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Guided by an expectancy-value model of achievement choice (Eccles et al., 1983; Wigfield & Eccles, 2000), the relationships among expectancy-related beliefs, subjective task values (importance, interest, and usefulness), and achievement outcomes (intention, engagement, and performance) were examined in a college-level beginning weight training class. A total of 156 students (73 males, 83 females) completed questionnaires assessing their expectancy-related beliefs, subjective task values, and intention for future participation. Their engagement was measured via self-recorded workout log entries in class, and their performance was determined by two skill tests. Results of the study supported the application of the expectancy-value model in the context of a college weight training class. Importance and interest were significant predictors of intention and engagement, whereas expectancy-related beliefs emerged as the only predictor of performance. Males reported higher scores on expectancy-related beliefs and performed better than females.

This study uncovers the predictive relationship of middle school students’ ability beliefs (self-efficacy and expectancy-related beliefs) and incentives (outcome expectancy, importance, interest, and usefulness) to intention, cardiovascular fitness, and teacher-rated effort in physical education. Participants (N = 252; 118 boys, 134 girls) completed questionnaires assessing their ability beliefs, incentives, and intention for future participation in physical education, and then had their cardiovascular fitness assessed with the Progressive Aerobic Cardiovascular Endurance Run (PACER) test. Students’ effort in class was rated by their respective physical education teachers. Correlation analysis yielded significantly positive relationships between ability beliefs and incentives. Regression results revealed that ability beliefs, importance, interest, and usefulness significantly predicted intention for future participation. Ability beliefs also emerged as significant predictors of PACER test scores whereas self-efficacy was the only predictor of teacher-rated effort. Implications for educational practice are discussed.

The purpose of this study was to examine relationships among college students’ 2 × 2 goal orientations (mastery-approach [MAp], mastery-avoidance [MAv], performance-approach [PAp], performance-avoidance [PAv]), situational motivation (intrinsic motivation, identified regulation, external regulation and amotivation) and effort/persistence in physical activity classes. Participants (140 female, 109 male) completed a battery of questionnaires assessing the outcome variables at the last week of instruction. Regression analyses revealed that MAp and PAp emerged as positive predictors for intrinsic motivation whereas MAp was the only positive predictor for identified regulation. MAp was negatively related to amotivation (AM), while PAp and PAv were positively related to AM. In addition, MAp, PAp, intrinsic motivation, and identified regulation were significant positive predictors of effort/persistence.

Background: This study examined the accuracy of Microsoft Band (MB), Fitbit Surge HR (FS), TomTom Cardio Watch (TT), and Apple Watch (AW) for energy expenditure (EE) estimation at rest and at different physical activity (PA) intensities. Method: During summer 2016, 25 college students (13 females; M _age = 23.52 ± 1.04 years) completed four separate 10-minute exercise sessions: rest (i.e., seated quietly), light PA (LPA; 3.0-mph walking), moderate PA (MPA; 5.0-mph jogging), and vigorous PA (VPA; 7.0-mph running) on a treadmill. Indirect calorimetry served as the criterion EE measure. The AW and TT were placed on the right wrist and the FS and MB on the left—serving as comparison devices. Data were analyzed in late 2017. Results: Pearson correlation coefficients revealed only three significant relationships (r = 0.43–0.57) between smartwatches’ EE estimates and indirect calorimetry: rest-TT; LPA-MB; and MPA-AW. Mean absolute percentage error (MAPE) values indicated the MB (35.4%) and AW (42.3%) possessed the lowest error across all sessions, with MAPE across all smartwatches lowest during the LPA (33.7%) and VPA (24.6%) sessions. During equivalence testing, no smartwatch’s 90% CI fell within the equivalence region designated by indirect calorimetry. However, the greatest overlap between smartwatches’ 90% CIs and indirect calorimetry’s equivalency region was observed during the LPA and VPA sessions. Finally, EE estimate variation attributable to the use of different manufacturer’s devices was greatest at rest (53.7 ± 12.6%), but incrementally decreased as PA intensity increased. Conclusions: MB and AW appear most accurate for EE estimation. However, smartwatch manufacturers may consider concentrating most on improving EE estimate accuracy during MPA.

Background: The effects of school-based exergaming interventions on adolescents’ physical activity (PA) and psychosocial outcomes have been mixed. Researchers speculate this may be attributed to design issues. Therefore, this study examined differences in urban minority adolescents’ PA, enjoyment, and self-efficacy during small-groups and full-class exergaming. Methods: Forty-seven urban minority adolescents (83% black; ${\overline{X}}_{\text{age}}=11.8+1.3\mathrm{y}$ ) completed two 15-minute exergaming sessions on the Xbox One Kinect Just Dance: (1) small groups (n = 3–4) and (2) full class (n = 23–24). Participants’ time in sedentary behavior, light PA, and moderate to vigorous PA and steps were retrieved from ActiGraph GT3X+ accelerometers with enjoyment and self-efficacy assessed using validated surveys. Results: Participants spent significantly more time in sedentary behavior (5.9 [5.2] min vs 3.5 [2.7] min, respectively: P < .001, d = 0.57) and less time in moderate-to-vigorous PA (2.1 [2.8] min vs 5.5 [2.2] min, respectively: P < .001, d = 0.85) during the full-class versus the small-groups session. Moreover, small-groups exergaming resulted in significantly higher steps than the full-class exergaming (504.2 [132.1] vs 387.8 [122.1], respectively: P = .01, d = 0.50) and significantly greater enjoyment (3.5 [1.1] vs 3.2 [1.0], respectively: P = .02, d = 0.37). There were no significant differences between sessions for time in light PA and self-efficacy. Conclusions: Small-groups exergaming appears ideal for promoting enjoyable PA at higher intensities and lower sedentary time in underserved minority adolescents.