Factors associated with child and adolescent electronic nicotine and non-nicotine delivery systems use: A scoping review.

OBJECTIVES: To identify, characterise and broadly synthesise factors associated with child and adolescent electronic nicotine delivery systems (ENDS) and/or electronic non-nicotine delivery systems (ENNDS) ever-use and/or current use. METHODS: Four electronic databases were searched from inception to 3rd June 2022. Non-experimental studies that provided quantitative factors associated with adolescent and/or child ENDS or ENNDS ever-use and/or current use were included. Factors associated with ever-use (any lifetime use) and/or current use (use in past 30 days) were included. All screening and data extraction was conducted independently by paired review authors. Frequencies for country, study design, sample size, measure of ENDS/ENNDS use and factors examined were calculated. Factors were categorised according to the Theory of Triadic Influence domains and sub-domains. RESULTS: The search of electronic databases identified 4756 records, 240 of which were included. The majority of studies examined factors categorised within the Biology and Personality domain of the Theory of Triadic Influence (89.2%; 95%CI 84.6, 82.5), followed by the Social Context (50.8%; 95%CI 44.5, 57.2) and Broader Environment domains (30.4%; 95%CI 24.6, 36.3). The proportion of factors significantly associated with ENDS/ENNDS use was >75% for the Behavioural (78.0%; factors included use of tobacco, other drugs and alcohol), Peer Attitudes and Behaviours (80.0%; factors included peer use of ENDS/ENNDS and tobacco), and Legislation/Policy sub-domains (78.6%; factors included accessibility and advertising). CONCLUSIONS: The evidence base on factors associated with ENDS/ENNDS use in children and adolescents is rapidly developing, predominately by research concentrated in high income regions and focused on behavioural- and personality-related factors.

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.

Healthy eating interventions delivered in early childhood education and care settings for improving the diet of children aged six months to six years.

BACKGROUND: Dietary intake during early childhood can have implications on child health and developmental trajectories. Early childhood education and care (ECEC) services are recommended settings to deliver healthy eating interventions as they provide access to many children during this important period. Healthy eating interventions delivered in ECEC settings can include strategies targeting the curriculum (e.g. nutrition education), ethos and environment (e.g. menu modification) and partnerships (e.g. workshops for families). Despite guidelines supporting the delivery of healthy eating interventions in this setting, little is known about their impact on child health. OBJECTIVES: To assess the effectiveness of healthy eating interventions delivered in ECEC settings for improving dietary intake in children aged six months to six years, relative to usual care, no intervention or an alternative, non-dietary intervention. Secondary objectives were to assess the impact of ECEC-based healthy eating interventions on physical outcomes (e.g. child body mass index (BMI), weight, waist circumference), language and cognitive outcomes, social/emotional and quality-of-life outcomes. We also report on cost and adverse consequences of ECEC-based healthy eating interventions. SEARCH METHODS: We searched eight electronic databases including CENTRAL, MEDLINE, Embase, CINAHL, PsycINFO, ERIC, Scopus and SportDiscus on 24 February 2022. We searched reference lists of included studies, reference lists of relevant systematic reviews, the World Health Organization International Clinical Trials Registry Platform, ClinicalTrials.gov and Google Scholar, and contacted authors of relevant papers. SELECTION CRITERIA: We included randomised controlled trials (RCTs), including cluster-RCTs, stepped-wedge RCTs, factorial RCTs, multiple baseline RCTs and randomised cross-over trials, of healthy eating interventions targeting children aged six months to six years that were conducted within the ECEC setting. ECEC settings included preschools, nurseries, kindergartens, long day care and family day care. To be included, studies had to include at least one intervention component targeting child diet within the ECEC setting and measure child dietary or physical outcomes, or both. DATA COLLECTION AND ANALYSIS: Pairs of review authors independently screened titles and abstracts and extracted study data. We assessed risk of bias for all studies against 12 criteria within RoB 1, which allows for consideration of how selection, performance, attrition, publication and reporting biases impact outcomes. We resolved discrepancies via consensus or by consulting a third review author. Where we identified studies with suitable data and homogeneity, we performed meta-analyses using a random-effects model; otherwise, we described findings using vote-counting approaches and via harvest plots. For measures with similar metrics, we calculated mean differences (MDs) for continuous outcomes and risk ratios (RRs) for dichotomous outcomes. We calculated standardised mean differences (SMDs) for primary and secondary outcomes where studies used different measures. We applied GRADE to assess certainty of evidence for dietary, cost and adverse outcomes.  MAIN RESULTS: We included 52 studies that investigated 58 interventions (described across 96 articles). All studies were cluster-RCTs. Twenty-nine studies were large (≥ 400 participants) and 23 were small (< 400 participants). Of the 58 interventions, 43 targeted curriculum, 56 targeted ethos and environment, and 50 targeted partnerships. Thirty-eight interventions incorporated all three components. For the primary outcomes (dietary outcomes), we assessed 19 studies as overall high risk of bias, with performance and detection bias being most commonly judged as high risk of bias. ECEC-based healthy eating interventions versus usual practice or no intervention may have a positive effect on child diet quality (SMD 0.34, 95% confidence interval (CI) 0.04 to 0.65; P = 0.03, I2 = 91%; 6 studies, 1973 children) but the evidence is very uncertain. There is moderate-certainty evidence that ECEC-based healthy eating interventions likely increase children's consumption of fruit (SMD 0.11, 95% CI 0.04 to 0.18; P < 0.01, I2 = 0%; 11 studies, 2901 children). The evidence is very uncertain about the effect of ECEC-based healthy eating interventions on children's consumption of vegetables (SMD 0.12, 95% CI -0.01 to 0.25; P =0.08, I2 = 70%; 13 studies, 3335 children). There is moderate-certainty evidence that ECEC-based healthy eating interventions likely result in little to no difference in children's consumption of non-core (i.e. less healthy/discretionary) foods (SMD -0.05, 95% CI -0.17 to 0.08; P = 0.48, I2 = 16%; 7 studies, 1369 children) or consumption of sugar-sweetened beverages (SMD -0.10, 95% CI -0.34 to 0.14; P = 0.41, I2 = 45%; 3 studies, 522 children). Thirty-six studies measured BMI, BMI z-score, weight, overweight and obesity, or waist circumference, or a combination of some or all of these. ECEC-based healthy eating interventions may result in little to no difference in child BMI (MD -0.08, 95% CI -0.23 to 0.07; P = 0.30, I2 = 65%; 15 studies, 3932 children) or in child BMI z-score (MD -0.03, 95% CI -0.09 to 0.03; P = 0.36, I2 = 0%; 17 studies; 4766 children). ECEC-based healthy eating interventions may decrease child weight (MD -0.23, 95% CI -0.49 to 0.03; P = 0.09, I2 = 0%; 9 studies, 2071 children) and risk of overweight and obesity (RR 0.81, 95% CI 0.65 to 1.01; P = 0.07, I2 = 0%; 5 studies, 1070 children). ECEC-based healthy eating interventions may be cost-effective but the evidence is very uncertain (6 studies). ECEC-based healthy eating interventions may have little to no effect on adverse consequences but the evidence is very uncertain (3 studies). Few studies measured language and cognitive skills (n = 2), social/emotional outcomes (n = 2) and quality of life (n = 3). AUTHORS' CONCLUSIONS: ECEC-based healthy eating interventions may improve child diet quality slightly, but the evidence is very uncertain, and likely increase child fruit consumption slightly. There is uncertainty about the effect of ECEC-based healthy eating interventions on vegetable consumption. ECEC-based healthy eating interventions may result in little to no difference in child consumption of non-core foods and sugar-sweetened beverages. Healthy eating interventions could have favourable effects on child weight and risk of overweight and obesity, although there was little to no difference in BMI and BMI z-scores. Future studies exploring the impact of specific intervention components, and describing cost-effectiveness and adverse outcomes are needed to better understand how to maximise the impact of ECEC-based healthy eating interventions.

Healthy eating interventions delivered in early childhood education and care settings for improving the diet of children aged six months to six years.

BACKGROUND: Dietary intake during early childhood can have implications on child health and developmental trajectories. Early childhood education and care (ECEC) services are recommended settings to deliver healthy eating interventions as they provide access to many children during this important period. Healthy eating interventions delivered in ECEC settings can include strategies targeting the curriculum (e.g. nutrition education), ethos and environment (e.g. menu modification) and partnerships (e.g. workshops for families). Despite guidelines supporting the delivery of healthy eating interventions in this setting, little is known about their impact on child health. OBJECTIVES: To assess the effectiveness of healthy eating interventions delivered in ECEC settings for improving dietary intake in children aged six months to six years, relative to usual care, no intervention or an alternative, non-dietary intervention. Secondary objectives were to assess the impact of ECEC-based healthy eating interventions on physical outcomes (e.g. child body mass index (BMI), weight, waist circumference), language and cognitive outcomes, social/emotional and quality-of-life outcomes. We also report on cost and adverse consequences of ECEC-based healthy eating interventions. SEARCH METHODS: We searched eight electronic databases including CENTRAL, MEDLINE, Embase, CINAHL, PsycINFO, ERIC, Scopus and SportDiscus on 24 February 2022. We searched reference lists of included studies, reference lists of relevant systematic reviews, the World Health Organization International Clinical Trials Registry Platform, ClinicalTrials.gov and Google Scholar, and contacted authors of relevant papers. SELECTION CRITERIA: We included randomised controlled trials (RCTs), including cluster-RCTs, stepped-wedge RCTs, factorial RCTs, multiple baseline RCTs and randomised cross-over trials, of healthy eating interventions targeting children aged six months to six years that were conducted within the ECEC setting. ECEC settings included preschools, nurseries, kindergartens, long day care and family day care. To be included, studies had to include at least one intervention component targeting child diet within the ECEC setting and measure child dietary or physical outcomes, or both. DATA COLLECTION AND ANALYSIS: Pairs of review authors independently screened titles and abstracts and extracted study data. We assessed risk of bias for all studies against 12 criteria within RoB 1, which allows for consideration of how selection, performance, attrition, publication and reporting biases impact outcomes. We resolved discrepancies via consensus or by consulting a third review author. Where we identified studies with suitable data and homogeneity, we performed meta-analyses using a random-effects model; otherwise, we described findings using vote-counting approaches and via harvest plots. For measures with similar metrics, we calculated mean differences (MDs) for continuous outcomes and risk ratios (RRs) for dichotomous outcomes. We calculated standardised mean differences (SMDs) for primary and secondary outcomes where studies used different measures. We applied GRADE to assess certainty of evidence for dietary, cost and adverse outcomes. MAIN RESULTS: We included 52 studies that investigated 58 interventions (described across 96 articles). All studies were cluster-RCTs. Twenty-nine studies were large (≥ 400 participants) and 23 were small (< 400 participants). Of the 58 interventions, 43 targeted curriculum, 56 targeted ethos and environment, and 50 targeted partnerships. Thirty-eight interventions incorporated all three components. For the primary outcomes (dietary outcomes), we assessed 19 studies as overall high risk of bias, with performance and detection bias being most commonly judged as high risk of bias. ECEC-based healthy eating interventions versus usual practice or no intervention may have a positive effect on child diet quality (SMD 0.34, 95% confidence interval (CI) 0.04 to 0.65; P = 0.03, I2 = 91%; 6 studies, 1973 children) but the evidence is very uncertain. There is moderate-certainty evidence that ECEC-based healthy eating interventions likely increase children's consumption of fruit (SMD 0.11, 95% CI 0.04 to 0.18; P < 0.01, I2 = 0%; 11 studies, 2901 children). The evidence is very uncertain about the effect of ECEC-based healthy eating interventions on children's consumption of vegetables (SMD 0.12, 95% CI -0.01 to 0.25; P =0.08, I2 = 70%; 13 studies, 3335 children). There is moderate-certainty evidence that ECEC-based healthy eating interventions likely result in little to no difference in children's consumption of non-core (i.e. less healthy/discretionary) foods (SMD -0.05, 95% CI -0.17 to 0.08; P = 0.48, I2 = 16%; 7 studies, 1369 children) or consumption of sugar-sweetened beverages (SMD -0.10, 95% CI -0.34 to 0.14; P = 0.41, I2 = 45%; 3 studies, 522 children). Thirty-six studies measured BMI, BMI z-score, weight, overweight and obesity, or waist circumference, or a combination of some or all of these. ECEC-based healthy eating interventions may result in little to no difference in child BMI (MD -0.08, 95% CI -0.23 to 0.07; P = 0.30, I2 = 65%; 15 studies, 3932 children) or in child BMI z-score (MD -0.03, 95% CI -0.09 to 0.03; P = 0.36, I2 = 0%; 17 studies; 4766 children). ECEC-based healthy eating interventions may decrease child weight (MD -0.23, 95% CI -0.49 to 0.03; P = 0.09, I2 = 0%; 9 studies, 2071 children) and risk of overweight and obesity (RR 0.81, 95% CI 0.65 to 1.01; P = 0.07, I2 = 0%; 5 studies, 1070 children). ECEC-based healthy eating interventions may be cost-effective but the evidence is very uncertain (6 studies). ECEC-based healthy eating interventions may have little to no effect on adverse consequences but the evidence is very uncertain (3 studies). Few studies measured language and cognitive skills (n = 2), social/emotional outcomes (n = 2) and quality of life (n = 3). AUTHORS' CONCLUSIONS: ECEC-based healthy eating interventions may improve child diet quality slightly, but the evidence is very uncertain, and likely increase child fruit consumption slightly. There is uncertainty about the effect of ECEC-based healthy eating interventions on vegetable consumption. ECEC-based healthy eating interventions may result in little to no difference in child consumption of non-core foods and sugar-sweetened beverages. Healthy eating interventions could have favourable effects on child weight and risk of overweight and obesity, although there was little to no difference in BMI and BMI z-scores. Future studies exploring the impact of specific intervention components, and describing cost-effectiveness and adverse outcomes are needed to better understand how to maximise the impact of ECEC-based healthy eating interventions.

Improving academic and public health impact of Cochrane public health reviews: what can we learn from bibliographic metrics and author dissemination strategies? A cross-sectional study.

BACKGROUND: To facilitate the development of impactful research dissemination strategies, this study aimed to: (i) survey authors of trials included in a sample of Cochrane reviews to describe strategies to disseminate trial findings, and examine their association with academic and policy impacts and (ii) audit academic and policy impact of CPH reviews. METHODS: Authors of 104 trials within identified Cochrane reviews completed survey items assessing the dissemination strategies. Field weighted citation (FWCI) data extracted from bibliographic databases served as a measure of academic impact of trials and CPH reviews. Policy and practice impacts of trials were assessed during the survey of trial authors using items based on the Payback Framework, and for CPH reviews using 'policy mention' data collected via Altmetric Explorer. RESULTS: Among the included trials, univariate (but not multivariable) regression models revealed significant associations between the use of dissemination strategies (i.e. posts on social media; workshops with end-users; media-releases) and policy or practice impacts. No significant associations were reported between dissemination strategies and trial FWCI. The mean FWCI of CPH reviews suggest that they are cited 220% more than other reviews in their field. CONCLUSIONS: Comprehensive dissemination strategies are likely required to maximize the potential the potential impacts of public health research.

Dissemination of public health research to prevent non-communicable diseases: a scoping review.

BACKGROUND: Dissemination is a critical element of the knowledge translation pathway, and a necessary step to ensure research evidence is adopted and implemented by key end users in order to improve health outcomes. However, evidence-based guidance to inform dissemination activities in research is limited. This scoping review aimed to identify and describe the scientific literature examining strategies to disseminate public health evidence related to the prevention of non-communicable diseases. METHODS: Medline, PsycInfo and EBSCO Search Ultimate were searched in May 2021 for studies published between January 2000 and the search date that reported on the dissemination of evidence to end users of public health evidence, within the context of the prevention of non-communicable diseases. Studies were synthesised according to the four components of Brownson and colleagues' Model for Dissemination of Research (source, message, channel and audience), as well as by study design. RESULTS: Of the 107 included studies, only 14% (n = 15) directly tested dissemination strategies using experimental designs. The remainder primarily reported on dissemination preferences of different populations, or outcomes such as awareness, knowledge and intentions to adopt following evidence dissemination. Evidence related to diet, physical activity and/or obesity prevention was the most disseminated topic. Researchers were the source of disseminated evidence in over half the studies, and study findings/knowledge summaries were more frequently disseminated as the message compared to guidelines or an evidence-based program/intervention. A broad range of dissemination channels were utilised, although peer-reviewed publications/conferences and presentations/workshops predominated. Practitioners were the most commonly reported target audience. CONCLUSIONS: There is a significant gap in the peer reviewed literature, with few experimental studies published that analyse and evaluate the effect of different sources, messages and target audiences on the determinants of uptake of public health evidence for prevention. Such studies are important as they can help inform and improve the effectiveness of current and future dissemination practices in public health contexts.

From trials to communities: implementation and scale-up of health behaviour interventions.

BACKGROUND: To maximise their potential benefits to communities, effective health behaviour interventions need to be implemented, ideally 'at scale', and are often adapted as part of this. To inform future implementation and scale-up efforts, this study broadly sought to understand (i) how often health behaviour interventions are implemented in communities, (ii) the adaptations that occur; (iii) how frequency it occurred 'at scale'; and (iv) factors associated with 'scale-up'. METHODS: A cross-sectional survey was conducted of corresponding authors of trials (randomised or non-randomised) assessing the effects of preventive health behaviour interventions. Included studies of relevant Cochrane reviews served as a sampling frame. Participants were asked to report on the implementation and scale-up (defined as investment in large scale delivery by a (non)government organisation) of their intervention in the community following trial completion, adaptations made, and any research dissemination strategies employed. Information was extracted from published reports of the trial including assessments of effectiveness and risk of bias. RESULTS: Authors of 104 trials completed the survey. Almost half of the interventions were implemented following trial completion (taking on average 19 months), and 54% of those were adapted prior to doing so. The most common adaptations were adding intervention components, and adapting the intervention to fit within the local service setting. Scale-up occurred in 33% of all interventions. There were no significant associations between research trial characteristics such as intervention effectiveness, risk of bias, setting, involvement of end-user, and incidence of scale-up. However the number of research dissemination strategies was positively associated to the odds of an intervention being scaled-up (OR = 1.50; 95% CI: 1.19, 1.88; p < 0.001). CONCLUSIONS: Adaptation of implemented trials is often undertaken. Most health behaviour interventions are not implemented or scaled-up following trial completion. The use of a greater number of dissemination strategies may increase the likelihood of scaled up.

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.

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.

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.

Selecting Review Outcomes for Systematic Reviews of Public Health Interventions.

For systematic reviews to have an impact on public health, they must report outcomes that are important for decision-making. Systematic reviews of public health interventions, however, have a range of potential end users, and identifying and prioritizing the most important and relevant outcomes represents a considerable challenge.In this commentary, we describe potentially useful approaches that systematic review teams can use to identify review outcomes to best inform public health decision-making. Specifically, we discuss the importance of stakeholder engagement, the use of logic models, consideration of core outcome sets, reviews of the literature on end users' needs and preferences, and the use of decision-making frameworks in the selection and prioritization of outcomes included in reviews.The selection of review outcomes is a critical step in the production of public health reviews that are relevant to those who use them. Utilizing the suggested strategies may help the review teams better achieve this.

How effective are physical activity interventions when they are scaled-up: a systematic review.

BACKGROUND: The 'scale-up' of effective physical activity interventions is required if they are to yield improvements in population health. The purpose of this study was to systematically review the effectiveness of community-based physical activity interventions that have been scaled-up. We also sought to explore differences in the effect size of these interventions compared with prior evaluations of their efficacy in more controlled contexts, and describe adaptations that were made to interventions as part of the scale-up process. METHODS: We performed a search of empirical research using six electronic databases, hand searched reference lists and contacted field experts. An intervention was considered 'scaled-up' if it had been intentionally delivered on a larger scale (to a greater number of participants, new populations, and/or by means of different delivery systems) than a preceding randomised control trial ('pre-scale') in which a significant intervention effect (p < 0.05) was reported on any measure of physical activity. Effect size differences between pre-scale and scaled up interventions were quantified ([the effect size reported in the scaled-up study / the effect size reported in the pre-scale-up efficacy trial] × 100) to explore any scale-up 'penalties' in intervention effects. RESULTS: We identified 10 eligible studies. Six scaled-up interventions appeared to achieve significant improvement on at least one measure of physical activity. Six studies included measures of physical activity that were common between pre-scale and scaled-up trials enabling the calculation of an effect size difference (and potential scale-up penalty). Differences in effect size ranged from 132 to 25% (median = 58.8%), suggesting that most scaled-up interventions typically achieve less than 60% of their pre-scale effect size. A variety of adaptations were made for scale-up - the most common being mode of delivery. CONCLUSION: The majority of interventions remained effective when delivered at-scale however their effects were markedly lower than reported in pre-scale trials. Adaptations of interventions were common and may have impacted on the effectiveness of interventions delivered at scale. These outcomes provide valuable insight for researchers and public health practitioners interested in the design and scale-up of physical activity interventions, and contribute to the growing evidence base for delivering health promotion interventions at-scale. TRIAL REGISTRATION: PROSPERO CRD42020144842 .

Consolidating evidence on the effectiveness of interventions promoting fruit and vegetable consumption: an umbrella review.

BACKGROUND: The overarching objective was to examine the effectiveness of intervention strategies to promote fruit and vegetable consumption. To do this, systematic review evidence regarding the effects of intervention strategies was synthesized; organized, where appropriate, by the setting in which the strategies were implemented. Additionally, we sought to describe gaps in the review of evidence; that is, where evidence regarding the effectiveness of recommended policy actions had not been systematically synthesised. METHODS: We undertook a systematic search of electronic databases and the grey literature to identify systematic reviews describing the effects of any intervention strategy targeting fruit and/or vegetable intake in children or adults of any age. RESULTS: The effects of 32 intervention strategies were synthesised from the 19 included reviews. The strategies were mapped across all three broad domains of the NOURISHING framework (i.e. food environment, food system and behaviour change communication), but covered just 14 of the framework's 65 sub-policy areas. There was evidence supporting the effectiveness of 19 of the 32 intervention strategies. The findings of the umbrella review suggest that intervention strategies implemented within schools, childcare services, homes, workplaces and primary care can be effective, as can eHealth strategies, mass media campaigns, household food production strategies and fiscal interventions. CONCLUSIONS: A range of effective strategy options are available for policy makers and practitioners interested in improving fruit and/or vegetable intake. However, the effects of many strategies - particularly those targeting agricultural production practices, the supply chain and the broader food system - have not been reported in systematic reviews. Primary studies assessing the effects of these strategies, and the inclusion of such studies in systematic reviews, are needed to better inform national and international efforts to improve public health nutrition. TRIAL REGISTRATION: The review protocol was deposited in a publicly available Open Science framework prior to execution of the search strategy. https://osf.io/unj7x/.

A systematic review of interventions to improve the dietary intake, physical activity and weight status of children attending family day care services.

OBJECTIVE: To (i) identify and synthesise findings from interventions to improve the dietary intake, physical activity and weight status of children aged 0-6 years attending family day care services; and (ii) assess the impact of interventions on family day care environments, intervention cost and adverse outcomes. DESIGN: Medline in Process, PsycINFO, ERIC, Embase, CINAHL, CENTRAL and Scopus databases were searched in March 2019. Studies were included if they (i) evaluated an intervention to improve the diet, physical activity and/or weight of children aged 0-6 years; (ii) were delivered in family day care services; (iii) targeted child diet, physical activity and/or weight; and (iv) used a parallel control group design. Screening was undertaken by two reviewers with disagreements resolved by a third reviewer. SETTING: Family day care services, also known as family childcare homes. PARTICIPANTS: Children aged 0-6 years attending family day care services. RESULTS: In total, 8977 titles were retrieved, and 199 full-texts reviewed. No studies met the inclusion criteria for the primary outcome; however, two studies reporting on the secondary outcome of family day care environments were included. The 4-year community-wide obesity prevention programme and the 12-month train-the-trainer programme both reported statistically significant improvements in the healthy eating and physical activity environments of family day care, compared to cross-sectional state-average control groups. CONCLUSIONS: Findings highlight few existing interventions in family day care services and a need for high-quality controlled trials to identify effective interventions to improve children's diet, activity and weight in this setting.

How to optimise public health interventions: a scoping review of guidance from optimisation process frameworks.

BACKGROUND: Optimisation processes have the potential to rapidly improve the impact of health interventions. Optimisation can be defined as a deliberate, iterative and data-driven process to improve a health intervention and/or its implementation to meet stakeholder-defined public health impacts within resource constraints. This study aimed to identify frameworks used to optimise the impact of health interventions and/or their implementation, and characterise the key concepts, steps or processes of identified frameworks. METHODS: A scoping review of MEDLINE, CINAL, PsycINFO, and ProQuest Nursing & Allied Health Source databases was undertaken. Two reviewers independently coded the key concepts, steps or processes involved in each frameworks, and identified if it was a framework aimed to optimise interventions or their implementation. Two review authors then identified the common steps across included frameworks. RESULTS: Twenty optimisation frameworks were identified. Eight frameworks were for optimising interventions, 11 for optimising implementation and one covered both intervention and implementation optimisation. The mean number of steps within the frameworks was six (range 3-9). Almost half (n = 8) could be classified as both linear and cyclic frameworks, indicating that some steps may occur multiple times in a single framework. Two meta-frameworks are proposed, one for intervention optimisation and one for implementation strategy optimisation. Steps for intervention optimisation are: Problem identification; Preparation; Theoretical/Literature base; Pilot/Feasibility testing; Optimisation; Evaluation; and Long-term implementation. Steps for implementation strategy optimisation are: Problem identification; Collaborate; Plan/design; Pilot; Do/change; Study/evaluate/check; Act; Sustain/endure; and Disseminate/extend. CONCLUSIONS: This review provides a useful summary of the common steps followed to optimise a public health intervention or its implementation according to established frameworks. Further opportunities to study and/or validate such frameworks and their impact on improving outcomes exist.

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.

Internet-Based Programs Incorporating Behavior Change Techniques Are Associated With Increased Smoking Cessation in the General Population: A Systematic Review and Meta-analysis.

Background and aims: This study aims to (i) examine the effectiveness of internet-based smoking cessation programs; (ii) describe the number and type of behavior change techniques (BCTs) employed; and (iii) explore whether BCTs included in internet-based smoking cessation programs are related to program effectiveness. Methods: MEDLINE, CINAHL, EMBASE, PsycINFO, and CENTRAL databases were searched. Randomized controlled trials were included if they described the study of a smoking cessation program delivered via the internet; included current adult tobacco smokers from the general population; and were written in English. Random effects meta-analyses and meta-regressions were used to examine program effectiveness (pooled odds ratios, by outcome measure, i.e., 7 day point prevalence abstinence [PPA], 30 day PPA, other abstinence measure) in short- and long-term outcomes, and examine the associations between BCT number and type (individual BCTs and BCT domain) and program effectiveness. Results: Results from 45 studies were included (n = 65,736). Intervention effectiveness was found in the short term for all outcome measures (OR = 1.29, 95% CI 1.12, 1.50, p = .001), for "prolonged abstinence" (OR = 1.43, 95% CI 1.09, 1.87, p = .009), and "30 day PPA" (OR = 1.75, 95% CI 1.13, 2.72, p = .013). Internet-based programs were effective in the long term for all outcome measures (OR = 1.19, 95% CI = 1.06, 1.35, p = .004) and for "prolonged abstinence" (OR = 1.40, 95% CI 1.19, 1.63, p < .001). On average, interventions used more BCTs than comparison groups (6.6 vs. 3.1, p = .0002). The impact of specific individual BCTs and BCT domains on effectiveness was examined and is reported. Conclusions: Internet-based smoking cessation interventions increased the odds of cessation by 29 per cent in the short term and by 19 per cent in the long term. Internet-based smoking cessation intervention development should incorporate BCTs to increase effectiveness. Registration: CRD42015014676.

Comorbid tobacco and other substance use and symptoms of anxiety and depression among hospitalised orthopaedic trauma patients.

BACKGROUND: No study has examined the prevalence of tobacco, other substance use, and symptoms of anxiety and depression, and rates of comorbidities among the orthopaedic trauma population, despite the impact they have on recovery from surgery. This study aims to 1) describe the rates of symptoms and substance use; 2) compare rates of symptoms and substance use among smokers versus non-smokers; and 3) examine the relationship between symptoms and substance use with smoking status. METHODS: A cross-sectional survey of orthopaedic trauma patients was conducted in two Australian public hospitals. Demographic characteristics, smoking status, alcohol consumption, recent cannabis use, and symptoms of anxiety and/or depression were examined. Differences between current and non-smokers were compared using Pearson Chi2 tests. Multivariate logistic regression explored variables related to tobacco smoking. RESULTS: Eight hundred nineteen patients participated. Over one-fifth (21.8%) identified as a current smoker, half (51.8%) reported consuming alcohol at hazardous levels in the last 12 months, and about 10% stated that they had used cannabis in the last 30 days (9.7%), or experienced symptoms of either anxiety (12.4%), or depression (12.9%) in the last two weeks. Over one-fifth of current tobacco smokers (21.8%) reported drinking heavily in the last 12 months and using cannabis recently. Males, with a lower educational attainment, who were unmarried, had used cannabis recently, and report drinking heavily were more likely to be current smokers. CONCLUSIONS: Health behaviour interventions addressing comorbidities are warranted among the orthopaedic trauma population given the high rate of comorbidity and impact these may have on recovery.