Existing guidance for developing public health interventions does not provide information for researchers about how to work with intervention providers to co-produce and prototype the content and delivery of new interventions prior to evaluation. The ASSIST + Frank study aimed to adapt an existing effective peer-led smoking prevention intervention (ASSIST), integrating new content from the UK drug education resource Talk to Frank ( www.talktofrank.com ) to co-produce two new school-based peer-led drug prevention interventions. A three-stage framework was tested to adapt and develop intervention content and delivery methods in collaboration with key stakeholders to facilitate implementation. The three stages of the framework were: 1) Evidence review and stakeholder consultation; 2) Co-production; 3) Prototyping. During stage 1, six focus groups, 12 consultations, five interviews, and nine observations of intervention delivery were conducted with key stakeholders (e.g. Public Health Wales [PHW] ASSIST delivery team, teachers, school students, health professionals). During stage 2, an intervention development group consisting of members of the research team and the PHW ASSIST delivery team was established to adapt existing, and co-produce new, intervention activities. In stage 3, intervention training and content were iteratively prototyped using process data on fidelity and acceptability to key stakeholders. Stages 2 and 3 took the form of an action-research process involving a series of face-to-face meetings, email exchanges, observations, and training sessions. Utilising the three-stage framework, we co-produced and tested intervention content and delivery methods for the two interventions over a period of 18 months involving external partners. New and adapted intervention activities, as well as refinements in content, the format of delivery, timing and sequencing of activities, and training manuals resulted from this process. The involvement of intervention delivery staff, participants and teachers shaped the content and format of the interventions, as well as supporting rapid prototyping in context at the final stage. This three-stage framework extends current guidance on intervention development by providing step-by-step instructions for co-producing and prototyping an intervention’s content and delivery processes prior to piloting and formal evaluation. This framework enhances existing guidance and could be transferred to co-produce and prototype other public health interventions. ISRCTN14415936 , registered retrospectively on 05 November 2014.

Patient-centered care requires different approaches depending on the clinical situation. Motivational interviewing and shared decision making provide practical and well-described methods to accomplish patient-centered care in the context of situations where medical evidence supports specific behavior changes and the most appropriate action is dependent on the patient’s preferences. Many clinical consultations may require elements of both approaches, however. This article describes these 2 approaches—one to address ambivalence to medically indicated behavior change and the other to support patients in making health care decisions in cases where there is more than one reasonable option—and discusses how clinicians can draw on these approaches alone and in combination to achieve patient-centered care across the range of health care problems.

Background: The common mental disorders (CMDs) of anxiety and depression are the most common form of poor mental health in the general population. Evidence from the small number of previous cohort studies on the role of neighbourhood factors in mental health is inconclusive. We tested the hypothesis that high levels of neighbourhood social cohesion modify an adverse association between change in individual mental health and neighbourhood deprivation.Method: We carried out a longitudinal multilevel analysis using data from the Caerphilly Health and Social Needs Cohort Study with a 7-year follow-up (n = 4426; age range 18–74 years at baseline). Neighbourhood deprivation and neighbourhood social cohesion were assessed at baseline and change in mental health between follow-up and baseline was assessed using the five-item Mental Health Inventory (MHI-5).Results: Residence in the most deprived neighbourhoods was negatively associated with change in mental health, after adjusting for baseline individual socio-economic risk factors and transitions in life events. This negative effect was significantly reduced in high social cohesion neighbourhoods. The predicted change in mental health score was calculated for the 10th and 90th centiles of the household low-income distribution. The difference between them was −2.8 in the low social cohesion group and 1.1 in the high cohesion group. The difference between the groups was 3.9 [95% confidence interval (CI) 0.2–7.6].Conclusions: The public health burden of poor mental health and mental health inequality could potentially be reduced by strengthening social cohesion in deprived neighbourhoods. This offers a mechanism to address the adverse effect of neighbourhood deprivation on population mental health.

Background Engagement in multiple risk behaviours can have adverse consequences for health during childhood, during adolescence, and later in life, yet little is known about the impact of different types of interventions that target multiple risk behaviours in children and young people, or the differential impact of universal versus targeted approaches. Findings from systematic reviews have been mixed, and effects of these interventions have not been quantitatively estimated. Objectives To examine the effects of interventions implemented up to 18 years of age for the primary or secondary prevention of multiple risk behaviours among young people. Search methods We searched 11 databases (Australian Education Index; British Education Index; Campbell Library; Cumulative Index to Nursing and Allied Health Literature (CINAHL); Cochrane Central Register of Controlled Trials (CENTRAL), in the Cochrane Library; Embase; Education Resource Information Center (ERIC); International Bibliography of the Social Sciences; MEDLINE; PsycINFO; and Sociological Abstracts) on three occasions (2012, 2015, and 14 November 2016)). We conducted handsearches of reference lists, contacted experts in the field, conducted citation searches, and searched websites of relevant organisations. Selection criteria We included randomised controlled trials (RCTs), including cluster RCTs, which aimed to address at least two risk behaviours. Participants were children and young people up to 18 years of age and/or parents, guardians, or carers, as long as the intervention aimed to address involvement in multiple risk behaviours among children and young people up to 18 years of age. However, studies could include outcome data on children > 18 years of age at the time of follow‐up. Specifically,we included studies with outcomes collected from those eight to 25 years of age. Further, we included only studies with a combined intervention and follow‐up period of six months or longer. We excluded interventions aimed at individuals with clinically diagnosed disorders along with clinical interventions. We categorised interventions according to whether they were conducted at the individual level; the family level; or the school level. Data collection and analysis We identified a total of 34,680 titles, screened 27,691 articles and assessed 424 full‐text articles for eligibility. Two or more review authors independently assessed studies for inclusion in the review, extracted data, and assessed risk of bias. We pooled data in meta‐analyses using a random‐effects (DerSimonian and Laird) model in RevMan 5.3. For each outcome, we included subgroups related to study type (individual, family, or school level, and universal or targeted approach) and examined effectiveness at up to 12 months' follow‐up and over the longer term (> 12 months). We assessed the quality and certainty of evidence using the Grades of Recommendation, Assessment, Development and Evaluation (GRADE) approach. Main results We included in the review a total of 70 eligible studies, of which a substantial proportion were universal school‐based studies (n = 28; 40%). Most studies were conducted in the USA (n = 55; 79%). On average, studies aimed to prevent four of the primary behaviours. Behaviours that were most frequently addressed included alcohol use (n = 55), drug use (n = 53), and/or antisocial behaviour (n = 53), followed by tobacco use (n = 42). No studies aimed to prevent self‐harm or gambling alongside other behaviours. Evidence suggests that for multiple risk behaviours, universal school‐based interventions were beneficial in relation to tobacco use (odds ratio (OR) 0.77, 95% confidence interval (CI) 0.60 to 0.97; n = 9 studies; 15,354 participants) and alcohol use (OR 0.72, 95% CI 0.56 to 0.92; n = 8 studies; 8751 participants; both moderate‐quality evidence) compared to a comparator, and that such interventions may be effective in preventing illicit drug use (OR 0.74, 95% CI 0.55 to 1.00; n = 5 studies; 11,058 participants; low‐quality evidence) and engagement in any antisocial behaviour (OR 0.81, 95% CI 0.66 to 0.98; n = 13 studies; 20,756 participants; very low‐quality evidence) at up to 12 months' follow‐up, although there was evidence of moderate to substantial heterogeneity (I² = 49% to 69%). Moderate‐quality evidence also showed that multiple risk behaviour universal school‐based interventions improved the odds of physical activity (OR 1.32, 95% CI 1.16 to 1.50; I² = 0%; n = 4 studies; 6441 participants). We considered observed effects to be of public health importance when applied at the population level. Evidence was less certain for the effects of such multiple risk behaviour interventions for cannabis use (OR 0.79, 95% CI 0.62 to 1.01; P = 0.06; n = 5 studies; 4140 participants; I² = 0%; moderate‐quality evidence), sexual risk behaviours (OR 0.83, 95% CI 0.61 to 1.12; P = 0.22; n = 6 studies; 12,633 participants; I² = 77%; low‐quality evidence), and unhealthy diet (OR 0.82, 95% CI 0.64 to 1.06; P = 0.13; n = 3 studies; 6441 participants; I² = 49%; moderate‐quality evidence). It is important to note that some evidence supported the positive effects of universal school‐level interventions on three or more risk behaviours. For most outcomes of individual‐ and family‐level targeted and universal interventions, moderate‐ or low‐quality evidence suggests little or no effect, although caution is warranted in interpretation because few of these studies were available for comparison (n ≤ 4 studies for each outcome). Seven studies reported adverse effects, which involved evidence suggestive of increased involvement in a risk behaviour among participants receiving the intervention compared to participants given control interventions. We judged the quality of evidence to be moderate or low...

Objectives The influence of neighbourhood deprivation on the risk of harmful alcohol consumption, measured by the separate categories of excess consumption and binge drinking, has not been studied. The study objective was to investigate the effect of neighbourhood deprivation with age, gender and socioeconomic status (SES) on (1) excess alcohol consumption and (2) binge drinking, in a representative population survey. Design Cross-sectional study: multilevel analysis. Setting Wales, UK, adult population ∼2.2 million. Participants 58 282 respondents aged 18 years and over to four successive annual Welsh Health Surveys (2003/2004–2007), nested within 32 692 households, 1839 census lower super output areas and the 22 unitary authority areas in Wales. Primary outcome measure Maximal daily alcohol consumption during the past week was categorised using the UK Department of Health definition of ‘none/never drinks’, ‘within guidelines’, ‘excess consumption but less than binge’ and ‘binge’. The data were analysed using continuation ratio ordinal multilevel models with multiple imputation for missing covariates. Results Respondents in the most deprived neighbourhoods were more likely to binge drink than in the least deprived (adjusted estimates: 17.5% vs 10.6%; difference=6.9%, 95% CI 6.0 to 7.8), but were less likely to report excess consumption (17.6% vs 21.3%; difference=3.7%, 95% CI 2.6 to 4.8). The effect of deprivation varied significantly with age and gender, but not with SES. Younger men in deprived neighbourhoods were most likely to binge drink. Men aged 35–64 showed the steepest increase in binge drinking in deprived neighbourhoods, but men aged 18–24 showed a smaller increase with deprivation. Conclusions This large-scale population study is the first to show that neighbourhood deprivation acts differentially on the risk of binge drinking between men and women at different age groups. Understanding the socioeconomic patterns of harmful alcohol consumption is important for public health policy development.