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.

Evaluating the scaling up of an effective implementation intervention (PACE) to increase the delivery of a mandatory physical activity policy in primary schools.

BACKGROUND: Physically Active Children in Education (PACE) is an effective implementation intervention for increasing the number of minutes classroom teachers schedule physical activity each week. To date, evaluations of PACE have included a smaller number of schools from only one region in New South Wales Australia. If PACE is to have population-wide benefits we must be able to deliver this support to a larger number of schools across multiple regions. This study aimed to evaluate the scale-up of PACE. METHODS: An uncontrolled before and after study, with 100 schools from three regions was conducted. Participating schools received PACE for approximately 12 months. We assessed the following outcomes: delivery of the evidence-based intervention (EBI) (i.e. minutes of physical activity scheduled by classroom teachers per week); delivery of the implementation strategies (i.e. reach, dose delivered, adherence and indicators of sustainability); and key determinants of implementation (i.e. acceptability of strategies and cost). Data were collected via project officer records, and principal and teacher surveys. Linear mixed models were used to assess EBI delivery by evaluating the difference in the mean minutes teachers scheduled physical activity per week from baseline to follow-up. Descriptive data were used to assess delivery of the implementation strategies and their perceived acceptability (i.e. PACE). A prospective, trial-based economic evaluation was used to assess cost. RESULTS: Delivery of the EBI was successful: teachers increas their average minutes of total physical activity scheduled across the school week by 26.8 min (95% CI: 21.2, 32.4, p < 0.001) after receiving PACE. Indicators for delivery of implementation strategies were high: 90% of consenting schools received all strategies and components (reach); 100% of strategies were delivered by the provider (dose); >50% of schools adhered to the majority of strategies (11 of the 14 components); and acceptability was > 50% agreement for all strategies. The incremental cost per additional minute of physical activity scheduled per week was $27 per school (Uncertainty Interval $24, $31). CONCLUSIONS: PACE can be successfully delivered across multiple regions and to a large number of schools. Given the ongoing and scalable benefits of PACE, it is important that we continue to extend and improve this program while considering ways to reduce the associated cost.

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

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

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

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

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

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

A cluster randomised controlled trial to assess the effectiveness of a multi-strategy sustainability intervention on teachers' sustained implementation of classroom physical activity breaks (energisers): study protocol.

BACKGROUND: Governments internationally have invested hugely in the implementation and scale-up of school-based physical activity interventions, but have little evidence of how to best sustain these interventions once active implementation support ceases. This study will assess the effectiveness of a multi-strategy sustainability intervention on classroom teachers' sustainment of energisers (short 3-5 min physical activity breaks during class-time) scheduled across the school day from baseline to 12 and 24-month follow-up. METHODS: A cluster randomised controlled trial will be conducted in 50 primary schools within the Hunter New England, Illawarra Shoalhaven, Murrumbidgee and Northern New South Wales (NSW) Local Health Districts of NSW Australia. Schools will be randomly allocated to receive either usual support or the multi-strategy sustainability intervention that includes: centralised technical assistance from a trained project officer; formal commitment and mandated change obtained from school principals; training in-school champions; reminders for teachers; educational materials provided to teachers; capturing and sharing local knowledge; and engagement of parents, carers and the wider school community. The primary trial outcome will be measured via a teacher logbook to determine the between-group difference in the change in mean minutes of energisers scheduled across the school day at 12 and 24-month follow-up compared to baseline. Analyses will be performed using an intention to treat framework. Linear mixed models will be used to assess intervention effects on the primary outcome at both follow-up periods. DISCUSSION: This study will be one of the first randomised controlled trials to examine the impact of a multi-strategy sustainability intervention to support schools' sustainment of a physical activity intervention. The proposed research will generate new evidence needed for the partnering organisations to protect their considerable investments to date in physical activity promotion in this setting and will provide seminal evidence for the field globally. TRIAL REGISTRATION: ACTRN12620000372987 version 1 registered 17th March 2020. Version 3 (current version) updated 4th August 2023.

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

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

Prevalence and type of unmet needs experienced by carers of people living with dementia.

OBJECTIVES: Carers of people with dementia experience significant physical, emotional, and social burdens. Needs assessment can provide important information to assist services in providing support to carers to reduce these burdens. However, few studies have examined the prevalence of unmet needs experienced by carers of people with dementia using a quantitative instrument. This study aimed to examine the prevalence and type of unmet needs experienced by carers of people with dementia in Australia. METHODS: This was a cross-sectional survey of carers providing support to community-dwelling individuals living with dementia. Carers were recruited through geriatric clinics, aged care providers, support services and community organisations. Consenting carers completed a survey including an 80-item study-specific unmet needs instrument for carers (UNI-C) and sociodemographic characteristics. Descriptive statistics were used to identify the most prevalent unmet needs reported by carers. RESULTS: A total of 169 carers (response rate 47%) completed the survey. Most (87%) carers reported at least one unmet need. Carers reported a median of 16.0 (IQR = 24.0; max = 58) out of a possible 80 unmet needs. The most frequently endorsed unmet needs spanned a range of areas including emotional wellbeing, accessing health and aged care services, managing apathy, and finding information. CONCLUSION: This study highlighted that a large proportion of carers experience unmet needs associated with caring for someone with dementia. Developing and rigorously testing interventions to meet carers' commonly reported unmet needs are warranted.Supplemental data for this article is available online at https://doi.org/10.1080/13607863.2022.2053833 .

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

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

Identifying essential implementation strategies: a mixed methods process evaluation of a multi-strategy policy implementation intervention for schools.

BACKGROUND: Physically Active Children in Education (PACE) is composed of eight implementation strategies that improves schools' implementation of a government physical activity policy. A greater understanding of each discrete implementation strategy could inform improvements to PACE for delivery at-scale. This study aimed to: (A) measure the dose delivered, fidelity, adoption and acceptability of each strategy using quantitative data; (B) identify implementation barriers and facilitators using qualitative data; and (C) explore the importance of each strategy by integrating both data sets (mixed methods). METHODS: This study used data from a cluster randomised noninferiority trial comparing PACE with an adapted version (Adapted PACE) that was delivered with reduced in-person external support to reduce costs and increase scalability. Data were collected from both trials arms for between-group comparison. Descriptive statistics were produced using surveys of principals, in-school champions and teachers; and project records maintained by PACE project officers (objective A). Thematic analysis was performed using in-school champion and project officer interviews (objective B). Both data sets were integrated via a triangulation protocol and findings synthesized in the form of meta-inferences (objective C). RESULTS: Eleven in-school champions and six project officers completed interviews; 33 principals, 51 in-school champions and 260 teachers completed surveys. Regardless of group allocation, implementation indicators were high for at least one component of each strategy: dose delivered =100%, fidelity ≥95%, adoption ≥83%, acceptability ≥50%; and several implementation barriers and facilitators were identified within three broad categories: external policy landscape, inner organizational structure/context of schools, and intervention characteristics and processes. All strategies were considered important as use varied by school, however support from a school executive and in-school champions' interest were suggested as especially important for optimal implementation. CONCLUSION: This study highlights the importance of both executive support and in-school champions for successful implementation of school physical activity policies. In particular, identifying and supporting an in-school champion to have high power and high interest is recommended for future implementation strategies. This may reduce the need for intensive external support, thus improving intervention scalability.

Optimising a multi-strategy implementation intervention to improve the delivery of a school physical activity policy at scale: findings from a randomised noninferiority trial.

BACKGROUND: To maximise their potential health benefits, school-based physical activity policies need to be implemented at scale. This paper describes the third in a sequence of trials that sought to optimise an effective strategy (PACE) to assist schools' implementation of a physical activity policy. Specifically, it aimed to determine the probability that a multi-strategy intervention adapted to reduce in-person contact (Adapted PACE) was "as good as" the original intervention (PACE) in increasing the weekly minutes of structured physical activity implemented by classroom teachers. METHODS: A noninferiority cluster randomised controlled trial was undertaken with 48 primary schools in New South Wales, Australia. Schools were randomised to receive PACE or a model with adaptations made to the delivery modes (Adapted PACE). Teachers' scheduled minutes of weekly physical activity was assessed at baseline (Oct 2018-Feb 2019) and 12-month follow-up (Oct-Dec 2019). The noninferiority margin was set at - 16.4 minutes based on previous data and decision panel consensus. A linear mixed model analysed within a Bayesian framework was used to explore noninferiority between the two PACE models. A cost minimisation analysis was conducted from the health service provider perspective, using the Australian dollar (AUD). RESULTS: The posterior estimate for the between group difference at follow-up was - 2.3 minutes (95% credible interval = - 18.02, 14.45 minutes). There was an estimated 96% probability of Adapted PACE being considered noninferior (only 4% of the posterior samples crossed the noninferiority margin of - 16.4 minutes). That is, the minutes of physical activity implemented by teachers at Adapted PACE schools was not meaningfully less than the minutes of physical activity implemented by teachers at PACE schools. The mean total cost was AUD$25,375 (95% uncertainty interval = $21,499, $29,106) for PACE and AUD$16,421 (95% uncertainty interval = $13,974, $19,656) for Adapted PACE; an estimated reduction of AUD$373 (95% uncertainty interval = $173, $560) per school. CONCLUSIONS: It is highly probable that Adapted PACE is noninferior to the original model. It is a cost-efficient alternative also likely to be a more suitable approach to supporting large scale implementation of school physical activity policies. TRIAL REGISTRATION: Retrospectively registered with the Australian New Zealand Clinical Trials Registry (ACTRN12619001229167).

Video-telehealth to support clinical assessment and management of acutely unwell older people in Residential Aged Care: a pre-post intervention study.

BACKGROUND: Older people living in Residential Aged Care (RAC) are at high risk of clinical deterioration. Telehealth has the potential to provide timely, patient-centred care where transfer to hospital can be a burden and avoided. The extent to which video telehealth is superior to other forms of telecommunication and its impact on management of acutely unwell residents in aged care facilities has not been explored previously. METHODS: In this study, video-telehealth consultation was added to an existing program, the Aged Care Emergency (ACE) program, aiming at further reducing Emergency Department (ED) visits and hospital admissions. This controlled pre-post study introduced video-telehealth consultation as an additional component to the ACE program for acutely unwell residents in RACs. Usual practice is for RACs and ACE to liaise via telephone. During the study, when the intervention RACs called the ED advanced practice nurse, video-telehealth supported clinical assessment and management. Five intervention RACs were compared with eight control RACs, all of whom refer to one community hospital in regional New South Wales, Australia. Fourteen months pre-video-telehealth was compared with 14 months post-video-telehealth using generalized linear mixed models for hospital admissions after an ED visit and ED visits. One thousand two hundred seventy-one ED visits occurred over the 28-month study period with 739 subsequent hospital admissions. RESULTS: There were no significant differences in hospital admission or ED visits after the introduction of video-telehealth; adjusted incident rate ratios (IRR) were 0.98 (confidence interval (CI) 0.55 to 1.77) and 0.89 (95% CI 0.53 to 1.47) respectively. CONCLUSIONS: Video-telehealth did not show any incremental benefit when added to a structured hospital avoidance program with nursing telephone support. TRIAL REGISTRATION: The larger Aged Care Emergency evaluation is registered with ANZ Clinical Trials Registry, ACTRN12616000588493.

School-level factors associated with the sustainment of weekly physical activity scheduled in Australian elementary schools: an observational study.

BACKGROUND: We aimed to: (1) identify school-level factors associated with the sustainment of weekly physical activity (PA) scheduled in elementary schools following withdrawal of effective implementation support; and (2) determine teacher's perceived usefulness of suggested strategies for sustaining the scheduling of weekly PA. METHODS: A secondary exploratory analysis was employed of data from the intervention arm (n = 31 schools) of a randomised controlled trial. Self-report survey data from 134 classroom teachers in New South Wales, Australia, collected following withdrawal of initial implementation support (follow-up T1) and six-months following completion of support (follow-up T2) were used. The outcomes of sustainment of weekly overall PA and energisers (short classroom PA breaks) scheduled were measured via teachers' completion of a daily activity logbook, with results presented as the difference in mean minutes of PA and energisers scheduled at T1 and T2. An adapted version of the Program Sustainability Assessment Tool (PSAT) was used to measure capacity for program sustainability across seven key domains at follow-up T2. Linear mixed regressions were conducted to evaluate associations between school-level sociodemographic characteristics (e.g., school size, remoteness, and type), teacher-reported school factors (i.e., seven adapted PSAT domains) and the sustainment of PA and energisers scheduled across the school week. Perceived usefulness of 14 proposed sustainability strategies was measured via the teacher survey at follow-up T2 and reported descriptively. RESULTS: No school-level factor was statistically associated with the sustainment of overall weekly PA or energisers scheduled. Teacher-reported factors in two PSAT domains - 'strategic planning' and 'program evaluation' were statistically negatively associated with the sustainment of weekly energisers scheduled (- 6.74, 95% CI: - 13.02; - 0.47, p = 0.036 and - 6.65, 95% CI: - 12.17; - 1.12, p = 0.019 respectively). The proposed support sustainability strategy - 'provision of PA equipment packs that enable energisers or integrated lessons' was perceived useful by the most teachers (85%). CONCLUSIONS: Further research is required to explore additional contextual-specific, and end-user appropriate factors associated with schools' sustainment of weekly PA scheduled. This will help accurately inform the development of strategies to address these determinants and support the sustainment and long-term benefits of school-based health interventions more broadly.

Multi-strategy intervention increases school implementation and maintenance of a mandatory physical activity policy: outcomes of a cluster randomised controlled trial.

OBJECTIVES: To assess if a multi-strategy intervention effectively increased weekly minutes of structured physical activity (PA) implemented by classroom teachers at 12 months and 18 months. METHODS: A cluster randomised controlled trial with 61 primary schools in New South Wales Australia. The 12-month multi-strategy intervention included; centralised technical assistance, ongoing consultation, principal's mandated change, identifying and preparing school champions, development of implementation plans, educational outreach visits and provision of educational materials. Control schools received usual support (guidelines for policy development via education department website and telephone support). Weekly minutes of structured PA implemented by classroom teachers (primary outcome) was measured via teacher completion of a daily log-book at baseline (October-December 2017), 12-month (October-December 2018) and 18-month (April-June 2019). Data were analysed using linear mixed effects regression models. RESULTS: Overall, 400 class teachers at baseline, 403 at 12 months follow-up and 391 at 18 months follow-up provided valid primary outcome data. From baseline to 12-month follow-up, teachers at intervention schools recorded a greater increase in weekly minutes of PA implemented than teachers assigned to the control schools by approximately 44.2 min (95% CI 32.8 to 55.7; p<0.001) which remained at 18 months, however, the effect size was smaller at 27.1 min (95% CI 15.5 to 38.6; p≤0.001). CONCLUSION: A multi-strategy intervention increased mandatory PA policy implementation. Some, but not all of this improvement was maintained after implementation support concluded. Further research should assess the impact of scale-up strategies on the sustainability of PA policy implementation over longer time periods. TRIAL REGISTRATION NUMBER: Australian New Zealand Clinical Trials Registry (ACTRN12617001265369).

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

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

Exploring the effect of a school-based cluster-randomised controlled trial to increase the scheduling of physical activity for primary school students on teachers' physical activity.

BACKGROUND: To determine if a school-based physical activity (PA) intervention that supported primary school teachers to schedule PA during school hours impacted their own PA. METHODS: A 2x2 factorial group cluster-randomised controlled trial was undertaken in 12 Australian primary schools. The nine-month intervention supported classroom teachers to increase scheduled weekly PA for their class via physical education, sport, Energisers and integrated lessons. Teachers' PA (n = 76) was measured at follow-up only using accelerometers (Actigraph GT3X or GT9X). Linear mixed models were used to estimate between-group differences in teachers' mean minutes of sedentary, light, moderate-to-vigorous-intensity physical activity (MVPA) across the school day and during class-time. RESULTS: At follow-up, there were non-significant between-group differences favouring intervention teachers, compared to controls, for light PA (4.9 minutes, 95% CI: -6.3, 16.0; P = .33) and MVPA (0.4 minutes, 95% CI: -10.9, 11.6; P = .94) across the school day; although not favouring the intervention for sedentary behaviour (5.1 minutes, 95% CI: -11.4, 21.7; P = .48). Similar patterns were seen during class-time for light PA and sedentary time, but not for MVPA. CONCLUSIONS: Supporting teachers with the scheduling of PA for their class may impact on their own PA. Fully powered studies are needed to better understand the impact of the intervention on teachers' PA. TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry (ANZCTR) ACTRN12616001228471 (http://www.anzctr.org.au/).

The impact of school uniforms on primary school student's physical activity at school: outcomes of a cluster randomized controlled trial.

BACKGROUND: Many school-based physical activity (PA) interventions are complex and have modest effects when delivered in real world contexts. A commonly reported barrier to students' PA, particularly among girls, are uniforms that are impractical (e.g. tunic/dress and black leather shoes). Modifying student uniforms may represent a simple intervention to enhance student PA. The primary aim of this trial was to assess the impact of a PA enabling uniform intervention (shorts, polo shirt and sports shoes) on girls' moderate-to-vigorous physical activity (MVPA) and total PA i.e. counts per minute (cpm). METHODS: A cluster randomized controlled trial was undertaken in 42 primary schools in New South Wales, Australia. Schools were randomized on one school day to the intervention group, where students wore a PA enabling uniform (their sports uniform) or a control group, where students wore their usual traditional uniform. Student PA was measured using wrist-worn Actigraph GT3X and GT9X accelerometers. Linear mixed models controlling for student characteristics were used to examine the effects of the intervention.. RESULTS: Of the 3351 eligible students, 2315 (69.1%) had parental consent and 2180 of these consenting students participated (94.2%) of which 1847 (84.7%) were included in the analysis. For the primary aim the study found no significant differences between girls at schools allocated to the intervention relative to the control on change in MVPA (0.76 min, 95% CI - 0.47 to 1.99, p = 0.22) or cpm (36.99, 95% CI - 13.88 to 87.86, p = 0.15). Exploratory analysis revealed small effects for a number of findings, including significant reduction in sedentary activity (- 1.77, 95% CI - 3.40 to - 0.14, p = 0.035) among all students at schools allocated to the intervention, and non-significant improvements in girls' light intensity PA (1.47 min, 95% CI - 0.06 to 3.00, p = 0.059) and sedentary activity (- 2.23 min; 95% CI - 4.49 to 0.02, p = 0.052). CONCLUSION: The findings suggests that the intervention may yield small improvements in some measure of PA and require substantiation in a larger RCT with longer-term follow-up. The inclusion of additional intervention components may be required to achieve more meaningful effects. TRIAL REGISTRATION: The trial was prospectively registered with Australian New Zealand Clinical Trials Register ACTRN12617001266358 1st September 2017.

Efficacy of a school-based physical activity and nutrition intervention on child weight status: Findings from a cluster randomized controlled trial.

Despite the benefits of factorial designs in quantifying the relative benefits of different school-based approaches to prevent unhealthy weight gain among students, few have been undertaken. The aims of this 2 × 2 cluster randomized factorial trial was to evaluate the impact of a physical activity and nutrition intervention on child weight status and quality of life. Twelve primary schools in New South Wales, Australia randomly allocated to one of four groups: (i.) physical activity (150 min of planned in-school physical activity); (ii.) nutrition (a healthy school lunch-box); (iii.) combined physical activity and nutrition; or (iv.) control. Outcome data assessing child weight and quality of life were collected at baseline and 9-months post-baseline. Within Grades 4-6 in participating schools, 742 students participated in anthropometric measurements, including child body mass index (BMI) and waist circumference, at baseline and follow-up. Findings indicated that students that received the nutrition intervention had higher odds of being classified in the BMI category of underweight/healthy weight (OR 1.64 95%CI 1.07, 2.50; p = 0.0220), while those who received the physical activity intervention reported a lower waist circumference (mean difference - 1.86 95%CI -3.55, -0.18; p = 0.030). There were no significant effects of the nutrition or physical activity intervention on child BMI scores or child quality of life, and no significant synergistic effects of the two interventions combined. Future research assessing the longer-term impact of both intervention strategies, alone and combined, is warranted to better understand their potential impact on child health. TRIAL REGISTRATION: Australian Clinical Trials Registry ACTRN: ACTRN12616001228471.

Associations Between Digital Health Intervention Engagement, Physical Activity, and Sedentary Behavior: Systematic Review and Meta-analysis.

BACKGROUND: The effectiveness of digital health interventions is commonly assumed to be related to the level of user engagement with the digital health intervention, including measures of both digital health intervention use and users' subjective experience. However, little is known about the relationships between the measures of digital health intervention engagement and physical activity or sedentary behavior. OBJECTIVE: This study aims to describe the direction and strength of the association between engagement with digital health interventions and physical activity or sedentary behavior in adults and explore whether the direction of association of digital health intervention engagement with physical activity or sedentary behavior varies with the type of engagement with the digital health intervention (ie, subjective experience, activities completed, time, and logins). METHODS: Four databases were searched from inception to December 2019. Grey literature and reference lists of key systematic reviews and journals were also searched. Studies were eligible for inclusion if they examined a quantitative association between a measure of engagement with a digital health intervention targeting physical activity and a measure of physical activity or sedentary behavior in adults (aged ≥18 years). Studies that purposely sampled or recruited individuals on the basis of pre-existing health-related conditions were excluded. In addition, studies were excluded if the individual engaging with the digital health intervention was not the target of the physical activity intervention, the study had a non-digital health intervention component, or the digital health interventions targeted multiple health behaviors. A random effects meta-analysis and direction of association vote counting (for studies not included in meta-analysis) were used to address objective 1. Objective 2 used vote counting on the direction of the association. RESULTS: Overall, 10,653 unique citations were identified and 375 full texts were reviewed. Of these, 19 studies (26 associations) were included in the review, with no studies reporting a measure of sedentary behavior. A meta-analysis of 11 studies indicated a small statistically significant positive association between digital health engagement (based on all usage measures) and physical activity (0.08, 95% CI 0.01-0.14, SD 0.11). Heterogeneity was high, with 77% of the variation in the point estimates explained by the between-study heterogeneity. Vote counting indicated that the relationship between physical activity and digital health intervention engagement was consistently positive for three measures: subjective experience measures (2 of 3 associations), activities completed (5 of 8 associations), and logins (6 of 10 associations). However, the direction of associations between physical activity and time-based measures of usage (time spent using the intervention) were mixed (2 of 5 associations supported the hypothesis, 2 were inconclusive, and 1 rejected the hypothesis). CONCLUSIONS: The findings indicate a weak but consistent positive association between engagement with a physical activity digital health intervention and physical activity outcomes. No studies have targeted sedentary behavior outcomes. The findings were consistent across most constructs of engagement; however, the associations were weak.

Correction: Associations Between Digital Health Intervention Engagement, Physical Activity, and Sedentary Behavior: Systematic Review and Meta-analysis.

[This corrects the article DOI: 10.2196/23180.].