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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. [ABSTRACT FROM AUTHOR]

Background and aims: Population‐level alcohol use data are available from high‐income countries, but limited research has been conducted in sub‐Saharan Africa. This systematic review and meta‐analysis aimed to summarize population‐level alcohol use in sub‐Saharan Africa. Method: Databases searched included PubMed, EMBASE, PsycINFO and AJOL, without language restrictions. Searches were also conducted in the Global Health Data Exchange (GHDx) and Google Scholar. Search terms encompassed 'substance' or 'substance‐related disorders' and 'prevalence' and 'sub‐Saharan Africa'. We included general population studies on alcohol use (including any use, high‐risk alcohol use and alcohol use disorders) from 2018 onwards. Prevalence data for alcohol use among sub‐Saharan African adolescents (10–17) and adults (18+) were extracted. Analyses included life‐time and past 12‐ and 6‐month alcohol use. Results: We included 141 papers. Among adolescents, the life‐time prevalence of alcohol use was 23.3% [95% confidence interval (CI) = 11.3–37.1%], 36.2% (CI = 18.4–56.1%) in the past year and 11.3% (CI = 4.5–20.4%) in the past 6 months. Among adolescents, 12‐month prevalence of alcohol use disorder and alcohol dependence were 7.7% (CI = 0.0–27.8%) and 4.1% (CI = 1.4–7.9%), respectively. Among adults, the life‐time prevalence of alcohol use was 34.9% (CI = 17.7–54.1%), 27.1% (CI = 5.0–56.4%) in the past year and 32.2% (CI = 19.8–46.0%) in the past 6 months. Among adults, the 12‐month prevalence of alcohol use disorder and alcohol dependence were 9.5% (CI = 0.0–30.4%) and 4.3% (CI = 0.8–9.8%), respectively. The highest weighted life‐time prevalence of alcohol use, 86.4%, was reported in Tanzania among adults. The highest weighted past 6‐month prevalence of alcohol use, 80.6%, was found in Zambia among adolescents. Conclusion: Alcohol use patterns vary across countries and subregions within sub‐Saharan Africa, and comprehensive population‐level data on alcohol use remain scarce in numerous sub‐Saharan African countries. The prevalence of alcohol use disorder is common among adolescents in sub‐Saharan Africa. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Introduction: Substance use, including drugs, alcohol and smoking have a significant health, social and economic impact. We aim to assess the rate and factors associated with treatment access among individuals with high‐risk substance use. Method: This study is a cross‐sectional analysis of the 2019 Australian National Drug Strategy Household Survey (N = 22,015). Participants were persons with high‐risk substance use based on the Alcohol, Smoking and Substance Involvement Screening Test—Lite (ASSIST‐Lite) and current smokers. We measured self‐reports of past 12‐month engagement in a tobacco, alcohol or other drugs treatment program. Results: Overall, 0.4% had high‐risk drug use (0.3% cannabis, 0.1% meth/amphetamine or 0.1% opioids), 7.4% had high‐risk alcohol use, and 14.0% currently smoked. Among high‐risk users, past 12‐month treatment access rates were 50.6% [22.3–78.9%] for opioids, 27.1% [8.1–46.1%] for meth/amphetamine, 14.5% [4.3–24.7%] for cannabis, 9.6% [8.1–11.0%] for alcohol and 11.7% [10.6–12.9%] for current smoking. The primary source of treatment support was information and education (12.7% drugs, 4.6% alcohol, 4.0% smoking), followed by counselling (6.7% drugs, 4.5% alcohol, 3.0% smoking). Online or internet support was accessed by 5.9% (drug) and 1.6% (alcohol) people with high‐risk use. Psychological distress was associated with treatment access (drugs: odds ratio 3.03 [0.77–11.95], p = 0.111; alcohol: odds ratio 3.16 [2.20–4.56], p ≤ 0.001; smoking: odds ratio 1.95 [1.52–2.49], p ≤ 0.001). Discussion and Conclusions: The proportion of people engaging in risky substance use who had used treatment programs remains low, especially for alcohol. Public health strategies to scale up treatment access are warranted. [ABSTRACT FROM AUTHOR]

Background and Aims: The most available data on the prevalence of cannabis use come from population surveys conducted in high‐income countries in North America, Oceania and Europe. Less is known about the prevalence of cannabis use in Africa. This systematic review aimed to summarize general population‐level cannabis use in sub‐Saharan Africa since 2010. Methods: A comprehensive search was conducted in PubMed, EMBASE, PsycINFO and AJOL databases in addition to Global Health Data Exchange and grey literature without language restriction. Search terms related to 'substance', 'Substance‐Related Disorders' and 'Prevalence' and 'Africa South of the Sahara' were used. Studies that reported cannabis use in the general population were selected, while studies from clinical populations and high‐risk groups were excluded. Prevalence data on cannabis use in the general population of adolescents (10–17 years) and adults (≥ 18 years) in sub‐Saharan Africa were extracted. Results: The study included 53 studies for the quantitative meta‐analysis and included 13 239 participants. Among adolescents, the life‐time, 12‐month and 6‐month prevalence of cannabis use were 7.9% [95% confidence interval (CI) = 5.4–10.9%], 5.2% (95% CI = 1.7–10.3%) and 4.5% (95% CI = 3.3–5.8%), respectively. The corresponding life‐time, 12‐month and 6‐month prevalence of cannabis use among adults were 12.6% (95% CI = 6.1–21.2%), 2.2% (95% CI = 1.7–2.7%, with data only available from Tanzania and Uganda) and 4.7% (95% CI = 3.3–6.4%), respectively. The male‐to‐female life‐time cannabis use relative risk was 1.90 (95% CI = 1.25–2.98) among adolescents and 1.67 (CI = 0.63–4.39) among adults. Conclusions: Life‐time cannabis use prevalence in sub‐Saharan Africa appears to be approximately 12% for adults and just under 8% for adolescents. [ABSTRACT FROM AUTHOR]

Aims: There is a growing body of literature exploring the types of substance‐related content and their portrayals on various social media platforms. We aimed to summarize how content related to substances is portrayed on various social media platforms. Methods: This systematic review was pre‐registered on PROSPERO (ref: CRD42021291853). A comprehensive search was conducted in the databases of PubMed, Scopus, PsycINFO and Web of Science in April 2021. Original qualitative studies published post‐2004 that included thematic and sentiment analyses of social media content on tobacco, alcohol, psychostimulant, e‐cigarette, cannabis, opiate, stimulant/amphetamine, inhalant and novel psychoactive substance were included. Social media platforms were defined as online web‐ or application‐based platforms that allowed users to generate content and interact via 'liking', comment or messaging features. Only studies that included summative and/or thematic content analyses of substance‐related social media content were included. Results: A total of 73 studies, which covered 15 905 182 substance‐related posts on Twitter, YouTube, Instagram, Pinterest, TikTok and Weibo, were identified. A total of 76.3% of all substance‐related content was positive in its depiction of substance use, with 20.2% of content depicting use negatively. Sentiment regarding opiate use however was commonly negative (55.5%). Most studies identified themes relating to Health, Safety and Harms (65.0%) of substance use. Themes relating to Promotions/Advertisements (63.3%), Informative content (55.0%) and Use behaviours (43.3%) were also frequently identified. Conclusions: Substance‐related content that promotes engagement with substance use or actively depicts use appears to be widely available on social media. The large public presence of this content may have concerning influences on attitudes, behaviours and risk perceptions relating to substance use, particularly among the most vulnerable and heaviest users of social media—adolescents and young adults. [ABSTRACT FROM AUTHOR]

Introductions: In the United States (US), support for cannabis legalization has increased over time. This study examines historical changes in legalization attitudes and the period-specific individual and external influences on these. A systematic search was conducted for publications in PubMed, EMBASE, and PsycINFO up to October 2019. Six studies with a regionally or nationally representative adult US-based populations were included. A secondary analysis was conducted using data from the National Survey of Drug Use and Health. Hierarchical age-period-cohort analysis assessed the trends in perceived harmfulness and availability of cannabis between 1996 and 2018. Ecological comparisons were made between these perceptions and support for cannabis legalization over time. A steep growth in support for cannabis legalization began in the 1990s and continued to grow in a relatively linear manner. Most people developed more liberal views, with no evidence that changes within any one sociodemographic group was disproportionately responsible for the overall attitudinal change. Increases in the proportion of people who use cannabis, non-religious population and political liberalism may partially explain the increased support for legalization. The decline in perceived harmfulness of cannabis, as reflected in the media, may have contributed to the increased support for legalization. However, perceptions of the availability of cannabis remained stable despite significant relaxations in cannabis regulations. The US population has become more accepting of cannabis legalization. The attitudinal change is related to changes in the perceived risks and benefits of cannabis use, influenced by broader political and cultural changes over the study period. [ABSTRACT FROM AUTHOR]

Background: Alcohol and other drug (AOD) use patterns have altered as a result of the coronavirus (COVID-19) pandemic restrictions. This study aimed to: (i) determine the impact of the pandemic on patterns of AOD use among individuals seeking treatment, (ii) identify which mental health and resilience factors were associated with changes in patterns of AOD use and (iii) evaluate changes in the contextual factors (eg, motivations) associated with use. Methods: Cross-sectional surveys were completed by clients (n = 325) who had sought AOD treatment from January 2020 onwards. We measured quantity and frequency of AOD use now compared to before the pandemic, mental health (depression, anxiety, trauma exposure), resilience and contextual factors related to AOD use. Results: Quantity of tobacco and cannabis use increased post-pandemic, while methamphetamine and alcohol did not change. Depression was associated with more frequent alcohol use now compared to before the pandemic, while anxiety and lower resilience were associated with less frequent cannabis use now. Lower resilience was associated changes in methamphetamine use. Depression was associated with using more frequently for enjoyment and to alleviate loneliness following the pandemic, and anxiety was associated with using earlier in the day and to alleviate boredom. Conclusions: The pandemic has led to increased frequency of AOD use for a subset of individuals seeking treatment. Depression, anxiety and resilience are important factors associated with altered AOD use, and changes in the motivations and control surrounding use. Special consideration of this should be considered during AOD treatment through the pandemic. [ABSTRACT FROM AUTHOR]

Introduction: Individuals with moderate to severe substance use disorders may seek residential treatment, but outcomes after discharge for this hard‐to‐reach population are often unknown. Using linked data, we examined mortality outcomes among individuals after residential treatment. Methods: We included 1056 individuals admitted to three residential treatment facilities across Queensland, Australia, from 1 January 2014 to 31 December 2016. Records were linked to Queensland death registration data and cause of death records from the Australian Coordinating Registry (1 January‐31 December 2018). Standard mortality ratios were assessed, comparing participants to the Queensland, Australia, general population. Causes of death and years of potential life lost (YPLL) were examined. Results: Thirty‐six participants died (3.4%) in 3408 years of follow‐up data. The age‐ and sex‐adjusted standard mortality ratios were 3.96 (95% confidence interval: 2.78, 5.48) overall, 8.19 (3.74, 15.55) in females and 3.38 (2.23, 4.92) in males. Two‐thirds of deaths were due to suicide/overdose. There was an average of 45.50 YPLL (SD 9.16). Discussion and Conclusions: This study used linked data to quantify mortality following residential substance use treatment. The YPLL and avoidable nature of deaths highlight the need for continuing care following discharge from residential services. [ABSTRACT FROM AUTHOR]

Individuals seeking alcohol and other drug (AOD) treatment consistently experience higher rates of suicidal behaviours and death by suicide when compared to the general population. By linking residential AOD treatment data to administrative healthcare and death datasets, we aimed to examine suicide-related behaviours and identify risk and protective factors for these events following discharge from residential treatment. Participants included 1056 individuals aged 18–69 (M = 32.06, SD = 9.55, male = 696,65.9 %) admitted to three residential treatment facilities in Queensland, Australia from January 1, 2014 to December 31, 2016. Treatment data was linked to administrative hospital, emergency department (ED), mental health service, and Registry of Deaths data 2-years post-discharge. ICD-10 codes were used to identify and analyse suicide-related events. Within 2-years post-discharge, 175 (16.6 %) individuals had a suicide-related event (n = 298 episodes). The highest proportion of episodes (11.1 %) occurred within 1-month of discharge. Higher risk of a recurrent suicide-related event was associated with receiving a Disability Support Pension (aHR = 1.69 (95%CI:1.10,2.59), two or more previous episodes of residential AOD treatment (aHR = 1.49 (95%CI:1.30,2.15). Completing residential treatment was associated with a lower risk of suicide-related events (aHR = 0.54 (95%CI:0.35,0.83). The amalgamation of suicidal ideation, attempts, and death into a single outcome oversimplifies their complex nature and interplay. The exclusive focus on one service provider limits generalisability, and data constraints and missingness preclude many analyses. Understanding suicidal behaviours and critical risk periods following discharge from residential treatment is crucial for improving continuing care, developing effective suicide prevention, and implementing targeted interventions among this high-risk population. • Suicide-related events were common among individuals seeking substance use treatment. • Suicide-related events were not isolated and often indicated further suicide-related events. • Factors indicating disadvantage were associated with a greater likelihood of suicidal behaviour. • Health service presentations currently represent missed opportunities for suicide prevention. • Continuing care and targeted suicide interventions are needed following substance use treatment. [ABSTRACT FROM AUTHOR]

Background: The ICD-11 diagnosis of Gaming Disorder (GD) requires the presence of impaired control over gaming, increasing priority over other activities, continued gaming despite adverse consequences, and demonstrable impairment. Tolerance and withdrawal, which are characteristic features of substance dependence, are not accepted as diagnostic features; instead they are noted as "additional clinical features". This study, part of IGS22, sought to examine whether tolerance and dependence are integral components of GD. Method: Data were from 803 participants (age <=65) in the IGS22. There were 76 items in the study measuring impaired control over gaming, increasing priority over other activities, continued gaming despite adverse consequences, e impairment, and tolerance and withdrawal. Results: Tolerance was reported by 32%, and withdrawal by 33.5%, compared with 33.7% reporting impaired control. Exploratory factor analysis (EFA) shows that both tolerance and withdrawal loaded on the same factor as impaired control. Increasing priority loaded on to a second factor and impairment on to a third. We then conducted two sets of confirmatory factor analysis, one with the 3-factor structure identified in the EFA and one with 6-factor with impaired control, tolerance and withdrawal loaded on separate factors. The 3-factor model fitted the data well (CFI=0.962, RMSEA=0.025); with substantially increased model complexity, the 6-factor model only marginally fitted the data better (CFI=0.973, RMSEA= 0.022). Conclusions: The constructs of tolerance and withdrawal largely overlap with impaired control. While they could be additional clinical features, they are unlikely to be necessary for diagnosis and screening for gaming disorder. [ABSTRACT FROM AUTHOR]

Importance: Extramedical opioid use has escalated in recent years. A better understanding of cause-specific mortality in this population is needed to inform comprehensive responses.Objective: To estimate all-cause and cause-specific crude mortality rates (CMRs) and standardized mortality ratios (SMRs) among people using extramedical opioids, including age- and sex-specific estimates when possible.Data Sources: For this systematic review and meta-analysis, MEDLINE, PsycINFO, and Embase were searched for studies published from January 1, 2009, to October 3, 2019, and an earlier systematic review on this topic published in 2011.Study Selection: Cohort studies of people using extramedical opioids and reporting mortality outcomes were screened for inclusion independently by 2 team members.Data Extraction and Synthesis: Data were extracted by a team member and checked by another team member. Study quality was assessed using a custom set of items that examined risk of bias and quality of reporting. Data were pooled using random-effects meta-analysis models. Heterogeneity was assessed using stratified meta-analyses and meta-regression.Main Outcomes and Measures: Outcome measures were all-cause and cause-specific CMRs and SMRs among people using extramedical opioids compared with the general population of the same age and sex.Results: Of 8683 identified studies, 124 were included in this analysis (100 primary studies and 24 studies providing additional data for primary studies). The pooled all-cause CMR, based on 99 cohorts of 1 262 592 people, was 1.6 per 100 person-years (95% CI, 1.4-1.8 per 100 person-years), with substantial heterogeneity (I2 = 99.7%). Heterogeneity was associated with the proportion of the study sample that injected opioids or was living with HIV infection or hepatitis C. The pooled all-cause SMR, based on 43 cohorts, was 10.0 (95% CI, 7.6-13.2). Excess mortality was observed across a range of causes, including overdose, injuries, and infectious and noncommunicable diseases.Conclusions and Relevance: The findings suggest that people using extramedical opioids experience significant excess mortality, much of which is preventable. The range of causes for which excess mortality was observed highlights the multiplicity of risk exposures experienced by this population and the need for comprehensive responses to address these. Better data on cause-specific mortality in this population in several world regions appear to be needed. [ABSTRACT FROM AUTHOR]

Aims: To (1) identify population‐level classes of polysubstance use among young Australians between 2004 and 2016, (2) test if these classes changed over the same period, in terms of class prevalence and probabilities of substance use within each class, and (3) identify demographic and health‐related correlates of polysubstance use. Design Repeated cross‐sectional nationally representative household surveys. Setting: All Australian states/territories. Participants: Young adult samples (aged 18–30 years; 58% females) from the National Drug Strategy Household Surveys (n = 20 350) Measurements Outcomes were the extent of past‐year use of 10 licit (e.g. alcohol), and illicit substances (e.g. cannabis) were used to derive polysubstance use classes. The correlates were gender, age, psychological distress, general health, language background, personal income, education level, remoteness of residence and socio‐economic index for area of residence. Findings Three polysubstance use classes were consistently identified between 2004 and 2016 (SSABIC: 188349): minimal users (MU, ~60%), mainly tobacco, alcohol and cannabis users (TAC, ~30%) and extended range polysubstance users (POLY, ~10%). There were substantial changes in use of different substances within each class over the study period. For example, smoking decreased in all classes (P < 0.05), while harmful alcohol use only decreased in the first two classes (P < 0.05). Factors associated with TAC and POLY were similar over the study period. These included: being male and having an English‐speaking background, a high level of psychological distress, suboptimal health and high personal income. Living in an affluent area was associated with reduced likelihood of being TAC, but an increased likelihood of being POLY. Conclusion: At the population‐level among young Australians between 2004 and 2016, six in 10 did not engage in polysubstance use; four in 10 used a limited range of substances (mainly alcohol, tobacco and cannabis) and one in 10 used an extended range of substances. Over time, the types of substance within the extended polysubstance use class changed substantially. [ABSTRACT FROM AUTHOR]

Abstract: Aims: This review provides an up‐to‐date curated source of information on alcohol, tobacco and illicit drug use and their associated mortality and burden of disease. Limitations in the data are also discussed, including how these can be addressed in the future. Methods: Online data sources were identified through expert review. Data were obtained mainly from the World Health Organization, United Nations Office on Drugs and Crime and Institute for Health Metrics and Evaluation. Results: In 2015, the estimated prevalence among the adult population was 18.4% for heavy episodic alcohol use (in the past 30 days); 15.2% for daily tobacco smoking; and 3.8, 0.77, 0.37 and 0.35% for past‐year cannabis, amphetamine, opioid and cocaine use, respectively. European regions had the highest prevalence of heavy episodic alcohol use and daily tobacco use. The age‐standardized prevalence of alcohol dependence was 843.2 per 100 000 people; for cannabis, opioids, amphetamines and cocaine dependence it was 259.3, 220.4, 86.0 and 52.5 per 100 000 people, respectively. High‐income North America region had among the highest rates of cannabis, opioid and cocaine dependence. Attributable disability‐adjusted life‐years (DALYs) were highest for tobacco smoking (170.9 million DALYs), followed by alcohol (85.0 million) and illicit drugs (27.8 million). Substance‐attributable mortality rates were highest for tobacco smoking (110.7 deaths per 100 000 people), followed by alcohol and illicit drugs (33.0 and 6.9 deaths per 100 000 people, respectively). Attributable age‐standardized mortality rates and DALYs for alcohol and illicit drugs were highest in eastern Europe; attributable age‐standardized tobacco mortality rates and DALYs were highest in Oceania. Conclusions: In 2015 alcohol use and tobacco smoking use between them cost the human population more than a quarter of a billion disability‐adjusted life years, with illicit drugs costing further tens of millions. Europeans suffered proportionately more, but in absolute terms the mortality rate was greatest in low‐ and middle‐income countries with large populations and where the quality of data was more limited. Better standardized and rigorous methods for data collection, collation and reporting are needed to assess more accurately the geographical and temporal trends in substance use and its disease burden. [ABSTRACT FROM AUTHOR]

Objectives: Timely and accurate assessments of disease burden are essential for developing effective national health policies. We used the Global Burden of Disease Study 2015 to examine burden due to mental and substance use disorders in Australia. Methods: For each of the 20 mental and substance use disorders included in Global Burden of Disease Study 2015, systematic reviews of epidemiological data were conducted, and data modelled using a Bayesian meta-regression tool to produce prevalence estimates by age, sex, geography and year. Prevalence for each disorder was then combined with a disorder-specific disability weight to give years lived with disability, as a measure of non-fatal burden. Fatal burden was measured as years of life lost due to premature mortality which were calculated by combining the number of deaths due to a disorder with the life expectancy remaining at the time of death. Disability-adjusted life years were calculated by summing years lived with disability and years of life lost to give a measure of total burden. Uncertainty was calculated around all burden estimates. Results: Mental and substance use disorders were the leading cause of non-fatal burden in Australia in 2015, explaining 24.3% of total years lived with disability, and were the second leading cause of total burden, accounting for 14.6% of total disability-adjusted life years. There was no significant change in the age-standardised disability-adjusted life year rates for mental and substance use disorders from 1990 to 2015. Conclusion: Global Burden of Disease Study 2015 found that mental and substance use disorders were leading contributors to disease burden in Australia. Despite several decades of national reform, the burden of mental and substance use disorders remained largely unchanged between 1990 and 2015. To reduce this burden, effective population-level preventions strategies are required in addition to effective interventions of sufficient duration and coverage. [ABSTRACT FROM AUTHOR]

Background Personal vaporisers or e-cigarettes are gaining popularity as an alternative route of administration for illicit substances. Data from the Centers for Disease Control and Prevention on the recent epidemic of vaping related lung injuries has confirmed that victims had vaped blackmarket tetrahydracannabidiol, including some sourced from online cryptomarkets. We examined the diversity and prevalence of illicit substances in vaping products available from these marketplaces. Methods Vaping related listings were extracted from three online cryptomarkets ('Agartha', 'Cryptonia', and 'Tochka') using The Onion Router browser. Data collection occurred between October and November 2019. Results We identified 1929 listings from 201 unique sellers. The top product across the three markets were vape cartridges (range = 39.4% to 70.4%). The most common substance in these products was cannabis oil (range = 82.1% to 96.1%), followed by synthetic cannabinoids (range = 3.7% to 9.8%) and psychedelic substances (range = 0.2% to 6.4%). Vendors were primarily from the USA. Many products offered worldwide shipping (range = 42.4% to 96.3%). Conclusions Our study fills knowledge gaps by providing information on what vaping products are being sold through online cryptomarkets. Future studies should continue to monitor cryptomarkets to identify emerging trends of substances used in personal vaporisers. Key messages Online cryptomarkets provide a new way of monitoring emerging vaping trends and identify factors that contributes to the current vaping epidemic. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

The prevalence of cannabis use disorders (CUDs) in people who use cannabis recreationally has been estimated at 22%, yet there is a dearth of literature exploring CUDs among people who use medicinal cannabis. We aimed to systematically review the prevalence of CUDs in people who use medicinal cannabis. In our systematic review and meta-analysis, we followed PRISMA guidelines and searched three databases (PsychInfo, Embase and PubMed) to identify studies examining the prevalence of CUDs in people who use medicinal cannabis. Meta-analyses were calculated on the prevalence of CUDs. Prevalence estimates were pooled across different prevalence periods using the DSM-IV and DSM-5. We conducted a systematic review of 14 eligible publications, assessing the prevalence of CUDs, providing data for 3681 participants from five different countries. The systematic review demonstrated that demographic factors, mental health disorders and the management of chronic pain with medicinal cannabis were associated with an elevated risk of CUDs. Meta-analyses were conducted on the prevalence of CUDs. For individuals using medicinal cannabis in the past 6–12 months, the prevalence of CUDs was 29% (95% CI: 21-38%) as per DSM-5 criteria. Similar prevalence was observed using DSM-IV (24%, CI: 14–38%) for the same period. When including all prevalence periods and using the DSM-5, the prevalence of CUDs in people who use medicinal cannabis was estimated at 25% (CI: 18-33%). The prevalence of CUDs in people who use medicinal cannabis is substantial and comparable to people who use cannabis for recreational reasons, emphasizing the need for ongoing research to monitor the prevalence of CUDs in people who use medicinal cannabis. • The prevalence of cannabis use disorders in people who use medicinal cannabis is estimated at 25% (CI: 18-33%). • People with chronic non-cancer pain, mental health or substance use disorders may have a higher risk of cannabis use disorder. • The study highlights the need to carefully consider the risk of cannabis use disorder when prescribing medicinal cannabis. [ABSTRACT FROM AUTHOR]

[Display omitted] • Reliability for online self-report measures was moderate to high for most substance types when measured by the ATOP in people seeking treatment for substance use problems. • An underreporting of lifetime substance use during online self-report of the ASSIST led to poor reliability outcomes for nearly all substance types, indicating the need for researcher and clinician support for these ASSIST items (e.g., through pre-recorded instructions). • Reliability for the ASSIST past 3-month substance use and related harms was moderate to high for all substance types. • Reliability of illicit quantity estimates have previously been avoided for the ATOP, however standardising quantities and calculating the average quantity per day was a reliable estimate for most substance types. • Researchers planning to use online self-report measures of the ASSIST and ATOP among treatment-seeking populations should consider ways to address limitations in reliability for certain frequently used substance types (e.g., alcohol and cannabis) during the study design phase. Online self-report measures are resource-efficient and widely used for monitoring substance use, yet few studies have assessed their reliability. This study assessed the reliability of online self-report versions of the Australian Treatment Outcomes Profile (ATOP) and Alcohol, Smoking, and Substance Involvement Screening Test (ASSIST) among people seeking treatment for substance use problems. One-hundred and five clients entering residential treatment for substance use problems (Mage = 33.34, 65% male) were recruited from two facilities in Queensland, Australia. Using a repeated-measures design, we compared online self-report with the original interview versions of the ASSIST, which measured (i) lifetime substance use and (ii) past 3-month substance-use and related harms, and the ATOP, which measured (i) past month frequency of substance use and (ii) the typical quantity used per day. Assessments were administered 1–7 days apart. The ATOP demonstrated moderate-excellent inter-rater reliability for the past month use (yes/no) for all substance types, but had poor reliability for alcohol and cannabis. ATOP reliability was high-excellent for the total number of days used in the past month for all substances. The ASSIST demonstrated moderate-excellent inter-rater reliability for substance-use and related harms for all substances except tobacco, however was poor for lifetime use for most substances due to greater reporting in the interview assessment. Reliable responding was observed for the frequency of substance use in the past month on the ATOP, and past 3-month substance-use and related harms on the ASSIST. These findings support use of online-self report measures a resource-efficient method to monitor substance use. Underreporting of lifetime use was found in self-report online version of the ASSIST, highlighting the need for improved instruction or interviewer/clinician assistance for lifetime use. [ABSTRACT FROM AUTHOR]