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David Russell and Jo-Ana D. Chase

This study examined sedentary behaviors among older adults and explored associations with social context and health measures using cross-sectional data from the National Health and Aging Trends Study (N = 1,687). Multivariate models were estimated to explore associations of time in six sedentary behaviors (i.e., television watching, sitting and talking, hobbies, computer use, driving, and resting) with sociodemographic characteristics and level of social engagement and with health status. Results indicated substantial variability in sedentary behaviors, with television watching being the most frequent and resting the least frequent activities. Sedentary behaviors varied by sociodemographic characteristics, including age, race/ethnicity, and education, as well as by level of social engagement. Television watching and resting, but not other behaviors, were associated with poorer health. These findings help to unpack the role of social context in sedentary behaviors and could inform public health interventions aimed at reducing time spent in behaviors that are adversely associated with health.

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Davy Vancampfort, Justin Richards, Brendon Stubbs, Grace Akello, Caleb Ademola Gbiri, Philip B. Ward and Simon Rosenbaum

Background:

People with posttraumatic stress disorder (PTSD) are more likely than the general population to be physically inactive. The present review systematically evaluated correlates of physical activity across the socioecological model for people with PTSD.

Methods:

Two independent reviewers searched Embase, PubMed, PsycARTICLES, and CINAHL from inception until June 2015, combining the medical subject heading “posttraumatic stress disorder” or “PTSD,” with “physical activity” or “exercise.” Data were extracted by the same independent researchers and summarized according to the socioecological model.

Results:

Eight papers involving 1368 (994 men) participants (age range = 18–70 years) were eligible and enabled evaluation of 21 correlates. The only correlate (n ≥ 4) consistently associated with lower physical activity participation in people with PTSD was symptoms of hyperarousal. No consistent facilitators were identified.

Conclusions:

Hyperarousal symptoms are associated with lower physical activity participation among people with PTSD and should be considered in the design and delivery of individualized exercise programs targeting this population. The role of social, environmental, and policy factors on physical activity participation among people with PTSD is unknown and should be addressed by future research.

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Iva Obrusnikova and Dannielle L. Miccinello

The study assessed parental perceptions of the benefits of physical activity (PA) and the factors that influence participation of children with autism spectrum disorders in PA after school. Data were collected from 103 parents using an online open-ended questionnaire and focus-group interviews. Data were analyzed using a socioecological model. Parents provided 225 responses that were coded as advantages, 106 as disadvantages, 225 as facilitators, and 250 as barriers of PA. The most frequently reported advantages were physical, followed by psychosocial, and cognitive. Disadvantages were psychosocial and physical. The most frequently reported barriers were intrapersonal, followed by interpersonal, physical, community, and institutional. Facilitators were intrapersonal, followed by physical, interpersonal, community, and institutional. Public policy factors were elicited in the interviews.

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Kathleen Van Royen, Roosmarijn Verstraeten, Susana Andrade, Angélica Ochoa-Avilés, Silvana Donoso, Lea Maes and Patrick Kolsteren

Background:

Physical inactivity levels are increasingly prevalent among Ecuadorian adolescents. School-based interventions can be potentially effective in promoting physical activity but must be informed by cultural-specific factors.

Methods:

Twelve focus groups were carried out with adolescents (n = 80) in rural and urban Ecuador to identify factors influencing physical activity. In addition, 4 focus group discussions with parents (n = 32) and 4 with school staff (n = 32) were conducted. Individual and environmental factors were questioned using the ‘Attitude, Social influences and Self-efficacy’ model and the socioecological model as theoretical frameworks.

Results:

Factors influencing physical activity varied between groups. In the rural area farming and norms for girls impeded leisure-time physical activity, whereas urban groups emphasized traffic and crime concerns. Groups from a low socioeconomic status more frequently mentioned a fear of injuries and financial constraints. Several factors were common for all groups including preferences for sedentary activities, poor knowledge, time constraints and laziness, as well as a lack of opportunities at home and school, unsupportive parental rules and lack of role models.

Conclusion:

A conceptual framework including the identified factors emerged to inform the design of a cultural-sensitive school-based intervention to improve physical activity among Ecuadorian adolescents. Future interventions should be tailored to each setting.

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Claire R. Jenkin, Rochelle M. Eime, Hans Westerbeek and Jannique G.Z. van Uffelen

of sport policy is worth exploring for other population groups, such as older adults. The socioecological model can provide a framework to explore how these different factors can influence older adult sport participation. The model outlines that behaviors are influenced by a range of intrapersonal

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Margaret McGladrey, Angela Carman, Christy Nuetzman and Nicole Peritore

initiatives spanning all levels of the socioecological model to target individuals, families and other interpersonal relationships, the community, and society at large. 5 Solutions are needed to increase and improve conditions at all levels of the socioecological model that support physical activity. The

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Ka-Man Leung, Pak-Kwong Chung, Tin-Lok Yuen, Jing Dong Liu and Donggen Wang

between the environment and healthy behavior (such as regular exercise) is the socioecological model ( Stokols, 1996 ). This model posits that multiple factors influence active behaviors such as walking. Walking was shown to improve the health of older adults ( Paterson et al., 2007 ); therefore, walking

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E. Kipling Webster, Leah E. Robinson and Danielle D. Wadsworth

levels and improve health. The theoretical framework used for this intervention is the socioecological model, which aims to understand the complex interconnections of behavioral changes within an individual and their surroundings. 35 , 36 This model suggests that interventions are most effective in

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Freja Gheysen, Karel Herman and Delfien Van Dyck

; Bauman, Merom, Bull, Buchner, & Fiatarone Singh, 2016 ), so initiatives to increase PA in this age group are urgently needed. To develop population-wide interventions, the key PA correlates for this age group need to be identified. Socioecological models of health behaviors posit that PA, among other

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Kenneth E. Powell and Steven N. Blair

report summarizes information about interventions promoting physical activity at different levels of the socioecological model. Conundrums Associated with the cornucopia of benefits are conundrums: perplexing issues about the nature of the relationship between physical activity and health. Some of these