Emotion regulation and motor performance: an integrated review and proposal of the Temporal Influence Model of Emotion Regulation (TIMER)

ABSTRACT

Adaptive regulation of emotions is imperative for successful sport performance. However, the lion’s share of mainstream emotion regulation (ER) literature is founded on perspectives prioritising mental health, not performance. Consequently, ER strategies are predominantly classified as adaptive or maladaptive based on effectiveness in achieving targeted mental health outcomes. These conventional mental health classifications can catalyse misapplication of ER strategies within sport and other motor performance contexts when (1) ER motives are instrumentally directed towards performance enhancement and (2) Minimal consideration is given to the consequences of ER on the coordination and execution of motor actions. Herein, we review the current state of relevant ER research within and outside of sport contexts. We also present a novel conceptual framework, the Temporal Influence Model of Emotion Regulation (TIMER). TIMER proposes that ER strategies exert distinct, temporally dependent demands upon perceptual-cognitive and motoric resources. These unique regulatory profiles influence subsequent motor performance outcomes. Critically, the degree to which regulatory strategies are appropriate or ideal varies given environmental constraints along with performers’ affective and performance goals. The model includes testable hypotheses to guide theoretical and applied research in the domain of ER within sport and other motor performance contexts.     

Understanding the relative contribution of technical and tactical performance to match outcome in Australian Football

ABSTRACT

The aim of this study was to assess if tactical and technical performance indicators (PIs) could be used in combination to model match outcomes in Australian Football (AF). A database of 101 technical PIs and 14 tactical PIs from every match in the 2009–2016 Australian Football League (AFL) seasons was merged. Two outcome measures Win-loss and Score margin were used as dependent variables. The top 45 ranked technical and tactical PIs from a feature selection process were used to model match outcome using decision tree and Generalised Linear Models (GLMs). Of the top 45 selected features, this included seven tactical PIs. The Win-loss-based Decision tree model achieved a classification accuracy of 89.0% and GLM 93.2%. A Score margin-based GLM achieved a root mean squared error (RMSE) of 6.9 points. A combined approach to the classification of match outcomes provided no improvement in model accuracy compared with previous literature. However, this study has established the relative importance of technical and tactical measures of performance in relation to successful team performance in AF.     

Conflict-Framed News,Self-Categorization,and Partisan Polarization

Two experiments tested whether exposure to partisan conflict-framed news polarizes news consumers along party lines. Partisan self-categorization and motivated reasoning were examined as potential mediators of this effect. In two samples, path analyses showed that Democrats and Republicans exposed to partisan conflict-framed news adopted more polarized opinions on a disputed issue. This polarization effect was consistently mediated by perceived argument validity, an indicator of motivated reasoning; increased partisan self-categorization also mediated the effect, though less reliably and consistently. Thus, the present study adds to the literature on polarization by providing experimental evidence that exposure to conflict-framed news may contribute to partisan polarization. Theoretical and practical implications are discussed.     

An Interdisciplinary Model of School Absenteeism in Youth to Inform Professional Practice and Public Policy

Problematic school absenteeism in youth has long been a complex and vexatious issue for psychologists, educators, and researchers from other disciplines. An examination of problematic school absenteeism from different perspectives over many decades has led to poor comparability across publications, policies, and assessment and intervention protocols. This article briefly reviews literature from psychology, social/criminal justice, and education to outline important factors that influence school absenteeism. An interdisciplinary model is then proposed with an emphasis on common terminology and definitions, comprehensiveness with respect to proximal and distal influences, fluidity and flexibility to account for rapid changes in this population, and user-friendliness to generate suggestions regarding assessment and intervention. Implications of the model are then drawn for professional practice and public policy, including recommendations for individual and systemic intervention at multiple levels of risk and severity.     

College Students’ Time Management: a Self-Regulated Learning Perspective

Educational Psychology Review - Despite its recognized importance for academic success, much of the research investigating time management has proceeded without regard to a comprehensive...     

From research to reality: Australian evidence-based practice in autism education

Many teachers are sporadic in using evidence-based practice (EBP) concerning students with autism spectrum disorder (ASD). Numerous reasons have been posited for this. However, no single study has worked to understand the relative importance of identified criteria in the EBP decision-making processes of teachers. Through the development of a new survey tool, the Evidence-Based Practice Innovation Survey (EBPIAS), an exploration of the decision-making process of Australian teachers in their adoption and cessation of EBP was undertaken. Teachers rated the perception that an EBP would meet the needs of their students as the most important criteria in determining their use of EBP. Conversely, the judgement that an EBP did not meet the needs of their student was the most important criteria in their decision to cease use. In comparing the relevant importance of identified criteria, teachers rated the perception of training as the second-lowest consideration in their decision to adopt and cease using EBP. Consequently, there may need to be greater promotion of, or information concerning, the training required by teachers for effective implementation supporting a more balanced and holistic approach in assessing criteria impacting the adoption of EBP by teachers in the first instance, potentially lowering cessation rates.     

Choosing and leaving science in highly selective institutions

This study sought to discover some of the causes of initial interset in and atrition from the natural sciences and engineering among the students (N=5320) who entered four highly selective institutions in 1988, with particular attention to possible special causes for the disproportionate attrition of women from science. Though a smaller proportion of women (35 percent) than men (49 percent) were initially interested in science, gender added little to the prediction of such initial choice when preadmission measures of developed abilities were taken into account in regression analysis. Of the group of 2,276 students initially interested in science, 40 percent did not finally concentrate in science, and smaller proportions of women (48 percent) than of men (66 percent) persisted. The most significant cognitive, factor predicting these losses was low grades earned in science courses taken during the first two years of study. With grades held equal, gender was not a significant predictor of persistence in engineering and biology; gender added strongly to grades, however, as a factor associated with unusually large losses of women from a category that included the physical sciences and mathematics. Responses to a questionnaire administered in the fall of 1991 showed that science majors regarded their instruction as too competitive, with too few opportunities to ask questions, taught by professors who were relatively unresponsive, not dedicated, and not motivating. Students who defected from science did so largely because of the attraction of other fields, but many shared the criticism of overcompetitiveness and inferior instruction, along with the view that the work was too difficult. Several items were about elements of classroom instruction and atmosphere thought to be especially difficult for women (i.e., the chilly climate), but except for perceived competitiveness, women did not rate their classroom experiences as being more unpleasant than did men. This research was supported by grants from the Alfred P. Sloan Foundation and the National Science Foundation.     

Modeling Zero-Inflated and Overdispersed Count Data: An Empirical Study of School Suspensions

The purpose of this article is to develop a statistical model that best explains variability in the number of school days suspended. Number of school days suspended is a count variable that may be zero-inflated and overdispersed relative to a Poisson model. Four models were examined: Poisson, negative binomial, Poisson hurdle, and negative binomial hurdle. Additionally, the probability of a student being suspended for at least 1 day was modeled using a binomial logistic regression model. Of the count models considered, the negative binomial hurdle model had the best fit. Modeling the probability of a student being suspended for at least 1 day using a binomial logistic regression model with interactions fit both the training and test data and had adequate fit. Findings here suggest that both the negative binomial hurdle and the binomial logistic regression models should be considered when modeling school suspensions.