; in particular, we show that reactivation in that context plays a minor role. This may suggest that, while the screening for tuberculous is necessary prior to initiating biologics, when considering non-tuberculous mycobacteria only a watchful monitoring during the treatment is recommended. The framework outlined in this paper is quite general and could be extremely promising in further researches on drug-related adverse events.Comment: 26 pages, 7 figure