Search

The volatile and 24/7 nature of the cryptocurrency market allows traders to engage in speculative trading patterns closely resembling gambling. Its potential for harm and financial loss warrant investigation from a public health perspective. Therefore, we summarized the emerging literature on cryptocurrency trading and its link to problematic gambling and other mental health outcomes such as depression and anxiety. We also examined demographic or psychological factors associated with cryptocurrency trading.We searched PubMed, Scopus, and Embase for published, original studies investigating associations with cryptocurrency trading behavior. We also conducted supplementary searches using Google Scholar.Eight papers were included after eligibility screening. Our scoping review revealed associations between problem gambling symptoms and cryptocurrency trading engagement and intensity. Furthermore, we found cryptocurrency traders share similar demographic and personality characteristics with share-traders and problem gamblers. Studies on cryptocurrency trading and mental health produced mixed results.Our scoping review indicates a likely relationship between problem gambling and cryptocurrency trading. Findings also suggest overlap with high-risk stock traders, with similarities in gambling behaviors, demographics, and personality traits. These findings justify further research into problem cryptocurrency trading behaviors and their potential for harm, especially concerning mental health. To assess what behaviors are problematic, future research should also look to explore differences between long-term investors and short-term traders of cryptocurrency.

E-cigarettes may benefit public health if they are effective for smoking cessation. Evidence suggests that the frequency of e-cigarette use is likely an important predicator of smoking cessation success, so we examined the associations between frequency of e-cigarette use and smoking reduction and cessation in an Australian population sample of past year adult smokers.Data from the 2019 National Drug Strategy Household Survey were used (N = 22,015). The sample was restricted to 3868 adults who had smoked within the past year. The outcome was self-reported smoking status and smoking reduction, adjusted for key potential confounders.Compared with no current e-cigarette use, daily e-cigarette users reported an increased likelihood for smoking reduction among current daily smokers (RRR = 2.83; 95% CI = 1.53, 5.22) and were more likely to report quitting smoking among past year smokers (RRR = 2.16; 95% CI = 1.30, 3.58). Smoking reduction and cessation for occasional e-cigarette use were not significantly different from no e-cigarette use.Daily, but not occasional, e-cigarette users were more likely to quit or reduce smoking cigarettes than Australian smokers who did not use e-cigarettes.

Aims In Australia, sales of nicotine containing electronic cigarettes (also known as e-cigarette) are banned unless approved as a therapeutic good. The aims of this study were to estimate the prevalence of e-cigarette use and its correlates in Australia using a nationally representative survey. Method We analysed data from the largest drug use survey in Australia (the National Drug Strategy Household Survey [NDSHS]; N = 22,354). Results We estimated that 227,000 Australians (1.2% of the population) were current e-cigarettes users, and 97,000 (0.5%) used them daily. Individuals who were male, younger, had higher level of psychological distress, and smoked were more likely to use electronic cigarettes. Among smokers, an intention to quit and reduction in smoking was associated with experimentation and daily use of e-cigarette, but not with occasional use. Recent quitting was associated with daily use. Conclusion Overall, the prevalence of e-cigarette use was low in 2016 in Australia. Smoking status was the strongest correlates of e-cigarette use. Patterns of vaping were differentialy associated with an intention to quit smoking, smoking reduction and recent quitting. Some smokers may attempt to use e-cigarettes to cut-down their tobacco use, and those who vaped daily were mostly likely to be recent quitters.

Introduction An increase in electronic cigarette (EC) use among US youth has raised concerns that their use may increase conventional cigarette smoking. Methods Repeated cross-sectional data from two large nationally representative samples of US youth were drawn from the National Youth Tobacco Survey (NYTS) and Monitoring the Future (MTF). Students from grade 6–12 of the NYTS (N = 98,454–132,003) and students from grade 12 of the MTF (N = 17,870–30,981) were included in the analyses. Trends in smoking behavior, intention to smoke in the future and perceived smoking harms among youth who do and do not use ECs were estimated from 2014 to 2020 using weighted multinomial logistic regression and predicted marginal probabilities. Results The prevalence for regular smoking decreased among youth who regularly use ECs. For example, among regular EC users, smoking prevalence decreased from 27.8% to 6.7% (−21%; 99.67% CI:[−32.3%, −9.9%]) in the NYTS between 2014 and 2020 and from 31.8% to 10.6% (−21.2%, 99.67% CI:[−35.0%, −7.3%]) in the MTF between 2014 and 2018. Intent to smoke in the future and perceiving smoking as harmless decreased or remained unchanged during the same period. For example, among regular EC users, there was no significant change in intention to smoke next year in the NYTS between 2014 and 2018; intention to smoke in the next 5 years decreased significantly from 30.7% to 11.2% (−19.5%, 99.67% CI:[−37.7%, −1.3%]) in the MTF. Conclusions In two national samples of US youth, smoking prevalence declined by a sizeable relative percentage. Intent to smoke in the future and harm perceptions of smoking declined or remained unchanged while EC use increased. Results provide little evidence that EC use has increased conventional cigarette smoking among youth.

We examine age-related trends in past-year cannabis use in a series of nationally representative surveys in Australia.We analysed data from the largest nationally representative survey in Australia collected between 2001 and 2019 (National Drug Strategy Household Survey [NDSHS]; N = 157,151). Prevalence of past-year daily/occasional (non-daily)/non-use of cannabis use were estimated using weighted multinomial logistic regression and predicted marginal probabilities. Difference-in-difference analysis was used to examine if trends of cannabis use across age groups were different.The youngest age group (14-17 s) witnessed the largest increase in past-year abstinence rate from 79% to 92% from 2001 to 2019 (p .003); the increase in abstinent rate among the 18-24 and 25-39 were relatively moderate (from 68 to 76% and from 81% to 84% respectively; p .003). The abstinent rate among the 40-54 s and 55-74 s decreased significantly from 93% to 90% and from 99% to 95% respectively (p .003). There were similar diverging trends in occasional and daily cannabis use, with decreases in both patterns of use observed among the younger age group (14-17 s and 18-25 s) but increases among the older age group (40-54 s and 55-74 s).There is a diverging trend in cannabis use among younger and older age groups in Australia between 2001 and 2019. Cannabis use substantially decreased among the youngest age group (14-17 s) but modestly increased among older people (55-74 s).

Aim E-cigarettes, or nicotine vaping products, are potential smoking cessation aids that provide both nicotine and behavioural substitution for combustible cigarette smoking. This review aims to compare the effectiveness of nicotine e-cigarettes for smoking cessation with licensed nicotine replacement therapies (NRT) and nicotine-free based control conditions by using network meta-analysis (NMA). Methods We searched PubMed, Web of Science and PsycINFO for randomised controlled trials (RCTs) that allocated individuals to use nicotine e-cigarettes, compared to those that used licensed NRT (e.g., nicotine patches, nicotine gums, etc), or a nicotine-free control condition such as receiving placebo (nicotine-free) e-cigarettes or usual care. We only included studies of healthy individuals who smoked. Furthermore, we identified the latest Cochrane review on NRT and searched NRT trials that were published in similar periods as the e-cigarette trials we identified. NMA was conducted to compare the effect of e-cigarettes on cessation relative to NRT and control condition. Cochrane risk-of-bias tool for randomized trials Version 2 was used to access study bias. Results For the e-cigarette trials, our initial search identified 4,717 studies and we included 7 trials for NMA after removal of duplicates, record screening and assessment of eligibility (Total N = 5,674). For NRT trials, our initial search identified 1,014 studies and we included 9 trials that satisfied our inclusion criteria (Total N = 6,080). Results from NMA indicated that participants assigned to use nicotine e-cigarettes were more likely to remain abstinent from smoking than those in the control condition (pooled Risk Ratio (RR) = 2.08, 97.5% CI = [1.39, 3.15]) and those who were assigned to use NRT (pooled RR = 1.49, 97.5% CI = [1.04, 2.14]. There was a moderate heterogeneity between studies (I2 = 42%). Most of the e-cigarette trials has moderate or high risk of bias. Conclusion Smokers assigned to use nicotine e-cigarettes were more likely to remain abstinent from smoking than those assigned to use licensed NRT, and both were more effective than usual care or placebo conditions. More high quality studies are required to ascertain the effect of e-cigarette on smoking cessation due to risk of bias in the included studies.

To test the age, cohort, and period effect on past-year use trends in psychedelic drugs and ecstasy.Data were from a repeated cross-sectional nationally representative household survey in Australia conducted every three years between 2001 and 2019. An age-period-cohort model was used to test the effect of age, birth cohort, and period on past year psychedelic and ecstasy use. Participants were between 18 and 80 years old at the time of the survey. The total sample size was 149,296 (Mean age = 45.8; 56% female). Past-year use of psychedelics and ecstasy were the key outcome variables. There were six birth cohorts that were derived in each survey: 1936-50, 1951-60, 1961-70, 1971-80, 1981-90, and 1991-2001. There were seven periods that coincided with survey years: 2001, 2004, 2007, 2010, 2013, 2016 and 2019. Age was treated as continuous.Past-year use of both psychedelics and ecstasy decreased with age, b = -0.87, 95% CI [-1.14, -0.61] and b = -0.84, 95% CI [-1.08, -0.60]. For ecstasy, while there was significant variation across periods (p .001), there was no obvious trend. There was a significant birth cohort effect (p .001), with prevalence increasing from the 1936-50 cohort, peaking in the 1971-80 cohort and then decreasing in the 1991-2001 cohort. For psychedelics, there was significant variation across periods (p .001) with an upward trend. There was a significant birth cohort effect (p .001), with prevalence increasing from the 1936-50 cohort to similarly high prevalence for the three most recent cohorts (1971-80, 1981-90, 1991-2001).There were strong cohort and period effects in trends in the use of psychedelic and ecstasy.

Background and Aims We aim to quantify the prevalence and risk of having a cannabis use disorder (CUD), cannabis abuse (CA) or cannabis dependence (CD) among people in the general population who have used cannabis. Method We conducted a systematic review of epidemiological cross-sectional and longitudinal studies on the prevalence and risks of CUDs among cannabis users. We identified studies published between 2009 and 2019 through PubMed, the Global Burden Disease (GBD) Database, and supplementary searches up to 2020. The outcomes of interest were CUDs based on DSM or ICD criteria. Estimates were synthesized using random-effects meta-analyses, followed by meta-regression of study characteristics on effect sizes. Results From 1383 records identified, 21 studies were included. Meta-analyses showed that among people who used cannabis, 22% (18–26%) have CUD, 13% (8–18%) have CA, and 13% (10–15%) have CD. Estimates from cohort studies, showed that the risk of developing CD increased to 33% (22–44%) among young people who engaged in regular (weekly or daily) use of cannabis. There was a lack of data from cohort studies to estimate the risk of CUD or CA among regular cannabis users. Conclusions Cannabis users need to be informed about the risks of developing CUDs and the higher risks among those who initiate early and use frequently during adolescence. Future studies are needed to examine how changes in cannabis policies may affect the risks of CUDs in the population.

Aims: This study estimated the extent of familial alcohol supply in 45 low and middle income countries (LMIC), and examined the country-level effects of familial alcohol supply on adolescents’ alcohol use. Method: We used data from 45 LMICs that participated in the Global School-Based Student Health Survey (GSHS) between 2003 and 2013 (n=139,840). The weighted prevalence of familial alcohol supply in each country was estimated. Multilevel binary and ordinal logistic regression analyses were used to examine the country-level effect of familial alcohol supply on early onset of alcohol use (first alcohol before 12), past 30-day alcohol use, lifetime drunkenness and alcohol-related social problems. Results: There were large variations between LMICs in the prevalence of familial alcohol supply and pattern of adolescent alcohol use. The prevalence of familial supply ranged from 0.1% in Tajikistan to 23.8% in St Lucia. It was estimated that a one percentage change in prevalence of familial alcohol supply was associated with 10%, 12% and 12% change in the odds of lifetime drunkenness (OR = 1.10, 95% CI = [1.04, 1.16]), early onset of alcohol use (OR = 1.12, 95% CI = [1.07, 1.08]) and more frequent drinking in the past month (OR = 1.12, 95% CI = [1.04, 1.20]). Conclusion: There were large variations in the prevalence of familial alcohol supply and adolescent alcohol use among LMICs. Adolescents in countries with higher prevalence of familial alcohol supply were more likely to start using alcohol at an earlier age, to have used alcohol in the past 30 days and experience intoxication.