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.

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).

The long-term effectiveness of a personality-targeted substance use prevention program on aggression from adolescence to early adulthood.

BACKGROUND: Addressing aggressive behavior in adolescence is a key step toward preventing violence and associated social and economic costs in adulthood. This study examined the secondary effects of the personality-targeted substance use preventive program Preventure on aggressive behavior from ages 13 to 20. METHODS: In total, 339 young people from nine independent schools (M age = 13.03 years, s.d. = 0.47, range = 12-15) who rated highly on one of the four personality traits associated with increased substance use and other emotional/behavioral symptoms (i.e. impulsivity, anxiety sensitivity, sensation seeking, and negative thinking) were included in the analyses (n = 145 in Preventure, n = 194 in control). Self-report assessments were administered at baseline and follow-up (6 months, 1, 2, 3, 5.5, and 7 years). Overall aggression and subtypes of aggressive behaviors (proactive, reactive) were examined using multilevel mixed-effects analysis accounting for school-level clustering. RESULTS: Across the 7-year follow-up period, the average yearly reduction in the frequency of aggressive behaviors (b = -0.42; 95% confidence interval [CI] -0.64 to -0.20; p < 0.001), reactive aggression (b = -0.22; 95% CI 0.35 to -0.10; p = 0.001), and proactive aggression (b = -0.14; 95% CI -0.23 to -0.05; p = 0.002) was greater for the Preventure group compared to the control group. CONCLUSIONS: The study suggests a brief personality-targeted intervention may have long-term impacts on aggression among young people; however, this interpretation is limited by imbalance of sex ratios between study groups.

Effect of a selective personality-targeted prevention program on 7-year illicit substance related outcomes: A secondary analysis of a cluster randomized controlled trial.

BACKGROUND: This study evaluated the efficacy of the selective personality-targeted PreVenture program in reducing cannabis and stimulant use over a 7-year period spanning adolescence and early adulthood. METHODS: A cluster randomized controlled trial was conducted in 14 Australian schools. Schools were randomized to PreVenture, a brief personality-targeted selective intervention, comprising two 90-minute facilitator-led sessions delivered one week apart, or a control group (health education as usual). Only students who scored highly on one of four personality traits (anxiety sensitivity, negative thinking, impulsivity, sensation seeking) were included. Students completed online self-report questionnaires between 2012 and 2019: at baseline; post-intervention; 1-, 2-, 3-, 5.5- and 7-years post-baseline. Outcomes were past 6-months cannabis use, stimulant use (MDMA, methamphetamine or amphetamine) and cannabis-related harms. RESULTS: The sample comprised 438 adolescents (Mage=13.4 years; SD=0.47) at baseline. Retention ranged from 51% to 79% over the 7-years. Compared to controls, the PreVenture group had significantly reduced odds of annual cannabis-related harms (OR=0.78, 95% CI=0.65-0.92). However, there were no significant group differences in the growth of cannabis use (OR=0.84, 95% CI=0.69-1.02) or stimulant use (OR=1.07, 95% CI=0.91-1.25) over the 7-year period. CONCLUSIONS: PreVenture was effective in slowing the growth of cannabis-related harms over time, however owing to missing data over the 7-year trial, replication trials may be warranted to better understand the impact of the PreVenture intervention on cannabis and stimulant use among young Australians. Alternative implementation strategies, such as delivering the intervention in later adolescence and/or providing booster sessions, may be beneficial.

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.

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.

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.

An on-line school-based substance use harm reduction programme: The Illicit Project randomized controlled trial results.

AIMS: The aim of this study was to measure the effectiveness of an on-line, neuroscience-based harm reduction intervention (The Illicit Project) on substance use, harms and knowledge over a 12-month period. DESIGN: We used a two-arm cluster-randomized controlled trial. SETTING: The study was conducted at eight secondary schools across New South Wales, Australia. PARTICIPANTS: A total of 950 (mean age = 15.9; standard deviation = 0.68) in grades 10-12 at participating schools in 2020 took part. INTERVENTION AND COMPARATOR: The Illicit Project intervention group (schools = five, n = 681) received an on-line, universal substance use and harm reduction programme over three classes. The active control group (schools = three, n = 269) received school-based health education as usual. MEASUREMENTS: Self-report questionnaires assessed primary [alcohol, nicotine, cannabis, 3,4-methylenedioxymethamphetamine (MDMA), cocaine and prescription drug misuse] and secondary outcomes (alcohol-related harms and drug literacy) at baseline and the 6- and 12-month follow-up assessment. FINDINGS: Approximately 63% (n = 595) of the sample completed the 12-month follow-up assessment, including 58% of the intervention group (n = 396/679) and 66% of the active control group (n = 179/271). Participants in the intervention group had slower annual increases in binge drinking [odds ratio (OR) = 0.33, 95% confidence interval (CI) = 0.12-0.89], nicotine use (OR = 0.80, 95% CI = 0.52-1.23), MDMA use (OR = 0.14, 95% CI = 0.02-1.00), cocaine use (OR = 0.06, 95% CI = 0.01-0.64) and prescription drug misuse (OR = 0.07, 95% CI = 0.01-0.54) compared with the active control group. There was limited evidence of an intervention effect on cannabis use and alcohol-related harm (P > 0.5). The secondary outcomes showed that the intervention group maintained higher levels of drug literacy knowledge (ß = 3.71, 95% CI = 1.86-5.56) and harm reduction help-seeking skills (ß = 1.55, 95% CI = 0.62-2.48) compared with the active control group. CONCLUSION: The Illicit Project (an on-line, neuroscience-based substance use harm reduction intervention) was effective in slowing the uptake of risky substance use and improving drug literacy skills among late secondary school students in Australia, compared with school-based health education as usual.

Striking the right balance: co-designing the Health4Me healthy lifestyle digital health intervention with adolescents.

BACKGROUND: Adolescents are navigating a period of rapid growth and development within an era of digitalization. Mobile phone ownership among adolescents is nearly ubiquitous, and this provides an opportunity to harness text messaging to promote a healthy lifestyle and reduce chronic disease risk factors. Inclusion of adolescents throughout the design process has been recognized as essential for engagement and future implementation of such interventions. This study aimed to co-design a bank of text messages to promote a healthy lifestyle which are useful, acceptable, and engaging for adolescents aged 12-18 years old. METHODS: Iterative, mixed-methods design with consumer partnership. Co-design occurred over three stages: text message development, text message review and final refinement and testing. The text message development included literature searches and consumer partnership with an established youth advisory group (n = 16). Participants who gave e-consent participated in text message review. Demographic characteristics were collected, and quantitative surveys were distributed to adolescents (n = up to 50) and health professionals (n = up to 30), who rated text message content for understanding, usefulness and appropriateness (total score out of 15). Final refinement was completed by the research team to edit or remove messages which had low scores and to assess readability and interactivity of the text messages. RESULTS: The Heath Advisory Panel for Youth at the University of Sydney (HAPYUS) identified the top six lifestyle health issues for young people today in relation to chronic disease prevention, which became the key content areas for the text message bank and drafted new text messages. Following text message development, 218 messages were available for review. Adolescents (n = 18, mean age 16.3 [SD 1.4]) and healthcare professionals (n = 16) reviewed the text messages. On average, all reviewers found that the text messages were easy to understand (mean = 13.4/15) and useful (mean = 12.7/15). Based on scoring and open ended-feedback, 91 text messages were edited and 42 deleted. The final text message bank included 131 text messages. The overall program is suitable for a seventh-grade reading level, and interactive. CONCLUSIONS: This study describes the process of effectively engaging adolescents to co-design a text message bank intervention, which are useful, acceptable and engaging for an adolescent audience. The effectiveness of the co-designed text message bank is currently being tested in the Health4Me RCT.

Today's adolescents are growing and developing through a period of increased technology use. Most adolescents have access to a mobile phone which can be used to deliver healthy lifestyle information to them through text messages. However, it is important that researchers engage with adolescents as collaborators to develop any information which may be sent to them, to ensure that it is acceptable and engaging. We aimed to co-design a bank of text messages to promote a healthy lifestyle which are useful, acceptable and engaging for adolescents 12­18 years old. We engaged with 16 adolescents from an established youth advisory group who advised on top health issues they face today in terms of leading a healthy lifestyle, which became key content areas for the text message program. They also drafted text messages around these content areas (218 total). Next, the text messages underwent review with 34 adolescents and healthcare professionals to ensure they were useful, easy to understand and appropriate. After the review, the research team edited, deleted and replaced text messages which did not score well. This resulted in a text message bank to promote a healthy lifestyle with 131 text messages which were useful, acceptable and engaging for adolescents 12­18 years old.

24-month outcomes of an eHealth universal program for students and parents to prevent adolescent alcohol use: A cluster randomized controlled trial in schools.

Background: Parents play a critical role in delaying adolescent initiation of alcohol and other drug use. However, the majority of prevention programs focus on adolescents only. This study tested the acceptability and effectiveness of an eHealth universal program for students and parents to prevent adolescent alcohol use. Methods: A cluster randomized controlled trial (RCT) was conducted between 2018 and 2020 with students from one grade level (aged 12-14 years) from 12 Australian secondary schools randomly allocated to the intervention or control conditions. Students accessed a web-based program in class and parents accessed the program online at their convenience. Data were collected via online questionnaires from students (N = 572) and parents (N = 78) at baseline, and 12- and 24- months post baseline. Multilevel, mixed effects regression models were used to analyse student data. Findings: More students in the control group reported having at least one standard alcoholic drink and engaging in heavy episodic drinking in the previous 12 months at both 12- and 24-month follow up compared to students in the intervention, however, these differences were not statistically significant. Students in the intervention group reported greater increases in alcohol-related knowledge, compared to the control students. Qualitative data from parents indicated that they found the program useful, however, the number of parents who enrolled in the research study (13.9 %) was low. Parent engagement increased following implementation of an interactive parent/adolescent homework task. Conclusions: Small sample size, low prevalence of alcohol use and parental engagement, and relatively short follow-up period may have contributed to lack of observed intervention effect, other than on alcohol-related knowledge. Parents who engaged with the program found it useful, however, implementation strategies that encourage parent-child interaction and communication may increase parent engagement for future programs.

Longitudinal relationships between lifestyle risk factors and neurodevelopment in early adolescence.

OBJECTIVE: The goal of this study is to investigate the cross-sectional and longitudinal relationships between clustered lifestyle risk factors (sleep, physical activity, body mass index [BMI], and screen time) and neurodevelopment over the early adolescent period. METHOD: Data from the ABCD Study Data Release 3.0 consisted of 11,878 participants (aged 9-10 years) at baseline and 6,571 participants (aged 11-12 years) at 2-year follow-up. The interrelationships between lifestyle risk factors and brain structure were analyzed using bivariate multiple indicator latent change score models. Using confirmatory factor analysis, a single lifestyle risk factor domain (measured by sleep, physical activity, BMI, and screen time) was shown to fit the data well. Using exploratory and confirmatory factor analysis, seven brain structure domains were extracted and labeled as temporal-parietal, frontotemporal, occipital, orbitofrontal, temporal, cingulate, parietal, and cuneus domains. All bivariate latent change score models accounted for age, sex at birth, race/ethnicity, parental education, and marital status. RESULTS: Higher lifestyle risk was associated with smaller brain volume at baseline. Higher baseline lifestyle risk was also associated with a greater rate of change (i.e., greater decreases) in brain volume for the temporal-parietal, frontotemporal, orbitofrontal, parietal, and cuneus domains. Effects were not reciprocal; baseline brain volume did not predict changes in lifestyle behaviors over time. CONCLUSION: These findings are important for understanding the biological mechanisms underpinning health risk factors and can be used to target interventions and improve brain health during this critical developmental phase. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

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.

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.

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).

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.