977 resultados para Non-supervised physical activity


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Despite the well-known benefits of physical activity, in 2012, only 37.5% of older adults aged 60 years or older met recommended aerobic physical activity levels and 16.1% met muscle-strengthening guidelines. Effective exercise programs can help combat the problem of inactivity but 50% of those who start participating in an exercise program drop out within first few weeks, preventing them from gaining any health benefits. Since fall 2008, the Healthy Aging Regional Collaborative of South Florida has offered EnhanceFitness (EF), an evidence-based physical activity program to older adults. This dissertation compared EF effectiveness at 4-, 8-, and 12-months and examined the factors that were associated with program completion. A paired sample t-test identified changes at 4-months and repeated measures design was used to identify changes from baseline to 4-, 8-, and 12- months. Logistic regression was used to identify correlates associated with completion.^ Between October 1, 2008 and December 31, 2012, 4,531 older adults (>=60 years) attended one or more EF sessions. Participants showed significant improvement in the number of chair stands performed in 30-seconds with mean change of 1.7, 1.6, and 2.0 respectively at 4-,8-,and 12- months (p<0.001). Results suggest Black, non-Haitian men were less likely to complete the program when compared to white, non-Hispanic men (OR=0.41, p=0.02). Men who self-reported having at least one risk factor were more likely to complete the program (OR=1.81, p= 0.03). In addition, women who lived in Miami-Dade County (OR=2.13, p<0.001) and were 80 years or older (OR=1.46, p<0.05) were more likely to complete the program. When compared with non-Hispanic whites, Black women were less likely to complete the program (OR=0.613, p<0.01). Women who did not report depression were 1.6 times more likely to complete the program (OR=1.62, p<0.05). Absence of risk factors for chronic conditions increased completion rates among women (OR=1.63, p<0.01).^ Effectiveness results revealed that all participants significantly improved on all outcome measures. However, improvement is more than double for those who completed recommended sessions (p<0.01). Study findings reaffirm the successful translation of EF in community-based settings. Our findings suggest that participants should attend the minimum recommended sessions to attain greater health benefits.^

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Minimal research has explored what comprises a quality physical activity (PA) participation experience, particularly among military Veterans with a physical disability for whom evidence of the benefits of PA is growing. To address this research gap, this dissertation examines quality PA participation among military Veterans with a physical disability. Manuscript 1 explores the views of Veterans with a physical disability regarding what elements constitute a quality PA experience, and how these elements may be fostered. Eighteen Veterans with various physical disabilities and PA experiences participated in interviews. Four quality elements were identified via thematic analysis: group cohesion, challenge, having a role, and independence and choice. A further three factors (the physical and social environments, and program structure) were identified as precursors for a quality experience. Manuscript 2 explores how PA programs for Veterans with a physical disability are delivered, and how these delivery strategies link conceptually to quality participation. Interviews were conducted with program staff from three PA programs for Veterans, and program documentation collected, to develop an understanding of program delivery strategies. Four strategies with potential links to quality participation were identified through thematic analysis: foster social connections, challenge participants, tailor programs and outcomes to match participant needs, and include knowledgeable coaches and instructors. Manuscript 3 evaluates the participation of Veterans with functional impairments in PA events, and examines the relationships among quality precursors, quality elements, and participation outcomes. Results indicate that program participation did not promote long-term increases in PA indicators. However, an indicator of the quality element belongingness mediated the relationship at particular time-points between coach interpersonal skills and three participation outcomes: family integration, PA intentions, and PA planning. These findings suggest that a quality participation experience created by coaches may positively impact the transition to civilian life, and promote efforts to engage in ongoing PA. Overall, this dissertation contributes towards a greater depth in understanding of the experiences of Veterans with a physical disability in PA programs. The findings begin to provide a foundation for researchers and practitioners aiming to create, deliver, and promote quality PA interventions and programming for Veterans with a physical disability.

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BACKGROUND: mHealth programs offer potential for practical and cost-effective delivery of interventions capable of reaching many individuals.

PURPOSE: To (1) compare the effectiveness of mHealth interventions to promote physical activity (PA) and reduce sedentary behavior (SB) in free-living young people and adults with a comparator exposed to usual care/minimal intervention; (2) determine whether, and to what extent, such interventions affect PA and SB levels and (3) use the taxonomy of behavior change techniques (BCTs) to describe intervention characteristics.

METHODS: A systematic review and meta-analysis following PRISMA guidelines was undertaken to identify randomized controlled trials (RCTs) comparing mHealth interventions with usual or minimal care among individuals free from conditions that could limit PA. Total PA, moderate-to-vigorous intensity physical activity (MVPA), walking and SB outcomes were extracted. Intervention content was independently coded following the 93-item taxonomy of BCTs.

RESULTS: Twenty-one RCTs (1701 participants-700 with objectively measured PA) met eligibility criteria. SB decreased more following mHealth interventions than after usual care (standardised mean difference (SMD) -0.26, 95 % confidence interval (CI) -0.53 to -0.00). Summary effects across studies were small to moderate and non-significant for total PA (SMD 0.14, 95 % CI -0.12 to 0.41); MVPA (SMD 0.37, 95 % CI -0.03 to 0.77); and walking (SMD 0.14, 95 % CI -0.01 to 0.29). BCTs were employed more frequently in intervention (mean = 6.9, range 2 to 12) than in comparator conditions (mean = 3.1, range 0 to 10). Of all BCTs, only 31 were employed in intervention conditions.

CONCLUSIONS: Current mHealth interventions have small effects on PA/SB. Technological advancements will enable more comprehensive, interactive and responsive intervention delivery. Future mHealth PA studies should ensure that all the active ingredients of the intervention are reported in sufficient detail.

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Recent data indicate that levels of overweight and obesity are increasing at an alarming rate throughout the world. At a population level (and commonly to assess individual health risk), the prevalence of overweight and obesity is calculated using cut-offs of the Body Mass Index (BMI) derived from height and weight. Similarly, the BMI is also used to classify individuals and to provide a notional indication of potential health risk. It is likely that epidemiologic surveys that are reliant on BMI as a measure of adiposity will overestimate the number of individuals in the overweight (and slightly obese) categories. This tendency to misclassify individuals may be more pronounced in athletic populations or groups in which the proportion of more active individuals is higher. This differential is most pronounced in sports where it is advantageous to have a high BMI (but not necessarily high fatness). To illustrate this point we calculated the BMIs of international professional rugby players from the four teams involved in the semi-finals of the 2003 Rugby Union World Cup. According to the World Health Organisation (WHO) cut-offs for BMI, approximately 65% of the players were classified as overweight and approximately 25% as obese. These findings demonstrate that a high BMI is commonplace (and a potentially desirable attribute for sport performance) in professional rugby players. An unanswered question is what proportion of the wider population, classified as overweight (or obese) according to the BMI, is misclassified according to both fatness and health risk? It is evident that being overweight should not be an obstacle to a physically active lifestyle. Similarly, a reliance on BMI alone may misclassify a number of individuals who might otherwise have been automatically considered fat and/or unfit.

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There is increased recognition that determinants of health should be investigated in a life-course perspective. Retirement is a major transition in the life course and offers opportunities for changes in physical activity that may improve health in the aging population. The authors examined the effect of retirement on changes in physical activity in the GLOBE Study, a prospective cohort study known by the Dutch acronym for "Health and Living Conditions of the Population of Eindhoven and surroundings," 1991–2004. They followed respondents (n = 971) by postal questionnaire who were employed and aged 40–65 years in 1991 for 13 years, after which they were still employed (n = 287) or had retired (n = 684). Physical activity included 1) work-related transportation, 2) sports participation, and 3) nonsports leisure-time physical activity. Multinomial logistic regression analyses indicated that retirement was associated with a significantly higher odds for a decline in physical activity from work-related transportation (odds ratio (OR) = 3.03, 95% confidence interval (CI): 1.97, 4.65), adjusted for sex, age, marital status, chronic diseases, and education, compared with remaining employed. Retirement was not associated with an increase in sports participation (OR = 1.12, 95% CI: 0.71, 1.75) or nonsports leisure-time physical activity (OR = 0.80, 95% CI: 0.54, 1.19). In conclusion, retirement introduces a reduction in physical activity from work-related transportation that is not compensated for by an increase in sports participation or an increase in nonsports leisure-time physical activity.