996 resultados para violent youth subcultures


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Objective To test a conceptual model linking parental physical activity orientations, parental support for physical activity, and children's self-efficacy perceptions with physical activity participation. Participants and setting The sample consisted of 380 students in grades 7 through 12 (mean age, 14.0±1.6 years) and their parents. Data collection took place during the fall of 1996. Main outcome measures Parents completed a questionnaire assessing their physical activity habits, enjoyment of physical activity, beliefs regarding the importance of physical activity, and supportive behaviors for their child's physical activity. Students completed a 46-item inventory assessing physical activity during the previous 7 days and a 5-item physical activity self-efficacy scale. The model was tested via observed variable path analysis using structural equation modeling techniques (AMOS 4.0). Results An initial model, in which parent physical activity orientations predicted child physical activity via parental support and child self-efficacy, did not provide an acceptable fit to the data. Inclusion of a direct path from parental support to child physical activity and deletion of a nonsignificant path from parental physical activity to child physical activity significantly improved model fit. Standardized path coefficients for the revised model ranged from 0.17 to 0.24, and all were significant at the p<0.0001 level. Conclusions Parental support was an important correlate of youth physical activity, acting directly or indirectly through its influence on self-efficacy. Physical activity interventions targeted at youth should include and evaluate the efficacy of individual-level and community-level strategies to increase parents’ capacity to provide instrumental and motivational support for their children's physical activity.

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Objectives To review the effects of physical activity on health and behavior outcomes and develop evidence-based recommendations for physical activity in youth. Study design A systematic literature review identified 850 articles; additional papers were identified by the expert panelists. Articles in the identified outcome areas were reviewed, evaluated and summarized by an expert panelist. The strength of the evidence, conclusions, key issues, and gaps in the evidence were abstracted in a standardized format and presented and discussed by panelists and organizational representatives. Results Most intervention studies used supervised programs of moderate to vigorous physical activity of 30 to 45 minutes duration 3 to 5 days per week. The panel believed that a greater amount of physical activity would be necessary to achieve similar beneficial effects on health and behavioral outcomes in ordinary daily circumstances (typically intermittent and unsupervised activity). Conclusion School-age youth should participate daily in 60 minutes or more of moderate to vigorous physical activity that is developmentally appropriate, enjoyable, and involves a variety of activities.

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The purpose of this study was to evaluate the validity and inter-rater reliability of the Observation System for Recording Activity in Children: Youth Sports (OSRAC:YS). Children (N=29) participating in a parks and recreation soccer program were observed during regularly scheduled practices. Physical activity (PA) intensity and contextual factors were recorded by momentary time-sampling procedures (10-sec observe, 20-sec record). Two observers simultaneously observed and recorded children's PA intensity, practice context, social context, coach behavior, and coach proximity. Inter-rater reliability was based on agreement (Kappa) between the observer's coding for each category, and the Intraclass Correlation Coefficient (ICC) for percent of time spent in MVPA. Validity was assessed by calculating the correlation between OSRAC:YS estimated and objectively measured MVPA. Kappa statistics for each category demonstrated substantial to almost perfect inter-observer agreement (Κappa = 0.67 to 0.93). The ICC for percent time in MVPA was 0.76 (95% C.I. = 0.49 - 0.90). A significant correlation (r = 0.73) was observed for MVPA recorded by observation and MVPA measured via accelerometry. The results indicate the OSRAC:YS is a reliable and valid tool for measuring children's PA and contextual factors during a youth soccer practice.

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OBJECTIVES: To compare the classification accuracy of previously published RT3 accelerometer cut-points for youth using energy expenditure, measured via portable indirect calorimetry, as a criterion measure. DESIGN: Cross-sectional cross-validation study. METHODS: 100 children (mean age 11.2±2.8 years, 61% male) completed 12 standardized activities trials (3 sedentary, 5 lifestyle and 4 ambulatory) while wearing an RT3 accelerometer. V˙O2 was measured concurrently using the Oxycon Mobile portable calorimeter. Cut-points by Vanhelst (VH), Rowlands (RW), Chu (CH), Kavouras (KV) and the RT3 manufacturer (RT3M) were used to classify PA intensity as sedentary (SED), light (LPA), moderate (MPA) or vigorous (VPA). Classification accuracy was evaluated using the area under the Receiver Operating Characteristic curve (ROC-AUC) and weighted Kappa (κ). RESULTS: For moderate-to-vigorous PA (MVPA), VH, KV and RW exhibited excellent accuracy classification (ROC-AUC≥0.90), while the CH and RT3M exhibited good classification accuracy (ROC-AUC>0.80). Classification accuracy for LPA was fair to poor (ROC-AUC<0.76). For SED, VH exhibited excellent classification accuracy (ROC-AUC>0.90), while RW, CH, and RT3M exhibited good classification accuracy (ROC-AUC>0.80). Kappa statistics ranged from 0.67 (VH) to 0.55 (CH). CONCLUSIONS: All cut-points provided acceptable classification accuracy for SED and MVPA, but limited accuracy for LPA. On the basis of classification accuracy over all four levels of intensity, the use of the VH cut-points is recommended.

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Purpose Potential positive associations between youth physical activity and wellness scores could emphasize the value of youth physical activity engagement and promotion interventions, beyond the many established physiological and psychological benefits of increased physical activity. The purpose of this study was to explore the associations between adolescents' self-reported physical activity and wellness. Methods This investigation included 493 adolescents (165 males and 328 females) aged between 12 and 15 years. The participants were recruited from six secondary schools of varying socioeconomic status within a metropolitan area. Students were administered the Five-Factor Wellness Inventory and the International Physical Activity Questionnaire for Adolescents to assess both wellness and physical activity, respectively. Results Data indicated that significant associations between physical activity and wellness existed. Self-reported physical activity was shown to be positively associated with four dimensions including friendship, gender identity, spirituality, and exercise—the higher order factor physical self and total wellness, and negatively associated with self-care, self-worth, love, and cultural identity. Conclusion This study suggests that relationships exist between self-reported physical activity and various elements of wellness. Future research should use controlled trials of physical activity and wellness to establish causal links among youth populations. Understanding the nature of these relationships, including causality, has implications for the justification of youth physical activity promotion interventions and the development of youth physical activity engagement programs.

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The paper presents a participatory design research framework as a primary method for structuring youth engagement, participation and contribution to the design, development and usability evaluation of three evidencebased e-tools for wellbeing, which include smart phone mobile apps as well as e-health websites. The three projects are part of a series of six e-tools part of Safe and Supportive program under Young and Well CRC. The participatory design method, developed by Zelenko (2012) for application in design of online health promoting technologies, was further piloted in partnership with Inspire USA for specific application within the CRC, deploying a combination of creative design workshops and speculative design activities in developing e-tool prototypes with young people. This paper presents the resulting participatory research framework as it was implemented across the e-tool projects to facilitate active youth participation in co-designing the e-tools and ensuring the final designs are relevant to young people and deliver health messages in engaging ways. The principles of Participatory Design (PD) that inform the new framework include a high degree of participant agency in creative decisionmaking and a commitment to the process of co-designing, with young people working alongside designers and developers. The paper will showcase how the PD framework was applied across three projects to increase young people’s contribution to final design outcome.

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Objective The purpose of this study was to identify the psychosocial and environmental correlates of objectively measured physical activity behavior in a diverse sample of sixth-grade students. Design Cross-sectional. Participants and Setting One hundred ninety-eight sixth-grade students from 4 public middle schools in Columbia, South Carolina. The study group was 52.0% female, 55.1% African-American, with a mean age of 11.4 +/- 0.6 years. Main Outcome Measures Time spent in moderate physical activity (MPA) and vigorous physical activity (VPA) was assessed using a uniaxial accelerometer (CSA WAM 7164) (Computer Science and Applications Inc., Shalimar, FL). Determinant variables included: age, gender, race/ethnicity (demographic); physical activity self-efficacy, social norms related to physical activity, and beliefs regarding physical activity outcomes (psychosocial); and perceived physical activity habits of parents and peers, involvement in community physical activity organizations, involvement in community-based sports programs, access to fitness/sporting equipment at home, and self-reported hours spent watching television or playing video games (environmental). Results For boys, physical activity self-efficacy, social norms related to physical activity, and involvement in community physical activity organizations were salient predictors of MPA and VPA. Among girls, only physical activity self-efficacy emerged as a clear predictor of objectively measured physical activity. Conclusions These findings are consistent with previous studies using self-reported physical activity and suggest that interventions to increase physical. activity in preadolescent youth should endeavor to boost physical activity self-efficacy by offering a wide selection of enjoyable, developmentally-appropriate physical activity options.

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The absence of comparative validity studies has prevented researchers from reaching consensus regarding the application of intensity-related accelerometer cut points for children and adolescents. PURPOSE This study aimed to evaluate the classification accuracy of five sets of independently developed ActiGraph cut points using energy expenditure, measured by indirect calorimetry, as a criterion reference standard. METHODS A total of 206 participants between the ages of 5 and 15 yr completed 12 standardized activity trials. Trials consisted of sedentary activities (lying down, writing, computer game), lifestyle activities (sweeping, laundry, throw and catch, aerobics, basketball), and ambulatory activities (comfortable walk, brisk walk, brisk treadmill walk, running). During each trial, participants wore an ActiGraph GT1M, and VO 2 was measured breath-by-breath using the Oxycon Mobile portable metabolic system. Physical activity intensity was estimated using five independently developed cut points: Freedson/Trost (FT), Puyau (PU), Treuth (TR), Mattocks (MT), and Evenson (EV). Classification accuracy was evaluated via weighted κ statistics and area under the receiver operating characteristic curve (ROC-AUC). RESULTS Across all four intensity levels, the EV (κ = 0.68) and FT (κ = 0.66) cut points exhibited significantly better agreement than TR (κ = 0.62), MT (κ = 0.54), and PU (κ = 0.36). The EV and FT cut points exhibited significantly better classification accuracy for moderate-to vigorous-intensity physical activity (ROC-AUC = 0.90) than TR, PU, or MT cut points (ROC-AUC = 0.77-0.85). Only the EV cut points provided acceptable classification accuracy for all four levels of physical activity intensity and performed well among children of all ages. The widely applied sedentary cut point of 100 counts per minute exhibited excellent classification accuracy (ROC-AUC = 0.90). CONCLUSIONS On the basis of these findings, we recommend that researchers use the EV ActiGraph cut points to estimate time spent in sedentary, light-, moderate-, and vigorous-intensity activity in children and adolescents. Copyright © 2011 by the American College of Sports Medicine.

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Purpose The purpose of this study was to establish the minimal number of days of monitoring required for accelerometers to assess usual physical activity in children. Methods A total of 381 students (189 M, 192 F) wore a CSA 7164 uniaxial accelerometer for seven consecutive days. To examine age-related trends students were grouped as follows: Group I: grades 1-3 (N = 92); Group II: grades 4-6 (N = 98); Group III: grades 7-9 (N = 97); Group IV: grades 10-12 (N = 94). Average daily time spent in moderate-to-vigorous physical activity (MVPA) was calculated from minute-by-minute activity counts using the regression equation developed by Freedson et al. (1997). Results Compared with adolescents in grades 7 to 12, children in grades 1 to 6 exhibited less day-to-day variability in MVPA behavior. Spearman-Brown analysts indicated that between 4 and 5 d of monitoring would be necessary to a achieve a reliability of 0.80 in children, and between 8 and 9 d of monitoring would be necessary to achieve a reliability of 0.80 in adolescents. Within all grade levels, the 7-d monitoring protocol produced acceptable estimates of daily participation in MVPA (R = 0.76 (0.71-0.81) to 0.87 (0.84-0.90)). Compared with weekdays, children exhibited significantly higher levels of MVPA on weekends, whereas adolescents exhibited significantly lower levels of MVPA on weekends. Principal components analysis revealed two distinct time components for MVPA during the day for children (early morning, rest of the day), and three distinct time components for MVPA during the day for adolescents (morning, afternoon, early evening). Conclusions These results indicate that a 7-d monitoring protocol provides reliable estimates of usual physical activity behavior in children and adolescents and accounts for potentially important differences in weekend versus weekday activity behavior as well as differences in activity patterns within a given day.

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Previous studies have demonstrated that pattern recognition approaches to accelerometer data reduction are feasible and moderately accurate in classifying activity type in children. Whether pattern recognition techniques can be used to provide valid estimates of physical activity (PA) energy expenditure in youth remains unexplored in the research literature. Purpose: The objective of this study is to develop and test artificial neural networks (ANNs) to predict PA type and energy expenditure (PAEE) from processed accelerometer data collected in children and adolescents. Methods: One hundred participants between the ages of 5 and 15 yr completed 12 activity trials that were categorized into five PA types: sedentary, walking, running, light-intensity household activities or games, and moderate-to-vigorous intensity games or sports. During each trial, participants wore an ActiGraph GTIM on the right hip, and (V) Over dotO(2) was measured using the Oxycon Mobile (Viasys Healthcare, Yorba Linda, CA) portable metabolic system. ANNs to predict PA type and PAEE (METs) were developed using the following features: 10th, 25th, 50th, 75th, and 90th percentiles and the lag one autocorrelation. To determine the highest time resolution achievable, we extracted features from 10-, 15-, 20-, 30-, and 60-s windows. Accuracy was assessed by calculating the percentage of windows correctly classified and root mean square en-or (RMSE). Results: As window size increased from 10 to 60 s, accuracy for the PA-type ANN increased from 81.3% to 88.4%. RMSE for the MET prediction ANN decreased from 1.1 METs to 0.9 METs. At any given window size, RMSE values for the MET prediction ANN were 30-40% lower than the conventional regression-based approaches. Conclusions: ANNs can be used to predict both PA type and PAEE in children and adolescents using count data from a single waist mounted accelerometer.

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This study examined associations between psychosocial factors and physical activity in a group of youth (n = 520). Students completed the Previous Day Physical Activity Recall and a survey of potential determinants of physical activity. Regression analyses of intentions to be physically active revealed that enjoyment and self-efficacy predicted intentions for both males and females. Attitudes predicted moderate to vigorous activity (MVPA), and enjoyment and self-efficacy predicted vigorous activity (VPA) for males. Self-efficacy predicted both MVPA and VPA for females. The findings suggest that intervention programs targeted at youth should include developmentally appropriate activities that are fun and promote physical activity self-efficacy.

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The purpose of this study was to examine the validity of the 3-Day Physical Activity Recall (3DPAR) self-report instrument in a sample of eighth and ninth grade girls (n = 70, 54.3% white, 37.1% African American). Criterion measures of physical activity were derived using the CSA 7164 accelerometer. Participants wore a CSA monitor for 7 consecutive days and completed the self-report physical activity recall for the last 3 of those days. Self-reported total METs, 30-min blocks of MVPA, and 30-min blocks of VPA were all significantly correlated with analogous CSA variables for 7 days (r = 0.35-0.51; P < 0.01) and 3 days (r = 0.27-0.46; P < 0.05) of monitoring. The results indicate that the 3DPAR is a valid instrument for assessing overall, vigorous, and moderate to vigorous physical activity in adolescent girls.

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This study examined the tracking of selected measures of physical activity, inactivity, and fitness in a cohort of rural youth. Students (N = 181, 54.7% female, 63.5% African American) completed test batteries during their fifth-(age = 10.7 +/- 0.7 years), sixth-, and seventh-grade years. The Previous Day Physical Activity Recall (PDPAR) was used to assess 30-min blocks of vigorous physical activity (VPA), moderate-to-vigorous physical activity (MVPA), TV watching and other sedentary activities, and estimated energy expenditure (EE). Fitness measures included the PWC 170 cycle ergometer test, strength tests, triceps skinfold thickness, and BMI. Intraclass correlation coefficients (ICCs) for VPA, MVPA, and after-school EE ranged from 0.63 to 0.78. ICCs ranged from 0.49 to 0.71 for measures of inactivity and from 0.78 to 0.82 for the fitness measures. These results indicate that measures of physical activity, inactivity, and physical fitness tend to track during the transition from elementary to middle school.

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In recent years a compelling body of knowledge has been accumulated to support the belief that physical activity and dietary behaviors carry important health consequences for young people. It has long been known that adequate nutrition and physical activity are essential for normal growth and development [1]. Recently, however, clear evidence has emerged that diet and physical activity during childhood and adolescence also affect an array of physiological factors associated with risk for developing chronic diseases; these factors include body composition (e.g., adiposity), blood lipid concentrations, blood pressure, and bone mineral density It also appears that physical activity and dietary behaviors and the physiological outcomes associated with them often track from childhood and adolescence into adulthood. Thus, risky health behaviors adopted early in life may negatively influence health in adulthood by having both a short-term effect on physiological risk factors and a long-term impact on health behavior.