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Wearable physical activity (PA) monitors are widely promoted as a means to motivate people to be more active, but the motivational profile of users has never been assessed. This study's purpose was to classify adult users by their motivational regulation scores and examine how these profiles were associated with moderate to vigorous PA (MVPA). Current users (N = 320) recruited across the United States completed a Web-based survey. Motivational regulations were measured using the Behavioral Regulation in Exercise Questionnaire, and associations with MVPA were explored using bivariate correlations. MVPA was more highly correlated with autonomous rather than controlling regulations. A cluster analysis was conducted using the respondents' motivational regulation scores. Five motivational profiles emerged from this analysis, and they differed significantly across motivation and MVPA scores. PA monitor users characterized by more autonomous motives presented with higher MVPA. As technology use increases, assessing the multidimensionality of PA monitor users' motivation may add value when researching PA behaviors.This study examined the relationships among cognitive acceptance, behavioral commitment, psychological need satisfaction, autonomous extrinsic motivation (EM) for physical activity (PA), and PA behavior. Participants (N = 456, Mage = 40.7 years) completed online measures of these variables, and data were analyzed using structural equation modeling. Results indicated a direct pathway from behavioral commitment to autonomous EM, plus indirect effects via autonomy, competence, and relatedness. There was no direct pathway from cognitive acceptance to autonomous EM, but there were indirect effects via competence and autonomy satisfaction. There was a direct pathway from cognitive acceptance to self-reported PA plus indirect effects via autonomous EM. A1874 price There was no direct pathway from behavioral commitment to self-reported PA, but there were indirect effects via autonomous EM. Cognitive acceptance and behavioral commitment potentially support the development of autonomous EM for PA. Future research using longitudinal and intervention-based research designs is required to determine the causal relationships among these variables.OBJECTIVE To (1) compare the 1-repetition-maximum (1RM) performance between the push press, push jerk, and split jerk and (2) explore these differences between weightlifters, CrossFit athletes, and a mixed group of athletes. METHODS Forty-six resistance-trained males (age 28.8 [6.4] y; height 180.0 [6.0] cm; body mass 84.1 [10.2] kg; weightlifting training experience 3.64 [3.14] y) participated in this study. The 1RM performance of the push press, push jerk, and split jerk was assessed during the same session in a sequential order (ie, combined 1RM assessment method). Thirty-six participants were retested to determine between-sessions reliability of the 1RM values. RESULTS Intraclass correlation coefficients (ICCs) and associated 95% confidence intervals (CIs) showed a high between-sessions reliability for the push press (ICC = .98; 95% CI, .95-.99), push jerk (ICC = .99; 95% CI, .98-1.00), and split jerk (ICC = .99; 95% CI, .98-1.00). There was a significant main effect of exercise (η2 = .101) and exercise × group interaction (η2 = .012) on 1RM performance (P less then .001), whereas the main effect of group did not reach statistical significance (P = .175). CONCLUSIONS This study provides evidence that the weightlifting overhead press derivatives affect 1RM performance. In addition, the interaction of exercise and sport group was caused by the higher differences in 1RM performance between exercises for weightlifters compared with CrossFit and a mixed group of athletes. Therefore, strength and conditioning professionals should be aware that the differences in 1RM performance between weightlifting overhead-press derivatives may be affected by sport group.OBJECTIVE To assess the discriminative ability of several fitness dimensions and anthropometric attributes for forecasting competitive success in female karate athletes. METHODS Fitness and anthropometric data from 98 female junior karatekas obtained during the training camps of the Spanish National Karate Federation between 1999 and 2012 were used. Binary logistic-regression models were built to ascertain whether the set of fitness and anthropometric variables could predict future sporting-performance levels. For this purpose, participants were classified as elite (medalist in World or European Championships in the senior category) or subelite (at least a medalist in Spanish National Championships in cadet or junior but not included in the elite group), according to the results achieved up to 2019. RESULTS Participants who were subsequently classified as elite karatekas showed significant differences in agility, upper- and lower-body muscle power, and general fitness in comparison with those who were classified as subelite in the senior category. A total of 57 junior female karatekas who were subsequently classified as elite (7) or subelite (50) were included in the binary logistic-regression analysis. Resultant models showed significant capacity to predict karate performance. CONCLUSIONS Assessing physical fitness in junior categories can be a useful resource to determine future karate success. Coaches in this sport should pay special attention to the levels of muscle power and agility shown by their athletes, as both fitness dimensions could be indicators of future sportive success.PURPOSE Studies often assess the impact of sex on the relation between core body temperature (CBT), whole-body sweat rate (WBSR), and heat production during exercise in laboratory settings, but less is known in free-living conditions. Therefore, the authors compared the relation between CBT, WBSR, and heat production between sexes in a 15-km race under cool conditions. METHODS During 3 editions of the Seven Hills Run (Nijmegen, the Netherlands) with similar ambient conditions (8-12°C, 80-95% relative humidity), CBT and WBSR were measured among 375 participants (52% male) before and immediately after the 15-km race. Heat production was estimated using initial body mass and mean running speed, assuming negligible external work. RESULTS Men finished the race in 76 (12) minutes and women in 83 (13) minutes (P less then .001, effect size [ES] = 0.55). Absolute heat production was higher in men than in women (1185 [163] W vs 867 [122] W, respectively, P less then .001, ES = 1.47), even after normalizing to body mass (15.
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