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Objective: This two-site randomised trial compared the effectiveness of a voluntary sector-led, community-based diabetes prevention programme to a waiting-list control group at 6 months, and included an observational follow-up of the intervention arm to 12 months., Methods: Adults aged 18-75 years at increased risk of developing type 2 diabetes due to elevated blood glucose and being overweight were recruited from primary care practices at two UK sites, with data collected in participants' homes or community venues. Participants were randomised using an online central allocation service. The intervention, comprising the prototype "Living Well, Taking Control" (LWTC) programme, involved four weekly two-hour group sessions held in local community venues to promote changes in diet and physical activity, plus planned follow-up contacts at two, three, six, nine and 12 months alongside 5 hours of additional activities/classes. Waiting list controls received usual care for 6 months before accessing the programme. The primary outcome was weight loss at 6 months. Secondary outcomes included glycated haemoglobin (HbA1c), blood pressure, physical activity, diet, health status and well-being. Only researchers conducting analyses were blinded., Results: The target sample of 314 participants (157 each arm) was largely representative of local populations, including 44% men, 26% from ethnic minorities and 33% living in deprived areas. Primary outcome data were available for 285 (91%) participants (141 intervention, 144 control). Between baseline and 6 months, intervention participants on average lost more weight than controls (- 1.7 kg, 95% CI - 2.59 to - 0.85). Higher attendance was associated with greater weight loss (- 3.0 kg, 95% CI - 4.5 to - 1.5). The prototype LWTC programme more than doubled the proportion of participants losing > 5% of their body weight (21% intervention vs. 8% control, OR 2.83, 95% CI 1.36 to 5.90) and improved self-reported dietary behaviour and health status. There were no impacts on HbA1c, blood pressure, physical activity and well-being at 6 months and, amongst intervention participants, few further changes from six to 12-months (e.g. average weight re-gain 0.36 kg, 95% CI - 0.20 to 0.91). There were no serious adverse events but four exercise-related injuries were reported in the intervention arm., Conclusions: This voluntary sector-led diabetes prevention programme reached a broad spectrum of the population and had modest effects on weight-related outcomes, but limited impacts on other diabetes risk factors., Trial Registration: Trial registration number: ISRCTN70221670, 5 September 2014 Funder (National Institute for Health Research School for Public Health Research) project reference number: SPHR-EXE-PES-COM.

Investigate associations between quantity, content and specificity of action-plans and weight loss in a diabetes prevention study. Prospective cohort study nested within a randomised controlled trial. Participants completed action-planning worksheets during intervention sessions. Action-plans were coded in terms of: number of plans set, their content, and specificity. Multivariate regression analyses assessed associations with weight loss at four-months. 890 planning-worksheets from 106 participants were analysed. Participants wrote a mean of 2.12 (SD = 1.20) action-plans per worksheet, using a mean of 2.20 (SD = 0.68) specificity components per action-plan. Quantity of action-plans per worksheet decreased over time (r = −0.137, p < 0.001) and increased quantity was associated with reduced specificity [r = −.215, p < 0.001]. Walking (34.9% of action-plans) and reducing high fat/sugar snacks (26.1%) were the most commonly planned lifestyle actions. In multivariate modelling, increased quantity of action-plans was associated with greater weight loss (R2 = 0.135, Unstandardised Beta = 0.144, p = 0.002). Specificity was not significantly associated with weight-loss (p = 0.096). Producing more action-plans was associated with greater weight loss. Further research should directly compare more versus less specific action-plans and explore ways to sustain engagement in action-planning. Our findings imply that participants should freely set numerous action-plans, rather than being encouraged to focus on specificity Supplemental data for this article is available online at https://doi.org/10.1080/08870446.2022.2055026. [ABSTRACT FROM AUTHOR]

Group-based interventions are widely used to promote health-related behaviour change. While processes operating in groups have been extensively described, it remains unclear how behaviour change is generated in group-based health-related behaviour-change interventions. Understanding how such interventions facilitate change is important to guide intervention design and process evaluations. We employed a mixed-methods approach to identify, map and define change processes operating in group-based behaviour-change interventions. We reviewed multidisciplinary literature on group dynamics, taxonomies of change technique categories, and measures of group processes. Using weight-loss groups as an exemplar, we also reviewed qualitative studies of participants' experiences and coded transcripts of 38 group sessions from three weight-loss interventions. Finally, we consulted group participants, facilitators and researchers about our developing synthesis of findings. The resulting 'Mechanisms of Action in Group-based Interventions' (MAGI) framework comprises six overarching categories: (1) group intervention design features, (2) facilitation techniques, (3) group dynamic and development processes, (4) inter-personal change processes, (5) selective intra-personal change processes operating in groups, and (6) contextual influences. The framework provides theoretical explanations of how change occurs in group-based behaviour-change interventions and can be applied to optimise their design and delivery, and to guide evaluation, facilitator training and further research. [ABSTRACT FROM AUTHOR]

Background: There are thousands of apps promoting dietary improvement, increased physical activity (PA) and weight management. Despite a growing number of reviews in this area, popular apps have not been comprehensively analysed in terms of features related to engagement, functionality, aesthetics, information quality, and content, including the types of change techniques employed. Methods: The databases containing information about all Health and Fitness apps on GP and iTunes (7,954 and 25,491 apps) were downloaded in April 2015. Database filters were applied to select the most popular apps available in both stores. Two researchers screened the descriptions selecting only weight management apps. Features, app quality and content were independently assessed using the Mobile App Rating Scale (MARS) and previously-defined categories of techniques relevant to behaviour change. Inter-coder reliabilities were calculated, and correlations between features explored. Results: Of the 23 popular apps included in the review 16 were free (70 %), 15 (65 %) addressed weight control, diet and PA combined; 19 (83 %) allowed behavioural tracking. On 5-point MARS scales, apps were of average quality (Md = 3.2, IQR= 1.4); "functionality" (Md=4.0, IQR= 1.1) was the highest and "information quality" (Md = 2.0, IQR= 1.1) was the lowest domain. On average, 10 techniques were identified per app (range: 1-17) and of the 34 categories applied, goal setting and self-monitoring techniques were most frequently identified. App quality was positively correlated with number of techniques included (rho = .58, p < .01) and number of "technical" features (rho = .48, p<.05), which was also associated with the number of techniques included (rho = .61, p < .01). Apps that provided tracking used significantly more techniques than those that did not. Apps with automated tracking scored significantly higher in engagement, aesthetics, and overall MARS scores. Those that used change techniques previously associated with effectiveness (i.e., goal setting, self-monitoring and feedback) also had better "information quality". Conclusions: Popular apps assessed have overall moderate quality and include behavioural tracking features and a range of change techniques associated with behaviour change. These apps may influence behaviour, although more attention to information quality and evidence-based content are warranted to improve their quality. [ABSTRACT FROM AUTHOR]