The underbelly of E-cigarette advertising: regulating online markets on social media platforms.

Australia prohibits the sale of nicotine-vaping products unless prescribed by medical practitioners. Significant policy reforms were announced on the 28th of November 2023 including a ban on single-use disposable vapes with and without nicotine, and the removal of the personal importation scheme. Despite stringent regulations, loopholes exist such that e-cigarette vendors are getting around it, and online markets provide a route to do so. We discuss strategies used by vendors to covertly market e-cigarettes online through social media. In this perspective, we highlight three proposed policies to strengthen social media regulations that may be feasible to implement. Our proposed strategies to regulate e-cigarette product listings on social media involve implementing robust age verification measures, enhancing the system for flagging and reporting prohibited content, and developing a more effective system to identify and flag content related to e-cigarettes.

Through the looking glass: An alcohol advertisement every 3 minutes.

INTRODUCTION: There is growing concern over the lack of regulation of alcohol advertisements on social media platforms frequented by youths. This study aims to build upon existing literature by assessing the frequency with which young Australians (17-25) are shown advertisements promoting alcohol use and the themes utilised in these advertisements. METHODS: A total of 125 Australian youths (mean age 18.74 years; 74.40% female) were recruited in exchange for course credit to participate in an online study. Participants scrolled through Facebook or Instagram for a period of 30 min and screenshotted any alcohol advertisements encountered. Participants then identified the advertisement qualities (or 'themes') present in the advertisements, based on pre-identified categories. Demographic, social media usage and historical personal, peer or familial substance use behaviour data was also collected. RESULTS: Seventy-one university students were exposed to 796 alcohol advertisements across both platforms, and they encountered an advertisement every 2 min and 43 s on average. Most advertisements included call to action features on both Facebook (78.80%) and Instagram (71.17%). Advertisements relating to ease of access (promoting subscription/home delivery; 41.72% and 42.56%) and sales incentives (special offers, promotions, samples or bonuses with purchase; 43.70% and 46.84%) were most common across both platforms. DISCUSSION AND CONCLUSIONS: Alcohol advertisements are highly prevalent online, particularly among Australian youth social media users. Future research should endeavour to identify whether temporal use of alcohol is a predictor of subsequent exposure to alcohol advertising on social media, and whether this exposure is likely to increase successive alcohol use behaviours.

Designing observational studies for credible causal inference in addiction research-Directed acyclic graphs, modified disjunctive cause criterion and target trial emulation.

Randomized controlled trials (RCTs) are considered the gold standard for causal inference. With a sufficient sample size, randomization removes confounding up to the time of randomization and allows the treatment effect to be isolated. However, RCTs may have limited generalizability and transportability and are often not feasible in addiction research due to ethical or logistical constraints. The importance of observational studies from real-world settings has been increasingly recognized in research on health. This paper provides an overview of modern approaches to designing observational studies that enable causal inference. It illustrates three key techniques, Directed Acyclic Graphs (DAGs), modified Disjunctive Cause Criterion and Target Trial Emulation, and discusses the strengths and limitations of their applications.

The Gaming Disorder Identification Test (GADIT) - A screening tool for Gaming Disorder based on ICD-11.

Background: Gaming Disorder was included as an addictive disorder in the latest version of the International Classification of Diseases (ICD-11), published in 2022. The present study aimed to develop a screening tool for Gaming Disorder, the Gaming Disorder Identification Test (GADIT), based on the four ICD-11 diagnostic criteria: impaired control, increasing priority, continued gaming despite harm, and functional impairment. Method: We reviewed 297 questionnaire items from 48 existing gaming addiction scales and selected 68 items based on content validity. Two datasets were collected: 1) an online panel (N = 803) from Australia, United States, United Kingdom and Canada, split into a development set (N = 589) and a validation dataset (N = 214); and 2) a university sample (N = 408) from Australia. Item response theory and confirmatory factor analyses were conducted to select eight items to form the GADIT. Validity was established by regressing the GADIT against known correlates of Gaming Disorder. Results: Confirmatory factor analyses of the GADIT showed good model fit (RMSEA=<0.001-0.108; CFI = 0.98-1.00), and internal consistency was excellent (Cronbach's alphas = 0.77-0.92). GADIT scores were strongly associated with the Internet Gaming Disorder Test (IGDT-10), and significantly associated with gaming intensity, eye fatigue, hand pain, wrist pain, back or neck pain, and excessive in-game purchases, in both the validation and the university sample datasets. Conclusion: The GADIT has strong psychometric properties in two independent samples from four English-speaking countries collected through different channels, and shown validity against existing scales and variables that are associated with Gaming Disorder. A cut-off of 5 is tentatively recommended for screening for Gaming Disorder.