Coach Effectiveness Training (CET) has been shown to have positive effects on a range of outcome variables, especially in young athletes (Smith & Smoll, 2005). Based on CET principles, and coupled with behavioral feedback, an individualized goal-setting intervention was developed and assessed using a replicated case study approach. Outcome variables included observed, athlete-perceived, and coach-perceived behaviors measured before the intervention and late in the season, as well as coaches’ evaluations of the intervention. Four soccer coaches selected three target behaviors that they wished to improve after viewing videotaped behavioral feedback. Behavioral assessment revealed that two of the coaches achieved positive changes on all three of their targeted behaviors. A third coach improved on two of the three targeted behaviors. The fourth coach did not achieve any of the established goals. We conclude that this approach is sufficiently promising to warrant additional research, and we discuss strengths and limitations of the study.
Catarina Sousa, Ronald E. Smith, and Jaume Cruz
Cristina Garagarza, Ana Valente, Cristina Caetano, Inês Ramos, Joana Sebastião, Mariana Pinto, Telma Oliveira, Aníbal Ferreira, and Catarina Sousa Guerreiro
Background: Physical inactivity and muscle wasting potentiate each other and are highly prevalent among hemodialysis (HD) patients. The authors evaluated the association between physical activity (PA), clinical, nutritional, and body composition parameters in HD patients. Methods: Multicenter cross-sectional study with 581 HD patients. Clinical, body composition, dietary intake, and PA data were recorded. For the analysis, patients were divided into active (follow World Health Organization recommendations) and inactive groups. Results: A total of 20% of the patients followed World Health Organization recommendations on PA. Differences between physically active and physically inactive patients were observed in age, biochemical parameters and total body water, intracellular water, lean tissue index (LTI), body cell mass, energy, and protein intake. PA was a predictor of higher LTI, body cell mass, and energy intake independently of age, gender, presence of diabetes, dialysis adequacy, and dialysis vintage. Controlling for the effect of age, walking and vigorous PA were positively correlated with energy and protein intake. Vigorous PA was also positively correlated with LTI. Conclusion: The PA is a predictor of higher LTI, body cell mass, and energy intake. Vigorous PA is associated with an improved body composition and dietary pattern, whereas walking seems to be also associated with a favorable nutritional status.
Filipe Jesus, Mónica Sousa, Catarina L. Nunes, Ruben Francisco, Paulo Rocha, Cláudia S. Minderico, Luís B. Sardinha, and Analiza M. Silva
During the athletic season, changes in body composition occur due to fluctuations in energy expenditure and energy intake. Literature regarding changes of energy availability (EA) is still scarce. The aim was to estimate EA of athletes from nonweight and weight-sensitive sports during the athletic season (i.e., preparatory and competitive phase). Eighty-eight athletes (19.1 ± 4.2 years, 21.8 ± 2.0 kg/m2, 27% females, self-reported eumenorrheic) from five sports (basketball [n = 29]; handball [n = 7]; volleyball [n = 9]; swimming [n = 18]; and triathlon [n = 25]) were included in this observational study. Energy intake and exercise energy expenditure were measured through doubly labeled water (over 7 days and considering neutral energy balance) and metabolic equivalents of tasks, respectively. Fat-free mass (FFM) was assessed through a four-compartment model. EA was calculated as EA = (energy intake − exercise energy expenditure)/FFM. Linear mixed models, adjusted for sex, were performed to assess EA for the impact of time by sport interaction. Among all sports, EA increased over the season: basketball, estimated mean (SE): 7.2 (1.5) kcal/kg FFM, p < .001; handball, 14.8 (2.9) kcal/kg FFM, p < .001; volleyball, 7.9 (2.8) kcal/kg FFM, p = .006; swimming, 8.7 (2.0) kcal/kg FFM, p < .001; and triathlon, 9.6 (2.0) kcal/kg FFM, p < .001. Eleven athletes (12.5%) had clinical low EA at the preparatory phase and none during the competitive phase. During both assessments, triathletes’ EA was below optimal, being lower than basketballers (p < .001), volleyballers (p < .05), and swimmers (p < .001). Although EA increased in all sports, triathlon’s EA was below optimal during both assessments. Risk of low EA might be seasonal and resolved throughout the season, with higher risk during the preparatory phase. However, in weight-sensitive sports, namely triathlon, low EA is still present.