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Sexual and gender minority populations are at elevated risk of experiencing suicidal thoughts and attempting suicide. The COVID-19 pandemic exacerbated mental health and substance use challenges among this population. We aimed to examine the relative importance and effects of intersectional factors and strong interactions associated with the risk of suicidal thoughts among Canadian lesbian, gay, bisexual, transgender, queer, questioning, intersex and Two Spirit (LGBTQI2S+) young adults. A cross-sectional online survey was conducted among LGBTQI2S + participants aged 16-29 years living in two Canadian provinces (Ontario, Quebec). Among 1414 participants (mean age 21.90 years), 61% (n = 857) participants reported suicidal thoughts in last 12 months. We built a random forest model to predict the risk of having past year suicidal thoughts, which achieved high performance with an area under the receiver operating characteristic curve (AUC) of 0.84. The top 10 correlates identified were: seeking help from health professionals for mental health or substance use issues since the start of the pandemic, current self-rated mental health status, insulted by parents or adults in childhood, ever heard that being identifying as LGBTQI2S+ is not normal, age in years, past week feeling depressed, lifetime diagnosis of mental illness, lifetime diagnosis of depressive disorder, past week feeling sad, ever pretended to be straight or cisgender to be accepted. The increase in the risk of suicidal thoughts for those having mental health challenges or facing minority stressors is more pronounced in those living in urban areas or being unemployed than those living in rural areas or being employed.

It is a systematic review of longitudinal studies to summarize predictors of different vaping behaviours among adolescents, youth and young adults.

The COVID-19 pandemic has worsened the mental health and substance use challenges among many people who are Two Spirit, lesbian, gay, bisexual, transgender, queer, questioning, and intersex (2SLGBTQI+). We aimed to identify the important correlates and their effects on the predicted likelihood of wanting to seek help among 2SLGBTQI+ young adults for mental health or substance use concerns during the pandemic. A cross-sectional survey was conducted in 2020–2021 among 2SLGBTQI+ young adults aged 16–29 living in two Canadian provinces (Ontario and Quebec). Among 1414 participants, 77% (n = 1089) wanted to seek help for their mental health or substance use concerns during the pandemic, out of these, 69.8% (n = 760) reported delay in accessing care. We built a random forest (RF) model to predict the status of wanting to seek help, which achieved moderately high performance with an area under the receiver operating characteristic curve (AUC) of 0.85. The top 10 correlates of wanting to seek help were worsening mental health, age, stigma and discrimination, and adverse childhood experiences. The interactions of adequate housing with certain sexual orientations, gender identities and mental health challenges were found to increase the likelihood of wanting to seek help. We built another RF model for predicting risk of delay in accessing care among participants who wanted to seek help (n = 1089). The model identified a similar set of top 10 correlates of delay in accessing care but lacked adequate performance (AUC 0.61). These findings can direct future research and targeted prevention measures to reduce health disparities for 2SLGBTQI+ young adults.

Jurisdictions around the world have adopted different policies in order to regulate e-cigarette products, to allow for the use of e-cigarettes by cigarette smokers for cessation or harm reduction and to reduce the likelihood of non-smokers initiating e-cigarette use. The purpose of this review is to provide a brief overview of different e-cigarette regulations across the world, focusing on regulations of sales, product standards, nicotine concentrations, flavours and marketing restrictions. This review was conducted between February and April 2020. There are a large range of policies that countries around the world have chosen in order to regulate vaping products to prevent use and limit harm associated with use of e-cigarettes. Many countries provide avenues for separate regulation of therapeutic and consumer e-cigarette devices. E-cigarettes have the potential of causing harm among young vapers and reducing harm among adult cigarette smokers. The most effective strategies would balance both of these properties and prevent access to vaping products among adolescents and youths and at the same time increase the availability of the regulated therapeutic products among people trying to quit smoking. Future efforts of research should focus on evaluating the impact of different regulatory policies to achieve these purposes and exploring the use of e-cigarettes as a smoking cessation aid. Our recommendations are based on existing literature on the effectiveness of current e-cigarette regulations.

This economic evaluation uses wholesale cigarette sales data from manufacturers to compare cigarette sales before and after implementation of provincial and federal bans of menthol cigarettes in Canada.

Cannabis use is associated with various adverse physical and mental health outcomes as well as increased risk of motor vehicle collision. Many organizations and the "Lower-Risk Cannabis Use Guidelines" have recommended to use cannabis vaporizers instead of smoking to reduce the associated health risk. This commentary draws attention to the present evidence regarding harm reduction potential of cannabis vaping. Cannabis vaporizer use can reduce the emission of carbon monoxide, chronic respiratory symptoms, and exposure to several toxins while producing similar subjective effects and blood THC concentration compared with smoking cannabis, holding potential for harm reduction among habitual cannabis smokers. However, new cannabis users, regardless of method of administration of cannabis, may experience intense subjective effects and cognitive impairment with increased susceptibility to dependence. Hence, policy makers should consider limiting access to cannabis among young people and adopting strategies to reduce impaired driving under influence of cannabis. Future research should focus on impact of switching from cannabis smoking to dried herb vaping using cannabis vaporizers among chronic cannabis smokers, and long-term outcomes of medical cannabis vaping, and further explore association of vaping-associated lung injury with THC-containing e-liquids.RéSUMé: L’usage du cannabis est associé à une panoplie de résultats de santé physique et mentale indésirables et à un risque accru de collision entre véhicules automobiles. De nombreux organismes, ainsi que les « Recommandations canadiennes pour l’usage du cannabis à moindre risque », recommandent d’utiliser un vaporisateur au lieu de fumer le cannabis afin d’en réduire les risques pour la santé. Notre commentaire attire l’attention sur les preuves actuelles concernant le potentiel de réduction des méfaits du vapotage du cannabis. L’utilisation d’un vaporisateur de cannabis peut réduire l’émission de monoxyde de carbone, les symptômes respiratoires chroniques et l’exposition à plusieurs toxines tout en produisant des effets subjectifs et une concentration de THC dans le sang semblables à ceux du cannabis fumé, ce qui pourrait réduire les méfaits chez les fumeurs réguliers de cannabis. Par contre, les nouveaux consommateurs de cannabis, peu importe la méthode d’administration du cannabis choisie, peuvent éprouver des effets subjectifs intenses et une détérioration cognitive, ainsi qu’une susceptibilité accrue à la dépendance. Les responsables des politiques devraient donc songer à limiter l’accès des jeunes au cannabis et adopter des stratégies pour réduire la conduite avec facultés affaiblies par cette drogue. Des études futures devraient porter sur les conséquences, pour les fumeurs réguliers de cannabis, de vapoter l’herbe séchée à l’aide d’un vaporisateur au lieu de fumer le cannabis, et sur les effets à long terme du vapotage du cannabis médical, et explorer plus avant l’association entre les lésions pulmonaires associées au vapotage et les liquides à vapoter contenant du THC.

BACKGROUND As the prevalence of electronic cigarette (e-cigarette) use, or vaping, continues to grow, particularly among young people, so does the need for research and interventions to address vaping. OBJECTIVE This study examines the quality of free vaping cessation apps, their contents and features, popularity among users, and adherence to evidence-based principles. METHODS A systematic search of existing apps for vaping cessation was conducted in December 2020. Eligible apps were free, in English, and included features specifically targeting vaping cessation. Each app included in the analysis was used daily for at least seven consecutive days, assessed using the Mobile App Rating Scale, and rated by at least two authors (AK, EL, or SS) based on adherence to evidence-based practices. Intraclass correlation coefficient (ICC) estimates were computed to assess interrater reliability (excellent agreement; ICC 0.92; 95% CI 0.78-0.98). RESULTS A total of 8 apps were included in the quality assessment and content analysis: 3 were developed specifically for vaping cessation and 5 focused on smoking cessation while also claiming to address vaping cessation. The mean of app quality total scores was 3.66 out of 5. Existing vaping cessation apps employ similar approaches to smoking cessation apps. However, they are very low in number and have limited features developed specifically for vaping cessation. CONCLUSIONS Given the lack of vaping cessation interventions at a time when they are urgently needed, smartphone apps are potentially valuable tools. Therefore, it is recommended that these apps apply evidence-based practices and undergo rigorous evaluations that can assess their quality, contents and features, and popularity among users. Through this process, we can improve our understanding of how apps can be effective in helping users quit vaping.

BACKGROUND A high risk of mental health or substance addiction issues among sexual and gender minority populations may have more nuanced characteristics that may not be easily discovered by traditional statistical methods. OBJECTIVE This review aims to identify literature studies that used machine learning (ML) to investigate mental health or substance use concerns among the lesbian, gay, bisexual, transgender, queer or questioning, and two-spirit (LGBTQ2S+) population and direct future research in this field. METHODS The MEDLINE, Embase, PubMed, CINAHL Plus, PsycINFO, IEEE Xplore, and Summon databases were searched from November to December 2020. We included original studies that used ML to explore mental health or substance use among the LGBTQ2S+ population and excluded studies of genomics and pharmacokinetics. Two independent reviewers reviewed all papers and extracted data on general study findings, model development, and discussion of the study findings. RESULTS We included 11 studies in this review, of which 81% (9/11) were on mental health and 18% (2/11) were on substance use concerns. All studies were published within the last 2 years, and most were conducted in the United States. Among mutually nonexclusive population categories, sexual minority men were the most commonly studied subgroup (5/11, 45%), whereas sexual minority women were studied the least (2/11, 18%). Studies were categorized into 3 major domains: web content analysis (6/11, 54%), prediction modeling (4/11, 36%), and imaging studies (1/11, 9%). CONCLUSIONS ML is a promising tool for capturing and analyzing hidden data on mental health and substance use concerns among the LGBTQ2S+ population. In addition to conducting more research on sexual minority women, different mental health and substance use problems, as well as outcomes and future research should explore newer environments, data sources, and intersections with various social determinants of health. CLINICALTRIAL

ObjectiveIdentify and review the body of tobacco research literature that self-identified as using machine learning (ML) in the analysis.Data sourcesMEDLINE, EMABSE, PubMed, CINAHL Plus, APA PsycINFO and IEEE Xplore databases were searched up to September 2020. Studies were restricted to peer-reviewed, English-language journal articles, dissertations and conference papers comprising an empirical analysis where ML was identified to be the method used to examine human experience of tobacco. Studies of genomics and diagnostic imaging were excluded.Study selectionTwo reviewers independently screened the titles and abstracts. The reference list of articles was also searched. In an iterative process, eligible studies were classified into domains based on their objectives and types of data used in the analysis.Data extractionUsing data charting forms, two reviewers independently extracted data from all studies. A narrative synthesis method was used to describe findings from each domain such as study design, objective, ML classes/algorithms, knowledge users and the presence of a data sharing statement. Trends of publication were visually depicted.Data synthesis74 studies were grouped into four domains: ML-powered technology to assist smoking cessation (n=22); content analysis of tobacco on social media (n=32); smoker status classification from narrative clinical texts (n=6) and tobacco-related outcome prediction using administrative, survey or clinical trial data (n=14). Implications of these studies and future directions for ML researchers in tobacco control were discussed.ConclusionsML represents a powerful tool that could advance the research and policy decision-making of tobacco control. Further opportunities should be explored.

Background As the prevalence of electronic cigarette (e-cigarette) use, or vaping, continues to grow, particularly among young people, so does the need for research and interventions to address vaping. Objective This study examines the quality of free vaping cessation apps, their contents and features, popularity among users, and adherence to evidence-based principles. Methods A systematic search of existing apps for vaping cessation was conducted in December 2020. Eligible apps were free, in English, and included features specifically targeting vaping cessation. Each app included in the analysis was used daily for at least seven consecutive days, assessed using the Mobile App Rating Scale, and rated by at least two authors (AK, EL, or SS) based on adherence to evidence-based practices. Intraclass correlation coefficient (ICC) estimates were computed to assess interrater reliability (excellent agreement; ICC 0.92; 95% CI 0.78-0.98). Results A total of 8 apps were included in the quality assessment and content analysis: 3 were developed specifically for vaping cessation and 5 focused on smoking cessation while also claiming to address vaping cessation. The mean of app quality total scores was 3.66 out of 5. Existing vaping cessation apps employ similar approaches to smoking cessation apps. However, they are very low in number and have limited features developed specifically for vaping cessation. Conclusions Given the lack of vaping cessation interventions at a time when they are urgently needed, smartphone apps are potentially valuable tools. Therefore, it is recommended that these apps apply evidence-based practices and undergo rigorous evaluations that can assess their quality, contents and features, and popularity among users. Through this process, we can improve our understanding of how apps can be effective in helping users quit vaping.

Background A high risk of mental health or substance addiction issues among sexual and gender minority populations may have more nuanced characteristics that may not be easily discovered by traditional statistical methods. Objective This review aims to identify literature studies that used machine learning (ML) to investigate mental health or substance use concerns among the lesbian, gay, bisexual, transgender, queer or questioning, and two-spirit (LGBTQ2S+) population and direct future research in this field. Methods The MEDLINE, Embase, PubMed, CINAHL Plus, PsycINFO, IEEE Xplore, and Summon databases were searched from November to December 2020. We included original studies that used ML to explore mental health or substance use among the LGBTQ2S+ population and excluded studies of genomics and pharmacokinetics. Two independent reviewers reviewed all papers and extracted data on general study findings, model development, and discussion of the study findings. Results We included 11 studies in this review, of which 81% (9/11) were on mental health and 18% (2/11) were on substance use concerns. All studies were published within the last 2 years, and most were conducted in the United States. Among mutually nonexclusive population categories, sexual minority men were the most commonly studied subgroup (5/11, 45%), whereas sexual minority women were studied the least (2/11, 18%). Studies were categorized into 3 major domains: web content analysis (6/11, 54%), prediction modeling (4/11, 36%), and imaging studies (1/11, 9%). Conclusions ML is a promising tool for capturing and analyzing hidden data on mental health and substance use concerns among the LGBTQ2S+ population. In addition to conducting more research on sexual minority women, different mental health and substance use problems, as well as outcomes and future research should explore newer environments, data sources, and intersections with various social determinants of health.