The Triple E project: a factorial randomised controlled trial to enhance engagement with eHealth approaches to improve health risk behaviours among adolescents.

BACKGROUND: Digital, or eHealth, interventions are highly promising approaches to help adolescents improve their health behaviours and reduce their risk of chronic disease. However, they often have low uptake and retention. There is also a paucity of high-quality research into the predictors of eHealth engagement, and a lack of studies that have systematically evaluated existing engagement strategies in adolescent populations. This paper describes the protocol for a randomised controlled trial which primarily aims to assess the effectiveness of different strategies in increasing engagement with a healthy lifestyles app, Health4Life. Associations between the engagement strategies and improvements in adolescent health behaviours (healthy eating, physical activity, sleep, recreational screen time, smoking, alcohol use) will also be examined, along with potential predictors of adolescents' intentions to use health apps and their use of the Health4Life app. METHODS: The current study will aim to recruit 336 adolescent and parent/guardian dyads (total sample N = 672) primarily through Australia wide online advertising. All adolescent participants will have access to the Health4Life app (a multiple health behaviour change, self-monitoring mobile app). The trial will employ a 24 factorial design, where participants will be randomly allocated to receive 1 of 16 different combinations of the four engagement strategies to be evaluated: text messages, access to a health coach, access to additional gamified app content, and provision of parent/guardian information resources. Adolescents and parents/guardians will both complete consent processes, baseline assessments, and a follow-up assessment after 3 months. All participants will also be invited to complete a qualitative interview shortly after follow-up. The primary outcome, app engagement, will be assessed via an App Engagement Index (Ei) using data collected in the Health4Life app and the Mobile App Rating Scale - User version. DISCUSSION: This research will contribute significantly to building our understanding of the types of strategies that are most effective in increasing adolescents' engagement with health apps and which factors may predict adolescents' use of health apps. TRIAL REGISTRATION: The trial is registered at the Australian New Zealand Clinical Trials Registry (ACTRN12623000399695). Date registered: 19/04/2023.

A Systematic Review and Meta-analysis of School-Based Preventive Interventions Targeting E-Cigarette Use Among Adolescents.

This study aimed to examine the efficacy of school-based e-cigarette preventive interventions via a systematic review and meta-analysis. We searched Medline, Embase, PsycINFO, Scopus, CINAHL, Cochrane, and clinical trial registries for studies published between January 2000 and June 2023 using keywords for e-cigarettes, adolescents, and school. Of 1566 double-screened records, 11 met the criteria of targeting adolescents, evaluating an e-cigarette preventive intervention, being conducted in a secondary school, using a randomized controlled trial (RCT), cluster RCT, or quasi-experimental design, and comparing an intervention to a control. Pre-specified data pertaining to the study design, outcomes, and quality were extracted by one reviewer and confirmed by a second, and where necessary, a third reviewer. Meta-analyses found no evidence that school-based interventions prevented e-cigarette use at the longest follow-up, which ranged between 6 and 36 months post-intervention (OR = 0.43, 95% CI = 0.16, 1.12; p = 0.09). However, subgroup analyses identified significant effects at post-test and when studies with < 12-month follow-up were omitted. No effect was found for tobacco use at the longest follow-up (OR = 1.01, 95% CI = 0.65, 1.59, p = 0.95); however, reductions in past 30-day tobacco use (OR = 0.59, 95% CI = 0.39, 0.89, p = 0.01) which encompassed e-cigarettes in some studies were identified. Narrative synthesis supported these mixed results and found some school-based interventions prevented or reduced e-cigarette and/or tobacco use; however, some increased use. School-based interventions were also associated with improved knowledge (SMD = - 0.38, 95% CI = - 0.68, - 0.08, p = 0.01), intentions (SMD = - 0.15, 95% CI = - 0.22, - 0.07, p = 0.0001), and attitudes (SMD = - 0.14, 95% CI = - 0.22, - 0.06; p = 0.0007) in the short term. Overall, the quality of evidence was low-to-moderate. School-based interventions hold the potential for addressing e-cigarette use, however, can have null or iatrogenic effects. More high-quality research is needed to develop efficacious interventions, and schools must be supported to adopt evidence-based programs. This is the first systematic review and meta-analysis to examine the efficacy of school-based preventive interventions for e-cigarette use. It provides crucial new knowledge about the efficacy of such interventions in preventing e-cigarette use and improving other outcomes (e.g., tobacco use, knowledge, intentions, attitudes, and mental health) among adolescents and the key characteristics associated with efficacious interventions. Our findings have important practical implications, highlighting future research directions for the development and evaluation of e-cigarette preventive interventions, along with the need to provide support to schools to help them identify and adopt evidence-based programs.

Moderating effects of socioeconomic status and geographical location on the Health4Life school-based intervention.

Objective: This study evaluated the moderating effects of socioeconomic status (SES) and geographical location on the efficacy of an eHealth school-based multiple health behaviour change intervention - Health4Life - in targeting alcohol and tobacco use, dietary intake, knowledge, behavioural intentions, and psychological distress over 24-months. Methods: Data from the Health4Life cluster-randomised controlled trial conducted from 2019 to 2021 in 71 Australian secondary schools were analysed (N=6639; baseline age 11-14yrs). Schools were from metropolitan (89%) and regional (11%) areas, and participants' SES was classified as low (15%), mid (37%), and high (48%) relative to the study population. Primary outcomes included alcohol and tobacco use, and a composite indicator of poor diet. Secondary outcomes were knowledge, behavioural intentions, and psychological distress. Latent growth models assessed moderating effects of SES and geographical location on between-group change over 24-months. Results: Geographical location moderated the intervention's effect on odds of reporting a poor diet (OR = 1.79, 95% CI = 1.32-2.43, p < 0.001) and diet-related behavioural intentions (OR = 0.71, 95% CI = 0.56-0.89, p = 0.024) over time. Subset analyses indicated that intervention participants in regional areas had higher odds of reporting a poor diet (OR = 1.61, 95% CI = 1.13-2.29, p = 0.008), while those in metropolitan areas had higher odds of improving diet-related behavioural intentions (OR = 1.13, 95% CI = 1.01-1.27, p = 0.041), compared to the control group. No other significant moderation effects were observed. Conclusions: While significant disparities were generally not observed, the geographical differences in intervention effects on diet and diet-related intentions suggest that co-designed and tailored approaches may benefit disadvantaged adolescents to address the disproportionately high rates of lifestyle risk behaviours among these priority populations.

Vaping among young people-Our best defence is self-defence.

Use of electronic cigarettes (e-cigarettes or 'vapes') has risen rapidly among young Australians in recent years. To combat this, on 2 May 2023, the Albanese Government announced a suite of reforms to reduce the desirability and accessibility of e-cigarettes to young people-including a ban on disposable e-cigarettes, restricting flavours, colours and nicotine content and requiring pharmaceutical-like packaging. While many have welcomed this announcement, the efficacy of such reforms in reducing the availability of e-cigarettes to young people remain to be seen, particularly given the current prescription-only model has done little to curb youth vaping. We argue that, in an uncertain landscape where e-cigarettes will likely remain accessible and desirable to young people, it is critical that we also upskill, empower and arm our young people with the skills, resilience, resources and knowledge to make informed and positive health decisions so that: (i) fewer young people opt to take up vaping (primary prevention); and (ii) among those who already do vape, more seek help earlier on to reduce or cease their use before dependency develops (secondary prevention). Schools are an ideal setting for the delivery of these programs, where they can be delivered en masse, integrated into existing alcohol and other drug programs and aligned with school curricula. Skills-based school prevention programs have demonstrated significant and sustained reductions in drug-related harms up to 7 years post-intervention. For as long as vapes remain widely available, desirable and purposefully marketed towards young people, we believe our best defence is self-defence.

Potential Mediators of a School-Based Digital Intervention Targeting Six Lifestyle Risk Behaviours in a Cluster Randomised Controlled Trial of Australian Adolescents.

Lifestyle risk behaviours-physical inactivity, poor diet, poor sleep, recreational screen time, and alcohol and tobacco use-collectively known as the "Big 6" emerge during adolescence and significantly contribute to chronic disease development into adulthood. To address this issue, the Health4Life program targeted the Big 6 risk behaviours simultaneously via a co-designed eHealth school-based multiple health behaviour change (MHBC) intervention. This study used multiple causal mediation analysis to investigate some potential mediators of Health4Life's effects on the Big 6 primary outcomes from a cluster randomised controlled trial of Health4Life among Australian school children. Mediators of knowledge, behavioural intentions, self-efficacy, and self-control were assessed. The results revealed a complex pattern of mediation effects across different outcomes. Whilst there was a direct effect of the intervention on reducing moderate-to-vigorous physical activity risk, the impact on sleep duration appeared to occur indirectly through the hypothesised mediators. Conversely, for alcohol and tobacco use, both direct and indirect effects were observed in opposite directions cancelling out the total effect (competitive partial mediation). The intervention's effects on alcohol and tobacco use highlighted complexities, suggesting the involvement of additional undetected mediators. However, little evidence supported mediation for screen time and sugar-sweetened beverage intake risk. These findings emphasise the need for tailored approaches when addressing different risk behaviours and designing effective interventions to target multiple health risk behaviours. The trial was pre-registered with the Australian and New Zealand Clinical Trials Registry: ACTRN12619000431123.

Health4Life eHealth intervention to modify multiple lifestyle risk behaviours among adolescent students in Australia: a cluster-randomised controlled trial.

BACKGROUND: Lifestyle risk behaviours are prevalent among adolescents and commonly co-occur, but current intervention approaches tend to focus on single risk behaviours. This study aimed to evaluate the efficacy of the eHealth intervention Health4Life in modifying six key lifestyle risk behaviours (ie, alcohol use, tobacco smoking, recreational screen time, physical inactivity, poor diet, and poor sleep, known as the Big 6) among adolescents. METHODS: We conducted a cluster-randomised controlled trial in secondary schools that had a minimum of 30 year 7 students, in three Australian states. A biostatistician randomly allocated schools (1:1) to Health4Life (a six-module, web-based programme and accompanying smartphone app) or an active control group (usual health education) with the Blockrand function in R, stratified by site and school gender composition. All students aged 11-13 years who were fluent in English and attended participating schools were eligible. Teachers, students, and researchers were not masked to allocation. Primary outcomes were alcohol use, tobacco use, recreational screen time, moderate to vigorous physical activity (MVPA), sugar-sweetened beverage intake, and sleep duration at 24 months, measured by self-report surveys, and analysed in all students who were eligible at baseline. Latent growth models estimated between-group change over time. This trial is registered with the Australian New Zealand Clinical Trials Registry (ACTRN12619000431123). FINDINGS: Between April 1, 2019, and Sept 27, 2019, we recruited 85 schools (9280 students), of which 71 schools with 6640 eligible students (36 schools [3610 students] assigned to the intervention and 35 [3030 students] to the control) completed the baseline survey. 14 schools were excluded from the final analysis or withdrew, mostly due to a lack of time. We found no between-group differences for alcohol use (odds ratio 1·24, 95% CI 0·58-2·64), smoking (1·68, 0·76-3·72), screen time (0·79, 0·59-1·06), MVPA (0·82, 0·62-1·09), sugar-sweetened beverage intake (1·02, 0·82-1·26), or sleep (0·91, 0·72-1·14) at 24 months. No adverse events were reported during this trial. INTERPRETATION: Health4Life was not effective in modifying risk behaviours. Our results provide new knowledge about eHealth multiple health behaviour change interventions. However, further research is needed to improve efficacy. FUNDING: Paul Ramsay Foundation, the Australian National Health and Medical Research Council, the Australian Government Department of Health and Aged Care, and the US National Institutes of Health.

Study protocol of the Our Futures Vaping Trial: a cluster randomised controlled trial of a school-based eHealth intervention to prevent e-cigarette use among adolescents.

BACKGROUND: Effective and scalable prevention approaches are urgently needed to address the rapidly increasing rates of e-cigarette use among adolescents. School-based eHealth interventions can be an efficient, effective, and economical approach, yet there are none targeting e-cigarettes within Australia. This paper describes the protocol of the OurFutures Vaping Trial which aims to evaluate the efficacy and cost-effectiveness of the first school-based eHealth intervention targeting e-cigarettes in Australia. METHODS: A two-arm cluster randomised controlled trial will be conducted among Year 7 and 8 students (aged 12-14 years) in 42 secondary schools across New South Wales, Western Australia and Queensland, Australia. Using stratified block randomisation, schools will be assigned to either the OurFutures Vaping Program intervention group or an active control group (health education as usual). The intervention consists of four web-based cartoon lessons and accompanying activities delivered during health education over a four-week period. Whilst primarily focused on e-cigarette use, the program simultaneously addresses tobacco cigarette use. Students will complete online self-report surveys at baseline, post-intervention, 6-, 12-, 24-, and 36-months after baseline. The primary outcome is the uptake of e-cigarette use at 12-month follow-up. Secondary outcomes include the uptake of tobacco smoking, frequency/quantity of e-cigarettes use and tobacco smoking, intentions to use e-cigarettes/tobacco cigarettes, knowledge about e-cigarettes/tobacco cigarettes, motives and attitudes relating to e-cigarettes, self-efficacy to resist peer pressure and refuse e-cigarettes, mental health, quality of life, and resource utilisation. Generalized mixed effects regression will investigate whether receiving the intervention reduces the likelihood of primary and secondary outcomes. Cost-effectiveness and the effect on primary and secondary outcomes will also be examined over the longer-term. DISCUSSION: If effective, the intervention will be readily accessible to schools via the OurFutures platform and has the potential to make substantial health and economic impact. Without such intervention, young Australians will be the first generation to use nicotine at higher rates than previous generations, thereby undoing decades of effective tobacco control. TRIAL REGISTRATION: The trial has been prospectively registered with the Australian and New Zealand Clinical Trials Registry (ACTRN12623000022662; date registered: 10/01/2023).

Prevalence and correlates of addictive eating behaviours in a large cohort of Australian adolescents.

OBJECTIVE: Research shows highly palatable foods can elicit addictive eating behaviours or 'food addiction'. Early adolescence is theorised to be a vulnerable period for the onset of addictive eating behaviours, yet minimal research has examined this. This study explored the prevalence and correlates of addictive eating behaviours in a large early adolescent sample. METHODS: 6640 Australian adolescents (Mage = 12.7 ± 0.5, 49%F) completed an online survey. Addictive eating was measured with the Child Yale Food Addiction Scale (YFAS-C). Negative-binomial generalised linear models examined associations between addictive eating symptoms and high psychological distress, energy drink consumption, sugar-sweetened beverage (SSB) consumption, alcohol use, and cigarette use. RESULTS: Mean YFAS-C symptom criteria count was 1.36 ± 1.47 (of 7). 18.3% of participants met 3+ symptoms, 7.5% endorsed impairment and 5.3% met the diagnostic threshold for food addiction. All examined behavioural and mental health variables were significantly associated with addictive eating symptoms. Effects were largest for high psychological distress and cigarette use; with those exhibiting high psychological distress meeting 0.65 more criteria (95%CI = 0.58-0.72, p < 0.001) and those who smoked a cigarette meeting 0.51 more criteria (95%CI = 0.26-0.76, p < 0.001). High psychological distress and consumption of SSB and energy drinks remained significant when modelling all predictors together. CONCLUSION: In this large adolescent study, addictive eating symptoms were common. Further research should establish directionality and causal mechanisms behind the association between mental ill-health, alcohol and tobacco use, and addictive eating behaviours. Cross-disciplinary prevention initiatives that address shared underlying risk factors for addictive eating and mental ill-health may offer efficient yet substantial public health benefits.

Parental Information Needs and Intervention Preferences for Preventing Multiple Lifestyle Risk Behaviors Among Adolescents: Cross-sectional Survey Among Parents.

BACKGROUND: Parents play an influential role in the health behaviors of their children, such as physical activity, dietary intake, sleep, screen time, and substance use. However, further research is needed to inform the development of more effective and engaging parent-based interventions targeting adolescent risk behaviors. OBJECTIVE: This study aimed to assess parents' knowledge about adolescent risk behaviors, barriers and facilitators to engaging in healthy behaviors, and preferences for a parent-based prevention intervention. METHODS: An anonymous web-based survey was conducted from June 2022 to August 2022. Eligible participants were parents of children aged 11 to 18 years and were residing in Australia at the time of this study. The survey assessed the parents' perceived and actual knowledge about Australian health guidelines for youth, parent and adolescent engagement in health behaviors, parenting style and attitudes, barriers and facilitators to engaging in healthy behaviors, and delivery and component preferences for a parent-based preventive intervention. Descriptive statistics and logistic regressions were conducted to analyze the data. RESULTS: A total of 179 eligible participants completed the survey. The mean age of the parents was 42.22 (SD 7.03) years, and 63.1% (101/160) were female. Parent-reported sleep duration was high for both parents (mean 8.31, SD 1.00 hours) and adolescents (mean 9.18, SD 0.94 hours). However, the proportion of parents who reported that their child met the national recommendations for physical activity (5/149, 3.4%), vegetable intake (7/126, 5.6%), and weekend recreational screen time (7/130, 5.4%) was very low. Overall, parents' perceived knowledge of health guidelines was moderate, ranging from 50.6% (80/158) for screen time to 72.8% (115/158) for sleep guidelines (for children aged 5-13 years). Actual knowledge was lowest for vegetable intake and physical activity, with only 44.2% (46/104) and 42% (31/74) of parents reporting correct guidelines for these behaviors, respectively. The key issues of concern reported by parents were excessive use of technology, mental health, e-cigarette use, and negative peer relationships. The top-rated delivery method for a parent-based intervention was via a website (53/129, 41.1%). The highest rated intervention component was opportunities for goal-setting (89/126, 70.7% rated very or extremely important), and other important program features were ease of use (89/122, 72.9%), paced learning (79/126, 62.7%), and appropriate program length (74/126, 58.8%). CONCLUSIONS: The findings suggest that such interventions should be brief and web based and should aim to increase parental knowledge of health guidelines; provide opportunities for skill-building, such as goal-setting; and include effective behavior change techniques, such as motivational interviewing and social support. This study will inform the development of future parent-based preventive interventions to prevent multiple lifestyle risk behaviors among adolescents.

Dose-response associations between modifiable lifestyle behaviours and anxiety, depression and psychological distress symptoms in early adolescence.

OBJECTIVE: To investigate associations between key modifiable lifestyle behaviours (sleep; physical activity; fruit, vegetable and sugar-sweetened beverage consumption; screen time; alcohol use and tobacco use) and mental health among early adolescents in Australia. METHODS: Cross-sectional self-report data from 6,640 Year 7 students (Mage:12.7[0.5]; 50.6% male, 48.9% female, 0.5% non-binary) from 71 schools in New South Wales, Queensland and Western Australia were analysed using multivariate linear regression adjusting for sociodemographic factors and school-level clustering. RESULTS: All examined behaviours were associated with anxiety, depression and psychological distress (p≤0.001), with the lowest mental health symptom scores observed in participants who slept 9.5-10.5 hours per night; consumed three serves of fruit daily; consumed two serves of vegetables daily; never or rarely drank sugar-sweetened beverages; engaged in six days of moderate-to-vigorous physical activity per week; kept daily recreational screen time to 31-60 minutes; had not consumed a full standard alcoholic drink (past six months); or smoked a cigarette (past six months). CONCLUSIONS: Targeting modifiable risk behaviours offers promising prevention potential to improve adolescent mental health; however, further longitudinal research to determine directionality and behavioural interactions is needed. IMPLICATIONS FOR PUBLIC HEALTH: While Australian Dietary, Movement and Alcohol Guidelines target physical health, findings indicate similar behaviour thresholds may offer mental health benefits.

Multiple lifestyle risk behaviours and hierarchical dimensions of psychopathology in 6640 Australian adolescents.

OBJECTIVE: Physical inactivity, sugar sweetened beverage consumption, alcohol use, smoking, poor sleep and excessive recreational screen time (the 'Big 6' lifestyle risk behaviours) often co-occur and are key risk factors for psychopathology. However, the best fitting latent structure of the Big 6 is unknown and links between multiple lifestyle risk behaviours and hierarchical dimensions of psychopathology have not been explored among adolescents. This study aimed to address these gaps in the literature. METHODS: Confirmatory factor analysis, latent class analysis and factor mixture models were conducted among 6640 students (Mage = 12.7 years) to identify the latent structure of the Big 6 lifestyle risk behaviours. Structural equation models were then used to examine associations with psychopathology. RESULTS: A mixture model with three classes, capturing mean differences in a single latent factor indexing overall risk behaviours, emerged as the best fitting model. This included relatively low-risk (Class 1: 30%), moderate-risk (Class 2: 67%) and high-risk (Class 3: 3%) classes. Students high on externalizing demonstrated significantly greater odds of membership to the high-risk class (odds ratio = 8.75, 99% confidence interval = [3.30, 23.26]) and moderate-risk class (odds ratio = 2.93, 99% confidence interval = [1.43, 5.97]) in comparison to the low-risk class. Similarly, students high on internalizing demonstrated significantly higher odds of membership to the high-risk class (odds ratio = 1.89, 99% confidence interval = [1.06, 3.37]) and the moderate-risk class (odds ratio = 1.66, 99% confidence interval = [1.03, 2.67]) in comparison to the low-risk class. Associations between lower order factors of psychopathology and lifestyle risk behaviours were mostly accounted for by the more parsimonious higher order factors. CONCLUSION: Classes representing differences in probabilities of the Big 6 lifestyle risk behaviours relate to varying levels of hierarchical dimensions of psychopathology, suggesting multiple health behaviour change and transdiagnostic intervention approaches may be valuable for reducing risk of psychopathology.

Parent-based interventions to improve multiple lifestyle risk behaviors among adolescents: A systematic review and meta-analysis.

Lifestyle risk behaviors often co-occur and are prevalent among adolescents. Parent-based interventions addressing risk behaviors concurrently have the potential to improve youth and parent outcomes. This systematic review evaluated the efficacy of parent-based interventions targeting multiple lifestyle risk behaviors among adolescents and parents. MEDLINE (Ovid), Embase (Ovid), PsycInfo (Ovid), Scopus, CINAHL, the Cochrane Database of Systematic Reviews (CDSR) and Cochrane Central Register of Controlled Trials (CENTRAL) were searched from 2010-May 2021. Eligible studies were randomised controlled trials (RCTs) of parent-based interventions addressing 2+ risk behaviors: alcohol use, smoking, poor diet, physical inactivity, sedentary behaviors, and poor sleep. Studies directly targeting parents, and that assessed adolescent outcomes (11-18 years) were eligible. Where possible, random-effects meta-analysis was conducted. From 11,975 identified records, 46 publications of 36 RCTs (n = 28,322 youth, n = 7385 parents) were eligible. Parent-based interventions were associated with improved adolescent moderate-to-vigorous physical activity (MVPA) [Odds Ratio (OR) = 1.82, 95% CI = 1.18, 2.81; p = 0.007], and reduced screen time (SMD = -0.39, 95% CI = -0.62, -0.16, p = 0.0009) and discretionary food intake (SMD = -0.18; 95% CI = -0.30, -0.06; p = 0.002) compared to controls. However, there was some evidence that interventions increased the odds of ever using tobacco in the medium-term (OR = 1.47, 95% CI = 0.99, 2.18, p = 0.06) and of past month tobacco use in the long-term (OR = 1.46, 95% CI = 1.12, 1.90; p = 0.005). Overall, the quality of evidence was moderate. Parent-based interventions targeting multiple risk behaviors improved adolescent MVPA, and reduced screen time discretionary food intake. Further research is needed to address sleep problems and increase intervention efficacy, particularly for alcohol and tobacco use.

Measurement Properties of Smartphone Approaches to Assess Diet, Alcohol Use, and Tobacco Use: Systematic Review.

BACKGROUND: Poor diet, alcohol use, and tobacco smoking have been identified as strong determinants of chronic diseases, such as cardiovascular disease, diabetes, and cancer. Smartphones have the potential to provide a real-time, pervasive, unobtrusive, and cost-effective way to measure these health behaviors and deliver instant feedback to users. Despite this, the validity of using smartphones to measure these behaviors is largely unknown. OBJECTIVE: The aim of our review is to identify existing smartphone-based approaches to measure these health behaviors and critically appraise the quality of their measurement properties. METHODS: We conducted a systematic search of the Ovid MEDLINE, Embase (Elsevier), Cochrane Library (Wiley), PsycINFO (EBSCOhost), CINAHL (EBSCOHost), Web of Science (Clarivate), SPORTDiscus (EBSCOhost), and IEEE Xplore Digital Library databases in March 2020. Articles that were written in English; reported measuring diet, alcohol use, or tobacco use via a smartphone; and reported on at least one measurement property (eg, validity, reliability, and responsiveness) were eligible. The methodological quality of the included studies was assessed using the Consensus-Based Standards for the Selection of Health Measurement Instruments Risk of Bias checklist. Outcomes were summarized in a narrative synthesis. This systematic review was registered with PROSPERO, identifier CRD42019122242. RESULTS: Of 12,261 records, 72 studies describing the measurement properties of smartphone-based approaches to measure diet (48/72, 67%), alcohol use (16/72, 22%), and tobacco use (8/72, 11%) were identified and included in this review. Across the health behaviors, 18 different measurement techniques were used in smartphones. The measurement properties most commonly examined were construct validity, measurement error, and criterion validity. The results varied by behavior and measurement approach, and the methodological quality of the studies varied widely. Most studies investigating the measurement of diet and alcohol received very good or adequate methodological quality ratings, that is, 73% (35/48) and 69% (11/16), respectively, whereas only 13% (1/8) investigating the measurement of tobacco use received a very good or adequate rating. CONCLUSIONS: This review is the first to provide evidence regarding the different types of smartphone-based approaches currently used to measure key behavioral risk factors for chronic diseases (diet, alcohol use, and tobacco use) and the quality of their measurement properties. A total of 19 measurement techniques were identified, most of which assessed dietary behaviors (48/72, 67%). Some evidence exists to support the reliability and validity of using smartphones to assess these behaviors; however, the results varied by behavior and measurement approach. The methodological quality of the included studies also varied. Overall, more high-quality studies validating smartphone-based approaches against criterion measures are needed. Further research investigating the use of smartphones to assess alcohol and tobacco use and objective measurement approaches is also needed. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-https://doi.org/10.1186/s13643-020-01375-w.

Clustering of Six Key Risk Behaviors for Chronic Disease among Adolescent Females.

Chronic diseases are the leading cause of disability and mortality globally. In Australia, females are at heightened risk. This research explored the prevalence, patterns, and correlates of six key risk behaviors (physical inactivity, poor diet, recreational screen time, inadequate sleep, alcohol use, and smoking) among adolescent females and whether knowledge of health guidelines was associated with adherence. Adolescent females completed an anonymous online questionnaire (N = 687; Mage = 13.82). Logistic regression assessed the association between knowledge and adherence. A Latent Class Analysis (LCA) and three-step procedure identified risk behavior clusters and their correlates. Despite positive health self-ratings (77% good/very good), most participants reported insufficient moderate-to-vigorous physical activity (MVPA; 89%), vegetable intake (89%), and excessive screen time (63%). Knowledge of guidelines was associated with adherence for MVPA, vegetable intake, sleep, and alcohol abstinence. Three classes emerged: "moderate risk" (76%), "relatively active, healthy eaters" (19%), and "excessive screen users" (5%). These risk-behavior clusters were associated with perceived value of academic achievement and physical wellbeing. Adolescent females commonly perceive they are in good health, despite engaging in unhealthy behaviors. Public health interventions should utilize effective behavior change strategies, adopt a multiple health behavior change approach (MHBC), and be tailored to specific risk profiles and values among females.

Study protocol of the Health4Life initiative: a cluster randomised controlled trial of an eHealth school-based program targeting multiple lifestyle risk behaviours among young Australians.

INTRODUCTION: Lifestyle risk behaviours, including alcohol use, smoking, poor diet, physical inactivity, poor sleep (duration and/or quality) and sedentary recreational screen time ('the Big 6'), are strong determinants of chronic disease. These behaviours often emerge during adolescence and co-occur. School-based interventions have the potential to address risk factors prior to the onset of disease, yet few eHealth school-based interventions target multiple behaviours concurrently. This paper describes the protocol of the Health4Life Initiative, an eHealth school-based intervention that concurrently addresses the Big 6 risk behaviours among secondary school students. METHODS AND ANALYSIS: A multisite cluster randomised controlled trial will be conducted among year 7 students (11-13 years old) from 72 Australian schools. Stratified block randomisation will be used to assign schools to either the Health4Life intervention or an active control (health education as usual). Health4Life consists of (1) six web-based cartoon modules and accompanying activities delivered during health education (once per week for 6 weeks), and a smartphone application (universal prevention), and (2) additional app content, for students engaging in two or more risk behaviours when they are in years 8 and 9 (selective prevention). Students will complete online self-report questionnaires at baseline, post intervention, and 12, 24 and 36 months after baseline. Primary outcomes are consumption of sugar-sweetened beverages, moderate-to-vigorous physical activity, sleep duration, sedentary recreational screen time and uptake of alcohol and tobacco use. ETHICS AND DISSEMINATION: This study has been approved by the University of Sydney (2018/882), NSW Department of Education (SERAP no. 2019006), University of Queensland (2019000037), Curtin University (HRE2019-0083) and relevant Catholic school committees. Results will be presented to schools and findings disseminated via peer-reviewed journals and scientific conferences. This will be the first evaluation of an eHealth intervention, spanning both universal and selective prevention, to simultaneously target six key lifestyle risk factors among adolescents. TRIAL REGISTRATION NUMBER: Australian New Zealand Clinical Trials Registry (ACTRN12619000431123), 18 March 2019.

Sports Participation, Health Behaviours, and Body Fat during Childhood and Early Adolescence: A Multiple Mediation.

OBJECTIVES: The aim of this study was to simultaneously explore multiple pathways through which sports participation during childhood and adolescence may be associated with adiposity over time. DESIGN: Data were drawn from the Kindergarten cohort of the Longitudinal Study of Australian Children. A total of 4286 children provided sports participation data at age 10 years and were followed up 24 and 48 months later. METHOD: Time spent in organised sports at age 10 years and time spent in physical activity at age 12 years were measured via parental-reported time-use diary. Dietary behaviours were self-reported at age 12 years. Screen time was parent-reported. Body fat was measured at age 14 using bioelectrical impedance analysis. Two parallel multiple mediation models were tested to examine the longitudinal associations between sport participation at age 10 and body fat at age 14 via the mediating variables of physical activity, screen time, and dietary behaviours. One model was run for all participants, and a second model was run only for those participants who reported participating in organised sports. RESULTS: There were no significant indirect relationships between sports participation and body fat via any of the mediating variables in the total sample, or among sport participants. CONCLUSIONS: There is a dearth of evidence to support substantial rhetoric and policy to promote organised sports programs as public health initiatives in their current form during childhood and adolescence. Better quality evidence is needed, however, modifications to sport programs may be necessary to elucidate meaningful benefits for adiposity.

Effectiveness of school-based eHealth interventions to prevent multiple lifestyle risk behaviours among adolescents: a systematic review and meta-analysis.

BACKGROUND: Lifestyle risk behaviours typically emerge during adolescence, track into adulthood, and commonly co-occur. Interventions targeting multiple risk behaviours in adolescents have the potential to efficiently improve health outcomes, yet further evidence is required to determine their effect. We reviewed the effectiveness of eHealth school-based interventions targeting multiple lifestyle risk behaviours. METHODS: In this systematic review and meta-analysis, we searched Ovid MEDLINE, Embase, PsycINFO, and the Cochrane Library databases between Jan 1, 2000, and March 14, 2019, with no language restrictions, for publications on school-based eHealth multiple health behaviour interventions in humans. We also screened the grey literature for unpublished data. Eligible studies were randomised controlled trials of eHealth (internet, computers, tablets, mobile technology, or tele-health) interventions targeting two or more of six behaviours of interest: alcohol use, smoking, diet, physical activity, sedentary behaviour, and sleep. Primary outcomes of interest were the prevention or reduction of unhealthy behaviours, or improvement in healthy behaviours of the six behaviours. Outcomes were summarised in a narrative synthesis and combined using random-effects meta-analysis. This systematic review is registered with PROSPERO, identifier CRD42017072163. FINDINGS: Of 10 571 identified records, 22 publications assessing 16 interventions were included, comprising 18 873 students, of whom on average 56·2% were female, with a mean age of 13·41 years (SD 1·52). eHealth school-based multiple health behaviour change interventions significantly increased fruit and vegetable intake (standard mean difference 0·11, 95% CI 0·03 to 0·19; p=0·007) and both accelerometer-measured (0·33, 0·05 to 0·61; p=0·02) and self-reported (0·14, 0·05 to 0·23; p=0·003) physical activity, and reduced screen time (-0·09, -0·17 to -0·01; p=0·03) immediately after the intervention; however, these effects were not sustained at follow-up when data were available. No effect was seen for alcohol or smoking, fat or sugar-sweetened beverage or snack consumption. No studies examined sleep or used mobile health interventions. The risk of bias in masking of final outcome assessors and selective outcome reporting was high or unclear across studies and overall we deemd the quality of evidence to be low to very low. INTERPRETATION: eHealth school-based interventions addressing multiple lifestyle risk behaviours can be effective in improving physical activity, screen time, and fruit and vegetable intake. However, effects were small and only evident immediately after the intervention. Further high quality, adolescent-informed research is needed to develop eHealth interventions that can modify multiple behaviours and sustain long-term effects. FUNDING: Paul Ramsay Foundation and Australian National Health and Medical Research Council.