Effectiveness of a universal, school-based, online programme for the prevention of anxiety, depression, and substance misuse among adolescents in Australia: 72-month outcomes from a cluster-randomised controlled trial.

BACKGROUND: The CSC study found that the universal delivery of a school-based, online programme for the prevention of mental health and substance use disorders among adolescents resulted in improvements in mental health and substance use outcomes at 30-month follow-up. We aimed to compare the long-term effects of four interventions-Climate Schools Combined (CSC) mental health and substance use, Climate Schools Substance Use (CSSU) alone, Climate Schools Mental Health (CSMH) alone, and standard health education-on mental health and substance use outcomes among adolescents at 72-month follow-up into early adulthood. METHODS: This long-term study followed up adolescents from a multicentre, cluster-randomised trial conducted across three states in Australia (New South Wales, Queensland, and Western Australia) enrolled between Sept 1, 2013, and Feb 28, 2014, for up to 72 months after baseline assessment. Adolescents (aged 18-20 years) from the original CSC study who accepted contact at 30-month follow-up and provided informed consent at 60-month follow-up were eligible. The interventions were delivered in school classrooms through an online delivery format and used a mixture of peer cartoon storyboards and classroom activities that were focused on alcohol, cannabis, anxiety, and depression. Participants took part in two web-based assessments at 60-month and 72-month follow-up. Primary outcomes were alcohol use, cannabis use, anxiety, and depression, measured by self-reported surveys and analysed by intention to treat (ie, in all students who were eligible at baseline). This trial is registered with the Australian New Zealand Clinical Trials Registry (ACTRN12613000723785), including the extended follow-up study. FINDINGS: Of 6386 students enrolled from 71 schools, 1556 (24·4%) were randomly assigned to education as usual, 1739 (27·2%) to CSSU, 1594 (25·0%) to CSMH, and 1497 (23·4%) to CSC. 311 (22·2%) of 1401 participants in the control group, 394 (26·4%) of 1495 in the CSSU group, 477 (37·%) of 1289 in the CSMH group, and 400 (32·5%) of 1232 in the CSC group completed follow-up at 72 months. Adolescents in the CSC group reported slower year-by-year increases in weekly alcohol use (odds ratio 0·78 [95% CI 0·66-0·92]; p=0·0028) and heavy episodic drinking (0·69 [0·58-0·81]; p<0·0001) than did the control group. However, significant baseline differences between groups for drinking outcomes, and no difference in the predicted probability of weekly or heavy episodic drinking between groups were observed at 72 months. Sensitivity analyses increased uncertainty around estimates. No significant long-term differences were observed in relation to alcohol use disorder, cannabis use, cannabis use disorder, anxiety, or depression. No adverse events were reported during the trial. INTERPRETATION: We found some evidence that a universal online programme for the prevention of anxiety, depression, and substance use delivered in early adolescence is effective in reducing the use and harmful use of alcohol into early adulthood. However, confidence in these findings is reduced due to baseline differences, and we did not see a difference in the predicted probability of drinking between groups at 72-month follow-up. These findings suggest that a universal prevention programme in adolescence is not sufficient to have lasting effects on mental health and substance use disorders in the long term. In addition to baseline differences, substantial attrition warrants caution in interpretation and the latter factor highlights the need for future long-term follow-up studies to invest in strategies to increase engagement. FUNDING: Australian National Health and Medical Research Council.

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).

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.

Retrospective Self-Reports of How Adolescent Substance Use Changed with the COVID-19 Pandemic.

The final year of high school is a challenging phase of adolescents' lives and substance use can play an important role. We examined changes in the frequency and quantity of alcohol and cannabis use, and demographic correlates among Grade 12 students of 2020. Students (N = 844) from nine schools retrospectively self-reported changes in substance use after the easing of COVID-19 lockdowns (back to school), compared to before the pandemic. Changes in use were examined with age, gender, Aboriginal or Torres Islander, parental and family characteristics, and truancy. Thirty-one percent of students reported that they used alcohol less frequently, and 24% reported that they used it more frequently compared to pre-COVID-19. Most students (46%) reported that they used cannabis less, while a subset reported using more frequently (22%). A history of truancy was associated with an increased frequency (OR = 2.13 [1.18-3.83]) of cannabis use. A substantial minority of adolescents used more alcohol and cannabis after the initial COVID-19 lockdown period. Students in their final year who reported increased use may benefit from increased support to manage their substance use.

A two-stage social network intervention for reducing alcohol and other drug use in residential colleges: Protocol for a feasibility trial.

BACKGROUND: In many countries, the rate of binge drinking and alcohol-related harms among students living in residential colleges exceeds that observed among young people in the general population. Peer influence plays a key role in driving alcohol and other drug (AOD) use in colleges. This highlights the potential role of peer influence AOD-interventions in college student-networks. This protocol paper outlines the design of a two-stage social network intervention (SNI) for reducing AOD-use in four Australian first-year residential college networks. METHODS: In Stage 1, a peer-led workshop will provide education about AOD-use and harm-minimisation strategies to four first-year cohorts in the first week of semester one (N ~ 500). In Stage 2, a targeted SNI will be delivered to the largest co-educational, first-year cohort (N ~ 160), wherein heavy drinking 'Strategic Players' (influential students) will be identified and offered a brief, telephone-delivered motivational interviewing intervention for AOD-use (QuikFix). Participants will complete online surveys at baseline and 12-, 26-, and 52-weeks follow-up. RESULTS: Recruitment occurred in February 2021 and is now closed. Results are expected to be submitted for publication in late 2022. CONCLUSIONS: This protocol paper outlines the design of a feasibility trial exploring the impact of applied SNIs for reducing AOD-use and related consequences in residential college student networks. If effective, the two-stage SNI proposed could (i) reduce AOD-use and risk of harm across first-year student networks and (ii) provide an effective brief intervention (QuikFix) to high-risk drinkers who have greatest potential to spread the intervention effects to other risky drinkers in their network. TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry (ACTRN12621000494831).

Changes in Substance Use Among People Seeking Alcohol and Other Drug Treatment During the COVID-19 Pandemic: Evaluating Mental Health Outcomes and Resilience.

BACKGROUND: Alcohol and other drug (AOD) use patterns have altered as a result of the coronavirus (COVID-19) pandemic restrictions. This study aimed to: (i) determine the impact of the pandemic on patterns of AOD use among individuals seeking treatment, (ii) identify which mental health and resilience factors were associated with changes in patterns of AOD use and (iii) evaluate changes in the contextual factors (eg, motivations) associated with use. METHODS: Cross-sectional surveys were completed by clients (n = 325) who had sought AOD treatment from January 2020 onwards. We measured quantity and frequency of AOD use now compared to before the pandemic, mental health (depression, anxiety, trauma exposure), resilience and contextual factors related to AOD use. RESULTS: Quantity of tobacco and cannabis use increased post-pandemic, while methamphetamine and alcohol did not change. Depression was associated with more frequent alcohol use now compared to before the pandemic, while anxiety and lower resilience were associated with less frequent cannabis use now. Lower resilience was associated changes in methamphetamine use. Depression was associated with using more frequently for enjoyment and to alleviate loneliness following the pandemic, and anxiety was associated with using earlier in the day and to alleviate boredom. CONCLUSIONS: The pandemic has led to increased frequency of AOD use for a subset of individuals seeking treatment. Depression, anxiety and resilience are important factors associated with altered AOD use, and changes in the motivations and control surrounding use. Special consideration of this should be considered during AOD treatment through the pandemic.