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).

"What Do I Say? How Do I Say it?" Twitter as a Knowledge Dissemination Tool for Mental Health Research.

This study aims to generate evidence-based guidelines for researchers regarding how to effectively disseminate mental health research via Twitter. Three hundred mental health research Tweets posted from September 2018 to September 2019 were sampled from two large Australian organizations. Twenty-seven predictor variables were coded for each Tweet across five thematic categories: messaging; research area; mental health area; external networks; and media features. Regression analyses were conducted to determine associations with engagement outcomes of Favourites, Retweets, and Comments. Less than half (n = 10) of predictor variables passed validity tests. Notably, conclusions could not reliably be drawn on whether a Tweet featured evidence-based information. Tweets were significantly more likely to be Retweeted if they contained a hyperlink or multimedia. Tweets were significantly more likely to receive comments if they focused on a specific population group. These associations remain significant when controlling for organization. These findings indicate that researchers may be able to maximize engagement on Twitter by highlighting the population groups that the research applies to and enriching Tweets with multimedia content. In addition, care should be taken to ensure users can infer which messages are evidence-based. Guidelines and an accompanying resource are proposed.

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).

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.

Evaluating a Peer-Support Mobile App for Mental Health and Substance Use Among Adolescents Over 12 Months During the COVID-19 Pandemic: Randomized Controlled Trial.

BACKGROUND: Although it is well known that adolescents frequently turn to their friends for support around mental health and substance use problems, there are currently no evidence-based digital programs to support them to do this. OBJECTIVE: The aim of this study was to evaluate the efficacy of the Mind your Mate program, a digital peer-support program, in improving mental health symptoms, reducing the uptake of substance use, and increasing help seeking. The Mind your Mate program consists of a 40-minute web-based classroom lesson and a companion smartphone mobile app. The active control group received school-based health education as usual. METHODS: A cluster randomized controlled trial was conducted with 12 secondary schools and 166 students (mean age 15.3, SD 0.41 years; 72/166, 43.4% female; and 133/166, 80.1% born in Australia). Participants completed self-reported questionnaires assessing symptoms of mental health (depression, anxiety, and psychological distress), substance use (alcohol and other drug use), and help-seeking measures at baseline and at 6-month and 12-month follow-ups. RESULTS: Students who received the Mind your Mate program had greater reductions in depressive symptoms over a 12-month period than controls (b=-1.86, 95% CI -3.73 to 0.02; Cohen d=-0.31). Anxiety symptoms decreased among students in the intervention group; however, these reductions did not meet statistical significance thresholds. No differences were observed in relation to psychological distress or help-seeking. CONCLUSIONS: Small to moderate reductions in depression symptoms were observed among students allocated to receive the Mind your Mate intervention. Although the current results are encouraging, there is a need to continue to refine, develop, and evaluate innovative applied approaches for the prevention of mental disorders in real-world settings. TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry (ANZCTR) ACTRN12620000753954; https://anzctr.org.au/Trial/Registration/TrialReview.aspx?ACTRN=12620000753954. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/26796.

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.

Age-varying associations between lifestyle risk factors and major depressive disorder: a nationally representative cross-sectional study of adolescents.

PURPOSE: Lifestyle risk factors, such as alcohol use, smoking, high body mass index, poor sleep, and sedentary behavior, represent major public health issues for adolescents. These factors have been associated with increased rates of major depressive disorder (MDD). The purpose of this paper is to investigate critical peaks in the prevalence of MDD at certain ages and to examine how these peaks might be amplified or attenuated by the presence of lifestyle risk factors. METHODS: A nationally representative sample of adolescents aged 11-17 years old (n = 2967) and time-varying effect models were used to investigate the associations between lifestyle risk factors and the prevalence of MDD by sex. RESULTS: The estimated prevalence of MDD significantly increased among adolescents from 4% (95% CI 3-6%) at 13 years of age to 19% (95% CI 15-24%) at 16 years of age. From the age of 13, males were significantly less likely to have a diagnosis of MDD than females with the maximum sex difference occurring at the age of 15 (OR 0.24, 95% CI 0.13-0.47). All lifestyle risk factors were at some point significantly associated with MDD, but these associations did not differ by sex, except for body mass index. DISCUSSION: These findings suggest that interventions designed to prevent the development of depression should be implemented in early adolescence, ideally before or at the age of 13 and particularly among young females given that the prevalence of MDD begins to rise and diverge from young males. Interventions should also simultaneously address lifestyle risk factors and symptoms of major depression.

Lifestyle risk indices in adolescence and their relationships to adolescent disease burden: findings from an Australian national survey.

BACKGROUND: The current study investigates the extent to which an adolescent-specific lifestyle risk factor index predicts indicators of the leading causes of adolescent morbidity and mortality. METHODS: Data came from 13 to 17 year-old respondents from the 2013-2014 nationally representative Australian Child and Adolescent Survey of Mental Health and Wellbeing (n = 2314). Indicators of adolescent disease burden included Major Depressive Disorder, psychological distress, self-harm and suicide attempt. Risk factors included risky alcohol use, drug use, unprotected sex, smoking, BMI and sleep duration. The extent to which these risk factors co-occurred were investigated using tetrachoric correlations. Several risk indices were then constructed based on these risk factors. Receiver Operating Characteristic curves determined the precision with which these indices predicted the leading causes of adolescent disease burden. RESULTS: Risky alcohol use, drug use, smoking, unprotected sex, and sleep were all highly clustered lifestyle risk factors, whereas BMI was not. A risk index comprising risky alcohol use, drug use, unprotected sex and sleep duration predicted the disease burden outcomes with the greatest precision. 31.9% of the sample reported one or more of these behaviours. CONCLUSIONS: This lifestyle risk factor index represents a useful summary metric in the context of adolescent health promotion and non-communicable disease prevention. Lifestyle risk factors were found to cluster in adolescence, supporting the implementation of multiple health behaviour change interventions.

Associations between personality disorder characteristics and treatment outcomes in people with co-occurring alcohol misuse and depression.

BACKGROUND: Personality disorders are highly comorbid with alcohol misuse and depressive symptomatology; however, few studies have investigated treatment outcomes in this population. The aim of this study was to examine relationships between baseline personality disorder cluster profiles and overall and treatment-related changes for those with co-occurring alcohol misuse and depression. METHODS: Secondary analysis was conducted using a subset of data (N = 290) from two randomised controlled trials of psychological interventions for co-occurring alcohol misuse and depression, which did not specifically target personality disorders. Baseline dimensional personality disorder cluster scores were derived from the International Personality Disorder Examination Questionnaire (IPDEQ). Four treatment conditions were compared: a brief integrated intervention, followed by no further treatment, or nine further sessions of integrated-, alcohol-, or depression-focused treatment. Associations between IPDEQ scores and changes in alcohol use, depressive symptoms and functioning from baseline to the 6- and the 12-month follow-ups were of primary interest. RESULTS: Personality disorder cluster scores moderately negatively impacted on overall change (primarily Cluster C), as well as treatment-related outcomes (primarily Cluster A), particularly changes in depressive symptoms and psychosocial functioning. Longer interventions appeared to be more effective in the longer-term (e.g., at 12-month follow-up), with integrated interventions relatively more effective than single-focused ones for individuals with higher personality disorder cluster scores. CONCLUSIONS: Greater attention needs to be paid to particular personality disorder clusters during the assessment and treatment of individuals with co-occurring alcohol misuse and depression. Integrated interventions, incorporating motivational interviewing and cognitive behaviour therapy, may provide a useful therapeutic framework. Integrated interventions also provide opportunities for adjunctive components focussing on other issues and coping strategies (e.g., to offset negative affective states), potentially tailored to the characteristics and needs of individual participants.

'The convenience is a double-edged sword': Qualitative interviews with people who use online alcohol delivery services.

INTRODUCTION: The past decade has seen a shift towards online purchasing and home delivery of alcohol, with this trend accelerated due to the COVID-19 pandemic. However, research in this area is limited. This study aims to explore how and why people use online alcohol delivery services. METHODS: Semi-structured qualitative interviews (mean = 12.5 min; range = 7-19.5 min) with a convenience sample of 40 Australians ≥18 years who purchase alcohol online for delivery at least once per month. Reflexive thematic analysis was used to analyse and report the data. RESULTS: Three themes were generated. (i) The convenience is a 'double-edged sword': almost all participants expressed that they use alcohol delivery services because they reduce difficulty in obtaining alcohol by saving time or energy/effort; however, for some this could lead them to purchase and consume more alcohol than they otherwise would have. (ii) Cost savings motivate online purchases: some participants expressed that they could access alcohol more cheaply online than in-store due to promotions, cost-comparisons and the ability to shop at low-cost outlets. (iii) Initiating or increasing use during the COVID-19 pandemic: for some people continued or increased use had been maintained as they had grown accustomed to the convenience or changed shopping habits. DISCUSSION AND CONCLUSION: Participants purchased alcohol online for home delivery primarily for convenience; however, for some the convenience could lead them to purchase and consume more alcohol than they otherwise would have. Targeted improvements to the regulation of these services are needed to minimise the risks they may pose for alcohol harm.

Motherhood and drinking: The relative importance of mental health and psychosocial factors on maternal alcohol misuse during the postpartum period.

OBJECTIVE: Being a mother of a young child may be protective against alcohol misuse for some, but not all, women. This is the first paper to identify the mental health and psychosocial correlates of alcohol misuse among postpartum mothers. METHODS: Mothers with a child under 12-months (n=319) were recruited via social media to complete a cross-sectional online survey. Two hierarchical logistic regressions examined unique factors associated with heavy episodic drinking and hazardous alcohol use, including sociodemographic, mental ill-health, and psychosocial factors. RESULTS: On average, mothers drank alcohol at low levels (4 drinking days, 9 standard drinks in the past month). One in 10 (11.6%) reported heavy episodic drinking during this time and 1 in 12 (8.5%) were drinking at hazardous or greater levels. In the final models, older age and more severe postpartum anxiety were associated with higher likelihood of hazardous drinking (OR=1.37, OR=1.09, respectively), while breastfeeding was associated with lower odds of heavy episodic drinking (OR=0.29). Greater perceived social support was associated with lower odds of heavy episodic (OR=0.56) and hazardous drinking (OR=0.39), while higher coping-with-anxiety and social drinking motives were associated with greater odds of both forms of alcohol misuse (ORs=3.51-10.40). Conformity drinking motives (e.g., drinking to avoid social rejection) were negatively associated with heavy episodic drinking (OR=0.24). CONCLUSIONS: Maternal anxiety, coping-with-anxiety and social drinking motives, and reduced social support are important factors associated with postpartum alcohol misuse. These modifiable factors are potential targets for screening and intervention for mothers who may need additional support and preventative care.

Cross-sectional survey of a convenience sample of Australians who use alcohol home delivery services.

INTRODUCTION: Online alcohol purchasing and home delivery has increased in recent years, accelerated by the onset of the coronavirus disease 2019 pandemic. This article aims to investigate the purchasing and drinking behaviour of Australians who use online alcohol delivery services. METHOD: A cross-sectional self-report survey with a convenience sample of 1158 Australians ≥18 years (49.3% female) who used an online alcohol delivery service in the past 3 months, recruited through paid social media advertisements from September to November 2021. Quota sampling was used to obtain a sample with age and gender strata proportional to the Australian adult population. Descriptive statistics were generated and logistic regression used to explore variables that predict hazardous/harmful drinking (Alcohol Use Disorders Identification Test score ≥8). RESULTS: One-in-five (20.1%, 95% confidence interval [CI] 17.8-22.5) participants had used an alcohol delivery service to extend a home drinking session because they had run out of alcohol and wanted to continue drinking and, of these, one-third (33.9%, 95% CI 27.9-40.4) indicated that if the service was not available they would have stopped drinking. Using delivery services in this way was associated with six times higher odds of drinking at hazardous/harmful levels (odds ratio 6.26, 95% CI 3.78-10.36). Participants ≤25 years were significantly more likely to report never having their identification verified when receiving their alcohol delivery at the door compared with purchasing takeaway alcohol in-person at a bottle shop (p < 0.001, McNemar). DISCUSSION AND CONCLUSION: Given the risks associated with alcohol delivery, regulation of these services should be improved to meet the same standards as bricks-and-mortar bottle shops.

Can we use ChatGPT for Mental Health and Substance Use Education? Examining Its Quality and Potential Harms.

BACKGROUND: The use of generative artificial intelligence, more specifically large language models (LLMs), is proliferating, and as such, it is vital to consider both the value and potential harms of its use in medical education. Their efficiency in a variety of writing styles makes LLMs, such as ChatGPT, attractive for tailoring educational materials. However, this technology can feature biases and misinformation, which can be particularly harmful in medical education settings, such as mental health and substance use education. This viewpoint investigates if ChatGPT is sufficient for 2 common health education functions in the field of mental health and substance use: (1) answering users' direct queries and (2) aiding in the development of quality consumer educational health materials. OBJECTIVE: This viewpoint includes a case study to provide insight into the accessibility, biases, and quality of ChatGPT's query responses and educational health materials. We aim to provide guidance for the general public and health educators wishing to utilize LLMs. METHODS: We collected real world queries from 2 large-scale mental health and substance use portals and engineered a variety of prompts to use on GPT-4 Pro with the Bing BETA internet browsing plug-in. The outputs were evaluated with tools from the Sydney Health Literacy Lab to determine the accessibility, the adherence to Mindframe communication guidelines to identify biases, and author assessments on quality, including tailoring to audiences, duty of care disclaimers, and evidence-based internet references. RESULTS: GPT-4's outputs had good face validity, but upon detailed analysis were substandard in comparison to expert-developed materials. Without engineered prompting, the reading level, adherence to communication guidelines, and use of evidence-based websites were poor. Therefore, all outputs still required cautious human editing and oversight. CONCLUSIONS: GPT-4 is currently not reliable enough for direct-consumer queries, but educators and researchers can use it for creating educational materials with caution. Materials created with LLMs should disclose the use of generative artificial intelligence and be evaluated on their efficacy with the target audience.

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.

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.

You've got mail: Drinks are on sale! A study to assess volume and content of direct marketing received from online alcohol retailers in Australia.

BACKGROUND: Customers of online alcohol retailers are exposed to marketing displayed on alcohol retailers' websites and may also receive direct marketing via email and text message once contact details are provided in an online sale. To date, this direct marketing activity from online alcohol retailers has not been studied. This study aims to document the quantity and content of marketing material received by customers of online alcohol retailers in Australia, and whether the material complies with relevant regulation. METHODS: A cross-sectional study of direct marketing from the 100 most popular online alcohol retailers in Australia. Marketing material received via email and text message was collected for three-months from March to June 2021. Email and text messages were coded for 17 variables in four categories: primary purpose of the communication; compliance with relevant regulations; marketing themes and practices used; and offers, promotions, and discounts. RESULTS: We received 1496 emails from 85 of the 100 retailers. Of the retailers who sent emails, the number sent varied widely (Mdn=8; IQR=2-21). Seven retailers sent a total of 18 text messages. The primary purpose of most emails (67.4%) was to advertise a special or offer a discount. Almost all emails (98.6%) complied with spam legislation to include an unsubscribe link, but around half (46.5%) of emails from retailers in jurisdictions where the inclusion of a liquor license number is mandatory, failed to include one. The most common marketing theme was to link specific times or events to drinking (18.8%). Almost half (48.5%) of emails advertised free or discounted delivery for purchasing over a specified threshold. CONCLUSION: Most online alcohol retailers in Australia are engaging in direct marketing to their customers via email. More research is needed to understand how these emails may influence purchasing and consumption.