813 resultados para Sports for children--Coaching.
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Introduction: Why we need to base childrens’ sport and physical education on the principles of dynamical systems theory and ecological psychology As the childhood years are crucial for developing many physical skills as well as establishing the groundwork leading to lifelong participation in sport and physical activities, (Orlick & Botterill, 1977, p. 11) it is essential to examine current practice to make sure it is meeting the needs of children. In recent papers (e.g. Renshaw, Davids, Chow & Shuttleworth, in press; Renshaw, Davids, Chow & Hammond, in review; Chow et al., 2009) we have highlighted that a guiding theoretical framework is needed to provide a principled approach to teaching and coaching and that the approach must be evidence- based and focused on mechanism and not just on operational issues such as practice, competition and programme management (Lyle, 2002). There is a need to demonstrate how nonlinear pedagogy underpins teaching and coaching practice for children given that some of the current approaches underpinning children’s sport and P.E. may not be leading to optimal results. For example, little time is spent undertaking physical activities (Tinning, 2006) and much of this practice is not representative of the competition demands of the performance environment (Kirk & McPhail, 2002; Renshaw et al., 2008). Proponents of a non- linear pedagogy advocate the design of practice by applying key concepts such as the mutuality of the performer and environment, the tight coupling of perception and action, and the emergence of movement solutions due to self organisation under constraints (see Renshaw, et al., in press). As skills are shaped by the unique interacting individual, task and environmental constraints in these learning environments, small changes to individual structural (e.g. factors such as height or limb length) or functional constraints (e.g. factors such as motivation, perceptual skills, strength that can be acquired), task rules, equipment, or environmental constraints can lead to dramatic changes in movement patterns adopted by learners to solve performance problems. The aim of this chapter is to provide real life examples for teachers and coaches who wish to adopt the ideas of non- linear pedagogy in their practice. Specifically, I will provide examples related to specific issues related to individual constraints in children and in particular the unique challenges facing coaches when individual constraints are changing due to growth and development. Part two focuses on understanding how cultural environmental constraints impact on children’s sport. This is an area that has received very little attention but plays a very important part in the long- term development of sporting expertise. Finally, I will look at how coaches can manipulate task constraints to create effective learning environments for young children.
Postural stability and hand preference as constraints on one-handed catching performance in children
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A new accelerometer, the Kenz Lifecorder EX (LC; Suzuken Co. Ltd, Nagoya, Japan), offers promise as a feasible monitor alternative to the commonly used Actigraph (AG: Actigraph LLC, Fort Walton Beach, FL). Purpose: This study compared the LC and AG accelerometers and the Yamax SW-200 pedometer (DW) under free-living conditions with regard to children's steps taken and time in light-intensity physical activity (PA) and moderate to vigorous PA (MVPA). Methods: Participants (N = 31, age = 10.2 ± 0.4 yr) wore LC, AG, and DW monitors from arrival at school (7:45 a.m.) until they went to bed. Time in light and MVPA intensities were calculated using two separate intensity classifications for the LC (LC_4 and LC_5) and four classifications for the AG (AG_Treuth, AG_Puyau, AG_Trost, and AG_Freedson). Both accelerometers provided steps as outputs. DW steps were self-recorded. Repeated-measures ANOVA was used to assess overlapping monitor outputs. Results: There was no difference between DW and LC steps (Δ = 200 steps), but a nonsignificant trend was observed in the pairwise comparison between DW and AG steps (Δ = 1001 steps, P = 0.058). AG detected significantly greater steps than the LC (Δ = 801 steps, P = 0.001). Estimates of light-intensity activity minutes ranged from a low of 75.6 ± 18.4 min (LC_4) to a high of 309 ± 69.2 min (AG_Treuth). Estimates of MVPA minutes ranged from a low of 25.9 ± 9.4 min (LC_5) to a high of 112.2 ± 34.5 min (AG_Freedson). No significant differences in MVPA were seen between LC_5 and AG_Treuth (Δ = 4.9 min) or AG_Puyau (Δ = 1.7 min). Conclusion: The LC detected a comparable number of steps as the DW but significantly fewer steps than the AG in children. Current results indicate that the LC_5 and either AG_Treuth or AG_Puyau intensity derivations provide similar mean estimates of time in MVPA during-free living activity in 10-yr-old children.
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Objective: To critically appraise the Biodex System 4 isokinetic dynamometer for strength assessment of children. Methods: Appraisal was based on experiences from two independent laboratories involving testing of 213 children. Issues were recorded and the manufacturer was consulted regarding appropriate solutions. Results: The dynamometer had insufficient height adjustment for alignment of the knee for some children, requiring the construction of padding to better fit the child within the dynamometer. Potential for entrapment of the non-testing leg was evident in the passive and eccentric modes and a leg bracket restraint was constructed. Automated gravity correction did not operate when protocols were linked or data was exported to an external device. Conclusions: Limitations were noted, some of which were applicable to knee strength testing in general and others which were specific to use with children. However, most of these obstacles could be overcome, making the Biodex System 4 suitable for assessment of knee strength in children.
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OBJECTIVE To compare the physical activity (PA) patterns and the hypothesized psychosocial and environmental determinants of PA in an ethnically diverse sample of obese and non-obese middle school children. DESIGN Cross-sectional study. SUBJECTS One-hundred and thirty-three non-obese and 54 obese sixth grade children (mean age of 11.4 +/-0.6). Obesity status determined using the age-, race- and gender-specific 95th percentile for BMI from NHANES-1. MEASUREMENTS Objective measurements were collected of PA over a 7-day period using the CSA 7164 accelerometer: total daily counts; daily moderate (3-5.9 METs) physical activity (MPA); daily vigorous physical activity (greater than or equal to 6 METs; VPA); and weekly number of 5, 10 and 20 min bouts of moderate-to-vigorous physical activity (greater than or equal to 3 METs, MVPA). Self-report measures were collected of PA self-efficacy; social influences regarding PA, beliefs about PA outcomes; perceived PA levels of parents and peers, access to sporting and/or fitness equipment at home, involvement in community-based PA organizations; participation in community sports teams; and hours spent watching television or playing video games. RESULTS Compared to their non-obese counterparts, obese children exhibited significantly lower daily accumulations of total counts, MPA and VPA as well as significantly fewer 5, 10 and 20 min bouts of MVPA. Obese children reported significantly lower levels of PA self-efficacy, were involved in significantly fewer community organizations promoting PA and were significantly less likely to report their father or male guardian as physically active. CONCLUSIONS The results are consistent with the hypothesis that physical inactivity is an important contributing factor in the maintenance of childhood obesity. Interventions to promote PA in obese children should endeavor to boost self-efficacy perceptions regarding exercise, increase awareness of, and access to, community PA outlets, and increase parental modeling of PA.
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In this study, we evaluated agreement among three generations of ActiGraph (TM) accelerometers in children and adolescents. Twenty-nine participants (mean age = 14.2 +/- 3.0 years) completed two laboratory-based activity sessions, each lasting 60 min. During each session, participants concurrently wore three different models of the ActiGraph (TM) accelerometers (GT1M, GT3X, GT3X+). Agreement among the three models for vertical axis counts, vector magnitude counts, and time spent in moderate-to-vigorous physical exercise (MVPA) was evaluated by calculating intraclass correlation coefficients and Bland-Altman plots. The intraclass correlation coefficient for total vertical axis counts, total vector magnitude counts, and estimated MVPA was 0.994 (95% CI = 0.989-0.996), 0.981 (95% CI = 0.969-0.989), and 0.996 (95% CI = 0.989-0.998), respectively. Inter-monitor differences for total vertical axis and vector magnitude counts ranged from 0.3% to 1.5%, while inter-monitor differences for estimated MVPA were equal to or close to zero. On the basis of these findings, we conclude that there is strong agreement between the GT1M, GT3X, and GT3X+ activity monitors, thus making it acceptable for researchers and practitioners to use different ActiGraph (TM) models within a given study.
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The purpose of this study was to determine whether physical activity behavior tracks during early childhood. Forty-seven children (22 males, 25 females) aged 3-4 yr at the beginning of the study were followed over a 3-yr period. Heart rates were measured at least 2 and up to 4 d . yr(-1) with a Quantum XL Telemetry heart rate monitor. Physical activity was quantified as the percentage of observed minutes between 3:00 and 6:00 p.m. during which heart rate was 50% or more above individual resting heart rate (PAHR-50 Index). Tracking of physical activity was analyzed using Pearson and Spearman correlations. Yearly PAHR-50 index tertiles were created and examined for percent agreement and Cohen's kappa. Repeated measures ANOVA was used to calculate the intraclass correlation coefficient across the 3 yr of the study. Spearman rank order correlations ranged from 0.57 to 0.66 (P < 0.0001). Percent agreement ranged from 49% to 62%. The intraclass R for the 3 yr was 0.81. It was concluded that physical activity behavior tends to track during early childhood.
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Purpose To describe the physical activity (PA) levels of children attending after-school programs, 2) examine PA levels in specific after-school sessions and activity contexts, and 3) evaluate after-school PA differences in groups defined by sex and weight status. Methods One hundred forty-seven students in grades 3-6 (mean age: 10.1 +/- 0.7, 54.4% male, 16.5% overweight (OW), 22.8% at-risk for OW) from seven after-school programs in the midwestern United States wore Actigraph GT1M accelerometers for the duration of their attendance to the program. PA was objectively assessed on six occasions during an academic year (three fall and three spring). Stored activity counts were uploaded to a customized data-reduction program to determine minutes of sedentary (SED), light (LPA), moderate (MPA), vigorous (VPA), and moderate-to-vigorous (MVPA) physical activity. Time spent in each intensity category was calculated for the duration of program attendance, as well as specific after-school sessions (e.g., free play, snack time). Results On average, participants exhibited 42.6 min of SED, 40.8 min of LPA, 13.4 min of MPA, and 5.3 min of VPA. The average accumulation of MVPA was 20.3 min. Boys exhibited higher levels of MPA, VPA, and MVPA, and lower levels of SED and LPA, than girls. OW and at-risk-for-OW students exhibited significantly less VPA than nonoverweight students, but similar levels of LPA, MPA, and MVPA. MVPA levels were significantly higher during free-play activity sessions than during organized or structured activity sessions. Conclusion After-school programs seem to be an important contributor to the PA of attending children. Nevertheless, ample room for improvement exists by making better use of existing time devoted to physical activity.
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Purpose The purpose of this study was to evaluate the validity of the CSA activity monitor as a measure of children's physical activity using energy expenditure (EE) as a criterion measure. Methods Thirty subjects aged 10 to 14 performed three 5-min treadmill bouts at 3, 4, and 6 mph, respectively. While on the treadmill, subjects wore CSA (WAM 7164) activity monitors on the right and left hips. (V) over dot O-2 was monitored continuously by an automated system. EE was determined by multiplying the average (V) over dot O-2 by the caloric equivalent of the mean respiratory exchange ratio. Results Repeated measures ANOVA indicated that both CSA monitors were sensitive to changes in treadmill speed. Mean activity counts from each CSA unit were not significantly different and the intraclass reliability coefficient for the two CSA units across all speeds was 0.87. Activity counts from both CSA units were strongly correlated with EE (r = 0.86 and 0.87, P < 0.001). An EE prediction equation was developed from 20 randomly selected subjects and cross-validated on the remaining 10. The equation predicted mean EE within 0.01 kcal.min(-1). The correlation between actual and predicted values was 0.93 (P < 0.01) and the SEE was 0.93 kcal.min(-1). Conclusion These data indicate that the CSA monitor is a valid and reliable tool for quantifying treadmill walking and running in children.
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Purpose This Study evaluated the predictive validity of three previously published ActiGraph energy expenditure (EE) prediction equations developed for children and adolescents. Methods A total of 45 healthy children and adolescents (mean age: 13.7 +/- 2.6 yr) completed four 5-min activity trials (normal walking. brisk walking, easy running, and fast running) in ail indoor exercise facility. During each trial, participants were all ActiGraph accelerometer oil the right hip. EE was monitored breath by breath using the Cosmed K4b(2) portable indirect calorimetry system. Differences and associations between measured and predicted EE were assessed using dependent t-tests and Pearson correlations, respectively. Classification accuracy was assessed using percent agreement, sensitivity, specificity, and area under the receiver operating characteristic (ROC) curve. Results None of the equations accurately predicted mean energy expenditure during each of the four activity trials. Each equation, however, accurately predicted mean EE in at least one activity trial. The Puyau equation accurately predicted EE during slow walking. The Trost equation accurately predicted EE during slow running. The Freedson equation accurately predicted EE during fast running. None of the three equations accurately predicted EE during brisk walking. The equations exhibited fair to excellent classification accuracy with respect to activity intensity. with the Trost equation exhibiting the highest classification accuracy and the Puyau equation exhibiting the lowest. Conclusions These data suggest that the three accelerometer prediction equations do not accurately predict EE on a minute-by-minute basis in children and adolescents during overground walking and running. The equations maybe, however, for estimating participation in moderate and vigorous activity.
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Background Understanding the factors that influence physical activity behavior is important in the design of intervention programs targeted at youth. Methods A prospective study design was used to identify the predictors of vigorous physical activity (VPA) (greater than or equal to 6 METs) and moderate and vigorous physical activity (MVPA) (greater than or equal to 3 METs) among 202 rural, predominantly African-American children. Selected social-cognitive determinants of physical activity were assessed via questionnaire in the fifth grade. Participation in VPA and MVPA was assessed via the previous day physical activity recall 1 year later in the sixth grade. Results For girls, participation in community sports, self-efficacy in overcoming barriers, enjoyment of school physical education, race (white > black), and perception of mother's activity level (active vs inactive) were significant predictors of VPA. For MVPA, participation in community sports and self-efficacy in overcoming barriers were significant predictors. For boys, self-efficacy in overcoming barriers was the only significant predictor of VPA, while beliefs regarding activity outcomes and participation in community sports were significant predictors of MVPA. Conclusion Social-cognitive constructs such as physical activity self-efficacy, access to community physical activity outlets, and positive beliefs regarding physical activity outcomes are important predictors of future physical activity behavior among rural, predominantly African-American children.
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This study determined if gender differences in physical activity could be accounted for by differences in selected social-cognitive determinants of activity behavior. Some 334 fifth grade, predominantly African-American students provided information regarding after-school physical activity and the hypothesized determinants of activity behavior. Boys reported significantly greater participation in vigorous (greater than or equal to 6 METs) and in moderate to vigorous (greater than or equal to 4 METs). Relative to girls, boys demonstrated higher levels of physical fitness, greater self-efficacy in overcoming barriers to physical activity, greater amounts of television watching, and higher levels of participation in community sports and physical activity organizations. When mean physical activity scores for girls and boys were adjusted for the effects of these determinant variables, the significant gender difference in physical activity remained. However, adjustment for self-efficacy in overcoming barriers and community sports reduced the gender gap by 5% and 7%, respectively. In contrast, adjustment for television watching increased the gender gap by about 8%. Results indicated perceived confidence in overcoming barriers to physical activity and participation in community physical activity programs are factors related to the gender difference in physical activity.