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.

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.

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).

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.

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.

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.

Response: Sports participation and interventions to reduce risk of mental health problems during childhood: a response to Crowell (2018).

One of the most salient purposes of examining the potential existence and predictors of distinct trajectories of mental health during childhood is to enable effective prevention and intervention strategies. More specifically, the aim is to inform an understanding of the types of prevention and intervention strategies that may be effective in reducing risk, as well the time period in which such strategies are going to be most beneficial.

Trajectories and predictors of risk for mental health problems throughout childhood.

BACKGROUND: Children fluctuate in their risk for mental health-related problems. While children have demonstrated consistent trajectories for various types of mental health problems, the existence of developmental trajectories of overall risk of mental health problems has not been explored. This study aimed to identify distinct trajectories of overall mental health risk among children from ages 4-12 years. A secondary objective was to identify predictors of the mental health risk trajectories. METHOD: Data from the first five waves of the Longitudinal Study of Australian Children (LSAC) were used to assess mental health risk and potential predictors. The primary parent (n = 3717) completed questionnaires, time-use diaries, and face-to-face interviews over the five waves. Growth mixture modeling was used to identify distinct latent trajectories of mental health risk. Multinomial logistic regression was used to identify predictors of the trajectories. RESULTS: Six distinct trajectories of mental health risk were identified: Low Difficulty (72.9%), Improvers (9.7%), Decliners (7.9%), Early Decliners/Late Improvers (4.7%), Early Improvers/Late Decliners (2.7%), and High Difficulty (2.2%). Child sex, sociability, parental warmth, sports participation, and household income were identified as significant predictors of mental health trajectories. CONCLUSIONS: There are distinct trajectories of overall risk for mental health problems during childhood. Research should focus on the High Difficulties group and the Early Improvers/Late Decliners group to address the predictors and improve access to early mental health services.

Social climate profiles in adolescent sports: Associations with enjoyment and intention to continue.

This study explored whether adolescent sports participants' perceptions of the social climate fall into distinct profiles, and whether these profiles are related to enjoyment and intention to continue. A Latent Profile Analysis using 313 Australian sports participants (Mage = 13.03 years) revealed four distinct profiles: positive social climate (45.1%), diminished social climate (19.8%), positive coach relationship quality (19.8%), and positive friendship quality (15.3%). Individuals within the positive social climate and the positive coach relationship quality profiles reported relatively higher levels of enjoyment and intention to continue than individuals in the diminished social climate and the positive friendship quality profiles. Indirect path analyses found the social climate profiles were linked with intention to continue through enjoyment. Results highlight the value of investigating multiple dimensions of the social climate and suggest that the coach may be of particular importance in this age group. Findings have implications for understanding youth sports participation and preventing dropout.

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.

Alcohol initiation before age 15 predicts earlier hazardous drinking: A survival analysis of a 7-year prospective longitudinal cohort of Australian adolescents.

BACKGROUND AND AIMS: Early alcohol use may predict later alcohol problems, but the magnitude of this effect and impact of delayed onset remain uncertain. This study measured age-based differences in progression from first full alcoholic drink to hazardous drinking in one of the largest and most recent prospective cohorts of Australian adolescents. DESIGN, SETTINGS, PARTICIPANTS AND MEASUREMENT: A 7-year (2012-19) prospective longitudinal cohort of 2082 Australian adolescents was established from the Climate and Preventure (cohort 1) and Climate Schools Combined (cohort 2) studies. Participants completed surveys annually from ages 13 to 20 years. Interval censored survival analyses were conducted with first episode of hazardous drinking [three or more on proxy Alcohol Use Disorders Identification Test (AUDIT-C)] as the survival end-point, controlling for age, sex and mental health symptomatology. Onset of hazardous drinking was expressed as hazard ratios (HRs), and median survival time (years) was used to model first onset of hazardous alcohol use in survival curves. FINDINGS: Compared with those aged 15 or older, those who had their first full drink at 12 or younger had significantly elevated risk of hazardous drinking onset during the study period [log (HR): 9.3; 95% confidence interval (CI) = 7.0-12.0, P < 0.001]. Compared with those who had their first full drink at ages 13-14, those who delayed until 15 or older had significantly later onset of hazardous drinking; 1.63 years for males (95% CI = 1.31-1.92, P < 0.001) and 1.50 for females (95% CI = 1.15-1.81, P < 0.001), resulting in a median age of onset of hazardous drinking of > 19 for both sexes (male: 19.05 years, 95% CI = 18.74-19.38; female: 19.47 years, 95% CI = 19.19-19.75). First drink at ages 13-14 was associated with the earliest onset of hazardous drinking (males: 17.43 years; females: 17.98 years). CONCLUSIONS: In Australia, alcohol initiation prior to age 15 appears to be associated with an earlier onset of hazardous drinking than initiation after age 15.

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.

Accelerating implementation of adolescent digital health prevention programs: analysis of insights from Australian stakeholders.

Background: Chronic disease risk factors are increasing amongst adolescents, globally. Digital health prevention programs, which provide education and information to reduce chronic disease risk factors need to be equitable and accessible for all. For their success, multiple highly engaged stakeholders should be involved in development and implementation. This study aimed to evaluate stakeholders' support for, and perspectives on potential public health impact of digital health prevention programs for adolescents and potential pathways for future implementation. Methods: Qualitative semi-structured online interviews with stakeholders. Stakeholder mapping identified key individuals, groups and organizations across Australia that may influence the implementation of digital health prevention programs for adolescents. Recorded and transcribed interviews were analyzed within the Reach, Effectiveness, Adoption, Implementation and Maintenance (RE-AIM) Framework, using deductive content analysis. Findings: Nineteen interviews were conducted in 2023 with stakeholders from government, health, non-government organizations, youth services, education, community settings and others. Four overarching themes were identified: (i) existing digital health initiatives are not fit for purpose; (ii) the co-creation of digital health prevention programs is critical for successful implementation; (iii) digital health prevention programs must address equity and the unique challenges raised by technology and; (iv) system level factors must be addressed. Interpretation: Stakeholders broadly supported digital health prevention programs, yet raised unique insights to ensure that future programs create public health impact by improving chronic disease risk factors among adolescents. These insights can be applied in future development of digital health prevention programs for adolescents to strengthen widespread implementation.

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.

Associations Between Personality Traits and Energy Balance Behaviors in Emerging Adulthood: Cross-Sectional Study.

BACKGROUND: Internalizing and externalizing personality traits are robust risk factors for substance use and mental health, and personality-targeted interventions are effective in preventing substance use and mental health problems in youth. However, there is limited evidence for how personality relates to other lifestyle risk factors, such as energy balance-related behaviors, and how this might inform prevention efforts. OBJECTIVE: This study aimed to examine concurrent cross-sectional associations between personality traits (ie, hopelessness, anxiety sensitivity, impulsivity, and sensation seeking) and sleep, diet, physical activity (PA), and sedentary behaviors (SB), 4 of the leading risk factors for chronic disease, among emerging adults. METHODS: Data were drawn from a cohort of young Australians who completed a web-based, self-report survey in 2019 during early adulthood. A series of Poisson and logistic regressions were conducted to examine the concurrent associations between the risk behaviors (sleep, diet, PA, and sitting and screen time) and personality traits (hopelessness, anxiety sensitivity, impulsivity, and sensation seeking) among emerging adults in Australia. RESULTS: A total of 978 participants (mean age 20.4, SD 0.5 years) completed the web-based survey. The results indicated that higher scores on hopelessness were associated with a greater daily screen (risk ratio [RR] 1.12, 95% CI 1.10-1.15) and sitting time (RR 1.05, 95% CI 1.0-1.08). Similarly, higher scores on anxiety sensitivity were associated with a greater screen (RR 1.04, 95% CI 1.02-1.07) and sitting time (RR 1.04, 95% CI 1.02-1.07). Higher impulsivity was associated with greater PA (RR 1.14, 95% CI 1.08-1.21) and screen time (RR 1.06, 95% CI 1.03-1.08). Finally, higher scores on sensation seeking were associated with greater PA (RR 1.08, 95% CI 1.02-1.14) and lower screen time (RR 0.96, 95% CI 0.94-0.99). CONCLUSIONS: The results suggest that personality should be considered when designing preventive interventions for lifestyle risk behaviors, particularly in relation to SB, such as sitting and screen time. TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry ACTRN12612000026820; https://tinyurl.com/ykwcxspr.

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.

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.

The directionality of anxiety and gaming disorder: An exploratory analysis of longitudinal data from an Australian youth population.

Gaming activities among adolescents have increased during the COVID-19 pandemic, bringing with it a growing concern for the potential harms of excessive gaming and its risk factors. Anxiety is frequently linked with gaming disorder, but studies investigating this association were mostly cross-sectional in design. Longitudinal studies that explore risk factors associated with gaming disorder are sparse and the trajectories of gaming disorder remain unclear. To address this paucity, the present study analyzed a large longitudinal dataset with a 12-month follow-up of 4,968 Australian adolescents (ages 13-14) during the pandemic. Logistic regression and multiple regression analyses were conducted to investigate the temporal relationships between anxiety, gaming frequency, the amount of money spent within video games, and gaming disorder. Prevalence rates for gaming disorder in adolescents aged 13 and 14 were 15 and 16%, respectively. The regression models indicated a bidirectional relationship between anxiety and gaming disorder symptoms, where higher levels of anxiety were associated with higher levels of gaming disorder 12 months later and vice versa. The study also found that the interaction between anxiety and higher gaming frequency could predict gaming disorder symptoms. Overall, the findings suggest that young adolescents may be more vulnerable to developing gaming disorder and highlight the importance of addressing the interactions between risk factors and gaming disorder in treatment approaches.