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Dana Perlman

The purpose of this study is to examine the influence of the Sport Education Model (SEM) on amotivated students affect and needs satisfaction. 78 amotivated students from an original pool of 1,176 students enrolled in one of 32 physical education classes. Classes were randomly assigned to either the SEM (N = 16) or traditional class (N = 16). Data were collected using a pretest/posttest design measuring affect (enjoyment) and needs satisfaction. Analysis of data used repeated-measures ANOVAs to examine differences. Results indicated significant changes in amotivated student’s perceptions of enjoyment and relatedness satisfaction within the SEM.

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Amber D. Mosewich, Catherine M. Sabiston, Kent C. Kowalski, Patrick Gaudreau and Peter R.E. Crocker

differences in resources and approaches that affect how they navigate the sport environment (e.g.,  Krane, Ross, Sullivan Barak, Lucas-Carr, & Robinson, 2014 ; Mosewich et al., 2014 ; Mosewich, Vangool, Kowalski, & McHugh, 2009 ). In addition, Warner and Dixon ( 2015 ) suggest that women tend to view and

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Andrew Renfree, Julia West, Mark Corbett, Clare Rhoden and Alan St Clair Gibson

Purpose:

This study examined the determinants of pacing strategy and performance during self-paced maximal exercise.

Methods:

Eight well-trained cyclists completed two 20-km time trials. Power output, rating of perceived exertion (RPE), positive and negative affect, and iEMG activity of the active musculature were recorded every 0.5 km, confidence in achieving preexercise goals was assessed every 5 km, and blood lactate and pH were measured postexercise. Differences in all parameters were assessed between fastest (FAST) and slowest (SLOW) trials performed.

Results:

Mean power output was significantly higher during the initial 90% of FAST, but not the final 10%, and blood lactate concentration was significantly higher and pH significantly lower following FAST. Mean iEMG activity was significantly higher throughout SLOW. Rating of perceived exertion was similar throughout both trials, but participants had significantly more positive affect and less negative affect throughout FAST. Participants grew less confident in their ability to achieve their goals throughout SLOW.

Conclusions:

The results suggest that affect may be the primary psychological regulator of pacing strategy and that higher levels of positivity and lower levels of negativity may have been associated with a more aggressive strategy during FAST. Although the exact mechanisms through which affect acts to influence performance are unclear, it may determine the degree of physiological disruption that can be tolerated, or be reflective of peripheral physiological status in relation to the still to be completed exercise task.

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Paul E. Yeatts, Ronald Davis, Jun Oh and Gwang-Yon Hwang

Physical activity affect refers to a person’s acute exercise-induced psychological and emotional status ( Ekkekakis, 2013 ; Lox, Jackson, Tuholski, Wasley, & Treasure, 2000 ). Components of physical activity affect include positive affect (PA—energetic, enthusiastic, and upbeat), negative affect

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Ken Lodewyk and Lauren McNamara

gender and between children and adolescents ( Jarrett & Duckett-Hedgebeth, 2003 ; Pellegrini, 2005 ; Ridgers, Salmon, Parrish, Stanley, & Okely, 2012 ; Woods, Graver, Daum, & Gentry, 2015 ). The aim of this study was to assess levels and relations between children’s enjoyment, positive affect

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K. Andrew R. Richards, Nicholas Washburn and Ye Hoon Lee

conceptual model for understanding the relationships among POS, emotional labor, affective commitment, and job satisfaction in in-service physical educators (Figure  1 ). These constructs can be explored through affective events theory (AET; Weiss & Cropanzano, 1996 ), which highlights the role of workplace

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April Tripp and Terry L. Rizzo

This study assessed the affect of the label (i.e., CP) attached to a description of a child’s motor ability and teacher attributes on the variables of the Theory of Planned Behavior (TpB) on two groups of elementary teachers (label and no-label). Results from a Hotelling = s T2 MANOVA showed a labeling effect. Results from a simple linear regression procedure also showed that of the teacher attributes assessed, only perceived teaching competence (p < .01) predicted favorable intentions. Support for the TpB was demonstrated for the group with the label for the social normative component (p < .000). Further analyses showed that for the group that receive that label information, only the school principal (p < .05) was associated with favorable intentions.

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Rachael C. Stone, Shane N. Sweet, Marie-Josée Perrier, Tara MacDonald, Kathleen A. Martin Ginis and Amy E. Latimer-Cheung

). A well-established method for displaying and interpreting the intersection of these SCM warmth and competence perceptions for diverse social groups is the behaviors from intergroup affect and stereotypes (BIAS) map formed via cluster analyses ( Fiske et al., 2002 ). Cluster analyses and group

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Júlio A. Costa, João Brito, Fábio Y. Nakamura, Eduardo M. Oliveira, Ovidio P. Costa and António N. Rebelo

frequency [HF, in milliseconds squared]) were significantly altered compared with rest days. Interestingly, in a recent study 6 it was shown that late-night soccer training did not affect HRV indices, using the “hour-by-hour” method (recording all RR intervals over the night sleep) as proposed by Myllymaki

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Susan A. McDonald and Charles J. Hardy

This study examined the affective response pattern of severely injured athletes. Five athletes from an NCAA Division I university athletic program were followed within 24 hours of injury for 4 weeks. On two nonconsecutive days a week at the same time and place, the athletes completed the Profile of Mood States and indicated their perceived percent rehabilitation. In addition, at the first meeting the athletes were given the Marlowe-Crowne Social Desirability Scale and a demographic data sheet. At the final meeting the athletes completed an open-ended questionnaire designed to explore affective, cognitive, and behavioral reflections about rehabilitation. ANOVA indicated that affect significantly changed (p<.05) across the 4 week period. Post hoc analyses indicated that this change fits a two-stage process: Stage 1, Times 1−2; Stage 2, Times 3−8, with the two stages being significantly different from each other. The correlation between perceived rehabilitation and total mood disturbance was r=−.69, p<.0001. Correlations for each affective measure and perceived rehabilitation indicated that affective patterns of the rehabilitating athlete were highly related to the perception of rehabilitation, with negative affect diminishing and positive affect increasing as perceived rehabilitation increased.