BackgroundThere 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.MethodsThe 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.ResultsOf 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”.ConclusionsPopular 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.Electronic supplementary materialThe online version of this article (doi:10.1186/s12966-016-0359-9) contains supplementary material, which is available to authorized users.

Disease status scores in AS correlated significantly with anxiety, depression, internality and health status. Interpretation of AS disease scores should take an account of psychological status and the choice of measures used. These findings have important potential applications in AS management and monitoring, including the identification of patients for biological therapies.

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. ARTICLE HISTORY

BackgroundPublished descriptions of group-based behaviour-change interventions (GB-BCIs) often omit design and delivery features specific to the group setting. This impedes the ability to compare behaviour-change interventions, synthesise evidence on their effectiveness and replicate effective interventions. The aim of this study was to develop a checklist of elements that should be described to ensure adequate reporting of GB-BCIs.MethodsA range of characteristics needed to replicate GB-BCIs were extracted from the literature and precisely defined. An abbreviated checklist and a coder manual were developed, pilot tested and refined. The final checklist and coder manual were used to identify the presence or absence of specified reporting elements in 30 published descriptions of GB-BCIs by two independent coders. Reliability of coding was assessed.ResultsThe checklist comprises 26 essential reporting elements, covering intervention design, intervention content, participant characteristics, and facilitator characteristics. Inter-rater reliability for identification of reporting elements was high (95 % agreement, Mean AC1 = 0.89).ConclusionThe checklist is a practical tool that can be used, alongside other reporting guidelines, to ensure comprehensive description and to assess reporting quality of GB-BCIs. It can also be helpful for designing group-based health interventions.Electronic supplementary materialThe online version of this article (doi:10.1186/s12889-015-2300-6) contains supplementary material, which is available to authorized users.

Background Patients at risk of severe exacerbations contribute disproportionally to asthma mortality, morbidity and costs. We evaluated the effectiveness and costs of using 'asthma risk registers' for these patients in primary care. Methods In a cluster-randomised trial, 29 primary care practices identified 911 at-risk asthma patients using British asthma guideline criteria (severe asthma plus adverse psychosocial characteristics). Intervention practices added electronic alerts to identified patients' records to flag their at-risk status and received practicebased training about using the alerts to improve patient access and opportunistic management. Control practices continued routine care. Numbers of patients experiencing the primary outcome of a moderate-severe exacerbation (resulting in death, hospitalisation, accident and emergency attendance, out-of-hours contact, or a course/boost in oral prednisolone for asthma), other healthcare and medication usage, and costs over 1 year were derived from practice-based records. Results There was no significant effect on exacerbations (control: 46.5%; intervention: 53.6%, OR, 95% CI 1.30, 0.93 to 1.80). However, this composite outcome masked relative reductions in intervention patients experiencing hospitalisations (OR 0.50, 95% CI 0.26 to 0.94), accident and emergency (OR 0.74, 95% CI 0.42 to 1.31) and out-of-hours contacts (OR 0.79, 95% CI 0.45 to 1.37); and a relative increase in prednisolone prescription for exacerbations (OR 1.31, 95% CI 0.92 to 1.85). Furthermore, prescription of nebulised short-acting b-agonists reduced and long-acting b-agonists increased for intervention relative to control patients. The adjusted mean per patient healthcare cost was £138.21 lower (p¼0.837) among intervention practices. Conclusion Using asthma risk registers in primary care did not reduce treated exacerbations, but reduced hospitalisations and increased prescriptions of recommended preventative therapies without increasing costs.

Question Does our group-based lifestyle intervention (with or without trained volunteers with Type 2 diabetes) reduce the risk of Type 2 diabetes in people with the current high risk intermediate glycemic categories of impaired fasting glucose or non-diabetic hyperglycemia Finding In this trial of 1,028 participants with high risk intermediate glycemic categories , the intervention significantly reduced the 2 year risk of Type 2 diabetes by 40-47%, although lay volunteer support did not reduce the risk further. For every 11 participants treated, one diabetes diagnosis was prevented. Meaning Nearly half the adult population have diabetes or a high risk glycemic category, and this low-cost group-delivered intervention significantly reduced the risk of diabetes.

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ObjectiveThis 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.MethodsAdults 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.ResultsThe 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.ConclusionsThis 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 registrationTrial registration number: ISRCTN70221670, 5 September 2014Funder (National Institute for Health Research School for Public Health Research) project reference number: SPHR-EXE-PES-COM.