Interventions to prevent obesity in children aged 5 to 11 years old.

BACKGROUND: Prevention of obesity in children is an international public health priority given the prevalence of the condition (and its significant impact on health, development and well-being). Interventions that aim to prevent obesity involve behavioural change strategies that promote healthy eating or 'activity' levels (physical activity, sedentary behaviour and/or sleep) or both, and work by reducing energy intake and/or increasing energy expenditure, respectively. There is uncertainty over which approaches are more effective and numerous new studies have been published over the last five years, since the previous version of this Cochrane review. OBJECTIVES: To assess the effects of interventions that aim to prevent obesity in children by modifying dietary intake or 'activity' levels, or a combination of both, on changes in BMI, zBMI score and serious adverse events. SEARCH METHODS: We used standard, extensive Cochrane search methods. The latest search date was February 2023. SELECTION CRITERIA: Randomised controlled trials in children (mean age 5 years and above but less than 12 years), comparing diet or 'activity' interventions (or both) to prevent obesity with no intervention, usual care, or with another eligible intervention, in any setting. Studies had to measure outcomes at a minimum of 12 weeks post baseline. We excluded interventions designed primarily to improve sporting performance. DATA COLLECTION AND ANALYSIS: We used standard Cochrane methods. Our outcomes were body mass index (BMI), zBMI score and serious adverse events, assessed at short- (12 weeks to < 9 months from baseline), medium- (9 months to < 15 months) and long-term (≥ 15 months) follow-up. We used GRADE to assess the certainty of the evidence for each outcome. MAIN RESULTS: This review includes 172 studies (189,707 participants); 149 studies (160,267 participants) were included in meta-analyses. One hundred forty-six studies were based in high-income countries. The main setting for intervention delivery was schools (111 studies), followed by the community (15 studies), the home (eight studies) and a clinical setting (seven studies); one intervention was conducted by telehealth and 31 studies were conducted in more than one setting. Eighty-six interventions were implemented for less than nine months; the shortest was conducted over one visit and the longest over four years. Non-industry funding was declared by 132 studies; 24 studies were funded in part or wholly by industry. Dietary interventions versus control Dietary interventions, compared with control, may have little to no effect on BMI at short-term follow-up (mean difference (MD) 0, 95% confidence interval (CI) -0.10 to 0.10; 5 studies, 2107 participants; low-certainty evidence) and at medium-term follow-up (MD -0.01, 95% CI -0.15 to 0.12; 9 studies, 6815 participants; low-certainty evidence) or zBMI at long-term follow-up (MD -0.05, 95% CI -0.10 to 0.01; 7 studies, 5285 participants; low-certainty evidence). Dietary interventions, compared with control, probably have little to no effect on BMI at long-term follow-up (MD -0.17, 95% CI -0.48 to 0.13; 2 studies, 945 participants; moderate-certainty evidence) and zBMI at short- or medium-term follow-up (MD -0.06, 95% CI -0.13 to 0.01; 8 studies, 3695 participants; MD -0.04, 95% CI -0.10 to 0.02; 9 studies, 7048 participants; moderate-certainty evidence). Five studies (1913 participants; very low-certainty evidence) reported data on serious adverse events: one reported serious adverse events (e.g. allergy, behavioural problems and abdominal discomfort) that may have occurred as a result of the intervention; four reported no effect. Activity interventions versus control Activity interventions, compared with control, may have little to no effect on BMI and zBMI at short-term or long-term follow-up (BMI short-term: MD -0.02, 95% CI -0.17 to 0.13; 14 studies, 4069 participants; zBMI short-term: MD -0.02, 95% CI -0.07 to 0.02; 6 studies, 3580 participants; low-certainty evidence; BMI long-term: MD -0.07, 95% CI -0.24 to 0.10; 8 studies, 8302 participants; zBMI long-term: MD -0.02, 95% CI -0.09 to 0.04; 6 studies, 6940 participants; low-certainty evidence). Activity interventions likely result in a slight reduction of BMI and zBMI at medium-term follow-up (BMI: MD -0.11, 95% CI -0.18 to -0.05; 16 studies, 21,286 participants; zBMI: MD -0.05, 95% CI -0.09 to -0.02; 13 studies, 20,600 participants; moderate-certainty evidence). Eleven studies (21,278 participants; low-certainty evidence) reported data on serious adverse events; one study reported two minor ankle sprains and one study reported the incident rate of adverse events (e.g. musculoskeletal injuries) that may have occurred as a result of the intervention; nine studies reported no effect. Dietary and activity interventions versus control Dietary and activity interventions, compared with control, may result in a slight reduction in BMI and zBMI at short-term follow-up (BMI: MD -0.11, 95% CI -0.21 to -0.01; 27 studies, 16,066 participants; zBMI: MD -0.03, 95% CI -0.06 to 0.00; 26 studies, 12,784 participants; low-certainty evidence) and likely result in a reduction of BMI and zBMI at medium-term follow-up (BMI: MD -0.11, 95% CI -0.21 to 0.00; 21 studies, 17,547 participants; zBMI: MD -0.05, 95% CI -0.07 to -0.02; 24 studies, 20,998 participants; moderate-certainty evidence). Dietary and activity interventions compared with control may result in little to no difference in BMI and zBMI at long-term follow-up (BMI: MD 0.03, 95% CI -0.11 to 0.16; 16 studies, 22,098 participants; zBMI: MD -0.02, 95% CI -0.06 to 0.01; 22 studies, 23,594 participants; low-certainty evidence). Nineteen studies (27,882 participants; low-certainty evidence) reported data on serious adverse events: four studies reported occurrence of serious adverse events (e.g. injuries, low levels of extreme dieting behaviour); 15 studies reported no effect. Heterogeneity was apparent in the results for all outcomes at the three follow-up times, which could not be explained by the main setting of the interventions (school, home, school and home, other), country income status (high-income versus non-high-income), participants' socioeconomic status (low versus mixed) and duration of the intervention. Most studies excluded children with a mental or physical disability. AUTHORS' CONCLUSIONS: The body of evidence in this review demonstrates that a range of school-based 'activity' interventions, alone or in combination with dietary interventions, may have a modest beneficial effect on obesity in childhood at short- and medium-term, but not at long-term follow-up. Dietary interventions alone may result in little to no difference. Limited evidence of low quality was identified on the effect of dietary and/or activity interventions on severe adverse events and health inequalities; exploratory analyses of these data suggest no meaningful impact. We identified a dearth of evidence for home and community-based settings (e.g. delivered through local youth groups), for children living with disabilities and indicators of health inequities.

Interventions to prevent obesity in children aged 12 to 18 years old.

BACKGROUND: Prevention of obesity in adolescents is an international public health priority. The prevalence of overweight and obesity is over 25% in North and South America, Australia, most of Europe, and the Gulf region. Interventions that aim to prevent obesity involve strategies that promote healthy diets or 'activity' levels (physical activity, sedentary behaviour and/or sleep) or both, and work by reducing energy intake and/or increasing energy expenditure, respectively. There is uncertainty over which approaches are more effective, and numerous new studies have been published over the last five years since the previous version of this Cochrane Review. OBJECTIVES: To assess the effects of interventions that aim to prevent obesity in adolescents by modifying dietary intake or 'activity' levels, or a combination of both, on changes in BMI, zBMI score and serious adverse events. SEARCH METHODS: We used standard, extensive Cochrane search methods. The latest search date was February 2023. SELECTION CRITERIA: Randomised controlled trials in adolescents (mean age 12 years and above but less than 19 years), comparing diet or 'activity' interventions (or both) to prevent obesity with no intervention, usual care, or with another eligible intervention, in any setting. Studies had to measure outcomes at a minimum of 12 weeks post baseline. We excluded interventions designed primarily to improve sporting performance. DATA COLLECTION AND ANALYSIS: We used standard Cochrane methods. Our outcomes were BMI, zBMI score and serious adverse events, assessed at short- (12 weeks to < 9 months from baseline), medium- (9 months to < 15 months) and long-term (≥ 15 months) follow-up. We used GRADE to assess the certainty of the evidence for each outcome. MAIN RESULTS: This review includes 74 studies (83,407 participants); 54 studies (46,358 participants) were included in meta-analyses. Sixty studies were based in high-income countries. The main setting for intervention delivery was schools (57 studies), followed by home (nine studies), the community (five studies) and a primary care setting (three studies). Fifty-one interventions were implemented for less than nine months; the shortest was conducted over one visit and the longest over 28 months. Sixty-two studies declared non-industry funding; five were funded in part by industry. Dietary interventions versus control The evidence is very uncertain about the effects of dietary interventions on body mass index (BMI) at short-term follow-up (mean difference (MD) -0.18, 95% confidence interval (CI) -0.41 to 0.06; 3 studies, 605 participants), medium-term follow-up (MD -0.65, 95% CI -1.18 to -0.11; 3 studies, 900 participants), and standardised BMI (zBMI) at long-term follow-up (MD -0.14, 95% CI -0.38 to 0.10; 2 studies, 1089 participants); all very low-certainty evidence. Compared with control, dietary interventions may have little to no effect on BMI at long-term follow-up (MD -0.30, 95% CI -1.67 to 1.07; 1 study, 44 participants); zBMI at short-term (MD -0.06, 95% CI -0.12 to 0.01; 5 studies, 3154 participants); and zBMI at medium-term (MD 0.02, 95% CI -0.17 to 0.21; 1 study, 112 participants) follow-up; all low-certainty evidence. Dietary interventions may have little to no effect on serious adverse events (two studies, 377 participants; low-certainty evidence). Activity interventions versus control Compared with control, activity interventions do not reduce BMI at short-term follow-up (MD -0.64, 95% CI -1.86 to 0.58; 6 studies, 1780 participants; low-certainty evidence) and probably do not reduce zBMI at medium- (MD 0, 95% CI -0.04 to 0.05; 6 studies, 5335 participants) or long-term (MD -0.05, 95% CI -0.12 to 0.02; 1 study, 985 participants) follow-up; both moderate-certainty evidence. Activity interventions do not reduce zBMI at short-term follow-up (MD 0.02, 95% CI -0.01 to 0.05; 7 studies, 4718 participants; high-certainty evidence), but may reduce BMI slightly at medium-term (MD -0.32, 95% CI -0.53 to -0.11; 3 studies, 2143 participants) and long-term (MD -0.28, 95% CI -0.51 to -0.05; 1 study, 985 participants) follow-up; both low-certainty evidence. Seven studies (5428 participants; low-certainty evidence) reported data on serious adverse events: two reported injuries relating to the exercise component of the intervention and five reported no effect of intervention on reported serious adverse events. Dietary and activity interventions versus control Dietary and activity interventions, compared with control, do not reduce BMI at short-term follow-up (MD 0.03, 95% CI -0.07 to 0.13; 11 studies, 3429 participants; high-certainty evidence), and probably do not reduce BMI at medium-term (MD 0.01, 95% CI -0.09 to 0.11; 8 studies, 5612 participants; moderate-certainty evidence) or long-term (MD 0.06, 95% CI -0.04 to 0.16; 6 studies, 8736 participants; moderate-certainty evidence) follow-up. They may have little to no effect on zBMI in the short term, but the evidence is very uncertain (MD -0.09, 95% CI -0.2 to 0.02; 3 studies, 515 participants; very low-certainty evidence), and they may not reduce zBMI at medium-term (MD -0.05, 95% CI -0.1 to 0.01; 6 studies, 3511 participants; low-certainty evidence) or long-term (MD -0.02, 95% CI -0.05 to 0.01; 7 studies, 8430 participants; low-certainty evidence) follow-up. Four studies (2394 participants) reported data on serious adverse events (very low-certainty evidence): one reported an increase in weight concern in a few adolescents and three reported no effect. AUTHORS' CONCLUSIONS: The evidence demonstrates that dietary interventions may have little to no effect on obesity in adolescents. There is low-certainty evidence that activity interventions may have a small beneficial effect on BMI at medium- and long-term follow-up. Diet plus activity interventions may result in little to no difference. Importantly, this updated review also suggests that interventions to prevent obesity in this age group may result in little to no difference in serious adverse effects. Limitations of the evidence include inconsistent results across studies, lack of methodological rigour in some studies and small sample sizes. Further research is justified to investigate the effects of diet and activity interventions to prevent childhood obesity in community settings, and in young people with disabilities, since very few ongoing studies are likely to address these. Further randomised trials to address the remaining uncertainty about the effects of diet, activity interventions, or both, to prevent childhood obesity in schools (ideally with zBMI as the measured outcome) would need to have larger samples.

Research outcomes informing the selection of public health interventions and strategies to implement them: A cross-sectional survey of Australian policy-maker and practitioner preferences.

BACKGROUND: A key role of public health policy-makers and practitioners is to ensure beneficial interventions are implemented effectively enough to yield improvements in public health. The use of evidence to guide public health decision-making to achieve this is recommended. However, few studies have examined the relative value, as reported by policy-makers and practitioners, of different broad research outcomes (that is, measures of cost, acceptability, and effectiveness). To guide the conduct of research and better inform public health policy and practice, this study aimed at describing the research outcomes that Australian policy-makers and practitioners consider important for their decision-making when selecting: (a) public health interventions; (b) strategies to support their implementation; and (c) to assess the differences in research outcome preferences between policy-makers and practitioners. METHOD: An online value-weighting survey was conducted with Australian public health policy-makers and practitioners working in the field of non-communicable disease prevention. Participants were presented with a list of research outcomes and were asked to select up to five they considered most critical to their decision-making. They then allocated 100 points across these - allocating more points to outcomes perceived as more important. Outcome lists were derived from a review and consolidation of evaluation and outcome frameworks in the fields of public health knowledge translation and implementation. We used descriptive statistics to report relative preferences overall and for policy-makers and practitioners separately. RESULTS: Of the 186 participants; 90 primarily identified as policy-makers and 96 as public health prevention practitioners. Overall, research outcomes of effectiveness, equity, feasibility, and sustainability were identified as the four most important outcomes when considering either interventions or strategies to implement them. Scores were similar for most outcomes between policy-makers and practitioners. CONCLUSION: For Australian policy-makers and practitioners working in the field of non-communicable disease prevention, outcomes related to effectiveness, equity, feasibility, and sustainability appear particularly important to their decisions about the interventions they select and the strategies they employ to implement them. The findings suggest researchers should seek to meet these information needs and prioritize the inclusion of such outcomes in their research and dissemination activities. The extent to which these outcomes are critical to informing the decision of policy-makers and practitioners working in other jurisdictions or contexts warrants further investigation.

Interventions to prevent or cease electronic cigarette use in children and adolescents.

BACKGROUND: The prevalence of e-cigarette use has increased globally amongst children and adolescents in recent years. In response to the increasing prevalence and emerging evidence about the potential harms of e-cigarettes in children and adolescents, leading public health organisations have called for approaches to address increasing e-cigarette use. Whilst evaluations of approaches to reduce uptake and use regularly appear in the literature, the collective long-term benefit of these is currently unclear. OBJECTIVES: The co-primary objectives of the review were to: (1) evaluate the effectiveness of interventions to prevent e-cigarette use in children and adolescents (aged 19 years and younger) with no prior use, relative to no intervention, waitlist control, usual practice, or an alternative intervention; and (2) evaluate the effectiveness of interventions to cease e-cigarette use in children and adolescents (aged 19 years and younger) reporting current use, relative to no intervention, waitlist control, usual practice, or an alternative intervention. Secondary objectives were to: (1) examine the effect of such interventions on child and adolescent use of other tobacco products (e.g. cigarettes, cigars types, and chewing tobacco); and (2) describe the unintended adverse effects of the intervention on individuals (e.g. physical or mental health of individuals), or on organisations (e.g. intervention displacement of key curricula or learning opportunities for school students) where such interventions are being implemented. SEARCH METHODS: We searched CENTRAL, Ovid MEDLINE, Ovid Embase, Ovid PsycINFO, EBSCO CINAHL, and Clarivate Web of Science Core Collection from inception to 1 May 2023. Additionally, we searched two trial registry platforms (WHO International Clinical Trials Registry Platform; US National Institutes of Health Ongoing Trials Register ClinicalTrials.gov), Google Scholar, and the reference lists of relevant systematic reviews. We contacted corresponding authors of articles identified as ongoing studies. SELECTION CRITERIA: We included randomised controlled trials (RCTs), including cluster-RCTs, factorial RCTs, and stepped-wedge RCTs. To be eligible, the primary targets of the interventions must have been children and adolescents aged 19 years or younger. Interventions could have been conducted in any setting, including community, school, health services, or the home, and must have sought to influence children or adolescent (or both) e-cigarette use directly. Studies with a comparator of no intervention (i.e. control), waitlist control, usual practice, or an alternative intervention not targeting e-cigarette use were eligible. We included measures to assess the effectiveness of interventions to: prevent child and adolescent e-cigarette use (including measures of e-cigarette use amongst those who were never-users); and cease e-cigarette use (including measures of e-cigarette use amongst children and adolescents who were e-cigarette current-users). Measures of e-cigarette use included current-use (defined as use in the past 30 days) and ever-use (defined as any lifetime use). DATA COLLECTION AND ANALYSIS: Two review authors independently screened the titles and abstracts of references, with any discrepancies resolved through consensus. Pairs of review authors independently assessed the full-text articles for inclusion in the review. We planned for two review authors to independently extract information from the included studies and assess risk of bias using the Cochrane RoB 2 tool. We planned to conduct multiple meta-analyses using a random-effects model to align with the co-primary objectives of the review. First, we planned to pool interventions to prevent child and adolescent e-cigarette use and conduct two analyses using the outcome measures of 'ever-use' and 'current-use'. Second, we planned to pool interventions to cease child and adolescent e-cigarette use and conduct one analysis using the outcome measure of 'current-use'. Where data were unsuitable for pooling in meta-analyses, we planned to conduct a narrative synthesis using vote-counting approaches and to follow the Cochrane Handbook for Systematic Reviews of Interventions and the Synthesis Without Meta-analysis (SWiM) guidelines. MAIN RESULTS: The search of electronic databases identified 7141 citations, with a further 287 records identified from the search of trial registries and Google Scholar. Of the 110 studies (116 records) evaluated in full text, we considered 88 to be ineligible for inclusion for the following reasons: inappropriate outcome (27 studies); intervention (12 studies); study design (31 studies); and participants (18 studies). The remaining 22 studies (28 records) were identified as ongoing studies that may be eligible for inclusion in a future review update. We identified no studies with published data that were eligible for inclusion in the review. AUTHORS' CONCLUSIONS: We identified no RCTs that met the inclusion criteria for the review, and as such, there is no evidence available from RCTs to assess the potential impact of interventions targeting children and adolescent e-cigarette use, tobacco use, or any unintended adverse effects. Evidence from studies employing other trial designs (e.g. non-randomised) may exist; however, such studies were not eligible for inclusion in the review. Evidence from studies using non-randomised designs should be examined to guide actions to prevent or cease e-cigarette use. This is a living systematic review. We search for new evidence every month and update the review when we identify relevant new evidence. Please refer to the Cochrane Database of Systematic Reviews for the current status of this review.

The Effectiveness of Strategies to Improve User Engagement With Digital Health Interventions Targeting Nutrition, Physical Activity, and Overweight and Obesity: Systematic Review and Meta-Analysis.

BACKGROUND: Digital health interventions (DHIs) are effective in improving poor nutrition, physical inactivity, overweight and obesity. There is evidence suggesting that the impact of DHIs may be enhanced by improving user engagement. However, little is known about the overall effectiveness of strategies on engagement with DHIs. OBJECTIVE: This study aims to assess the overall effectiveness of strategies to improve engagement with DHIs targeting nutrition, physical activity, and overweight or obesity and explore associations between strategies and engagement outcomes. The secondary aim was to explore the impact of these strategies on health risk outcomes. METHODS: The MEDLINE, Embase, PsycINFO, CINAHL, CENTRAL, Scopus, and Academic Source Complete databases were searched up to July 24, 2023. Eligible studies were randomized controlled trials that evaluated strategies to improve engagement with DHIs and reported on outcomes related to DHI engagement (use or user experience). Strategies were classified according to behavior change techniques (BCTs) and design features (eg, supplementary emails). Multiple-variable meta-analyses of the primary outcomes (usage and user experience) were undertaken to assess the overall effectiveness of strategies. Meta-regressions were conducted to assess associations between strategies and use and user experience outcomes. Synthesis of secondary outcomes followed the "Synthesis Without Meta-Analysis" guidelines. The methodological quality and evidence was assessed using the Cochrane risk-of-bias tool, and the Grading of Recommendations Assessment, Development, and Evaluation tool respectively. RESULTS: Overall, 54 studies (across 62 publications) were included. Pooled analysis found very low-certainty evidence of a small-to-moderate positive effect of the use of strategies to improve DHI use (standardized mean difference=0.33, 95% CI 0.20-0.46; P<.001) and very low-certainty evidence of a small-to-moderate positive effect on user experience (standardized mean difference=0.29, 95% CI 0.07-0.52; P=.01). A significant positive association was found between the BCTs social support (effect size [ES]=0.40, 95% CI 0.14-0.66; P<.001) and shaping knowledge (ES=0.39, 95% CI 0.03-0.74; P=.03) and DHI use. A significant positive association was found among the BCTs social support (ES=0.70, 95% CI 0.18-1.22; P=.01), repetition and substitution (ES=0.29, 95% CI 0.05-0.53; P=.03), and natural consequences (ES=0.29, 95% CI 0.05-0.53; P=.02); the design features email (ES=0.29, 95% CI 0.05-0.53; P=.02) and SMS text messages (ES=0.34, 95% CI 0.11-0.57; P=.01); and DHI user experience. For secondary outcomes, 47% (7/15) of nutrition-related, 73% (24/33) of physical activity-related, and 41% (14/34) of overweight- and obesity-related outcomes reported an improvement in health outcomes. CONCLUSIONS: Although findings suggest that the use of strategies may improve engagement with DHIs targeting such health outcomes, the true effect is unknown because of the low quality of evidence. Future research exploring whether specific forms of social support, repetition and substitution, natural consequences, emails, and SMS text messages have a greater impact on DHI engagement is warranted. TRIAL REGISTRATION: PROSPERO CRD42018077333; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=77333.

Disseminating health research to public health policy-makers and practitioners: a survey of source, message content and delivery modality preferences.

BACKGROUND: Understanding the views of policy-makers and practitioners regarding how best to communicate research evidence is important to support research use in their decision-making. AIM: To quantify and describe public health policy-makers and practitioners' views regarding the source, content and form of messages describing public health research findings to inform their decision-making. We also sought to examine differences in preferences between public health policy-makers and practitioners. METHODS: A cross sectional, value-weighting survey of policy-makers and practitioners was conducted. Participants were asked to allocate a proportion of 100 points across different (i) sources of research evidence, (ii) message content and (iii) the form in which evidence is presented. Points were allocated based on their rating of influence, usefulness and preference when making decisions about health policy or practice. RESULTS: A total of 186 survey responses were received from 90 policy-makers and 96 practitioners. Researchers and government department agencies were the most influential source of research evidence based on mean allocation of points, followed by knowledge brokers, professional peers and associations. Mean point allocation for perceived usefulness of message content was highest for simple summary of key findings and implications, and then evidence-based recommendations and data and statistical summaries. Finally, based on mean scores, policy-makers and practitioners preferred to receive research evidence in the form of peer-reviewed publications, reports, evidence briefs and plain language summaries. There were few differences in scores between policy-makers and practitioners across source, message content or form assessments or those with experience in different behavioural areas. CONCLUSIONS: The findings should provide a basis for the future development and optimization of dissemination strategies to this important stakeholder group.

Dissemination of public health research evidence and guidelines to Australian Early Childhood Education and Care staff: Views about source, content and format.

ISSUE ADDRESSED: Effective dissemination of public health research and evidence-based guidelines to Early Childhood Education and Care (ECEC) staff is critical for promoting research transfer and uptake and achieving positive outcomes for children. METHODS: A cross-sectional study was conducted during August 2021 to March 2022, with a sub-sample of Australian ECEC services participating in a larger survey completed online and via Computer-Assisted Telephone Interview. Survey items assessed: influential source for receiving research, type of content that would influence decisions to adopt research and preferred formats for receiving research. RESULTS: Overall, 993 service managers or staff from 1984 (50.0%) invited and eligible services completed the larger survey. Of these, 463 randomly allocated services (46.7%) had staff complete the dissemination items. The Australian Children's Education and Care Quality Authority, ECEC agencies and Government Departments were most frequently selected as influential sources of research evidence. Staff were most interested in content providing evidence-based recommendations for future actions and descriptions of health issues addressed. Workshops or conferences and webinars were the preferred format for receiving research. CONCLUSIONS: Findings highlight the importance of tailoring dissemination strategies to meet ECEC staff needs and engaging influential sources to disseminate research evidence. SO WHAT?: Understanding dissemination preferences of ECEC staff is crucial for supporting uptake of evidence-based health promotion in this setting. By developing tailored strategies based on ECEC preferences, research transfer and evidence-based decision making can be supported more effectively. These findings contribute to bridging the evidence-practice gap and improving the quality of care and health outcomes for children in ECEC settings.

Strategies for enhancing the implementation of school-based policies or practices targeting diet, physical activity, obesity, tobacco or alcohol use.

BACKGROUND: Several school-based interventions are effective in improving child diet and physical activity, and preventing excessive weight gain, and tobacco or harmful alcohol use. However, schools are frequently unsuccessful in implementing such evidence-based interventions. OBJECTIVES: 1. To evaluate the benefits and harms of strategies aiming to improve school implementation of interventions to address student diet, physical activity, tobacco or alcohol use, and obesity. 2. To evaluate the benefits and harms of strategies to improve intervention implementation on measures of student diet, physical activity, obesity, tobacco use or alcohol use; describe their cost or cost-effectiveness; and any harms of strategies on schools, school staff or students. SEARCH METHODS: We used standard, extensive Cochrane search methods. The latest search was between 1 September 2016 and 30 April 2021 to identify any relevant trials published since the last published review. SELECTION CRITERIA: We defined 'Implementation' as the use of strategies to adopt and integrate evidence-based health interventions and to change practice patterns within specific settings. We included any trial (randomised controlled trial (RCT) or non-randomised controlled trial (non-RCT)) conducted at any scale, with a parallel control group that compared a strategy to implement policies or practices to address diet, physical activity, overweight or obesity, tobacco or alcohol use by students to 'no intervention', 'usual' practice or a different implementation strategy. DATA COLLECTION AND ANALYSIS: We used standard Cochrane methods. Given the large number of outcomes reported, we selected and included the effects of a single outcome measure for each trial for the primary (implementation) and secondary (student health behaviour and obesity) outcomes using a decision hierarchy. Where possible, we calculated standardised mean differences (SMDs) to account for variable outcome measures with 95% confidence intervals (CI). For RCTs, we conducted meta-analyses of primary and secondary outcomes using a random-effects model, or in instances where there were between two and five studies, a fixed-effect model. The synthesis of the effects for non-randomised studies followed the 'Synthesis without meta-analysis' (SWiM) guidelines. MAIN RESULTS: We included an additional 11 trials in this update bringing the total number of included studies in the review to 38. Of these, 22 were conducted in the USA. Twenty-six studies used RCT designs. Seventeen trials tested strategies to implement healthy eating, 12 physical activity and six a combination of risk factors. Just one trial sought to increase the implementation of interventions to delay initiation or reduce the consumption of alcohol. All trials used multiple implementation strategies, the most common being educational materials, educational outreach and educational meetings. The overall certainty of evidence was low and ranged from very low to moderate for secondary review outcomes. Pooled analyses of RCTs found, relative to a control, the use of implementation strategies may result in a large increase in the implementation of interventions in schools (SMD 1.04, 95% CI 0.74 to 1.34; 22 RCTs, 1917 participants; low-certainty evidence). For secondary outcomes we found, relative to control, the use of implementation strategies to support intervention implementation may result in a slight improvement on measures of student diet (SMD 0.08, 95% CI 0.02 to 0.15; 11 RCTs, 16,649 participants; low-certainty evidence) and physical activity (SMD 0.09, 95% CI -0.02 to 0.19; 9 RCTs, 16,389 participants; low-certainty evidence). The effects on obesity probably suggest little to no difference (SMD -0.02, 95% CI -0.05 to 0.02; 8 RCTs, 18,618 participants; moderate-certainty evidence). The effects on tobacco use are very uncertain (SMD -0.03, 95% CIs -0.23 to 0.18; 3 RCTs, 3635 participants; very low-certainty evidence). One RCT assessed measures of student alcohol use and found strategies to support implementation may result in a slight increase in use (odds ratio 1.10, 95% CI 0.77 to 1.56; P = 0.60; 2105 participants). Few trials reported the economic evaluations of implementation strategies, the methods of which were heterogeneous and evidence graded as very uncertain. A lack of consistent terminology describing implementation strategies was an important limitation of the review. AUTHORS' CONCLUSIONS: The use of implementation strategies may result in large increases in implementation of interventions, and slight improvements in measures of student diet, and physical activity. Further research is required to assess the impact of implementation strategies on such behavioural- and obesity-related outcomes, including on measures of alcohol use, where the findings of one trial suggest it may slightly increase student risk. Given the low certainty of the available evidence for most measures further research is required to guide efforts to facilitate the translation of evidence into practice in this setting.

The benefits of data sharing and ensuring open sources of systematic review data.

AIMS: The benefits of increasing public access to data from clinical trials are widely accepted. Such benefits extend to the sharing of data from high-quality systematic reviews, given the time and cost involved with undertaking reviews. We describe the application of open sources of review data, outline potential challenges and highlight efforts made to address these challenges, with the intent of encouraging publishers, funders and authors to consider sharing review data more broadly. RESULTS: We describe the application of systematic review data in: (i) advancing understanding of clinical trials and systematic review methods, (ii) repurposing of data to answer public health policy and practice relevant questions, (iii) identification of research gaps and (iv) accelerating the conduct of rapid reviews to inform decision making. While access, logistical, motivational and legal challenges exist, there has been progress made by systematic review, academic and funding agencies to incentivise data sharing and create infrastructure to support greater access to systematic review data. CONCLUSION: There is opportunity to maximize the benefits of research investment in undertaking systematic reviews by ensuring open sources of systematic review data. Efforts to create such systems should draw on learnings and principles outlined for sharing clinical trial data.

Increased use of knowledge translation strategies is associated with greater research impact on public health policy and practice: an analysis of trials of nutrition, physical activity, sexual health, tobacco, alcohol and substance use interventions.

BACKGROUND: Greater use of knowledge translation (KT) strategies is recommended to improve the research impact of public health trials. The purpose of this study was to describe (1) the research impact of setting-based public health intervention trials on public health policy and practice; (2) the association between characteristics of trials and their research impact on public health policy and practice; and (3) the association between the use of KT strategies and research impacts on public health policy and practice. METHODS: We conducted a survey of authors of intervention trials targeting nutrition, physical activity, sexual health, tobacco, alcohol or substance use. We assessed the use of KT strategies aligned to domains of the Knowledge-To-Action Framework. We defined "research impact" on health policy and practice as any one or more of the following: citation in policy documents or announcements, government reports, training materials, guidelines, textbooks or court rulings; or endorsement by a (non)governmental organization; use in policy or practice decision-making; or use in the development of a commercial resource or service. RESULTS: Of the included trials, the authors reported that 65% had one or more research impacts. The most frequently reported research impact was citation in a policy document or announcement (46%). There were no significant associations between the effectiveness of the intervention, trial risk of bias, setting or health risk and trial impact. However, for every one unit increase in the total KT score (range 0-8), reflecting greater total KT activity, the odds of a health policy or practice research impact increased by approximately 30% (OR = 1.30, 95% CI: 1.02, 1.66; p = 0.031). Post hoc examination of KT domain scores suggests that KT actions focused on providing tailored support to facilitate program implementation and greater use of research products and tools to disseminate findings to end-users may be most influential in achieving impact. CONCLUSIONS: Trials of public health interventions frequently have public health impacts, and the use of more comprehensive KT strategies may facilitate greater research impact.

Interventions Targeting Smoking Cessation for Patients With Chronic Pain: An Evidence Synthesis.

INTRODUCTION: Smoking is a risk factor for chronic pain conditions. Epidemiological evidence suggests that smoking cessation may be an important treatment target in people with chronic pain. The aim of this study was to examine the effectiveness of smoking cessation interventions in people with chronic pain. METHODS: We systematically searched for clinical trials investigating the effectiveness of smoking cessation interventions for people with chronic pain, compared with any control comparator. Primary outcomes were pain and physical function. Secondary outcomes were smoking status, quality of life, psychological and cognitive function, and adverse events. We assessed risk of bias using the Cochrane Risk of Bias criteria and the quality of evidence with GRADE. RESULTS: Searches retrieved 3845 records and identified two trials for inclusion (total n = 99 participants). There was low-quality evidence of no effect of smoking cessation programs on pain and very low-quality evidence of no effect on function at short-term follow-up. There was conflicting evidence on the effect of smoking cessation interventions for changing the smoking status and number of cigarettes consumed per day. There was no effect on depression and anxiety. CONCLUSION: Current evidence does not indicate clinically important effects of smoking cessation interventions in people with chronic pain. There is a need for high-quality trials in this area. IMPLICATIONS: Our review highlights an important evidence gap. We found only two studies investigating smoking cessation programs for chronic pain conditions providing very low- to low-quality evidence.

Interventions for increasing fruit and vegetable consumption in children aged five years and under.

BACKGROUND: Insufficient consumption of fruits and vegetables in childhood increases the risk of future non-communicable diseases, including cardiovascular disease. Testing the effects of interventions to increase consumption of fruit and vegetables, including those focused on specific child-feeding strategies or broader multicomponent interventions targeting the home or childcare environment is required to assess the potential to reduce this disease burden. OBJECTIVES: To assess the effectiveness, cost effectiveness and associated adverse events of interventions designed to increase the consumption of fruit, vegetables or both amongst children aged five years and under. SEARCH METHODS: We searched CENTRAL, MEDLINE, Embase and two clinical trials registries to identify eligible trials on 25 January 2020. We searched Proquest Dissertations and Theses in November 2019. We reviewed reference lists of included trials and handsearched three international nutrition journals. We contacted authors of included trials to identify further potentially relevant trials. SELECTION CRITERIA: We included randomised controlled trials, including cluster-randomised controlled trials and cross-over trials, of any intervention primarily targeting consumption of fruit, vegetables or both among children aged five years and under, and incorporating a dietary or biochemical assessment of fruit or vegetable consumption. Two review authors independently screened titles and abstracts of identified papers; a third review author resolved disagreements. DATA COLLECTION AND ANALYSIS: Two review authors independently extracted data and assessed the risks of bias of included trials; a third review author resolved disagreements. Due to unexplained heterogeneity, we used random-effects models in meta-analyses for the primary review outcomes where we identified sufficient trials. We calculated standardised mean differences (SMDs) to account for the heterogeneity of fruit and vegetable consumption measures. We conducted assessments of risks of bias and evaluated the quality of evidence (GRADE approach) using Cochrane procedures. MAIN RESULTS: We included 80 trials with 218 trial arms and 12,965 participants. Fifty trials examined the impact of child-feeding practices (e.g. repeated food exposure) in increasing child vegetable intake. Fifteen trials examined the impact of parent nutrition education only in increasing child fruit and vegetable intake. Fourteen trials examined the impact of multicomponent interventions (e.g. parent nutrition education and preschool policy changes) in increasing child fruit and vegetable intake. Two trials examined the effect of a nutrition education intervention delivered to children in increasing child fruit and vegetable intake. One trial examined the impact of a child-focused mindfulness intervention in increasing vegetable intake. We judged 23 of the 80 included trials as free from high risks of bias across all domains. Performance, detection and attrition bias were the most common domains judged at high risk of bias for the remaining trials. There is low-quality evidence that child-feeding practices versus no intervention may have a small positive effect on child vegetable consumption, equivalent to an increase of 5.30 grams as-desired consumption of vegetables (SMD 0.50, 95% CI 0.29 to 0.71; 19 trials, 2140 participants; mean post-intervention follow-up = 8.3 weeks). Multicomponent interventions versus no intervention has a small effect on child consumption of fruit and vegetables (SMD 0.32, 95% CI 0.09 to 0.55; 9 trials, 2961 participants; moderate-quality evidence; mean post-intervention follow-up = 5.4 weeks), equivalent to an increase of 0.34 cups of fruit and vegetables a day. It is uncertain whether there are any short-term differences in child consumption of fruit and vegetables in meta-analyses of trials examining parent nutrition education versus no intervention (SMD 0.13, 95% CI -0.02 to 0.28; 11 trials, 3050 participants; very low-quality evidence; mean post-intervention follow-up = 13.2 weeks). We were unable to pool child nutrition education interventions in meta-analysis; both trials reported a positive intervention effect on child consumption of fruit and vegetables (low-quality evidence). Very few trials reported long-term effectiveness (6 trials), cost effectiveness (1 trial) or unintended adverse consequences of interventions (2 trials), limiting our ability to assess these outcomes. Trials reported receiving governmental or charitable funds, except for four trials reporting industry funding. AUTHORS' CONCLUSIONS: Despite identifying 80 eligible trials of various intervention approaches, the evidence for how to increase children's fruit and vegetable consumption remains limited in terms of quality of evidence and magnitude of effect. Of the types of interventions identified, there was moderate-quality evidence that multicomponent interventions probably lead to, and low-quality evidence that child-feeding practice may lead to, only small increases in fruit and vegetable consumption in children aged five years and under. It is uncertain whether parent nutrition education or child nutrition education interventions alone are effective in increasing fruit and vegetable consumption in children aged five years and under. Our confidence in effect estimates for all intervention approaches, with the exception of multicomponent interventions, is limited on the basis of the very low to low-quality evidence. Long-term follow-up of at least 12 months is required and future research should adopt more rigorous methods to advance the field. This is a living systematic review. Living systematic reviews offer a new approach to review updating, in which the review is continually updated, incorporating relevant new evidence as it becomes available. Please refer to the Cochrane Database of Systematic Reviews for the current status of this review.

Strategies to improve the implementation of healthy eating, physical activity and obesity prevention policies, practices or programmes within childcare services.

BACKGROUND: Despite the existence of effective interventions and best-practice guideline recommendations for childcare services to implement evidence-based policies, practices and programmes to promote child healthy eating, physical activity and prevent unhealthy weight gain, many services fail to do so. OBJECTIVES: The primary aim of the review was to examine the effectiveness of strategies aimed at improving the implementation of policies, practices or programmes by childcare services that promote child healthy eating, physical activity and/or obesity prevention. The secondary aims of the review were to: 1. Examine the cost or cost-effectiveness of such strategies; 2. Examine any adverse effects of such strategies on childcare services, service staff or children; 3. Examine the effect of such strategies on child diet, physical activity or weight status. 4. Describe the acceptability, adoption, penetration, sustainability and appropriateness of such implementation strategies. SEARCH METHODS: We searched the following electronic databases on February 22 2019: Cochrane Central Register of Controlled trials (CENTRAL), MEDLINE, MEDLINE In Process, Embase, PsycINFO, ERIC, CINAHL and SCOPUS for relevant studies. We searched reference lists of included studies, handsearched two international implementation science journals, the World Health Organization International Clinical Trials Registry Platform (www.who.int/ictrp/) and ClinicalTrials.gov (www.clinicaltrials.gov). SELECTION CRITERIA: We included any study (randomised or nonrandomised) with a parallel control group that compared any strategy to improve the implementation of a healthy eating, physical activity or obesity prevention policy, practice or programme by staff of centre-based childcare services to no intervention, 'usual' practice or an alternative strategy. Centre-based childcare services included preschools, nurseries, long daycare services and kindergartens catering for children prior to compulsory schooling (typically up to the age of five to six years). DATA COLLECTION AND ANALYSIS: Two review authors independently screened study titles and abstracts, extracted study data and assessed risk of bias; we resolved discrepancies via consensus. We performed meta-analysis using a random-effects model where studies with suitable data and homogeneity were identified; otherwise, findings were described narratively. MAIN RESULTS: Twenty-one studies, including 16 randomised and five nonrandomised, were included in the review. The studies sought to improve the implementation of policies, practices or programmes targeting healthy eating (six studies), physical activity (three studies) or both healthy eating and physical activity (12 studies). Studies were conducted in the United States (n = 12), Australia (n = 8) and Ireland (n = 1). Collectively, the 21 studies included a total of 1945 childcare services examining a range of implementation strategies including educational materials, educational meetings, audit and feedback, opinion leaders, small incentives or grants, educational outreach visits or academic detailing, reminders and tailored interventions. Most studies (n = 19) examined implementation strategies versus usual practice or minimal support control, and two compared alternative implementation strategies. For implementation outcomes, six studies (one RCT) were judged to be at high risk of bias overall. The review findings suggest that implementation strategies probably improve the implementation of policies, practices or programmes that promote child healthy eating, physical activity and/or obesity prevention in childcare services. Of the 19 studies that compared a strategy to usual practice or minimal support control, 11 studies (nine RCTs) used score-based measures of implementation (e.g. childcare service nutrition environment score). Nine of these studies were included in pooled analysis, which found an improvement in implementation outcomes (SMD 0.49; 95% CI 0.19 to 0.79; participants = 495; moderate-certainty evidence). Ten studies (seven RCTs) used dichotomous measures of implementation (e.g. proportion of childcare services implementing a policy or specific practice), with seven of these included in pooled analysis (OR 1.83; 95% CI 0.81 to 4.11; participants = 391; low-certainty evidence). Findings suggest that such interventions probably lead to little or no difference in child physical activity (four RCTs; moderate-certainty evidence) or weight status (three RCTs; moderate-certainty evidence), and may lead to little or no difference in child diet (two RCTs; low-certainty evidence). None of the studies reported the cost or cost-effectiveness of the intervention. Three studies assessed the adverse effects of the intervention on childcare service staff, children and parents, with all studies suggesting they have little to no difference in adverse effects (e.g. child injury) between groups (three RCTs; low-certainty evidence). Inconsistent quality of the evidence was identified across review outcomes and study designs, ranging from very low to moderate. The primary limitation of the review was the lack of conventional terminology in implementation science, which may have resulted in potentially relevant studies failing to be identified based on the search terms used. AUTHORS' CONCLUSIONS: Current research suggests that implementation strategies probably improve the implementation of policies, practices or programmes by childcare services, and may have little or no effect on measures of adverse effects. However such strategies appear to have little to no impact on measures of child diet, physical activity or weight status.

Effectiveness of embedding a specialist preventive care clinician in a community mental health service in increasing preventive care provision: A randomised controlled trial.

OBJECTIVE: Clinical practice guidelines recommend that community mental health services provide preventive care for clients' chronic disease risk behaviours; however, such care is often not routinely provided. This study aimed to assess the effectiveness of offering clients an additional consultation with a specialist clinician embedded within a community mental health service, in increasing client-reported receipt of, and satisfaction with, preventive care. METHOD: A randomised controlled trial was undertaken in one Australian community mental health service. Participants (N = 811) were randomised to receive usual care (preventive care in routine consultations; n = 405) or usual care plus the offer of an additional consultation with a specialist preventive care clinician (n = 406). Blinded interviewers assessed at baseline and 1-month follow-up the client-reported receipt of preventive care (assessment, advice and referral) for four key risk behaviours individually (smoking, poor nutrition, alcohol overconsumption and physical inactivity) and all applicable risks combined, acceptance of referrals and satisfaction with preventive care received. RESULTS: Analyses indicated significantly greater increases in 12 of the 18 preventive care delivery outcomes in the intervention compared to the usual care condition from baseline to follow-up, including assessment for all risks combined (risk ratio = 4.00; 95% confidence interval = [1.57, 10.22]), advice for all applicable risks combined (risk ratio = 2.40; 95% confidence interval = [1.89, 6.47]) and offer of referral to applicable telephone services combined (risk ratio = 20.13; 95% confidence interval = [2.56, 158.04]). For each component of care, there was a significant intervention effect for at least one of the individual risk behaviours. Participants reported high levels of satisfaction with preventive care received, ranging from 77% (assessment) to 87% (referral), with no significant differences between conditions. CONCLUSION: The intervention had a significant effect on the provision of the majority of recommended elements of preventive care. Further research is needed to maximise its impact, including identifying strategies to increase client uptake.

Adaptation of public health initiatives: expert views on current guidance and opportunities to advance their application and benefit.

While there is some guidance to support the adaptation of evidence-based public health interventions, little is known about adaptation in practice and how to best support public health practitioners in its operationalization. This qualitative study was undertaken with researchers, methodologists, policy makers and practitioners representing public health expert organizations and universities internationally to explore their views on available adaptation frameworks, elicit potential improvements to such guidance, and identify opportunities to improve implementation of public health initiatives. Participants attended a face to face workshop in Newcastle, Australia in October 2018 where World Café and focus group discussions using Appreciative Inquiry were undertaken. A number of limitations with current guidance were reported, including a lack of detail on 'how' to adapt, limited information on adaptation of implementation strategies and a number of structural issues related to the wording and ordering of elements within frameworks. A number of opportunities to advance the field was identified. Finally, a list of overarching principles that could be applied together with existing frameworks was generated and suggested to provide a practical way of supporting adaptation decisions in practice.

An economic evaluation of a specialist preventive care clinician in a community mental health service: a randomised controlled trial.

BACKGROUND: Clinical practice guidelines and policies direct community mental health services to provide preventive care to address chronic disease risks, however, such care is infrequently provided in routine consultations. An alternative model of care is to appoint a clinician to the dedicated role of offering and providing preventive care in an additional consultation: the 'specialist clinician' model. Economic evaluations of models of care are needed to determine the cost of adhering to guidelines and policies, and to inform pragmatic service delivery decisions. This study is an economic evaluation of the specialist clinician model; designed to achieve policy concordant preventive care delivery. METHODS: A retrospective analysis of the incremental costs, cost-effectiveness, and budget impact of a 'specialist preventive care clinician' (an occupational therapist) was conducted in a randomised controlled trial, where participants were randomised to receive usual care; or usual care plus the offer of an additional preventive care consultation with the specialist clinician. The study outcome was client acceptance of referrals to two free telephone-based chronic disease prevention services. This is a key care delivery outcome mandated by the local health district policy of the service. The base case analysis assumed the mental health service cost perspective. A budget impact analysis determined the annual budget required to implement the model of care for all clients of the community mental health service over 5 years. RESULTS: There was a significantly greater increase from baseline to follow-up in the proportion of intervention participants accepting referrals to both telephone services, compared to usual care. The incremental cost-effectiveness ratio was $347 per additional acceptance of a referral (CI: $263-$494). The annual budget required to implement the model of care for all prospective clients was projected to be $711,446 over 5-years; resulting in 2616 accepted referrals. CONCLUSIONS: The evaluation provides key information regarding the costs for the mental health service to adhere to policy targets, indicating the model of care involved a low per client cost whilst increasing key preventive care delivery outcomes. Additional modelling is required to further explore its economic benefits. TRIAL REGISTRATION: ACTRN12616001519448. Registered 3 November 2016, https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=371709.

Effectiveness of Technology-Enabled Knowledge Translation Strategies in Improving the Use of Research in Public Health: Systematic Review.

BACKGROUND: Knowledge translation (KT) aims to facilitate the use of research evidence in decision making. Changes in technology have provided considerable opportunities for KT strategies to improve access and use of evidence in decision making by public health policy makers and practitioners. Despite this opportunity, there have been no reviews that have assessed the effects of digital technology-enabled KT (TEKT) in the field of public health. OBJECTIVE: This study aims to examine the effectiveness of digital TEKT strategies in (1) improving the capacity for evidence-based decision making by public health policy makers and practitioners, (2) changing public health policy or practice, and (3) changes in individual or population health outcomes. METHODS: A search strategy was developed to identify randomized trials assessing the effectiveness of digital TEKT strategies in public health. Any primary research study with a randomized trial design was eligible. Searches for eligible studies were undertaken in multiple electronic bibliographic databases (Medical Literature Analysis and Retrieval System Online [MEDLINE], Excerpta Medica dataBASE [EMBASE], PsycINFO, Cumulative Index to Nursing and Allied Health Literature [CINAHL], and Scopus) and the reference lists of included studies. A hand search of 2 journals (Implementation Science and Journal of Medical Internet Research) and a gray literature search were also conducted. Pairs of independent review authors screened studies, assessed the risk of bias, and extracted data from relevant studies. RESULTS: Of the 6819 citations screened, 8 eligible randomized trials were included in the review. The studies examined the impact of digital TEKT strategies on health professionals, including nurses, child care health consultants, physiotherapists, primary health care workers, and public health practitioners. Overall, 5 of the interventions were web-training programs. The remaining 3 interventions included simulation games, access to digital resource materials and the use of tailored messaging, and a web-based registry. The findings suggest that digital TEKT interventions may be effective in improving the knowledge of public health professionals, relative to control, and may be as effective as a face-to-face KT approach. The effectiveness of digital TEKT strategies relative to a control or other digital KT interventions on measures of health professional self-efficacy to use evidence to enhance practice behavior or behavioral intention outcomes was mixed. The evidence regarding the effects on changes to health policy or practice following exposure to digital TEKT was mixed. No trials assessed the effects on individual or population-level health outcomes. CONCLUSIONS: This review is the first to synthesize the effectiveness of digital TEKT interventions in a public health setting. Despite its potential, relatively few trials have been undertaken to investigate the impacts of digital TEKT interventions. The findings suggest that although a digital TEKT intervention may improve knowledge, the effects of such interventions on other outcomes are equivocal.

The effectiveness of lunchbox interventions on improving the foods and beverages packed and consumed by children at centre-based care or school: a systematic review and meta-analysis.

OBJECTIVE: To assess the effectiveness of lunchbox interventions aiming to improve the foods and beverages packed and consumed by children at centre-based care or school; and subsequent impact on children's adiposity. METHODS: Systematic search of nine databases for controlled trials published in English between 1995-January 2017. Where appropriate, data were pooled in a random effects meta-analysis. RESULTS: Of the 1601 articles identified, ten studies (centre-based care n = 4, school n = 6) were included of which eight were RCTs. The impact of interventions on the packing of discretionary foods, sugar-sweetened drinks and other core foods was inconsistent. Meta-analysis of four RCTs trials found a moderate increase in provision of vegetables (SMD = 0.40 95% CI 0.16 to 0.64, p = 0.001, I2 = 82%; equivalent to a mean difference of 0.28 serves) but not fruit. Four studies reported impact on children's dietary intake, one reported no significant effect on consumption of discretionary foods, one reported improvements in the consumption of sugar-sweetened drinks and water, and two reported improvements in consumption of vegetables and fruit. Two studies, that were broader obesity prevention interventions, reported no significant impact on adiposity. CONCLUSIONS: There is some evidence that lunchbox interventions are effective in improving the packing of vegetables in children's lunchboxes, however more robust research is required to determine the impact on children's dietary intake and adiposity. TRIAL REGISTRATION: PROSPERO 2016: CRD42016035646 .

Identifying opportunities to develop the science of implementation for community-based non-communicable disease prevention: A review of implementation trials.

Implementation of interventions in community organisations such as schools, childcare centres, and sporting clubs are recommended to target a range of modifiable risks of non-communicable diseases. Poor implementation, however, is common and has contributed to the failure of non-communicable disease interventions globally. This study aimed to characterise experimental research regarding strategies to improve implementation of chronic disease prevention programs in community settings. The review used data collected in three comprehensive systematic reviews undertaken between August 2015 and July 2017. Randomised controlled trials, including cluster design, and non-randomised trials with a parallel control group were included. The data were extracted to describe trial characteristics, implementation strategies employed, implementation outcomes and study quality. Of the 40 implementation trials included in the study, unhealthy diet was the most common risk factor targeted (n = 20). The most commonly reported implementation strategies were educational meetings (n = 38, 95%), educational materials (n = 36, 90%) and educational outreach visits (n = 29, 73%). Few trials were conducted 'at-scale' (n = 8, 20%) or reported adverse effects (n = 5, 13%). The reporting of implementation related outcomes; intervention adoption (n = 13, 33%); appropriateness (n = 11, 28%); acceptability (n = 8, 20%); feasibility (n = 8, 20%); cost (n = 3, 8%); and sustainability (n = 2, 5%); was limited. For the majority of trials, risk of bias was high for blinding of study personnel/participants and outcome assessors. Testing of strategies to improve implementation of non-communicable disease prevention strategies in community settings, delivered 'at-scale', utilising implementation frameworks, including a comprehensive range of implementation outcomes should be priority areas for future research in implementation science.