The piloted mHealth programme provided some short-term positive changes in weight, nutrition and physical activity using a low cost, convenient delivery method for this population. However, changes were no different from those observed among controls. This might partly be explained by intervention participants' low engagement with the programme, which is likely to require further modification to provide more regular, personalised, monitored support.

BackgroundYoung adults (aged 18 to 35) are a population group at high risk for weight gain, yet we know little about how to intervene in this group. Easy access to treatment and support with self-monitoring of their behaviors may be important. Smartphones are gaining in popularity with this population group and software applications (“apps”) used on these mobile devices are a novel technology that can be used to deliver brief health behavior change interventions directly to individuals en masse, with potentially favorable cost-utility. However, existing apps for modifying nutrition or physical activity behaviors may not always reflect best practice guidelines for weight management.ObjectiveThis paper describes the process of developing four apps aimed at modifying key lifestyle behaviors associated with weight gain during young adulthood, including physical activity, and consumption of take-out foods (fast food), fruit and vegetables, and sugar-sweetened drinks.MethodsThe development process involved: (1) deciding on the behavior change strategies, relevant guidelines, graphic design, and potential data collection; (2) selecting the platform (Web-based versus native); (3) creating the design, which required decisions about the user interface, architecture of the relational database, and programming code; and (4) testing the prototype versions with the target audience (young adults aged 18 to 35).ResultsThe four apps took 18 months to develop, involving the fields of marketing, nutrition and dietetics, physical activity, and information technology. Ten subjects provided qualitative feedback about using the apps. The slow running speed of the apps (due to a reliance on an active Internet connection) was the primary issue identified by this group, as well as the requirement to log in to the apps.ConclusionsSmartphone apps may be an innovative medium for delivering individual health behavior change intervention en masse, but researchers must give consideration to the target population, available technologies, existing commercial apps, and the possibility that their use will be irregular and short-lived.

To systematically review studies of health promotion intervention in the police force. Four databases were searched for articles reporting on prepost single and multigroup studies in police officers and trainees. Data were extracted and bias assessed to evaluate study characteristics, intervention design and the impact of interventions on health. Database searching identified 25 articles reporting on 21 studies relevant to the aims of this review. Few studies (n=3) were of long duration (≥6 months). Nine of 21 studies evaluated structured physical activity and/or diet programmes only, 5 studies used education and behaviour change support-only interventions, 5 combined structured programmes with education and behaviour change support, and 2 studies used computer prompts to minimise sedentary behaviour. A wide array of lifestyle behaviour and health outcomes was measured, with 11/13 multigroup and 8/8 single-group studies reporting beneficial impacts on outcomes. High risk of bias was evident across most studies. In those with the lowest risk of bias (n=2), a large effect on blood pressure and small effects on diet, sleep quality, stress and tobacco use, were reported. Health promotion interventions can impact beneficially on health of the police force, particularly blood pressure, diet, sleep, stress and tobacco use. Limited reporting made comparison of findings challenging. Combined structured programmes with education and behaviour change support and programmes including peer support resulted in the most impact on health-related outcomes.

Physical activity and diet are major modifiable risk factors for chronic disease and have been shown to be associated with neighborhood built environment. Systematic review evidence from longitudinal studies on the impact of changing the built environment on physical activity and diet is currently lacking. A systematic review of natural experiments of neighborhood built environment was conducted. The aims of this systematic review were to summarize study characteristics, study quality, and impact of changes in neighborhood built environment on physical activity and diet outcomes among residents. Natural experiments of neighborhood built environment change, exploring longitudinal impacts on physical activity and/or diet in residents, were included. From five electronic databases, 2084 references were identified. A narrative synthesis was conducted, considering results in relation to study quality. Nineteen papers, reporting on 15 different exposures met inclusion criteria. Four studies included a comparison group and 11 were pre-post/longitudinal studies without a comparison group. Studies reported on the impact of redeveloping or introducing cycle and/or walking trails (n = 5), rail stops/lines (n = 4), supermarkets and farmers’ markets (n = 4) and park and green space (n = 2). Eight/15 studies reported at least one beneficial change in physical activity, diet or another associated health outcome. Due to limitations in study design and reporting, as well as the wide array of outcome measures reported, drawing conclusions to inform policy was challenging. Future research should consider a consistent approach to measure the same outcomes (e.g., using measurement methods that collect comparable physical activity and diet outcome data), to allow for pooled analyses. Additionally, including comparison groups wherever possible and ensuring high quality reporting is essential.

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