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The COVID‐19 pandemic has resulted in disruptions across many life domains. The distress associated with the pandemic itself, and with public health efforts to manage the outbreak, could result in increased alcohol use. This study aimed to quantify changes in alcohol use during the early stages of the pandemic and factors associated with different patterns of use. Data were obtained from a longitudinal survey of a representative Australian adult sample (N= 1296, 50% female, Mage= 46.0) conducted from March to June 2020, during the first wave of the COVID‐19 outbreak in Australia. Change in alcohol consumption was examined using Alcohol Use Disorders Identification Test‐Consumption (AUDIT‐C) scores from waves one, three, five, and seven of the study, each 4 weeks apart. Factors associated with alcohol consumption were examined, including depression (PHQ‐9) and anxiety (GAD‐7) symptoms, health risk tolerance, stress and coping, work and social impairment (WSAS), COVID impacts, and sociodemographic variables. We tested changes in alcohol use across the full sample using a mixed effects repeated measure ANOVA model and a multinomial logistic regression to identify factors assessed at wave 1 that were independently associated with alcohol use. There was no significant change in AUDIT‐C scores across the study. For most participants, alcohol use did not increase during the early phase of the COVID‐19 pandemic in Australia. COVID‐19 exposure, higher perceived coping, depression symptoms, and male gender were associated with greater odds of increasing or elevated levels of alcohol use. Social changes, which included working from home, had mixed effects on alcohol consumption. Although no evidence was found for increased alcohol use overall during the early months of the pandemic, several factors were associated with alcohol consumption at risky levels. Greater understanding of motivations for drinking across public and private contexts, along with targeted support for high‐risk groups, could assist in reducing harm associated with alcohol consumption. The COVID‐19 pandemic may have influenced alcohol use, but longitudinal evidence for changes in alcohol consumption is mixed. In a representative sample of 1,296 Australian adults, we found that alcohol use was stable overall in the early months of the pandemic, although with a slight decline in May‐June 2020. COVID‐19 exposure, depression symptoms, and male gender were associated with increasing or elevated alcohol consumption. It is probable that the pandemic had differential impacts on public and private alcohol consumption.

To estimate initial levels of symptoms of depression and anxiety, and their changes during the early months of the COVID‐19 pandemic in Australia; to identify trajectories of symptoms of depression and anxiety; to identify factors associated with these trajectories. Longitudinal cohort study; seven fortnightly online surveys of a representative sample of 1296 Australian adults from the beginning of COVID‐19‐related restrictions in late March 2020 to mid‐June 2020. Symptoms of depression and anxiety, measured with the Patient Health Questionnaire (PHQ‐9) depression and Generalised Anxiety Disorder (GAD‐7) scales; trajectories of symptom change. Younger age, being female, greater COVID‐19‐related work and social impairment, COVID‐19‐related financial distress, having a neurological or mental illness diagnosis, and recent adversity were each significantly associated with higher baseline depression and anxiety scores. Growth mixture models identified three latent trajectories for depression symptoms (low throughout the study, 81% of participants; moderate throughout the study, 10%; initially severe then declining, 9%) and four for anxiety symptoms (low throughout the study, 77%; initially moderate then increasing, 10%; initially moderate then declining, 5%; initially mild then increasing before again declining, 8%). Factors statistically associated with not having a low symptom trajectory included mental disorder diagnoses, COVID‐19‐related financial distress and social and work impairment, and bushfire exposure. Our longitudinal data enabled identification of distinct symptom trajectories during the first three months of the COVID‐19 pandemic in Australia. Early intervention to ensure that vulnerable people are clinically and socially supported during a pandemic should be a priority.

Objectives:Young people attending university for the first time may be at heightened risk of experiencing mental health problems. However, limited research has examined the mental health experiences of this cohort using longitudinal methods. This study aimed to examine mental health symptoms prior to commencing university, estimate changes in symptoms over the course of the first semester of study, and identify factors associated with initial symptom levels and changes. Methods:Australian first-year undergraduate students (N= 340) were recruited via social media and participated in a four-wave online longitudinal study conducted between February and June 2021. Symptoms of depression, anxiety, and psychological distress were assessed at each wave, along with psychosocial and lifestyle factors. Demographic characteristics were assessed at baseline. Results:Latent growth curve models indicated no significant linear change over time for depression (p= .26) or anxiety (p= .83) symptoms. However, a significant effect of time was observed for psychological distress (p= .03), indicating higher distress levels at wave 3 compared to baseline (p= .004). Financial stress, pressure to succeed, difficulty coping, greater loneliness, and more negative social interactions were each significantly associated with higher baseline depression, anxiety, and distress scores. Only greater loneliness and more negative social interactions were found to be associated with a greater increase in depression over time. Conclusion:The findings indicate that transition to university was not generally associated with an increase in poor mental health. However, several factors were associated with poorer mental health immediately prior to university commencement. Assisting students to manage financial distress, facilitating the development of social connections among students with limited social networks and skills training targeting coping and the development of realistic academic expectations may help support student mental health and promote improved wellbeing during transition to university.

Internet-based prevention programs for eating disorders are effective, but a variety of challenges have been found when offering them in real-world settings. The current study aimed to test ProYouth OZ,an Internet-based eating disorder prevention program consisting of multiple components including peer support. In total, 50 young adults (18–25 years) with eating disorder symptoms were allocated to one of three versions of the program. In total, 21% did not access the program. From 17 participants in the peer support group, 60% attended at least one chat session and 12% attended all six sessions. Given that only fifteen participants (30%) completed the questionnaire after the intervention, it is not possible to draw reliable conclusions about the effectiveness of the program. Findings demonstrate the difficulty of recruiting emerging adults, engaging them with the program and collecting data after participation. The majority of interested participants experienced an eating disorder, suggesting they may be searching for help online. Future studies should investigate the use of peer support, identify strategies for reaching eligible participants and develop approaches to increase engagement. Finally, it is important to develop innovative programs that provide self-help strategies and facilitate help-seeking for those who are experiencing an eating disorder.

Transdiagnostic online interventions have the potential to overcome help seeking barriers, address symptom comorbidity, and increase accessibility to evidence-based treatments. However, there is currently a lack of high quality studies examining brief transdiagnostic interventions, as well as research examining optimal methods for screening and providing members of the community with access to these interventions. This randomised controlled trial will compare a brief, video-based transdiagnostic online intervention (FitMindKit)to an attention matched control condition (HealthWatch).