Relationship between urban sprawl and physical activity, obesity, and morbidity - update and refinement.

The objective of this review was to systematically synthesize the results of original studies on the association between physical activity and social support in adolescents, published until April 2011. Searches were carried out in Adolec, Eric, Lilacs, Medline, SciELO, Scopus, SportsDiscus and Web of Science electronic databases and the reference lists of selected articles. Searches for articles, data extraction and assessment of methodological quality were conducted independently by two reviewers. In total, 75 articles met inclusion criteria and were analyzed. Most studies were published over the past 6 years (2006-11), conducted in high-income countries, with a cross-sectional design, using subjective measures of physical activity (e.g. questionnaires and recall) and exhibited medium to high methodological quality level. Social support was positive and consistently associated with the physical activity level of adolescents in cross-sectional and longitudinal studies. Those who received more overall social support as well as support from both parents, friends and family showed higher levels of physical activity. It is concluded that social support is an important factor associated with physical activity level in adolescents and should be targeted in intervention programs that aim to increase physical activity levels in this population group.

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Physical activity and social support in adolescents: a systematic review

OBJECTIVE Risk beliefs are central to most theories of health behavior, yet many unanswered questions remain about an increasingly studied risk construct, anticipated regret. The authors sought to better understand anticipated regret's role in motivating health behaviors. METHOD The authors systematically searched electronic databases for studies of anticipated regret and behavioral intentions or health behavior. They used random effects meta-analysis to synthesize effect sizes from 81 studies (n = 45,618). RESULTS Anticipated regret was associated with both intentions (r+ = .50, p < .001) and health behavior (r+ = .29, p < .001). Greater anticipated regret from engaging in a behavior (i.e., action regret) predicted weaker intentions and behavior, whereas greater anticipated regret from not engaging in a behavior (i.e., inaction regret) predicted stronger intentions and behavior. Anticipated action regret had smaller associations with behavioral intentions related to less severe and more distal hazards, but these moderation findings were not present for inaction regret. Anticipated regret generally was a stronger predictor of intentions and behavior than other anticipated negative emotions and risk appraisals. CONCLUSIONS Anticipated inaction regret has a stronger and more stable association with health behavior than previously thought. The field should give greater attention to understanding how anticipated regret differs from similar constructs, its role in health behavior theory, and its potential use in health behavior interventions. (PsycINFO Database Record

Anticipated regret and health behavior: A meta-analysis.

Theory: Although medical students begin medical school with better mental health than their peers, during medical school students have a higher prevalence of psychological distress. Medical students often do not seek help for mental health concerns. The use of approach coping strategies and social support has been shown in other populations to be related to mental health resiliency. Hypotheses: The rates of depression and burnout in this medical student population are expected to be high, with the majority not seeking help for their psychological distress in accordance with studies of medical students across the nation. Perceptions of stigma are hypothesized to be a potential source of this lack of care-seeking behavior. Approach coping strategies and social support are speculated to have an inverse relationship with the prevalence of depression and burnout in the medical student population. Method: Validated measures of depression and burnout along with items pertaining to diagnosis and treatment...

Resilience Among Medical Students: The Role of Coping Style and Social Support

Autonomous Vehicles (AVs) have the potential to make motorized transport safer and more sustainable, by integrating clean technologies and supporting flexible shared-mobility services. Leveraging this new form of transport to transform mobility in cities will depend fundamentally on public acceptance of AVs, and the ways in which individuals choose to use them, to meet their daily travel needs. Empirical studies exploring public attitudes towards automated driving technologies and interest in AVs have emerged in the last few years. However, within this strand of research there is a paucity of theory-driven and behaviourally consistent methodologies to unpack the determinants of user adoption decisions with respect to AVs. In this paper, we seek to fill this gap, by advancing and testing four conceptual frameworks which could be deployed to capture the range of possible behavioural influences on individuals’ AV adoption decisions. The frameworks integrate socio-demographic variables and relevant latent behavioural factors, including perceived benefits and perceived ease of use of AVs, public fears and anxieties regarding AVs, subjective norm, perceived behavioural control, and attitudinal factors covering the environment, technology, collaborative consumption, public transit and car ownership. We demonstrate the utility and validity of the frameworks, by translating the latent variables into indicator items in a structured questionnaire, and administering it online to a random sample of adult individuals (n = 507). Using the survey data in confirmatory factor analyses, we specify and demonstrate scale reliability of indicator items, and convergent and discriminant validity of relationships among latent variables. Ultimately, we advance four measurement models. These theory-grounded measurement models are intended for application in research aimed at understanding and predicting (a) AV interest and adoption intentions, and (b) user adoption decisions regarding three different AV modes: ownership, sharing and public transport.

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Capturing the behavioural determinants behind the adoption of autonomous vehicles: conceptual frameworks and measurement models to predict public transport, sharing and ownership trends of self-driving cars

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Health Behavior And Health Education Theory Research And Practice