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.

A systematic review to determine the effect of strategies to sustain chronic disease prevention interventions in clinical and community settings: study protocol.

BACKGROUND: The primary purpose of this review is to synthesise the effect of strategies aiming to sustain the implementation of evidenced-based interventions (EBIs) targeting key health behaviours associated with chronic disease (i.e. physical inactivity, poor diet, harmful alcohol use, and tobacco smoking) in clinical and community settings. The field of implementation science is bereft of an evidence base of effective sustainment strategies, and as such, this review will provide important evidence to advance the field of sustainability research. METHODS: This systematic review protocol is reported in accordance with the Preferred Reporting Items for Systematic review and Meta-Analysis (PRISMA) checklist. Methods will follow Cochrane gold-standard review methodology. The search will be undertaken across multiple databases, adapting filters previously developed by the research team, data screening and extraction will be performed in duplicate, strategies will be coded using an adapted sustainability-explicit taxonomy, and evidence will be synthesised using appropriate methods (i.e. meta-analytic following Cochrane or non-meta-analytic following SWiM guidelines). We will include any randomised controlled study that targets any staff or volunteers delivering interventions in clinical or community settings. Studies which report on any objective or subjective measure of the sustainment of a health prevention policy, practice, or programme within any of the eligible settings will be included. Article screening, data extraction, risk of bias, and quality assessment will be performed independently by two review authors. Risk of bias will be assessed using Version 2 of the Cochrane risk-of-bias tool for randomised trials (RoB 2). A random-effect meta-analysis will be conducted to estimate the pooled effect of sustainment strategies separately by setting (i.e. clinical and community). Sub-group analyses will be undertaken to explore possible causes of statistical heterogeneity and may include the following: time period, single or multi-strategy, type of setting, and type of intervention. Differences between sub-groups will be statistically compared. DISCUSSION/CONCLUSION: This will be the first systematic review to determine the effect of strategies designed to support sustainment on sustaining the implementation of EBIs in clinical and community settings. The findings of this review will directly inform the design of future sustainability-focused implementation trials. Further, these findings will inform the development of a sustainability practice guide for public health practitioners. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42022352333.

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

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

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

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

A collaborative network trial to evaluate the effectiveness of implementation strategies to maximize adoption of a school-based healthy lunchbox program: a study protocol.

Introduction: An important impediment to the large-scale adoption of evidence-based school nutrition interventions is the lack of evidence on effective strategies to implement them. This paper describes the protocol for a "Collaborative Network Trial" to support the simultaneous testing of different strategies undertaken by New South Wales Local Health Districts to facilitate the adoption of an effective school-based healthy lunchbox program ('SWAP IT'). The primary objective of this study is to assess the effectiveness of different implementation strategies to increase school adoption of the SWAP across New South Wales Local Health Districts. Methods: Within a Master Protocol framework, a collaborative network trial will be undertaken. Independent randomized controlled trials to test implementation strategies to increase school adoption of SWAP IT within primary schools in 10 different New South Wales Local Health Districts will occur. Schools will be randomly allocated to either the intervention or control condition. Schools allocated to the intervention group will receive a combination of implementation strategies. Across the 10 participating Local Health Districts, six broad strategies were developed and combinations of these strategies will be executed over a 6 month period. In six districts an active comparison group (containing one or more implementation strategies) was selected. The primary outcome of the trial will be adoption of SWAP IT, assessed via electronic registration records captured automatically following online school registration to the program. The primary outcome will be assessed using logistic regression analyses for each trial. Individual participant data component network meta-analysis, under a Bayesian framework, will be used to explore strategy-covariate interactions; to model additive main effects (separate effects for each component of an implementation strategy); two way interactions (synergistic/antagonistic effects of components), and full interactions. Discussion: The study will provide rigorous evidence of the effects of a variety of implementation strategies, employed in different contexts, on the adoption of a school-based healthy lunchbox program at scale. Importantly, it will also provide evidence as to whether health service-centered, collaborative research models can rapidly generate new knowledge and yield health service improvements. Clinical trial registration: This trial is registered prospectively with the Australian New Zealand Clinical Trials Registry (ACTRN12623000558628).

An initial typology of approaches used by policy and practice agencies to achieve sustained implementation of interventions to improve health.

BACKGROUND: Scientific investigation of how to sustain the implementation of evidence-based interventions (EBI) is emerging. Sustaining the implementation of EBIs helps ensure their effects on improving health endure. External policy or practice agencies, such as government health departments, are often tasked with supporting individual organisations with sustaining their delivery of EBIs, for example, through financing, training or the provision of other supports. However, to our knowledge, the approaches taken by policy and practice agencies to support the sustainment of EBIs have not been consolidated, categorised and described as a typology. MAIN BODY: To improve conceptual clarity and support both research and practice, we developed an initial working typology of the practical approaches to sustain implementation of EBIs (i.e. sustainment) in order to improve long term health from the perspective of these agencies. The working typology includes three broad approaches. The first, termed 'Self-Sustainment', is when implementation of the EBI by an organisation (e.g. hospital, clinic, school) is expected to continue (sustain) in the absence of external (agency) support. The second, termed 'Static Sustainment Support', involves the provision of pre-defined external (agency) support to assist organisations to continue implementation of an EBI. The final approach is termed 'Dynamic Sustainment Support', whereby support provided by an external agency is dynamic (continues to be adapted) overtime to assist organisations continue implementation of an intervention which may itself also evolve. CONCLUSIONS: We describe the contexts and circumstances where each may be most appropriate in achieving sustained implementation and discuss their research and practice implications.

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/.

Five-Year Mortality Outcomes for Eating As Treatment (EAT), a Health Behavior Change Intervention to Improve Nutrition in Patients With Head and Neck Cancer: A Stepped-Wedge, Randomized Controlled Trial.

PURPOSE: Malnutrition affects up to 80% of patients with head and neck cancer (HNC) and is associated with higher burden of disease, poorer treatment outcomes, and greater mortality. The Eating As Treatment (EAT) intervention is a behavioral intervention previously demonstrated to be effective in improving nutritional status, depression, and quality of life in patients with HNC. This article examines the effects of the EAT intervention on 5-year mortality among participants. METHODS AND MATERIALS: A multicenter, stepped-wedge, randomized controlled trial was conducted in 5 Australian hospitals. Dietitians were trained to deliver EAT, a combination of motivational interviewing and cognitive behavior therapy strategies, to patients with HNC receiving radiation therapy. Secondary analyses of survival benefit on an intention-to-treat basis were performed. Differences in proportions of 5-year all-cause mortality between the control and EAT intervention arms were analyzed using multivariable logistic regression, and 5-year survival rates were analyzed using Cox proportional hazards regression. Analyses controlled for temporal effects (study duration), hospital site (clustering), and baseline nutritional status differences. RESULTS: Overall, there were 64 deaths in the 5 years after enrollment, 36 (24%) among those assigned to the control condition and 28 (18%) among those assigned to EAT. Logistic regression showed statistically significant reduced odds in favor of EAT (odds ratio, 0.33; 95% CI, 0.11-0.96), with an absolute risk reduction of 17% (95% CI, 0.01-0.33) and a relative risk reduction of 55% (95% CI, 0.22-0.92), resulting in a number needed to treat of 6 (95% CI, 4-13). Survival analysis revealed that risk of death was significantly reduced by the EAT intervention (hazard ratio, 0.39; 0.16-0.96). CONCLUSIONS: Participation in EAT provided a statistically and clinically meaningful survival benefit, likely via improved nutrition during radiation therapy. This survival benefit strengthens the finding of the main trial, showing that a behavioral intervention focused on nutrition could improve HNC outcomes. Replication studies using stepped-wedge designs for implementation into clinical practice may be warranted.

Motivations for investigating health inequities in observational epidemiology: a content analysis of 320 studies.

OBJECTIVES: To enhance equity in clinical and epidemiological research, it is crucial to understand researcher motivations for conducting equity-relevant studies. Therefore, we evaluated author motivations in a randomly selected sample of equity-relevant observational studies published during the COVID-19 pandemic. STUDY DESIGN AND SETTING: We searched MEDLINE for studies from 2020 to 2022, resulting in 16,828 references. We randomly selected 320 studies purposefully sampled across income setting (high vs low-middle-income), COVID-19 topic (vs non-COVID-19), and focus on populations experiencing inequities. Of those, 206 explicitly mentioned motivations which we analyzed thematically. We used discourse analysis to investigate the reasons behind emerging motivations. RESULTS: We identified the following motivations: (1) examining health disparities, (2) tackling social determinants to improve access, and (3) addressing knowledge gaps in health equity. Discourse analysis showed motivations stem from commitments to social justice and recognizing the importance of highlighting it in research. Other discourses included aspiring to improve health-care efficiency, wanting to understand cause-effect relationships, and seeking to contribute to an equitable evidence base. CONCLUSION: Understanding researchers' motivations for assessing health equity can aid in developing guidance that tailors to their needs. We will consider these motivations in developing and sharing equity guidance to better meet researchers' needs.

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.

Informing the development of the SUCCEED reporting guideline for studies on the scaling of health interventions: A systematic review.

BACKGROUND: Quality reporting contributes to effective translation of health research in practice and policy. As an initial step in the development of a reporting guideline for scaling, the Standards for reporting stUdies of sCaling evidenCEd-informED interventions (SUCCEED), we performed a systematic review to identify relevant guidelines and compile a list of potential items. METHODS: We conducted a systematic review according to Cochrane method guidelines. We searched the following databases: MEDLINE, Embase, PsycINFO, Cochrane Library, CINAHL, Web of Science, from their respective inceptions. We also searched websites of relevant organizations and Google. We included any document that provided instructions or recommendations, e.g., reporting guideline, checklist, guidance, framework, standard; could inform the design or reporting of scaling interventions; and related to the health sector. We extracted characteristics of the included guidelines and assessed their methodological quality using a 3-item internal validity assessment tool. We extracted all items from the guidelines and classified them according to the main sections of reporting guidelines (title, abstract, introduction, methods, results, discussion and other information). We performed a narrative synthesis based on descriptive statistics. RESULTS: Of 7704 records screened (published between 1999 and 2019), we included 39 guidelines, from which data were extracted from 57 reports. Of the 39 guidelines, 17 were for designing scaling interventions and 22 for reporting implementation interventions. At least one female author was listed in 31 guidelines, and 21 first authors were female. None of the authors belonged to the patient stakeholder group. Only one guideline clearly identified a patient as having participated in the consensus process. More than half the guidelines (56%) had been developed using an evidence-based process. In total, 750 items were extracted from the 39 guidelines and distributed into the 7 main sections. CONCLUSION: Relevant items identified could inform the development of a reporting guideline for scaling studies of evidence-based health interventions. This and our assessment of guidelines could contribute to better reporting in the science and practice of scaling.

Unpacking the cost of the lunchbox for Australian families: a secondary analysis.

Ninety per cent of Australian school children bring a home-packed lunch to school, with 44% of the food consumed during school hours being unhealthy. Among other factors, cost is a key consideration for food provision; however, the costs to Australian families are not well understood. Therefore, we aimed to determine what families are currently paying for school lunchboxes in Australian primary schools and to examine associations between food costs and socio-demographic factors with dietary quality. An audit of local retail outlets was used to determine the food costs of lunchbox contents. Costs (AUD) were adjusted for inflation as of early 2023. The lunchboxes of 1026 children aged 4-12 years at 12 Catholic primary schools in New South Wales, Australia, were assessed at the start of the day, using photography assessment methods and a validated School Food Checklist. The mean cost of lunchbox contents was $4.48 AUD (SD 1.53), containing a mean energy of 2699 kJ (SD 859), with 37.3% (SD 23.9) of energy sourced from unhealthy foods. Multiple linear regression analyses found that the strongest predictors of higher lunchbox cost (P < 0.05) were a higher proportion of energy from unhealthy foods (B = 0.016) and lower Socio-Economic Indexes for Areas (B = -0.178), when controlling for child socio-demographics. The results indicated that lunchbox food costs to Australian families are comparable to alternative school food service models in Australia and internationally. Results demonstrate the cost of food is not the only barrier to providing a healthy school lunchbox. Demonstrating a need for cost-considerate systematic interventions addressing food provision challenges and socio-economic disparities faced by families.

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.

A bibliographic review of sustainability research output and investment in 10 leading public health journals across three time periods.

Objectives: Long-term delivery, or sustainability, of evidence-based interventions is necessary for public health benefits to be realised. However, sustainment of effective interventions is poor. Understanding the evidence-base and identifying potential gaps is necessary to inform where future research efforts are most warranted. Study design: We undertook a repeat cross-sectional bibliographic review of research published in 10 public health journals across three time periods (2010, 2015 and 2020/2021). Methods: Studies were eligible if they were a data-based study or review article. Studies were assessed as to whether they focused on sustainability. The percentage of public health research studies assessing sustainability overall and by the three time periods was calculated. The association between time period and the proportion of sustainability articles was assessed using logistic regression. Descriptive statistics were used to summarise study characteristics overall and by time period. Results: 10,588 data-based articles were identified, of which 1.3 % (n = 136) focused on sustainability. There was a statistically significant association between time period and the proportion of sustainability research, with a slight increase across the three time periods: 0.3 % (95 % CI: 0.1 %, 0.7 %) in 2010, 1.4 % (95 % CI: 1.0 %, 1.9 %) in 2015 and 1.6 % (95 % CI: 1.3 %, 1.9 %) in 2020/2021. Most research was descriptive/epidemiological (n = 69, 51 %), few focused on measurement (n = 2, 1.5 %) and none on cost effectiveness. Only one intervention study assessed the effect of specific sustainability strategies. Conclusions: This bibliographic review highlights the need for more public health research on sustainability, particularly in the areas of measurement, sustainability interventions, and cost effectiveness.

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.

Evaluation of an implementation support package to increase community mental health clinicians' routine delivery of preventive care for multiple health behaviours: a non-randomised controlled trial.

BACKGROUND: People with a mental health condition are more likely to engage in risk behaviours compared to people without. Delivery of preventive care to improve such behaviours is recommended for community mental health services, but inadequately implemented. This study assessed the effectiveness of an implementation support package on clinicians' delivery of preventive care (assessment, advice, referral) for four risk behaviours (tobacco smoking, harmful alcohol consumption, physical inactivity, inadequate fruit and vegetable intake) compared to no implementation support. The participatory approach to developing the support package, and fidelity of the implementation strategies, are also described. METHODS: A non-randomised controlled trial was undertaken in 2019-2020 with two community mental health services (control and target) in one health district in New South Wales, Australia. A 4-month support package consisting of multiple implementation strategies was delivered to one site following a two-phase participatory design process. Five implementation strategies were proposed to service managers by researchers. After consultation with managers and clinicians, the final implementation support package included four strategies: training and education materials, enabling resources and prompts, client activation material, and audit and feedback. Client-reported receipt of the three elements of preventive care for the four risk behaviours was collected from a cross-sectional sample of clients who had recently attended the service at baseline (6 months) and follow-up (5 months). Logistic regression models examined change in receipt of preventive care to assess effectiveness. RESULTS: A total of 860 client surveys were completed (control baseline n = 168; target baseline n = 261; control follow-up n = 164; and target follow-up n = 267). Analyses revealed no significant differential changes in preventive care receipt between the target and control sites from baseline to follow-up, including across the four primary outcomes: assessed for all behaviours (OR = 1.19; 95% CI 0.55, 2.57; p = 0.65); advised for all relevant risk behaviours (OR = 1.18; 95% CI 0.39, 3.61; p = 0.77); referred for any relevant risk behaviour (OR = 0.80; 95% CI 0.40, 1.63; p = 0.55); and complete care (OR = 3.11; 95% CI 0.62, 15.63; p = 0.17). Fidelity of the implementation strategies was limited as one of the four strategies (audit and feedback) was not delivered, components of two strategies (enabling resources and prompts, and client activation material) were not delivered as intended, and one strategy (education and training) was delivered as intended although some components were offered late in the implementation period. CONCLUSIONS: The implementation support package was ineffective at increasing preventive care delivery. Further investigation is required to determine optimal participatory design methods to develop effective implementation strategies, including those that support delivery of care in community mental health settings within the ongoing context of uncertain environmental challenges. TRIAL REGISTRATION: Australian and New Zealand Clinical Trials Registry ACTRN12619001379101.