791 resultados para activity interventions
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Objective To examine the relationship between pubertal timing and physical activity. Study design A longitudinal sample of 143 adolescent girls was assessed at ages 11 and 13 years. Girls' pubertal development was assessed at age 11 with blood estradiol levels, Tanner breast staging criteria, and parental report of pubertal development. Girls were classified as early maturers (n = 41) or later maturers (n = 102) on the basis of their scores on the 3 pubertal development measures. Dependent variables measured at age 13 were average minutes/day of moderate to vigorous and vigorous physical activity as measured by the ActiGraph accelerometer. Results Early-maturing girls had significantly lower self-reported physical activity and accumulated fewer minutes of moderate to vigorous and vigorous physical activity and accelerometer counts per day at age 13 than later maturing girls. These effects v.-ere independent of differences in percentage body fat and self-reported physical activity at age 11. Conclusion Girls experiencing early pubertal maturation at age 11 reported lower subsequent physical activity at age 13 than their later maturing peers. Pubertal maturation, in particular early maturation relative to peers, may lead to declines in physical activity among adolescent girls.
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The purposes of this study were to describe and compare the specific physical activity choices and sedentary pursuits of African American and Caucasian American girls. Participants were 1,124 African American and 1,068 Caucasian American eighth grade students from 31 middle schools. The 3-Day Physical Activity Recall (3DPAR) was used to measure participation in physical activities and sedentary pursuits. The most frequently reported physical activities were walking, basketball, jogging or running, bicycling, and social dancing. Differences between groups were found in 11 physical activities and 3 sedentary pursuits. Participation rates were higher in African American girls (p<.001)for social dancing, basketball, watching television, and church attendance but lower in calisthenics, ballet and other dance, jogging or running, rollerblading, soccer, softball or baseball, using an exercise machine, swimming, and homework. Cultural differences of groups should be considered when planning interventions to promote physical activity.
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Previous research has shown that early maturing girls at age I I have lower subsequent physical activity at age 13 in comparison to later maturing girls. Possible reasons for this association have not been assessed. This study examines girls' psychological response to puberty and their enjoyment of physical activity as intermediary factors linking pubertal maturation and physical activity. Participants included 178 girls who were assessed at age 11, of whom 168 were reassessed at age 13. All participants were non-Hispanic white and resided in the US. Three measures of pubertal development were obtained at age I I including Tanner breast stage, estradiol levels, and mothers' reports of girls' development on the Pubertal Development Scale (PDS). Measures of psychological well-being at ages I I and 13 included depression, global self-worth, perceived athletic competence, maturation fears, and body esteem. At age 13, girls' enjoyment of physical activity was assessed using the Physical Activity Enjoyment Scale and their daily minutes of moderate-to-vigorous physical activity (MVPA) were assessed using objective monitoring. Structural Equation Modeling was used to assess direct and indirect pathways between pubertal development at age I I and MVPA at age 13. In addition to a direct effect of pubertal development on MVPA, indirect effects were found for depression, global self-worth and maturity fears controlling for covariates. In each instance, more advanced pubertal development at age I I was associated with lower psychological wellbeing at age 13, which predicted lower enjoyment of physical activity at age 13 and in turn lower MVPA. Results from this study suggest that programs designed to increase physical activity among adolescent girls should address the self-consciousness and discontent that girls' experience with their bodies during puberty, particularly if they mature earlier than their peers, and identify activities or settings that make differences in body shape less conspicuous.
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Objective To compare the level of agreement in results obtained from four physical activity (PA) measurement instruments that are in use in Australia and around the world. Methods 1,280 randomly selected participants answered two sets of PA questions by telephone. 428 answered the Active Australia (AA) and National Health Surveys, 427 answered the AA and CDC Behavioural Risk Factor Surveillance System surveys (BRFSS), and 425 answered the AA survey and the short International Physical Activity Questionnaire (IPAQ). Results Among the three pairs of survey items, the difference in mean total PA time was lowest when the AA and NHS items were asked (difference=24) (SE:17) minutes, compared with 144 (SE:21) mins for AA/BRFSS and 406 (SE:27) mins for AA/IPAQ). Correspondingly, prevalence estimates for 'sufficiently active' were similar for AA and NHS (56% and 55% respectively), but about 10% higher when BRFSS data were used, and about 26% higher when the IPAQ items were used, compared with estimates from the AA survey. Conclusions The findings clearly demonstrate that there are large differences in reported PA times and hence in prevalence estimates of 'sufficient activity' from these four measures. Implications It is important to consistently use the same survey for population monitoring purposes. As the AA survey has now been used three times in national surveys, its continued use for population surveys is recommended so that trend data ever a longer period of time can be established.
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Existing techniques for automated discovery of process models from event logs largely focus on extracting flat process models. In other words, they fail to exploit the notion of subprocess, as well as structured error handling and repetition constructs provided by contemporary process modeling notations, such as the Business Process Model and Notation (BPMN). This paper presents a technique for automated discovery of BPMN models containing subprocesses, interrupting and non-interrupting boundary events, and loop and multi-instance markers. The technique analyzes dependencies between data attributes associated with events, in order to identify subprocesses and to extract their associated logs. Parent process and subprocess models are then discovered separately using existing techniques for flat process model discovery. Finally, the resulting models and logs are heuristically analyzed in order to identify boundary events and markers. A validation with one synthetic and two real-life logs shows that process models derived using the proposed technique are more accurate and less complex than those derived with flat process model discovery techniques.
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This study aimed to assess the efficacy of a general practice based intervention to increase physical activity (PA) levels among 50-70 year old adults. One hundred and thirty-six inactive patients (50-70 years) were randomised into three groups. All participants received brief advice and a written prescription from a GP. Group one received this 'usual care' only (GP, n=46); group two received individualised counselling and follow-up contact from an Exercise Scientist (ES, n=45); group three received a pedometer to supplement the ES counselling (PED, n=45). The Active Australia Survey was administered at baseline, after the 12- week intervention and at a 24-week follow-up. One-way ANOVA showed no significant group differences at baseline in self-reported PA. Average time spent walking increased in all three groups at the 24-week follow-up (GP, 68158min/wk, p=0.006; ES, 83160min/wk, p=0.001; PED, 87132min/wk, p<0.001). Total time in PA (weighted min/wk) also increased significantly in all three groups (GP, 98 213min/wk, p=0.003; ES, 108 182min/wk, p<0.001; PED, 158 229min/wk, p<0.001 ). The proportion of participants who initially did not meet National PA Guidelines (150 minutes and 5 sessions/week) but who met the Guidelines at the 12 and 24-week follow-up was 15% (12 weeks) and 20% (24 weeks) in the GP group compared with 36% and 24% in the ES group and 20% and 42% in the PED group. All three intervention strategies were effective in increasing PA, but the ES intervention resulted in a higher proportion of active participants after 12 weeks and the PED group resulted in a higher proportion of active participants after 24 weeks.
Resumo:
This study aimed to assess the efficacy of a general practice based intervention to increase physical activity (PA) levels among 50-70 year old adults. One hundred and thirty-six inactive patients (50-70 years) were randomised into three groups. All participants received brief advice and a written prescription from a GP. Group one received this 'usual care' only (GP, n=46); group two received individualised counselling and follow-up contact from an Exercise Scientist (ES, n=45); group three received a pedometer to supplement the ES counselling (PED, n=45). The Active Australia Survey was administered at baseline, after the 12- week intervention and at a 24-week follow-up. One-way ANOVA showed no significant group differences at baseline in self-reported PA. Average time spent walking increased in all three groups at the 24-week follow-up (GP, 68158min/wk, p=0.006; ES, 83160min/wk, p=0.001; PED, 87132min/wk, p<0.001). Total time in PA (weighted min/wk) also increased significantly in all three groups (GP, 98 213min/wk, p=0.003; ES, 108 182min/wk, p<0.001; PED, 158 229min/wk, p<0.001 ). The proportion of participants who initially did not meet National PA Guidelines (150 minutes and 5 sessions/week) but who met the Guidelines at the 12 and 24-week follow-up was 15% (12 weeks) and 20% (24 weeks) in the GP group compared with 36% and 24% in the ES group and 20% and 42% in the PED group. All three intervention strategies were effective in increasing PA, but the ES intervention resulted in a higher proportion of active participants after 12 weeks and the PED group resulted in a higher proportion of active participants after 24 weeks.
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PURPOSE To examine correlates and consequences of parents' encouragement of girls' physical activity (PA) for weight loss (ENCLOSS). METHODS Data were collected for 181 girls, mothers and fathers when girls were 9, 11, and 13 years old. Mothers and fathers completed a self-report questionnaire of ENCLOSS (e.g., “I have talked to my daughter about how to exercise to lose weight”). Correlates of ENCLOSS that were assessed include girls' Body Mass Index (BMI) z-score and parents' modeling of and logistic support for PA. Dependent variables assessed at age 13 include girls' self-reported and objectively-measured PA, enjoyment of physical activity, and weight concerns. Associations between ENCLOSS, girls' BMI, and parent's support for PA were assessed using spearman rank correlations. To examine links between ENCLOSS and the outcome variables, scores for ENCLOSS were divided into tertiles at each age. Three groups were created including girls who were in the highest tertile at each age (high ENCLOSS), girls who were in the lowest tertile at each age (low ENCLOSS), and girls who varied in their tertile ranking (mid ENCLOSS). Group differences in the outcome variables were assessed using regression analysis (referent group: low ENCLOSS), controlling for girls' BMI and the outcome variable at age 9. RESULTS Girls' with higher BMI had mothers and fathers who reported higher ENCLOSS (r = .61-. 69, p<. 0001). Parents'reports of ENCLOSS were not associated with modeling of or logistic support for PA. Girls in the high ENCLOSS group reported significantly lower enjoyment of PA and higher weight concerns at age 13, independent of covariates. No differences in PA were noted. CONCLUSION Parents who encourage their daughters to be active for weight loss do not model PA or facilitate girls' PA. Persistent encouragement of PA for weight loss may lead to low enjoyment of PA and higher weight concerns among adolescent girls.
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Background Promoting participation physical activity (PA) is an important means of promoting healthy growth and development in children with cerebral palsy (CP). The ActiGraph is a uniaxial accelerometer that provides a realtime measure of PA intensity, duration and frequency. Its small, light weight design makes it a promising measure of activity in children with CP. To date no study has validated the use of accelerometry as a measure of PA in ambulant adolescents with CP. Objectives To evaluate the validity of the ActiGraph accelerometer for measuring PA intensity in adolescents with CP, using oxygen consumption (VO2), measured using portable indirect calorimetry (Cosmed K4b2), as the criterion measure. Design Validation Study Participants/Setting: Ambulant adolescents with CP aged 10–16 years, GMFCS rating of I-III. The recruitment target is 30 (10 in each GMFCS level). Materials/Methods Participants wore the ActiGraph (counts/min) and a Cosmed K4b2 indirect calorimeter (mL/kg/min) during six activity trials: quiet sitting (QS), comfortable paced walking (CPW), brisk paced walking (BPW), fast paced walking (FPW), a ball-kicking protocol (KP) and a ball-throwing protocol (TP). MET levels (multiples of resting metabolism) for each activity were predicted from ActiGraph counts using the Freedson age-specific equation (Freedson et al. 2005) and compared with actual MET levels measured by the Cosmed. Predicted and measured METs for each activity trial were classified as light (> 1.5 METs and <4.6 METs) or moderate to vigorous intensity (≥ 4.6 METs). Results To date 36 bouts of activity have been completed (6 participants x 6 activities). Mean VO2 increased linearly as the intensity of the walking activity increased (CPW=9.47±2.16, BPW=14.06±4.38, FPW=19.21±5.68 ml/kg/min) and ActiGraph counts reflected this pattern (CPW=1099±574, BPW=2233±797 FPW=4707±1013 counts/min). The throwing protocol recording the lowest VO2 (TP=7.50±3.86 ml/kg/min) and lowest overall counts/min (TP=31±27 counts/min). When each of the 36 bouts were classified as either light or moderate to vigorous intensity using measured VO2 as the criterion measure, the Freedson equation correctly classified 28 from 36 bouts (78%). Conclusion/Clinical Implications These preliminary findings suggest that there is a relationship between the intensity of PA and direct measure of oxygen consumption and that therefore the ActiGraph may be a promising tool for accurately measuring free living PA in the community. Further data collection of the complete sample will enable secondary analysis of the relationship between PA and severity of CP (GMFCS level).
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PURPOSE Accurate monitoring of prevalence and trends in population levels of physical activity is fundamental to the planning of health promotion and disease-prevention strategies. Test-retest reliability (repeatability) was assessed for four self-report measures of physical activity commonly used in population surveys: the Active Australia survey (AA, N=356), the short form of the International Physical Activity Questionnaire (IPAQ-S, N=104), the physical activity items in the Behavioral Risk Factor Surveillance System (BRFSS, N=127) and the physical activity items in the Australian National Health Survey (NHS, N=122). METHODS Percent agreement and Kappa statistics were used to assess the reliability of classification of activity status (where ‘active’= 150 minutes of activity per week) and sedentariness (where ‘sedentary’ = reporting no physical activity). Intraclass correlations (ICCs) were used to assess agreement on minutes of activity reported for each item of each survey and on total minutes reported in each survey. RESULTS Percent agreement scores for both activity status and sedentariness were very good on all four instruments. Overall the percent agreement between repeated surveys was between 73% (NHS) and 87% (IPAQ) for the criterion measure of achieving 150 minutes per week, and between 77% (NHS) and 89% (IPAQ) for the criterion of being sedentary. Corresponding Kappa statistics ranged from 0.46 (NHS) to 0.61 (AA) for activity status and from 0.20 (BRFSS) to 0.52 (AA) for sedentariness. For the individual items ICCs were highest for walking (0.45 to 0.56) and vigorous activity (0.22 to 0.64) and lowest for the moderate questions (0.16 to 0.44). CONCLUSION All four measures provide acceptable levels of test-retest reliability for assessing both activity status and sedentariness, and moderate reliability for assessing total minutes of activity. Supported by the Australian Commonwealth Department of Health and Ageing.