The Relation Between Complexity and Resilient Motor Performance and the Effects of Differential Learning

Testing the hormesis hypothesis on motor behavior under stress

While much research has focused on the deleterious effects of stress on goal-directed behavior in recent decades, current views increasingly discuss growth under stress, often assuming dose-dependent effects of stress in a curvilinear association. This is based on the concept of hormesis, which postulates a strengthening effect of stress at low-to-moderate doses. Leveraging this approach, hormetic curves indicate under which stress dose an individual is able to maintain or even increase goal-directed behavior. The present study aimed to test the hormetic effect of low-to-moderate stress on tactical movement performance in the context of police operational scenarios in virtual reality. In teams of three to four, 37 riot police officers had to search a building for a potentially aggressive perpetrator in three scenarios with escalating stress potential (i.e., increasing weapon violence and number of civilians). Tactical movement performance as behavioral response was quantified by the sample entropy of each officer's velocity derived from positional data. To account for inter-individuality in response to the scenarios, we assessed self-reported stress, anxiety, mental effort, and vagally mediated heart rate variability. Specifically, we tested the quadratic associations between tactical movement performance and stress parameters, respectively. Random-intercept-random-slope regressions revealed neither significant linear nor quadratic associations between any of the stress parameters and performance. While we did not find evidence for hormesis in the present study, it stimulates theoretical discussions about the definition of "baseline" functioning and how the understanding of hormesis can move from psychological to behavioral adaptations to stressors.

How the Complexity of Psychological Processes Reframes the Issue of Reproducibility in Psychological Science

In the past decade, various recommendations have been published to enhance the methodological rigor and publication standards in psychological science. However, adhering to these recommendations may have limited impact on the reproducibility of causal effects as long as psychological phenomena continue to be viewed as decomposable into separate and additive statistical structures of causal relationships. In this article, we show that (a) psychological phenomena are patterns emerging from nondecomposable and nonisolable complex processes that obey idiosyncratic nonlinear dynamics, (b) these processual features jeopardize the chances of standard reproducibility of statistical results, and (c) these features call on researchers to reconsider what can and should be reproduced, that is, the psychological processes per se, and the signatures of their complexity and dynamics. Accordingly, we argue for a greater consideration of process causality of psychological phenomena reflected by key properties of complex dynamical systems (CDSs). This implies developing and testing formal models of psychological dynamics, which can be implemented by computer simulation. The scope of the CDS paradigm and its convergences with other paradigms are discussed regarding the reproducibility issue. Ironically, the CDS approach could account for both reproducibility and nonreproducibility of the statistical effects usually sought in mainstream psychological science.

Always Pay Attention to Which Model of Motor Learning You Are Using

This critical review considers the epistemological and historical background of the theoretical construct of motor learning for a more differentiated understanding. More than simply reflecting critically on the models that are used to solve problems-whether they are applied in therapy, physical education, or training practice-this review seeks to respond constructively to the recent discussion caused by the replication crisis in life sciences. To this end, an in-depth review of contemporary motor learning approaches is provided, with a pragmatism-oriented clarification of the researcher's intentions on fundamentals (what?), subjects (for whom?), time intervals (when?), and purpose (for what?). The complexity in which the processes of movement acquisition, learning, and refinement take place removes their predictable and linear character and therefore, from an applied point of view, invites a great deal of caution when trying to make generalization claims. Particularly when we attempt to understand and study these phenomena in unpredictable and dynamic contexts, it is recommended that scientists and practitioners seek to better understand the central role that the individual and their situatedness plays in the system. In this way, we will be closer to making a meaningful and authentic contribution to the advancement of knowledge, and not merely for the sake of renaming inventions.