Adolescents' trajectories of depression and anxiety symptoms prior to and during the COVID-19 pandemic and their association with healthy sleep patterns.

The COVID-19 pandemic has seen a rise in anxiety and depression among adolescents. This study aimed to investigate the longitudinal associations between sleep and mental health among a large sample of Australian adolescents and examine whether healthy sleep patterns were protective of mental health in the context of the COVID-19 pandemic. We used three waves of longitudinal control group data from the Health4Life cluster-randomized trial (N = 2781, baseline Mage = 12.6, SD = 0.51; 47% boys and 1.4% 'prefer not to say'). Latent class growth analyses across the 2 years period identified four trajectories of depressive symptoms: low-stable (64.3%), average-increasing (19.2%), high-decreasing (7.1%), moderate-increasing (9.4%), and three anxiety symptom trajectories: low-stable (74.8%), average-increasing (11.6%), high-decreasing (13.6%). We compared the trajectories on sociodemographic and sleep characteristics. Adolescents in low-risk trajectories were more likely to be boys and to report shorter sleep latency and wake after sleep onset, longer sleep duration, less sleepiness, and earlier chronotype. Where mental health improved or worsened, sleep patterns changed in the same direction. The subgroups analyses uncovered two important findings: (1) the majority of adolescents in the sample maintained good mental health and sleep habits (low-stable trajectories), (2) adolescents with worsening mental health also reported worsening sleep patterns and vice versa in the improving mental health trajectories. These distinct patterns of sleep and mental health would not be seen using mean-centred statistical approaches.

The Health4Life e-health intervention for modifying lifestyle risk behaviours of adolescents: secondary outcomes of a cluster randomised controlled trial.

OBJECTIVES: To investigate the effectiveness of a school-based multiple health behaviour change e-health intervention for modifying risk factors for chronic disease (secondary outcomes). STUDY DESIGN: Cluster randomised controlled trial. SETTING, PARTICIPANTS: Students (at baseline [2019]: year 7, 11-14 years old) at 71 Australian public, independent, and Catholic schools. INTERVENTION: Health4Life: an e-health school-based multiple health behaviour change intervention for reducing increases in the six major behavioural risk factors for chronic disease: physical inactivity, poor diet, excessive recreational screen time, poor sleep, and use of alcohol and tobacco. It comprises six online video modules during health education class and a smartphone app. MAIN OUTCOME MEASURES: Comparison of Health4Life and usual health education with respect to their impact on changes in twelve secondary outcomes related to the six behavioural risk factors, assessed in surveys at baseline, immediately after the intervention, and 12 and 24 months after the intervention: binge drinking, discretionary food consumption risk, inadequate fruit and vegetable intake, difficulty falling asleep, and light physical activity frequency (categorical); tobacco smoking frequency, alcohol drinking frequency, alcohol-related harm, daytime sleepiness, and time spent watching television and using electronic devices (continuous). RESULTS: A total of 6640 year 7 students completed the baseline survey (Health4Life: 3610; control: 3030); 6454 (97.2%) completed at least one follow-up survey, 5698 (85.8%) two or more follow-up surveys. Health4Life was not statistically more effective than usual school health education for influencing changes in any of the twelve outcomes over 24 months; for example: fruit intake inadequate: odds ratio [OR], 1.08 (95% confidence interval [CI], 0.57-2.05); vegetable intake inadequate: OR, 0.97 (95% CI, 0.64-1.47); increased light physical activity: OR, 1.00 (95% CI, 0.72-1.38); tobacco use frequency: relative difference, 0.03 (95% CI, -0.58 to 0.64) days per 30 days; alcohol use frequency: relative difference, -0.34 (95% CI, -1.16 to 0.49) days per 30 days; device use time: relative difference, -0.07 (95% CI, -0.29 to 0.16) hours per day. CONCLUSIONS: Health4Life was not more effective than usual school year 7 health education for modifying adolescent risk factors for chronic disease. Future e-health multiple health behaviour change intervention research should examine the timing and length of the intervention, as well as increasing the number of engagement strategies (eg, goal setting) during the intervention. TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry: ACTRN12619000431123 (prospective).

Exploring the association between adolescent-perceived parental monitoring on dietary intake.

Parenting practices such as parental monitoring are known to positively impact dietary behaviours in offspring. However, links between adolescent-perceived parental monitoring and dietary outcomes have rarely been examined and never in an Australian context. This study investigated whether adolescent-perceived parental monitoring is associated with more fruit and vegetable, and less sugar-sweetened beverages (SSB) and junk food consumption in Australian adolescents. Cross-sectional data was collected as part of baseline measurement for a randomised controlled trial in 71 Australian schools in 2019. Self-reported fruit, vegetable, SSB and junk food intake, perceived parental monitoring and sociodemographic factors were assessed. Each dietary variable was converted to "not at risk/at risk" based on dietary guidelines, binary logistic regressions examined associations between dietary intake variables and perceived parental monitoring while controlling for gender and socio-economic status. The study was registered in ANZCTR clinical trials. The sample comprised 6053 adolescents (Mage = 12.7, SD = 0.5; 50.6% male-identifying). The mean parental monitoring score was 20.1/24 (SD = 4.76) for males and 21.9/24 (SD = 3.37) for females. Compared to adolescents who perceived lower levels of parental monitoring, adolescents reporting higher parental monitoring had higher odds of insufficient fruit (OR = 1.03; 95% CI = 1.02-1.05) and excessive SSB (OR = 1.07; 95% CI = 1.06-1.09) intake, but lower odds of excessive junk food (OR = 0.96; 95% CI = 0.95-0.98) and insufficient vegetable (OR = 0.97, 95% CI = 0.96-0.99) intake. Adolescent dietary intake is associated with higher perceived parental monitoring; however, these associations for fruit and SSB differ to junk food and vegetable intake. This study may have implications for prevention interventions for parents, identifying how this modifiable parenting factor is related to adolescent diet has highlighted how complex the psychological and environmental factors contributing to dietary intake are.

What set some young adults apart during the COVID-19 pandemic? Mental health trajectories, risk and protective factors in an Australian longitudinal study.

OBJECTIVE: Evidence suggests that young adults (aged 18-34) were disproportionately impacted by the COVID-19 pandemic, but little is known about their longer-term mental health changes beyond the early pandemic period. This article investigates heterogeneous trajectories of mental health among Australian young adults across 2 years of the pandemic and identifies a broad range of associated risk and protective factors. METHOD: Young adults (N = 653, Mage = 27.8 years) from the longitudinal Alone Together Study were surveyed biannually between July 2020 and June 2022. Measures assessed anxiety (7-item Generalised Anxiety Disorder scale) and depression (9-item Patient Health Questionnaire) symptoms at Waves 1-4, as well as demographic, psychological, adversity and COVID-19 factors at baseline. RESULTS: Four and three distinct trajectories of anxiety and depressive symptoms, respectively, were identified through growth mixture modelling. The proportion of participants in each anxiety trajectory were Asymptomatic (45.9%), Mild Stable (17.9%), Moderate-Severe Stable (31.1%) and Initially Severe/Recovering (5.1%). For depression, Mild Stable (58.3%), Moderate-Severe Stable (30.5%) and Reactive/Recovering (11.2%). Baseline factors associated with severe symptom trajectories included a lifetime mental health disorder, pre-pandemic stressful events, identifying as LGBTQIA+ and/or female, and experiencing one or more infection-control measures. Higher household income was protective. CONCLUSION: Most young adults demonstrated stable trajectories of low or high symptoms during the pandemic, with smaller groups showing initially severe or reactive symptoms followed by marked improvements over time. Vulnerable subgroups (gender- or sexuality-diverse, those with prior adversity or pre-existing mental ill-health) may face ongoing impacts and require targeted psychosocial supports to assist their mental health recovery post-COVID-19 and in the event of future crises.

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.

Mental health and wellbeing outcomes of youth participation: A scoping review protocol.

There is growing recognition that young people should be given opportunities to participate in the decisions that affect their lives, such as advisory groups, representative councils, advocacy or activism. Positive youth development theory and sociopolitical development theory propose pathways through which youth participation can influence mental health and wellbeing outcomes. However, there is limited empirical research synthesising the impact of participation on youth mental health and/or wellbeing, or the characteristics of activities that are associated with better or worse mental health and/or wellbeing outcomes. This scoping review seeks to address this gap by investigating the scope and nature of evidence detailing how youth participation initiatives can influence mental health and/or wellbeing outcomes for participants. To be eligible, literature must describe youth (aged 15-24) in participation activities and the impact of this engagement on participant mental health and/or wellbeing outcomes. A systematic scoping review of peer-reviewed and grey literature will be conducted using Scopus, PsycINFO, Embase, Medline and grey literature databases. The scoping review will apply established methodology by Arksey and O'Malley, Levac and colleagues and the Joanna Briggs Institute. Title, abstract, and full text screening will be completed by two reviewers, data will be extracted by one reviewer. Findings will be reported in accordance with the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR), including a qualitative summary of the characteristics of youth participation and their influence on youth mental health outcomes. Youth advisory group members will be invited to deliver governance on the project from the outset; participate in, and contribute to, all stages of the review process; reflect on their own experiences of participation; and co-author the resulting publication. This scoping review will provide essential knowledge on how participation activities can be better designed to maximise beneficial psychosocial outcomes for involved youth.

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.

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.

A hidden pandemic? An umbrella review of global evidence on mental health in the time of COVID-19.

Background: The mental health impacts of the COVID-19 pandemic remain a public health concern. High quality synthesis of extensive global literature is needed to quantify this impact and identify factors associated with adverse outcomes. Methods: We conducted a rigorous umbrella review with meta-review and present (a) pooled prevalence of probable depression, anxiety, stress, psychological distress, and post-traumatic stress, (b) standardised mean difference in probable depression and anxiety pre-versus-during the pandemic period, and (c) comprehensive narrative synthesis of factors associated with poorer outcomes. Databases searched included Scopus, Embase, PsycINFO, and MEDLINE dated to March 2022. Eligibility criteria included systematic reviews and/or meta-analyses, published post-November 2019, reporting data in English on mental health outcomes during the COVID-19 pandemic. Findings: Three hundred and thirty-eight systematic reviews were included, 158 of which incorporated meta-analyses. Meta-review prevalence of anxiety symptoms ranged from 24.4% (95%CI: 18-31%, I 2: 99.98%) for general populations to 41.1% (95%CI: 23-61%, I 2: 99.65%) in vulnerable populations. Prevalence of depressive symptoms ranged from 22.9% (95%CI: 17-30%, I 2: 99.99%) for general populations to 32.5% (95%CI: 17-52%, I 2: 99.35) in vulnerable populations. Prevalence of stress, psychological distress and PTSD/PTSS symptoms were 39.1% (95%CI: 34-44%; I 2: 99.91%), 44.2% (95%CI: 32-58%; I 2: 99.95%), and 18.8% (95%CI: 15-23%; I 2: 99.87%), respectively. Meta-review comparing pre-COVID-19 to during COVID-19 prevalence of probable depression and probable anxiety revealed standard mean differences of 0.20 (95%CI = 0.07-0.33) and 0.29 (95%CI = 0.12-0.45), respectively. Conclusion: This is the first meta-review to synthesise the longitudinal mental health impacts of the pandemic. Findings show that probable depression and anxiety were significantly higher than pre-COVID-19, and provide some evidence that that adolescents, pregnant and postpartum people, and those hospitalised with COVID-19 experienced heightened adverse mental health. Policymakers can modify future pandemic responses accordingly to mitigate the impact of such measures on public mental health.

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.

Socio-Demographic, Self-Control, Bullying, Parenting, and Sleep as Proximal Factors Associated with Food Addiction among Adolescents.

Adolescence is considered an important period of neurodevelopment. It is a time for the emergence of psychosocial vulnerabilities, including symptoms of depression, eating disorders, and increased engagement in unhealthy eating behaviours. Food addiction (FA) in adolescents is an area of study where there has been substantial growth. However, to date, limited studies have considered what demographic characteristics of adolescents may predispose them to endorse greater symptoms of FA. Studies have found a variety of factors that often cluster with and may influence an adolescent's eating behaviour such as sleep, level of self-control, and parenting practices, as well as bullying. Therefore, this study investigated a range of socio-demographic, trait, mental health, and lifestyle-related profiles (including self-control, parenting, bullying, and sleep) as proximal factors associated with symptoms of FA, as assessed via the Yale Food Addiction Scale for Children (YFAS-C) in a large sample of Australian adolescents. Following data cleaning, the final analysed sample included 6587 students (age 12.9 years ± 0.39; range 10.9-14.9 years), with 50.05% identifying as male (n = 3297), 48.5% as female (n = 3195), 1.02% prefer not to say (n = 67), and 0.43% as non-binary (n = 28). Self-control was found to be the most significant predictor of total FA symptom score, followed by female gender, sleep quality, and being a victim of bullying. Universal prevention programs should therefore aim to address these factors to help reduce the prevalence or severity of FA symptoms within early adolescent populations.

In their own words: An Australian community sample's priority concerns regarding mental health in the context of COVID-19.

The COVID-19 pandemic has resulted in significant and unprecedented mental health impacts in Australia. However, there is a paucity of research directly asking Australian community members about their mental health experiences, and what they perceive to be the most important mental health issues in the context of the pandemic. This study utilises qualitative data from Alone Together, a longitudinal mixed-methods study investigating the effects of COVID-19 on mental health in an Australian community sample (N = 2,056). A total of 1,037 participants, ranging in sex (69.9% female), age (M = 40-49 years), state/territory of residence, and socioeconomic status, shared responses to two open-ended questions in the first follow up survey regarding their mental health experiences and priorities during COVID-19. Responses were analysed using thematic analysis. Participants described COVID-19 as primarily impacting their mental health through the disruption it posed to their social world and financial stability. A key concern for participants who reported having poor mental health was the existence of multiple competing barriers to accessing high quality mental health care. According to participant responses, the pandemic placed additional pressures on an already over-burdened mental health service system, leaving many without timely, appropriate support. Absent or stigmatising rhetoric around mental health, at both a political and community level, also prevented participants from seeking help. Insights gained from the present research provide opportunities for policymakers and health practitioners to draw on the expertise of Australians' lived experience and address priority issues through targeted policy planning. This could ultimately support a more responsive, integrated, and effective mental health system, during and beyond the COVID-19 pandemic.

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.