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.

Schools are identified as a key setting to influence children’s and adolescents’ healthy eating. This umbrella review synthesised evidence from systematic reviews of school-based nutrition interventions designed to improve dietary intake outcomes in children aged 6 to 18 years. We undertook a systematic search of six electronic databases and grey literature to identify relevant reviews of randomized controlled trials. The review findings were categorised for synthesis by intervention type according to the World Health Organisation Health Promoting Schools (HPS) framework domains: nutrition education; food environment; all three HPS framework domains; or other (not aligned to HPS framework domain). Thirteen systematic reviews were included. Overall, the findings suggest that school-based nutrition interventions, including nutrition education, food environment, those based on all three domains of the HPS framework, and eHealth interventions, can have a positive effect on some dietary outcomes, including fruit, fruit and vegetables combined, and fat intake. These results should be interpreted with caution, however, as the quality of the reviews was poor. Though these results support continued public health investment in school-based nutrition interventions to improve child dietary intake, the limitations of this umbrella review also highlight the need for a comprehensive and high quality systematic review of primary studies.

Digital food environments are now commonplace across many food service and retail settings, influencing how the population orders and accesses foods. As such, digital food environments represent a novel platform to deliver strategies to improve public health nutrition. The purpose of this review was to explore the impact of dietary interventions embedded within online food ordering systems, on user selection and purchase of healthier foods and beverages. A systematic search of eight electronic databases and grey literature sources was conducted up to October 2020. Eligible studies were randomized controlled trials and controlled trials, designed to encourage the selection and purchase of healthier products and/or discourage the selection and purchase of less-healthy products using strategies delivered via real-world online food ordering systems. A total of 9441 articles underwent title and abstract screening, 140 full-text articles were assessed for eligibility, and 11 articles were included in the review. Meta-analysis of seven studies indicated that interventions delivered via online food ordering systems are effective in reducing the energy content of online food purchases (standardized mean difference (SMD): −0.34, p = 0.01). Meta-analyses including three studies each suggest that these interventions may also be effective in reducing the fat (SMD: −0.83, p = 0.04), saturated fat (SMD: −0.7, p = 0.008) and sodium content (SMD: −0.43, p = 0.01) of online food purchases. Given the ongoing growth in the use of online food ordering systems, future research to determine how we can best utilize these systems to support public health nutrition is warranted.

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

There has been a proliferation of digital health interventions (DHIs) targeting dietary intake. Despite their potential, the effectiveness of DHIs are thought to be dependent, in part, on user engagement. However, the relationship between engagement and the effectiveness of dietary DHIs is not well understood. The aim of this review is to describe the association between DHI engagement and dietary intake. A systematic search of four electronic databases and grey literature for records published before December 2019 was conducted. Studies were eligible if they examined a quantitative association between objective measures of engagement with a DHI (subjective experience or usage) and measures of dietary intake in adults (aged ≥18 years). From 10,653 citations, seven studies were included. Five studies included usage measures of engagement and two examined subjective experiences. Narrative synthesis, using vote counting, found mixed evidence of an association with usage measures (5 of 12 associations indicated a positive relationship, 7 were inconclusive) and no evidence regarding an association with subjective experience (both studies were inconclusive). The findings provide early evidence supporting an association between measures of usage and dietary intake; however, this was inconsistent. Further research examining the association between DHI engagement and dietary intake is warranted.

Background: School food outlets represent a key setting for public health nutrition intervention. The recent proliferation of web-based food ordering systems provides a unique opportunity to support healthy purchasing from schools. Embedding evidence-based choice architecture strategies within these routinely used systems provides the opportunity to impact the purchasing decisions of many users simultaneously and warrants investigation. Objective: This study aims to assess the effectiveness of a multistrategy behavioral intervention implemented via a web-based school canteen lunch ordering system in reducing the energy, saturated fat, sugar, and sodium content of primary students’ web-based lunch orders. Methods: The study used a parallel-group, cohort, cluster randomized controlled trial design with 2207 students from 17 Australian primary schools. Schools with a web-based canteen lunch ordering system were randomly assigned to receive either a multistrategy behavioral intervention that included choice architecture strategies embedded in the web-based system (n=9 schools) or the standard web-based ordering system only (n=8 control schools). Automatically collected student purchasing data at baseline (term 2, 2018) and 12 months later (term 2, 2019) were used to assess trial outcomes. Primary trial outcomes included the mean energy (kJ), saturated fat (g), sugar (g), and sodium (mg) content of student lunch orders. Secondary outcomes included the proportion of all web-based lunch order items classified as everyday, occasional, and caution (based on the New South Wales Healthy School Canteen Strategy) and canteen revenue. Results: From baseline to follow-up, the intervention lunch orders had significantly lower energy content (−69.4 kJ, 95% CI −119.6 to −19.1; P=.01) and saturated fat content (−0.6 g, 95% CI −0.9 to −0.4; P<.001) than the control lunch orders, but they did not have significantly lower sugar or sodium content. There was also a small significant between-group difference in the percentage of energy from saturated fat (−0.9%, 95% CI −1.4% to −0.5%; P<.001) but not in the percentage of energy from sugar (+1.1%, 95% CI 0.2% to 1.9%; P=.02). Relative to control schools, intervention schools had significantly greater odds of having everyday items purchased (odds ratio [OR] 1.7, 95% CI 1.5-2.0; P<.001), corresponding to a 9.8% increase in everyday items, and lower odds of having occasional items purchased (OR 0.7, 95% CI 0.6-0.8; P<.001), corresponding to a 7.7% decrease in occasional items); however, there was no change in the odds of having caution (least healthy) items purchased (OR 0.8, 95% CI 0.7-1.0; P=.05). Furthermore, there was no change in schools’ revenue between groups. Conclusions: Given the evidence of small statistically significant improvements in the energy and saturated fat content, acceptability, and wide reach, this intervention has the potential to influence dietary choices at a population level, and further research is warranted to determine its impact when implemented at scale. Trial Registration: Australian New Zealand Clinical Trials Registry (ANZCTR) ACTRN12618000855224; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=375075. International Registered Report Identifier (IRRID): RR2-10.1136/bmjopen-2019-030538