Substance use, depression, and anxiety in adolescence are major public health problems requiring new scalable prevention strategies. We aimed to assess the effectiveness of a combined online universal (ie, delivered to all pupils) school-based preventive intervention targeting substance use, depression, and anxiety in adolescence. We did a multicentre, cluster-randomised controlled trial in secondary schools in Australia, with pupils in year 8 or 9 (aged 13-14 years). Participating schools were randomly assigned (1:1:1:1) to one of four intervention conditions: (1) Climate Schools-Substance Use, focusing on substance use only; (2) Climate Schools-Mental Health, focusing on depression and anxiety only; (3) Climate Schools-Combined, focusing on the prevention of substance use, depression, and anxiety; or (4) active control. The interventions were delivered in school classrooms in an online delivery format and used a mixture of peer cartoon storyboards and classroom activities that were focused on alcohol, cannabis, anxiety, and depression. The interventions were delivered for 2 years and primary outcomes were knowledge related to alcohol, cannabis, and mental health; alcohol use, including heavy episodic drinking; and depression and anxiety symptoms at 12, 24, and 30 months after baseline. This trial is registered with the Australian New Zealand Clinical Trials Registry (ACTRN12613000723785) and an extended follow-up is underway. Between Sept 1, 2013, and Feb 28, 2014, we recruited 88 schools (12 391 pupils), of whom 71 schools and 6386 (51·5%) pupils were analysed (17 schools dropped out and 1308 pupils declined to participate). We allocated 18 schools (1739 [27·25%] pupils; 1690 [97·2%] completed at least one follow-up) to the substance use condition, 18 schools (1594 [25·0%] pupils; 1560 [97·9%] completed at least one follow-up) to the mental health condition, 16 schools (1497 [23·4%] pupils; 1443 [96·4%] completed at least one follow-up) to the combined condition, and 19 schools (1556 [23·4%] pupils; 1513 [97·2%] completed at least one follow-up) to the control condition. Compared with controls, the combined intervention group had increased knowledge related to alcohol and cannabis at 12, 24, and 30 months (standardised mean difference [SMD] for alcohol 0·26 [95% CI 0·14 to 0·39] and for cannabis 0·17 [0·06 to 0·28] at 30 months), increased knowledge related to mental health at 24 months (0·17 [0·08 to 0·27]), reduced growth in their odds of drinking and heavy episodic drinking at 12, 24, and 30 months (odds ratio for drinking 0·25 [95% CI 0·12 to 0·51], and for heavy episodic drinking 0·15 [0·04 to 0·58] at 30 months), and reduced increases in anxiety symptoms at 12 and 30 months (SMD -0·12 [95% CI -0·22 to -0·01] at 30 months). We found no difference in symptoms or probable diagnosis of depression. The combined intervention group also showed improvement in alcohol use outcomes compared with the substance use and mental health interventions and improvements in anxiety outcomes when compared with the mental health intervention only. Combined online prevention of substance use, depression, and anxiety led to increased knowledge of alcohol, cannabis, and mental health, reduced increase in the odds of any drinking and heavy episodic drinking, and reduced symptoms of anxiety over a 30-month period. These findings provide the first evidence of the effectiveness of an online universal school-based preventive intervention targeting substance use, depression, and anxiety in adolescence. Australian National Health and Medical Research Council.

Introduction: Risk behaviors commonly co-occur, typically emerge in adolescence, and become entrenched by adulthood. This study investigated the clustering of established (physical inactivity, diet, smoking, and alcohol use) and emerging (sedentary behavior and sleep) chronic disease risk factors among young Australian adults, and examined how clusters relate to mental health. Methods: The sample was derived from the long-term follow-up of a cohort of Australians. Participants were initially recruited at school as part of a cluster randomized controlled trial. A total of 853 participants (M_age = 18.88 years, SD = 0.42) completed an online self-report survey as part of the 5-year follow-up for the RCT. The survey assessed six behaviors (binge drinking and smoking in the past 6 months, moderate-to-vigorous physical activity/week, sitting time/day, fruit and vegetable intake/day, and sleep duration/night). Each behavior was represented by a dichotomous variable reflecting adherence to national guidelines. Exploratory analyses were conducted. Clusters were identified using latent class analysis. Results: Three classes emerged: “moderate risk” (moderately likely to binge drink and not eat enough fruit, high probability of insufficient vegetable intake; Class 1, 52%); “inactive, non-smokers” (high probabilities of not meeting guidelines for physical activity, sitting time and fruit/vegetable consumption, very low probability of smoking; Class 2, 24%), and “smokers and binge drinkers” (high rates of smoking and binge drinking, poor fruit/vegetable intake; Class 3, 24%). There were significant differences between the classes in terms of psychological distress (p = 0.003), depression (p < 0.001), and anxiety (p = 0.003). Specifically, Class 3 (“smokers and binge drinkers”) showed higher levels of distress, depression, and anxiety than Class 1 (“moderate risk”), while Class 2 (“inactive, non-smokers”) had greater depression than the “moderate risk” group. Discussion: Results indicate that risk behaviors are prevalent and clustered in 18-year old Australians. Mental health symptoms were significantly greater among the two classes that were characterized by high probabilities of engaging in multiple risk behaviors (Classes 2 and 3). An examination of the clustering of lifestyle risk behaviors is important to guide the development of preventive interventions. Our findings reinforce the importance of delivering multiple health interventions to reduce disease risk and improve mental well-being.

Online Mendelian Inheritance in Animals (OMIA) is a freely available curated knowledgebase that contains information and facilitates research on inherited traits and diseases in animals. For the past 29 years, OMIA has been used by animal geneticists, breeders, and veterinarians worldwide as a definitive source of information. Recent increases in curation capacity and funding for software engineering support have resulted in software upgrades and commencement of several initiatives, which include the enhancement of variant information and links to human data resources, and the introduction of ontology-based breed information and categories. We provide an overview of current information and recent enhancements to OMIA and discuss how we are expanding the integration of OMIA into other resources and databases via the use of ontologies and the adaptation of tools used in human genetics.