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Research has highlighted the importance of peers for determining health behaviors in adolescents, yet these behaviors have typically been investigated in isolation. We need to understand common network processes operating across health behaviors collectively, in order to discern how social network processes impact health behaviors. Thus, this systematic review of studies investigated adolescent peer social networks and health behaviors. A search of six databases (CINAHL, Education Resources Information Centre, Embase, International Bibliography of the Social Sciences, Medline and PsycINFO) identified 55 eligible studies. The mean age of the participants was 15.1 years (range 13-18; 51.1% female). Study samples ranged from 143 to 20,745 participants. Studies investigated drinking (31%), smoking (22%), both drinking and smoking (13%) substance use (18%), physical activity (9%) and diet or weight management (7%). Study design was largely longitudinal (n = 41, 73%) and cross-sectional (n = 14, 25%). All studies were set in school and all but one study focused on school-based friendship networks. The Newcastle-Ottawa Scale was used to assess risk of bias: studies were assessed as good (51%), fair (16%) or poor (33%). The synthesis of results revolved around two network behavior patterns: 1) health behavior similarity within a social network, driven by homophilic social selection and/or social influence, and 2) popularity: health behavior engagement in relation to changes in social status; or network popularity predicting health behaviors. Adolescents in denser networks had statistically significant lower levels of harmful behavior (n = 2/2, 100%). Findings suggest that social network processes are important factors in adolescent health behaviors., (Copyright © 2019 Elsevier Inc. All rights reserved.)

Background: There has been a growing interest in understanding the effects of social networks on health-related behaviour, with a particular backdrop being the emerging prominence of complexity or systems science in public health. Social network interventions specifically use or alter the characteristics of social networks to generate, accelerate, or maintain health behaviours. We conducted a systematic review and meta-analysis to investigate health behaviour outcomes of social network interventions., Methods and Findings: We searched eight databases and two trial registries from 1990 to May 28, 2019, for English-language reports of randomised controlled trials (RCTs) and before-and-after studies investigating social network interventions for health behaviours and outcomes. Trials that did not specifically use social networks or that did not include a comparator group were excluded. We screened studies and extracted data from published reports independently. The primary outcome of health behaviours or outcomes at ≤6 months was assessed by random-effects meta-analysis. Secondary outcomes included those measures at >6-12 months and >12 months. This study is registered with the International Prospective Register of Systematic Reviews, PROSPERO: CRD42015023541. We identified 26,503 reports; after exclusion, 37 studies, conducted between 1996 and 2018 from 11 countries, were eligible for analysis, with a total of 53,891 participants (mean age 32.4 years [SD 12.7]; 45.5% females). A range of study designs were included: 27 used RCT/cluster RCT designs, and 10 used other study designs. Eligible studies addressed a variety of health outcomes, in particular sexual health and substance use. Social network interventions showed a significant intervention effect compared with comparator groups for sexual health outcomes. The pooled odds ratio (OR) was 1.46 (95% confidence interval [CI] 1.01-2.11; I2 = 76%) for sexual health outcomes at ≤6 months and OR 1.51 (95% CI 1.27-1.81; I2 = 40%) for sexual health outcomes at >6-12 months. Intervention effects for drug risk outcomes at each time point were not significant. There were also significant intervention effects for some other health outcomes including alcohol misuse, well-being, change in haemoglobin A1c (HbA1c), and smoking cessation. Because of clinical and measurement heterogeneity, it was not appropriate to pool data on these other behaviours in a meta-analysis. For sexual health outcomes, prespecified subgroup analyses were significant for intervention approach (p < 0.001), mean age of participants (p = 0.002), and intervention length (p = 0.05). Overall, 22 of the 37 studies demonstrated a high risk of bias, as measured by the Cochrane Risk of Bias tool. The main study limitations identified were the inclusion of studies of variable quality; difficulty in isolating the effects of specific social network intervention components on health outcomes, as interventions included other active components; and reliance on self-reported outcomes, which have inherent recall and desirability biases., Conclusions: Our findings suggest that social network interventions can be effective in the short term (<6 months) and longer term (>6 months) for sexual health outcomes. Intervention effects for drug risk outcomes at each time point were not significant. There were also significant intervention effects for some other health outcomes including alcohol misuse, well-being, change in HbA1c, and smoking cessation., Competing Interests: The authors have declared that no competing interests exist.

Background and Objectives: Previous studies have documented that high rates of delay discounting are associated with obesity. However, studies utilizing monetary reward experiments typically report no associations, as opposed to positive associations apparent in studies utilising food-reward experiments. Our objective was to investigate the reasons behind the mixed evidence from a methodological perspective using systematic review and meta-analytic methodologies., Methods: Seven databases (EMBASE, MEDLINE, PsycINFO, Scopus, Web of Science, Econlit and IBSS) were systematically searched. Logistic meta-regression was applied to identify the determinants of a significant association and risk of bias was assessed using a modified form of the Newcastle Ottawa cohort scale., Results: A total of 59 studies were identified, among which 29 studies (49.2%) found a significant positive association and 29 (49.2%) reported no association. A higher proportion of significant and positive associations was reported in those studies utilizing 'best-practice' methods (i.e. appropriate measurement models) to estimate monetary delay discounting (15/27; 55.6%) and incentive-compatible experiments (10/16; 62.5%) than those using non-'best-practice' methods (14/34; 41.2%) and hypothetical experiments (19/43; 44.2%). All five studies utilizing both 'best-practice' methods and incentive-compatible experiments generated a positive and significant relationship. Results from a logistic meta-regression also suggested that studies employing incentive-compatible experiments (OR: 4.38, 95% CI = 1.05-18.33, p value: 0.04), 'best-practice' methods (OR: 4.40, 95% CI = 0.88-22.99, p value: 0.07), parametric methods (OR: 3.36, 95% CI = 0.83-13.57, p value: 0.04), those conducted in children/adolescent populations (OR: 3.90, 95% CI = 0.85-17.88, p value: 0.08), and those with larger sample size (OR: 1.91, 95% CI = 1.15-3.18, p value: 0.01) tended to show positive and significant associations between delay discounting and obesity., Conclusions: This review suggests that the mixed evidence to date is a result of methodological heterogeneity, and that future studies should utilise 'best practice' methods.

Background: We evaluated the effectiveness and cost-effectiveness of a loyalty scheme based intervention involving rewards for increasing physical activity in public sector employees., Methods: A cluster randomised wait-list controlled trial in public sector organisations in Northern Ireland. We randomly assigned clusters (1:1) using a computer generated random sequence. Researchers were masked to allocation, but participants were not. Employees aged 18-65 years with no self-reported medical contraindications to physical activity were included. The Physical Activity Loyalty Scheme (PAL) intervention was based on high-street loyalty cards where participants earned points for minutes of activity that could be redeemed for rewards, complemented by evidence-based behaviour change techniques. The primary outcome was objectively measured mean steps/day at 6 months using a validated pedometer (Yamax Digi-Walker CW-701) over 7 days, assessed with intention to treat analysis. Secondary outcomes included health, mental wellbeing, quality of life, work absenteeism and presenteeism, and use of healthcare resources. Cost-effectiveness, cost-benefit and mediation analyses were conducted. Trial registered with Current Controlled Trials, number ISRCTN17975376., Results: Between September 2014 and October 2015, we recruited and randomly assigned 37 clusters (from nine organisations; mean clusters per organisation = four) and 853 participants to the intervention (n = 19 with 457 participants) or control group (n = 18 with 396 participants). Primary outcome data were available for 249 (54·4%) intervention and 236 (59·6%) control participants. Mean steps/day were significantly lower in the intervention vs control group (adjusted mean difference = - 336, 95% CI: -612 to - 60, p = 0·02) at 6 months. Participants redeemed only 39% (SD 43%) of their earned points. Using the Quality Adjusted Life Year outcome, the intervention was not cost effective from an NHS/PSS perspective. A net cost analysis from an employer perspective demonstrated the intervention group was associated with a mean of 2·97 h less absenteeism over a 4 week period (p = 0·62), which could result in net savings ranging from £66 to £735 depending on the wage rate employed. At 4-weeks post-baseline there were significant increases in identified regulation, integrated regulation, intrinsic motivation, social norms and intentions in intervention compared to control participants., Conclusions: Our mixed results pose challenges that are too infrequently exposed in public heath intervention trials. Although the intervention successfully altered several hypothesised mediating constructs it did not translate into long-term behaviour change. Our incentive level may have been too low to incentivise change, despite being designed a priori by a Contingent Valuation Survey. There were also major re-structuring of several organisations which presented significant implementation challenges, and technical limitations., Trial Registration: ISRCTN17975376 (Registered 19/09/2014).

Managing non-communicable diseases requires policy makers to adopt a whole systems perspective that adequately represents the complex causal architecture of human behaviour. Agent-based modelling is a computational method to understand the behaviour of complex systems by simulating the actions of entities within the system, including the way these individuals influence and are influenced by their physical and social environment. The potential benefits of this method have led to several calls for greater use in public health research. We discuss three challenges facing potential modellers: model specification, obtaining required data, and developing good practices. We also present steps to assist researchers to meet these challenges and implement their agent-based model., (Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Background: Regular physical activity is important for maintaining physical and mental health. Benefits are optimized when physical activity is maintained. Understanding causal mechanisms is important to inform future interventions., Purpose: To investigate mediators of physical activity maintenance., Methods: Six databases were searched (Medline, EMBASE, PsycINFO, CINAHL, Cochrane Database of Systematic Reviews, and Web of Science). Eligibility criteria included adult nonclinical populations, validated measure of physical activity behavior at baseline and at least 6 months postbaseline, control/comparison group(s), and reported mediators of physical activity behavior change. Mediators were examined according to (i) formal mediation tests, (ii) mediator association with physical activity outcome, and (iii) intervention effects on mediators., Results: There were few formal mediation tests conducted (n = 12/39 included studies), and various other methodological limitations were identified. There was some evidence that effective mediators in formal mediation tests at 6 months and later included the "behavioral processes of change" (n = 5/6). Many of the included interventions were not effective for changing targeted mediators (only 34% of 413 tests of mediator changes were significant)., Conclusions: There were a number of methodological and statistical limitations in the evidence base. In future, prespecified formal mediation tests should be carried out and could be aided by a formal framework. Social and environmental variables should be considered in addition to intrapersonal variables. Improving knowledge of how to change hypothesized mediators, based on theory and evidence, will reveal how physical activity behavior change maintenance can be achieved. Maintenance research would be enhanced by establishing a formal definition of behavior change "maintenance." PROSPERO registration: PROSPERO 2015:CRD- 42015025462.

Physical inactivity, an unhealthy diet, smoking, and alcohol consumption are key determinants of morbidity and mortality. These health behaviours often begin at a young age and track into adulthood, emphasising a need for interventions in children and young people. Previous research has demonstrated the potential effectiveness of behavioural incentive (BI) interventions in adults. However, little is known about their effectiveness in children and adolescents. Eight bibliographic databases were searched. Eligibility criteria included controlled trials using behavioural incentives (rewards provided contingent on successful performance of the target behaviour) as an intervention component for health behaviour change in children and adolescents. Intervention effects (standardised mean differences or odds ratios) were calculated and pooled by health behaviour, using a random effects model. Twenty-two studies were included (of n = 8392 identified), 19 of which were eligible for meta-analysis: physical activity (n = 8); healthier eating (n = 3); and smoking (n = 8). There was strong evidence that behavioural incentives may encourage healthier eating behaviours, some evidence that behavioural incentives were effective for encouraging physical activity behaviour, and limited evidence to support the use of behavioural incentives for smoking cessation and prevention in adolescents. Findings suggest that behavioural incentives may encourage uptake and initiation of healthy eating and physical activity in young people. However, this is a limited evidence base and a wide range of incentive designs have yet to be explored. Future research should further investigate the acceptability of these intervention approaches for young people., (Copyright © 2018 Elsevier Inc. All rights reserved.)

Objective: To explore the temporal changes of adolescents' views and experiences of participating in a gamified intervention to encourage physical activity behaviour and associated processes of behaviour change., Design: A qualitative longitudinal design was adopted whereby focus groups were conducted with the same participants in each intervention school (n=3) at four time-points (baseline, end of each of two intervention phases and 1-year follow-up). The framework method was used to thematically analyse the data., Setting: Secondary schools (n=3), Belfast (Northern Ireland)., Participants: A subsample (n=19 at four time-points) of individuals aged 12-14 years who participated in the StepSmart Challenge, a gamified intervention involving a pedometer competition and material rewards to encourage physical activity behaviour change., Results: Three core themes were identified: (1) competition; (2) incentives and (3) influence of friends. Participants indicated that a pedometer competition may help initiate physical activity but suggested that there were a number of barriers such as participants finding it ' boring ', and feeling as though they had a remote chance of ' winning '. 'Incentives' were viewed favourably, although there were participants who found not winning a prize ' annoying '. Friends were a motivator to be more physically active, particularly for girls who felt encouraged to walk more when with a friend., Conclusions: The intervention in general and specific gamified elements were generally viewed positively and deemed acceptable. Results suggest that gamification may have an important role to play in encouraging adolescents to engage in physical activity and in creating interventions that are fun and enjoyable. The longitudinal approach added additional depth to the analysis as themes were refined and tested with participants over time. The findings also suggest that gamified Behaviour Change Techniques align well with core concepts of Self-determination Theory and that various game elements may require tailoring for specific populations, for example, different genders., Trial Registration Number: NCT02455986; Pre-results., Competing Interests: Competing interests: None declared., (© Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.)

Background: Despite recent interest in the potential of incentivisation as a strategy for motivating healthier behaviors, little remains known about the effectiveness of incentives in promoting physical activity and reducing sedentary behavior, and improving associated health outcomes. This pre-post-test design study investigated the feasibility, appeal and effects of providing non-financial incentives for promoting increased physical activity, reduced sedentary time, and reduced body mass index (BMI) and blood pressure among inactive middle-aged adults., Methods: Inactive men (n = 36) and women (n = 46) aged 40-65 years were recruited via a not-for-profit insurance fund and participated in a 4 month pre-post design intervention. Baseline and post-intervention data were collected on self-reported physical activity and sitting time (IPAQ-Long), BMI and blood pressure. Participants were encouraged to increase physical activity to 150 mins/week and reduce sedentary behavior by 150 mins/week in progressive increments. Incentives included clothing, recipe books, store gift vouchers, and a chance to win one of four Apple iPad Mini devices. The incentive component of the intervention was supported by an initial motivational interview and text messaging to encourage participants and provide strategies to increase physical activity and reduce sedentary behaviors., Results: Only two participants withdrew during the program, demonstrating the feasibility of recruiting and retaining inactive middle-aged participants. While two-thirds of the sample qualified for the easiest physical activity incentive (by demonstrating 100 mins physical activity/week or 100 mins reduced sitting time/week), only one third qualified for the most challenging incentive. Goals to reduce sitting appeared more challenging, with 43% of participants qualifying for the first incentive, but only 20% for the last incentive. More men than women qualified for most incentives. Mean leisure-time physical activity increased by 252 mins/week (leisure-time), with 65% of the sample achieving at least 150 mins/week; and sitting time decreased by 3.1 h/day (both p < 0.001) between baseline and follow-up. BMI, systolic and diastolic (men only) blood pressure all significantly decreased. Most participants (50-85%) reported finding the incentives and other program components helpful/motivating., Conclusions: Acknowledging the uncontrolled design, the large pre-post changes in behavioral and health-related outcomes suggest that the ACHIEVE incentives-based behavior change program represents a promising approach for promoting physical activity and reducing sitting, and should be tested in a randomized controlled trial., Trial Registration: Australian New Zealand Clinical Trials Registry IDACTRN12616000158460 , registered 10/2/16.

Background: Increasing physical activity in the workplace can provide employee physical and mental health benefits, and employer economic benefits through reduced absenteeism and increased productivity. The workplace is an opportune setting to encourage habitual activity. However, there is limited evidence on effective behaviour change interventions that lead to maintained physical activity. This study aims to address this gap and help build the necessary evidence base for effective, and cost-effective, workplace interventions., Methods/design: This cluster randomised control trial will recruit 776 office-based employees from public sector organisations in Belfast and Lisburn city centres, Northern Ireland. Participants will be randomly allocated by cluster to either the Intervention Group or Control Group (waiting list control). The 6-month intervention consists of rewards (retail vouchers, based on similar principles to high street loyalty cards), feedback and other evidence-based behaviour change techniques. Sensors situated in the vicinity of participating workplaces will promote and monitor minutes of physical activity undertaken by participants. Both groups will complete all outcome measures. The primary outcome is steps per day recorded using a pedometer (Yamax Digiwalker CW-701) for 7 consecutive days at baseline, 6, 12 and 18 months. Secondary outcomes include health, mental wellbeing, quality of life, work absenteeism and presenteeism, and use of healthcare resources. Process measures will assess intervention "dose", website usage, and intervention fidelity. An economic evaluation will be conducted from the National Health Service, employer and retailer perspective using both a cost-utility and cost-effectiveness framework. The inclusion of a discrete choice experiment will further generate values for a cost-benefit analysis. Participant focus groups will explore who the intervention worked for and why, and interviews with retailers will elucidate their views on the sustainability of a public health focused loyalty card scheme., Discussion: The study is designed to maximise the potential for roll-out in similar settings, by engaging the public sector and business community in designing and delivering the intervention. We have developed a sustainable business model using a 'points' based loyalty platform, whereby local businesses 'sponsor' the incentive (retail vouchers) in return for increased footfall to their business., Trial Registration: ISRCTN17975376 (Registered 19/09/2014).

Walking is the most common form of moderate-intensity physical activity among adults, is widely accessible and especially appealing to obese people. Most often policy makers are interested in valuing the effect on walking of changes in some characteristics of a neighbourhood, the demand response for walking, of infrastructure changes. A positive demand response to improvements in the walking environment could help meet the public health target of 150 min of at least moderate-intensity physical activity per week. We model walking in an individual's local neighbourhood as a 'weak complement' to the characteristics of the neighbourhood itself. Walking is affected by neighbourhood characteristics, substitutes, and individual's characteristics, including their opportunity cost of time. Using compensating variation, we assess the economic benefits of walking and how walking behaviour is affected by improvements to the neighbourhood. Using a sample of 1209 respondents surveyed over a 12 month period (Feb 2010-Jan 2011) in East Belfast, United Kingdom, we find that a policy that increased walkability and people's perception of access to shops and facilities would lead to an increase in walking of about 36 min/person/week, valued at £13.65/person/week. When focussing on inactive residents, a policy that improved the walkability of the area would lead to guidelines for physical activity being reached by only 12.8% of the population who are currently inactive. Additional interventions would therefore be needed to encourage inactive residents to achieve the recommended levels of physical activity, as it appears that interventions that improve the walkability of an area are particularly effective in increasing walking among already active citizens, and, among the inactive ones, the best response is found among healthier, younger and wealthier citizens., (Copyright © 2015 Elsevier Ltd. All rights reserved.)

We investigated whether "hidden" (or unobserved) social networks were evident in a 2011 physical activity behavior change intervention in Belfast, Northern Ireland. Results showed evidence of unobserved social networks in the intervention and illustrated how the network evolved over short periods and affected behavior. Behavior change interventions should account for the interaction among participants (i.e., social networks) and how such interactions affect intervention outcome.

Background: Recently both the UK and US governments have advocated the use of financial incentives to encourage healthier lifestyle choices but evidence for the cost-effectiveness of such interventions is lacking. Our aim was to perform a cost-effectiveness analysis (CEA) of a quasi-experimental trial, exploring the use of financial incentives to increase employee physical activity levels, from a healthcare and employer's perspective., Methods: Employees used a 'loyalty card' to objectively monitor their physical activity at work over 12 weeks. The Incentive Group (n=199) collected points and received rewards for minutes of physical activity completed. The No Incentive Group (n=207) self-monitored their physical activity only. Quality of life (QOL) and absenteeism were assessed at baseline and 6 months follow-up. QOL scores were also converted into productivity estimates using a validated algorithm. The additional costs of the Incentive Group were divided by the additional quality adjusted life years (QALYs) or productivity gained to calculate incremental cost effectiveness ratios (ICERs). Cost-effectiveness acceptability curves (CEACs) and population expected value of perfect information (EVPI) was used to characterize and value the uncertainty in our estimates., Results: The Incentive Group performed more physical activity over 12 weeks and by 6 months had achieved greater gains in QOL and productivity, although these mean differences were not statistically significant. The ICERs were £2,900/QALY and £2,700 per percentage increase in overall employee productivity. Whilst the confidence intervals surrounding these ICERs were wide, CEACs showed a high chance of the intervention being cost-effective at low willingness-to-pay (WTP) thresholds., Conclusions: The Physical Activity Loyalty card (PAL) scheme is potentially cost-effective from both a healthcare and employer's perspective but further research is warranted to reduce uncertainty in our results. It is based on a sustainable "business model" which should become more cost-effective as it is delivered to more participants and can be adapted to suit other health behaviors and settings. This comes at a time when both UK and US governments are encouraging business involvement in tackling public health challenges.

Background: Financial incentives have been advocated by the UK and U.S. governments to encourage adoption of healthy lifestyles. However, evidence to support the use of incentives for changing physical activity (PA) behavior is sparse., Purpose: To investigate the effectiveness of financial incentives to increase PA in adults in the workplace., Design: Two-arm quasi-experimental design., Setting/participants: Employees (n=406) in a workplace setting in Belfast, Northern Ireland, UK., Intervention: Using a loyalty card to collect points and earn rewards, participants (n=199) in the Incentive Group monitored their PA levels and received financial incentives (retail vouchers) for minutes of PA completed over the course of a 12-week intervention period. Participants (n=207) in the comparison group used their loyalty card to self-monitor their PA levels but were not able to earn points or obtain incentives (No Incentive Group)., Main Outcome Measures: The primary outcome was minutes of PA objectively measured using a novel PA tracking system at baseline (April 2011); Week 6 (June 2011); and Week 12 (July 2011). Other outcomes, including a self-report measure of PA, were collected at baseline, Week 12, and 6 months (October 2011). Data were analyzed in June 2012., Results: No significant differences between groups were found for primary or secondary outcomes at the 12-week and 6-month assessments. Participants in the Incentive Group recorded 17.52 minutes of PA/week (95% CI=12.49, 22.56) compared to 16.63 minutes/week (95% CI=11.76, 21.51) in the No Incentive Group at Week 12 (p=0.59). At 6 months, participants in the Incentive Group recorded 26.18 minutes of PA/week (95% CI=20.06, 32.29) compared to 24.00 minutes/week (95% CI=17.45, 30.54) in the No Incentive Group (p=0.45)., Conclusions: Financial incentives did not encourage participants to undertake more PA than self-monitoring PA. This study contributes to the evidence base and has important implications for increasing participation in physical activity and fostering links with the business sector., (Copyright © 2013 American Journal of Preventive Medicine.)

The world's population is aging, and the number of people living with dementia and mild cognitive impairment is increasing, having doubled from 1990 to 2016.[1] Encouraging behavior change, such as regular physical activity, and the provision of supportive urban environments (encompassing built, natural, and social environmental factors) can prevent or delay the progress of cognitive decline and dementia and promote healthy aging.[2] Cognitive health promotion aims to maintain cognitive function in healthy individuals and minimize cognitive decline among those with mild cognitive impairment by targeting modifiable risk factors, reducing neurodegeneration risk, and increasing cognitive resilience.[3],[4] The lack of physical activity has been suggested as one of the main modifiable risk factors of dementia.[5] The environment is one of the main determinants of physical activity levels in the population. Preliminary evidence suggests that mixed land use and access to public transport are predictive of better cognitive health and brain health.[8] Residential neighborhoods also influence physical activity, cardiovascular health, and obesity,[6] which are established determinants of cognitive health. [Extracted from the article]

Background: There is a need for novel interventions to target inadequate levels of adolescent physical activity behavior. Previous research indicates that better understanding of the processes by which social networks influence physical activity behavior in adolescents may be useful to enhance intervention design.Methods: This study used a multi-methods approach to aid our understanding about the role of social networks for adolescent physical activity behavior. The quantitative phase of data collection was analyzed using a three-step linear regression model using cross-sectional data from the WiSe study (n = 529 participants, 48.6% female, mean age 14.38 years (SD 0.32)). A demographically reflective sub-sample of schools were invited to take part in the qualitative phase, which involved focus group discussions. Thematic analysis was used to explore findings from the quantitative phase in greater depth, and identify other themes pertaining to the association between social networks and physical activity behavior.Results: Males' physical activity behavior was predicted by their friend group (0.46, p = 0.007) whereas females' physical activity was predicted by their best friend (0.21, p = 0.03). The three main findings that were uncovered by the regression analysis were explored during the qualitative phase: 1) friends have similar physical activity behaviors; 2) friendship social networks may influence differently early adolescent male and female physical activity behavior; 3) popularity and sociability were not associated with physical activity behavior. Two additional themes emerged from the analysis of focus group data: 4) social norms and 5) external factors that may impact the relationship between adolescent physical activity behavior and social networks.Conclusions: The investigation of the interplay between the findings from each phase of the inquiry indicated that social networks influence in different ways and to different degrees the physical activity of adolescent males and females. In turn, these insights point to the need for a systematic tailoring process for the development and implementation of physical activity behavior interventions. [ABSTRACT FROM AUTHOR]

Background: Investigating the association of the neighborhood social environment on physical activity is complex. A systematic scoping review was performed to (1) provide an inventory of studies assessing the influence of the neighborhood social environment on physical activity since 2006; (2) describe methodologies employed; and (3) formulate recommendations for the field. Methods: Two databases were searched using terms related to 'physical activity,' 'neighborhood,' and 'social environment' in January 2017. Eligibility criteria included: 1) physical activity as an outcome; 2) neighborhood social environment as a predictor; 3) healthy population (without diagnosed clinical condition or special population); 4) observational or experimental design. Of 1352 studies identified, 181 were included. Textual data relevant to the social environment measurement and analysis were extracted from each article into qualitative software (MAXQDA) and coded to identify social environmental constructs, measurement methods, level of measurement (individual vs. aggregated to neighborhood), and whether authors explicitly recognized the construct as the social environment. The following measures were generated for each construct: number of unique measurements; % of times measured at an aggregate level; % of times authors referred to the construct as the social environment. Social environmental constructs were then grouped into larger descriptive dimensions. Results/findings: Fifty-nine social environmental constructs were identified and grouped into 9 dimensions: Crime & Safety (n = 133 studies; included in 73% of studies); Economic & Social Disadvantage (n = 55, 33%); Social Cohesion & Capital (n = 47, 26%); Social Relationships (n = 22, 12%); Social Environment (n = 16, 9%); Disorder & Incivilities (n = 15, 8%); Sense of Place/Belonging (n = 8, 4%); Discrimination/Segregation (n = 3, 2%); Civic Participation & Engagement (n = 2, 1%). Across all articles, the social environment was measured using 176 different methods, was measured at an aggregate-level 38% of the time, and referred to as the social environment 23% of the time. Conclusions: Inconsistent terminology, definitions, and measurement of the social environment and the lack of explicit language identifying constructs as the social environment make it challenging to compare results across studies and draw conclusions. Improvements are needed to increase our understanding of social environmental correlates and/or determinants of physical activity and facilitate cross-disciplinary conversations necessary to effectively intervene to promote physical activity. Trial registration: PROSPERO CRD42017059580. [ABSTRACT FROM AUTHOR]

Background Physical activity (PA) interventions are generally effective in supporting short-term behaviour change, but increases are not always maintained. This review examined the effectiveness of PA interventions for behaviour change maintenance in young and middle–aged adults, and investigated which Behaviour Change Techniques (BCTs) and other intervention features were associated with maintenance. Methods Six databases (Medline, EMBASE, PsycINFO, Cochrane Database of Systematic Reviews, CINAHL, Web of Science) were systematically searched. Eligibility criteria were controlled trials investigating the effectiveness of PA interventions with adult (mean age 18–64 years) non-clinical populations using validated measures of PA behaviour at baseline and ≥six months’ post-baseline. Results were pooled in meta-analyses using standardised mean differences (SMD) at five time intervals (6–9, 9–15, 15–21, 21–24, >24 months). Moderator analyses investigated the influence of sample and intervention characteristics on PA maintenance at 6–9 months. Results Sixty-two studies were included. PA interventions had a significant effect on behaviour maintenance 6–15 months post-baseline relative to controls. Interventions had a larger effect on maintenance at 6–9 months (SMD = 0.28; 95% CI : 0.20, 0.35; I 2 = 73%) compared to 9–15 months (SMD = 0.20; 95% CI : 0.13, 0.26; I 2 = 70%). Beyond 15 months, PA measurements were infrequent with little evidence supporting maintenance. Moderator analyses showed some BCTs and intervention settings moderated PA outcomes at 6–9 months. A multivariable meta-regression model showed interventions using the BCTs ‘Prompt self-monitoring of behavioural outcome’ ( b = 1.46, p < 0.01) and ‘Use of follow-up prompts’ ( b = 0.38, p < 0.01) demonstrated greater effectiveness at promoting PA maintenance at 6–9 months. Interventions implemented in primary care (versus community or workplace/university) settings ( b = −0.13, p = 0.10) tended to demonstrate less effectiveness. Conclusions This review provides evidence of some effective BCTs for maintaining behaviour to 15 months. Greater consideration must be given to how future interventions encourage and measure maintenance of changes, and investigate broader psychological, social and environmental influences of PA behaviour. PROSPERO registration PROSPERO 2015:CRD42015025462. [ABSTRACT FROM AUTHOR]