Long-Term Effectiveness of a Multi-Strategy Choice Architecture Intervention in Increasing Healthy Food Choices of High-School Students From Online Canteens (Click & Crunch High Schools): Cluster Randomized Controlled Trial.

BACKGROUND: School canteens are a recommended setting to influence adolescent nutrition due to their scope to improve student food choices. Online lunch ordering systems ("online canteens") are increasingly used and represent attractive infrastructure to implement choice architecture interventions that nudge users toward healthier food choices. A recent cluster randomized controlled trial demonstrated the short-term effectiveness (2-month follow-up) of a choice architecture intervention to increase the healthiness of foods purchased by high school students from online canteens. However, there is little evidence regarding the long-term effectiveness of choice architecture interventions targeting adolescent food purchases, particularly those delivered online. OBJECTIVE: This study aimed to determine the long-term effectiveness of a multi-strategy choice architecture intervention embedded within online canteen infrastructure in high schools at a 15-month follow-up. METHODS: A cluster randomized controlled trial was undertaken with 1331 students (from 9 high schools) in New South Wales, Australia. Schools were randomized to receive the automated choice architecture intervention (including menu labeling, positioning, feedback, and prompting strategies) or the control (standard online ordering). The foods purchased were classified according to the New South Wales Healthy Canteen strategy as either "everyday," "occasional," or "should not be sold." Primary outcomes were the average proportion of "everyday," "occasional," and "should not be sold" items purchased per student. Secondary outcomes were the mean energy, saturated fat, sugar, and sodium content of purchases. Outcomes were assessed using routine data collected by the online canteen. RESULTS: From baseline to 15-month follow-up, on average, students in the intervention group ordered significantly more "everyday" items (+11.5%, 95% CI 7.3% to 15.6%; P<.001), and significantly fewer "occasional" (-5.4%, 95% CI -9.4% to -1.5%; P=.007) and "should not be sold" items (-6%, 95% CI -9.1% to -2.9%; P<.001), relative to controls. There were no between-group differences over time in the mean energy, saturated fat, sugar, or sodium content of lunch orders. CONCLUSIONS: Given their longer-term effectiveness, choice architecture interventions delivered via online canteens may represent a promising option for policy makers to support healthy eating among high school students. TRIAL REGISTRATION: Australian Clinical Trials ACTRN12620001338954, https://anzctr.org.au/Trial/Registration/TrialReview.aspx?id=380546 ; Open Science Framework osf.io/h8zfr, https://osf.io/h8zfr/.

Assessing the scalability of evidence-based healthy eating and physical activity interventions in early childhood education and care: A cross-sectional study of end-user perspectives.

OBJECTIVES: To describe early childhood education and care (ECEC) services: i) perceptions regarding the scalability of healthy eating and physical activity interventions; and ii) associations between scalability and service characteristics. METHODS: A cross-sectional survey was conducted with a randomly selected sample of ECEC services across Australia. The scalability of 12 healthy eating and physical activity interventions was assessed using items based on the Intervention Scalability Assessment Tool. Higher scores represented higher perceived scalability. RESULTS: From 453 participants, the highest scoring healthy eating and physical activity interventions were 'providing healthy eating education and activities for children' (M43.05) (out of 50) and 'providing sufficient opportunities for child physical activity' (M41.43). The lowest scoring was 'providing families with lunchbox guidelines' (M38.99) and 'engaging families in activities to increase child physical activity' (M38.36). Services located in rural areas, compared to urban areas, scored the overall scalability of both healthy eating and physical activity interventions significantly lower. CONCLUSIONS: Perceptions regarding the scalability of healthy eating and physical activity interventions in the ECEC setting vary according to service characteristics. IMPLICATIONS FOR PUBLIC HEALTH: Findings identify where government investment and implementation efforts may be prioritised to facilitate scale-up. An investigation into the barriers and support required for lower-scoring interventions is warranted.

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.

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.

Assessing the scalability of healthy eating interventions within the early childhood education and care setting: secondary analysis of a Cochrane systematic review.

OBJECTIVE: Early childhood education and care (ECEC) is a recommended setting for the delivery of health eating interventions 'at scale' (i.e. to large numbers of childcare services) to improve child public health nutrition. Appraisal of the 'scalability' (suitability for delivery at scale) of interventions is recommended to guide public health decision-making. This study describes the extent to which factors required to assess scalability are reported among ECEC-based healthy eating interventions. DESIGN: Studies from a recent Cochrane systematic review assessing the effectiveness of healthy eating interventions delivered in ECEC for improving child dietary intake were included. The reporting of factors of scalability was assessed against domains outlined within the Intervention Scalability Assessment Tool (ISAT). The tool recommends decision makers consider the problem, the intervention, strategic and political context, effectiveness, costs, fidelity and adaptation, reach and acceptability, delivery setting and workforce, implementation infrastructure and sustainability. Data were extracted by one reviewer and checked by a second reviewer. SETTING: ECEC. PARTICIPANTS: Children 6 months to 6 years. RESULTS: Of thirty-eight included studies, none reported all factors within the ISAT. All studies reported the problem, the intervention, effectiveness and the delivery workforce and setting. The lowest reported domains were intervention costs (13 % of studies) and sustainability (16 % of studies). CONCLUSIONS: Findings indicate there is a lack of reporting of some key factors of scalability for ECEC-based healthy eating interventions. Future studies should measure and report such factors to support policy and practice decision makers when selecting interventions to be scaled-up.

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.

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.

An audit of the dissemination strategies and plan included in international food-based dietary guidelines.

OBJECTIVE: Food-based dietary guidelines (FBDG) are an important resource to improve population health; however, little is known about the types of strategies to disseminate them. This study sought to describe dissemination strategies and content of dissemination plans that were available for FBDG. DESIGN: A cross-sectional audit of FBDG with a published English-language version sourced from the United Nations FAO repository. We searched for publicly available dissemination strategies and any corresponding plans available in English language. Two authors extracted data on strategies, which were grouped according to the Model for Dissemination Research Framework (including source, audience, channel and message). For guidelines with a dissemination plan, we described goals, audience, strategies and expertise and resources according to the Canadian Institute for Health Research guidance. SETTING: FBDG from fifty-three countries mostly from high-income (n 28, 52·8 %), and upper-middle income (n 18, 34 %) areas were included. PARTICIPANTS: n/a. RESULTS: The source of guidelines was most frequently health departments (79·2 %). The message included quantities and types of foods, physical activity recommendations and 88·7 % included summarised versions of main messages. The most common channels were infographics and information booklets, and the main end-users were the public. For twelve countries (22·6 %), we were able to source an English-language dissemination plan, where none met all recommendations outlined by the Canadian Institute for Health Research. CONCLUSIONS: The public was the most frequently identified end-user and thus most dissemination strategies and plans focused on this group. Few FBDG had formal dissemination plans and of those there was limited detailed provided.

The impact of an e-newsletter or animated video to disseminate outdoor free-play information in relation to COVID-19 guidelines in New South Wales early childhood education and care services: a randomised controlled trial.

BACKGROUND: State-based Guidelines were issued for Early Childhood Education and Care (ECEC) services (caring for children 0-6 years) recommending greater time outdoors and inclusion of indoor-outdoor programs to facilitate social distancing to reduce spread of COVID-19. The aim of this 3-arm randomised controlled trial (RCT) was to examine the impact of different dissemination strategies on increasing ECEC service intentions to adopt recommendations from the Guidelines. METHODS: This was a post-intervention only RCT. A sample of eligible ECEC services in New South Wales (n = 1026) were randomly allocated to one of three groups; (i) e-newsletter resource; (ii) animated video resource; or (iii) control (standard email). The intervention was designed to address key determinants of guideline adoption including awareness and knowledge. Following delivery of the intervention in September 2021, services were invited to participate in an online or telephone survey from October-December 2021. The primary trial outcome was the proportion of services intending to adopt the Guidelines, defined as intention to; (i) offer an indoor-outdoor program for the full day; or (ii) offer more outdoor play time. Secondary outcomes included awareness, reach, knowledge and implementation of the Guidelines. Barriers to Guideline implementation, cost of the dissemination strategies and analytic data to measure fidelity of intervention delivery were also captured. RESULTS: Of the 154 services that provided post-intervention data, 58 received the e-newsletter (37.7%), 50 received the animated video (32.5%), and 46 received the control (29.9%). Services who received the animated video had nearly five times the odds (OR: 4.91 [1.03, 23.34] p = 0.046) than those in the control group, to report having intentions to adopt the Guidelines. There were no statistically significant differences in awareness or knowledge of the Guidelines between either intervention or control services. Development costs were greatest for the animated video. The extent to which the dissemination strategy was viewed in full, were similar for both the e-newsletter and animated video. CONCLUSION: This study found potential for the inclusion of interactive strategies to disseminate policy and guideline information within the ECEC setting, in the context of the need for rapid communication. Further research should explore the added benefits of embedding such strategies within a multi-strategy intervention. TRIAL REGISTRATION: Retrospectively registered with the Australian New Zealand Clinical Trials Registry (ANZCTR) on the 23/02/2023 (ACTRN 12,623,000,198,628).

Overcoming challenges in conducting systematic reviews in implementation science: a methods commentary.

Consolidation of the literature using systematic reviews is a critical way to advance a discipline and support evidence-based decision-making in healthcare. However, unique challenges exist that impact the conduct of systematic reviews in implementation science. In this commentary, we reflect on our combined experience to describe five key challenges unique to systematic reviews of primary implementation research. These challenges include (1) descriptors used in implementation science publications, (2) distinction between evidence-based interventions and implementation strategies, (3) assessment of external validity, (4) synthesis of implementation studies with substantial clinical and methodological diversity, and (5) variability in defining implementation 'success'. We outline possible solutions and highlight resources that can be used by authors of primary implementation research, as well as systematic review and editorial teams, to overcome the identified challenges and optimise the utility of future systematic reviews in implementation science.

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.

A rapid review of the scalability of interventions targeting obesity prevention in infants.

ISSUE ADDRESSED: Obesity in children is one of the most significant public health issues globally. Given the high prevalence of overweight and obesity in children, there is a need to identify effective obesity prevention efforts that can be delivered at scale to improve child health. We aimed to (i) identify obesity prevention interventions targeted at children aged 0-2 that have been scaled-up, and their relative efficacy compared to their pre-scale trial, (ii) describe adaptations made, and the extent to which factors related to scalability have been reported. METHODS: We conducted a rapid review of pre-scale randomised controlled trials targeting nutrition, physical activity and obesity prevention in infants, and calculated the relative effect size for relevant outcomes in the corresponding scaled up trial. We documented adaptations made to the pre-scale trial for scale up, and explored how different components of scalability had been reported according to the Intervention Scalability Assessment Tool. RESULTS: Of the 14 identified pre-scale trials, only one formal evaluation of the scale-up trial was identified. For body mass index, <10% of the effect was retained, however for nutrition and behavioural outcomes, the proportion of effect retained varied from -11.1% to 144%. Significant adaptations to modality were made in the scaled up trial primarily to reduce cost and increase reach of the intervention. Reporting of scalability components varied across the 14 trials, with only one trial reporting information for all assessed components. CONCLUSIONS: The majority of effective interventions targeting obesity prevention in infants have not been evaluated in a scaled up form. The magnitude of effect retained for the single trial that was scaled up was variable. In general, reporting of components of scalability was sub-optimal. SO WHAT?: The findings suggest that there is substantial need for the development and rigorous evaluation of obesity prevention interventions in children aged 0-2 which are amenable for scale.

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.

Exploratory analysis of a cluster randomized controlled trial of a multi-strategy intervention delivered via online canteens on improving the nutritional quality of primary school students' pre-ordered foods & drinks at recess.

School canteens are a recommended setting to deliver public health nutrition strategies given their wide reach, and frequent use by children. Online canteens, where users (i.e. students or their carers) pre-order and pay for food and drinks online, represent attractive systems to deliver strategies that encourage healthier food choices. There have been few studies exploring the efficacy of public health nutrition interventions in online food ordering environments. Therefore, this study aims to assess the efficacy of a multi-strategy intervention implemented in an online school canteen ordering system in reducing the energy, saturated fat, sugar, and sodium content of students' online recess orders (i.e. foods ordered during the mid-morning or afternoon snack period). This was an exploratory analysis of recess purchases for a cluster randomized controlled trial that initially sought to examine the efficacy of the intervention on lunch orders. A total of 314 students from 5 schools received the multi-strategy intervention (involving menu labelling, placement, prompting and availability) that was integrated into the online ordering system, and 171 students from 3 schools received the control (usual online ordering). Analysis of main outcomes found that the mean energy (difference: -269.3 kJ; P = 0.006), saturated fat (difference: -1.1 g; P = 0.011) and sodium (difference: -128.6 mg; P = 0.014) content per student recess order was significantly lower in the intervention group than the control group at 2-month follow-up. Findings suggest that embedding strategies to encourage healthier choices within online canteen ordering systems can improve the nutrient composition of student recess purchases. These results add to the current evidence base suggesting that interventions delivered via online food ordering systems represent an effective strategy for improving child public health nutrition in schools.

Parent-reported compared with researcher-measured child height and weight: impact on body mass index classification in Australian pre-school aged children.

ISSUE ADDRESSED: Parent-reported data may provide a practical and cheap way for estimating young children's weight status. This study aims to compare the validity and reliability of parent-reported height and weight to researcher-measured data for pre-school aged children (aged 2-6 years). METHODS: This was a nested study within a cluster randomised controlled trial (October 2016-April 2017), conducted within 32 Early Childhood Education and Care (ECEC) services across New South Wales, Australia. Parents of children reported on demographics and child height and weight via a survey. For the same child, height and weight data were objectively collected by trained research staff at the service. We calculated mean differences, intra-class correlations, Bland-Altman plots, percentage agreement and Cohen's kappa coefficient (>0.8 = "excellent"; 0.61-0.8 = "good"; 0.41-0.60 = "moderate"; 0.21 and 0.4 = "fair [weak]"; <0.2 = "poor"). RESULTS: Overall, 89 children were included (mean age: 4.7 years; 59.5% female). The mean difference between parent-reported and researcher-measured data were small (BMI z-score: mean difference -0.01 [95% CI: -0.45 to 0.44]). There was "fair/weak" agreement between parent-categorised child BMI compared with researcher-measured data (Cohen's Kappa 0.24 [95% CI: 0.06 to 0.42]). Agreement was poor (Cohen's kappa <0.2) for female children, when reported by fathers or by parents with a BMI > 25 kg/m2 . CONCLUSION: There was "fair/weak" agreement between parent-reported and measured estimates of child weight status. SO WHAT?: Parent's report of weight and height may be a weak indicator of adiposity at the level of individuals however it may be useful for aggregate estimates.

Describing the evidence-base for research engagement by health care providers and health care organisations: a scoping review.

BACKGROUND: Having a research-engaged health and medical workforce is associated with improvements in clinical outcomes for patients. As such, there has been significant government investment internationally to support health care organisations and services to increase staff engagement with research. OBJECTIVES: This scoping review sought to provide an overview of the literature describing strategies employed to increase research engagement by health care providers and organisations, and to undertake a qualitative analysis to generate a list of research engagement strategies. METHODS: A scoping review using systematic search strategies was undertaken to locate peer-review publications and grey literature related to research engagement by health care providers and organisations. Research engagement was defined as a 'deliberate set of intellectual and practical activities undertaken by health care staff and organisations to conduct research'. A database search of electronic records was performed with no limit on publication date. Publications were included regardless of study type (excluding systematic reviews) and categorised as either databased (presenting data or new analysis of existing data) and non-databased (no new data or analyses). Databased publications were further classified according to study type, study design and setting. A qualitative synthesis using a Framework Approach was undertaken with all studies that described a strategy to improve research engagement. RESULTS: A total of 152 publications were included in this study with 54% categorised as non-databased. Of the databased articles, the majority (72%) were descriptive studies describing prevalence of correlates of research engagement, 17 (25%) described intervention studies where only two were controlled studies. The following research engagement strategies were identified: i) dual skilled team/staff, ii) resources or physical infrastructure, iii) incentives, iv) leadership support of research, v) education/training, vi) networks, vii) forming partnerships or collaborations and viii) overall leadership structure of entity. CONCLUSIONS: The literature on research engagement is primarily opinion-based and descriptive in nature. To provide the evidence needed to inform strategies, this needs to progress beyond descriptive to more rigorous well-designed intervention research.

Interventions to prevent obesity in school-aged children 6-18 years: An update of a Cochrane systematic review and meta-analysis including studies from 2015-2021.

Background: Childhood obesity remains a global public health priority due to the enormous burden it generates. Recent surveillance data suggests there has been a sharp increase in the prevalence of childhood obesity during the COVID-19 pandemic. The Cochrane review of childhood obesity prevention interventions (0-18 years) updated to 2015 is the most rigorous and comprehensive review of randomised controlled trials (RCTs) on this topic. A burgeoning number of high quality studies have been published since that are yet to be synthesised. Methods: An update of the Cochrane systematic review was conducted to include RCT studies in school-aged children (6-18 years) published to 30 June 2021 that assessed effectiveness on child weight (PROSPERO registration: CRD42020218928). Available cost-effectiveness and adverse effect data were extracted. Intervention effects on body mass index (BMI) were synthesised in random effects meta-analyses by setting (school, after-school program, community, home), and meta-regression examined the association of study characteristics with intervention effect. Findings: Meta-analysis of 140 of 195 included studies (183,063 participants) found a very small positive effect on body mass index for school-based studies (SMD -0·03, 95%CI -0·06,-0·01; trials = 93; participants = 131,443; moderate certainty evidence) but not after-school programs, community or home-based studies. Subgroup analysis by age (6-12 years; 13-18 years) found no differential effects in any setting. Meta-regression found no associations between study characteristics (including setting, income level) and intervention effect. Ten of 53 studies assessing adverse effects reported presence of an adverse event. Insufficient data was available to draw conclusions on cost-effectiveness. Interpretation: This updated synthesis of obesity prevention interventions for children aged 6-18 years, found a small beneficial impact on child BMI for school-based obesity prevention interventions. A more comprehensive assessment of interventions is required to identify mechanisms of effective interventions to inform future obesity prevention public health policy, which may be particularly salient in for COVID-19 recovery planning. Funding: This research was funded by the National Health and Medical Research Council (NHMRC), Australia (Application No APP1153479).

The efficacy of a multi-strategy choice architecture intervention on improving the nutritional quality of high school students' lunch purchases from online canteens (Click & Crunch High Schools): a cluster randomized controlled trial.

BACKGROUND: High school canteens are an ideal setting for public health nutrition intervention, and choice architecture strategies that facilitate the purchase of healthier foods and beverages from school canteens are recommended by the World Health Organization. The rapid uptake of online lunch ordering within school canteens provides a unique opportunity to implement choice architecture strategies that support healthier food choices with high fidelity. Despite this, no trial has tested the efficacy of choice architecture strategies within an online lunch ordering system on improving the nutritional quality of high school student lunch purchases. The objective of this study was to assess the impact of embedding choice architecture strategies into an online lunch ordering system on the nutritional quality of the school canteen lunch purchases of high school students (aged 12-19 years). METHODS: A cluster randomized controlled trial was conducted with nine high schools in one Australian state. Schools were randomized to receive either a 2-month choice architecture intervention (involving menu labelling, prompts, item positioning, and feedback), or usual online ordering. Nutrient quality of online canteen lunch purchases was assessed using routine data collected by the online ordering system. Primary outcomes were the proportion of 'Everyday', 'Occasional', and 'Should not be sold' items purchased, categorized using the state healthy canteen policy. Secondary outcomes were the mean energy, saturated fat, sugar, and sodium content of purchases and the mean weekly revenue from online lunch orders. Linear mixed models were analyzed to assess outcomes. RESULTS: Analysis of the student cohort (Intervention: 4 schools, 656 students; Control: 5 schools, 675 students) showed significant between group differences over time for the intervention group for the mean percentage of online lunch items per student that were 'Everyday' (+ 5.5%; P < 0.001) and 'Should not be sold' (- 4.4%; P < 0.001). There were no between group differences over time in the mean percentage of online lunch items that were 'Occasional'; the average energy, saturated fat, sugar, or sodium content of lunch orders. There was also no difference in mean weekly revenue from high school student online lunch orders (P = 0.23). CONCLUSIONS: These findings suggest that a low intensity, choice architecture intervention embedded within an online ordering system can increase the purchase of healthier food items for high school students in one Australian state without any adverse impact on canteen revenue. TRIAL REGISTRATION: This trial was prospectively registered on Open Science Framework on 23rd October 2020 as osf.io/h8zfr.

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.