BACKGROUND: Cannabis use is prevalent among cancer patients and survivors and may provide some therapeutic benefits for this population. However, benefits may be attenuated when cannabis is co-used with tobacco, which is associated with more severe tobacco and cannabis use and adverse outcomes in noncancer populations. We compared cannabis use, primary mode of use, and therapeutic and/or nontherapeutic use among 3 groups of patients and survivors based on cigarette smoking status.
METHODS: Survey data was collected from patients and survivors with cancer (n = 1732) at 2 US National Cancer Institute-designated cancer centers in states with varying cannabis regulatory policy. Prevalence of cannabis use (prior to diagnosis, after diagnosis, before treatment, after treatment), primary mode of use, and therapeutic and/or nontherapeutic use were assessed by cigarette smoking status (current, former, never) within and across centers using weighted bivariate analyses and multivariable logistic regression, controlling for demographic and clinical variables.
RESULTS: Current cigarette use was associated with greater rates of cannabis use prior to diagnosis, after diagnosis, during treatment, and after treatment within each center (all P < .001) and in pooled analyses across centers (all P < .001). Primary mode of use, knowledge of cannabis products, and therapeutic and/or nontherapeutic use also statistically differed by tobacco status and study site.
CONCLUSIONS: Results illustrate the importance of conducting assessments for both tobacco and cannabis use among cancer patients during and after cancer treatment, regardless of the cannabis regulatory environment. Given previous data indicating harms from co-use and continued tobacco use during cancer treatment, this issue introduces new priorities for cancer care delivery and research.

BACKGROUND: Cannabis demand (i.e., relative value) is usually assessed as a trait-level risk-factor for cannabis use and consequences. This study examined within-person variability in day-level intensity (i.e., amount consumed at zero cost) and Omax (i.e., maximum cannabis expenditure) and tested hypotheses that demand would be positively associated with day-level cannabis use.
METHODS: Young adults (n=85) reporting past-month simultaneous alcohol and cannabis use completed two daily surveys for 30 days. Morning surveys assessed prior-day cannabis use and evening surveys assessed day-level demand (i.e., intensity, Omax). Multilevel models tested day-level effects of intensity and Omax on any cannabis use and flower use frequency and quantity (i.e., grams).
RESULTS: Approximately 52 % and 46 % of variability in intensity and Omax, respectively, was due to within-person change. At the day-level, higher intensity and Omax were associated with higher likelihood of any cannabis use, regardless of formulation; Omax was associated with use of flower in particular; and intensity was associated with the highest quantity of use. At the person-level, only Omax was associated with flower use likelihood, and only intensity was associated with flower quantity across days.
CONCLUSIONS: Cannabis demand demonstrated day-to-day variability, conceivably in response to various internal states and external factors. Intensity and Omax were related to elevated likelihood of using any cannabis, particularly flower, at the day-level. Overall, these data illustrate the validity and utility of brief cannabis demand measures, which might be used to further understand cannabis\' reinforcing value at a fine-grained level.

UNASSIGNED: We characterized trends in medical cannabis use; examined characteristics associated with medical cannabis use without medical authorization; and examined the association between recreational cannabis legalization and medical cannabis use in Ontario, Canada.
UNASSIGNED: Data were from a repeated, population-based, cross-sectional survey of adults (N = 19,543; 2014-2019). Cannabis use was categorized as either medical cannabis use, recreational cannabis use or no cannabis use. The analytical strategy included jointpoint regression, logistic regression and multinomial logistic regression.
UNASSIGNED: Medical cannabis use increased from 4 % to 11 % (Annual Percentage Change [APC]: 25 %, 95 % Confidence Interval [CI]: 17 %-33 %) and recreational cannabis use increased from 9 % to 15 % (APC: 9 %, 95 % CI: 3 %-15 %) between 2014 and 2019. Being 18 to 29 years old compared with being 65+ years old was associated with an increased likelihood of medical cannabis use without medical authorization (Odds Ratio [OR]: 4.05, 95 % CI: 2.12-7.72), while being of fair or poor self-perceived health compared with excellent, very good or good self-perceived health (OR: 0.61, 95 % CI: 0.40-0.95) was associated with a decreased likelihood of medical cannabis use without medical authorization. Recreational cannabis legalization was associated with an increased likelihood of medical cannabis use compared with no cannabis use (OR: 1.48, 95 % CI: 1.19-1.85) and of recreational cannabis use compared with no cannabis use (OR: 1.35, 95 % CI: 1.11-1.65).
UNASSIGNED: Although medical cannabis use increased, it was largely used without medical authorization. Guidance and education that encourages medical usage under clinical supervision is recommended, and mitigation of known barriers to medical cannabis authorization.

BACKGROUND: Co-use of tobacco and cannabis has long been an issue for prevention and intervention efforts targeting these substances. Blunt use-cannabis inside a cigar wrapper-has been a consistent mode of cannabis consumption since the 1990s. Since then, both tobacco control and cannabis policies have changed considerably. This paper examines the influence of tobacco taxes and smoke-free policies as well as medical and recreational cannabis policies on blunt use among young people.
METHODS: Combining state-level tobacco control and cannabis policy data with the restricted-access youth cohort of the Population Assessment of Tobacco and Health (PATH) study, we use multilevel logistic regression models to examine the impact of these policies on past-year blunt use.
RESULTS: While we found a main effect whereby both legal medical and recreational cannabis policies are associated with higher odds of blunt use among youth, interaction effects demonstrate that this association only emerges in states lacking a comprehensive tobacco smoke-free policy. In states with smoke-free policies, we found no significant associations between cannabis policy and odds of blunt use.
CONCLUSIONS: Denormalization through smoke-free policies may mitigate the effects of recreational and medical cannabis policies on blunt use. Smoke-free policies represent a possible cost-effective mechanism to curb the co-use of tobacco and cannabis in the form of blunts. States with medical and recreational cannabis policies may benefit from greater prevention efforts for young people specifically focused on blunt use, especially in states that do not have strong tobacco control.

BACKGROUND: Young adults in the United States, including college students, have the highest prevalence of cannabis use compared with other age groups. Although cannabis vaping is increasingly prevalent during young adulthood, little is known about factors contributing to the onset of cannabis vaping during this developmental period.
METHODS: Participants were 3085 cannabis vaping naïve young adults aged 18-25 years (M = 20.60; SD = 1.80), initially recruited from 24 Texas colleges and participating in a multi-wave, longitudinal study. A survival analysis was conducted to determine if participants reporting elevated depressive symptoms had an increased risk of onset of cannabis vaping over six follow-up waves from fall 2015 to spring 2019 compared to their peers with lower levels of depressive symptoms. Socio-demographic characteristics, time-varying past 30 day substance use, and time-varying peer nicotine vaping were included as covariates in the model.
RESULTS: Twenty-five percent of participants initiated cannabis vaping during the four-year study period, with stable initiation rates from 2015 to 2017 but doubling from 2017 to 2019. Analyses, both unadjusted and adjusted for study covariates, indicated that elevated depressive symptoms were significantly associated with an increased risk of cannabis vaping initiation.
CONCLUSIONS: Findings indicate that initiation of cannabis vaping during young adulthood is common, and particularly more likely among those with greater depressive symptoms, thus underscoring the importance of prevention programs that include mental health support services tailored to young adults.

Cannabinoids can be detected in breath after cannabis use, but different breath matrices need to be explored as studies to date with filter-based devices that collect breath aerosols have not demonstrated that breath-based measurements can reliably identify recent cannabis use. Exhaled breath condensate (EBC) is an unexplored aqueous breath matrix that contains condensed volatile compounds and water vapor in addition to aerosols. EBC was collected from participants both before and at two time points (0.7 ± 0.2 h and 1.7 ± 0.3 h) after observed cannabis use. Eleven different cannabinoids were monitored with liquid chromatography tandem mass spectrometry. Five different cannabinoids, including Δ9-tetrahydrocannabinol (THC), were detected in EBC collected from cannabis users. THC was detected in some EBC samples before cannabis use, despite the requested abstinence period. THC was detected in all EBC samples collected at 0.7 h post use and decreased for all participants at 1.7 h. Non-THC cannabinoids were only detected after cannabis use. THC concentrations in EBC samples collected at 0.7 h showed no trend with sample metrics like mass or number of breaths. EBC sampling devices deserve further investigation with respect to modes of cannabis use (e.g, edibles), post use time points, and optimization of cannabinoid recovery.

BACKGROUND: Little is known about the prevalence and predictors of adolescents\' intention to quit or reduce use of e-cigarettes and/or cannabis.
METHODS: Frequencies of intention to change (quit, reduce) e-cigarettes and/or cannabis use were examined among 23,915 surveyed middle and high school students with sole and co-use. Predictors of intention to change were identified via LASSO/multilevel logistic regression.
RESULTS: Among those with sole e-cigarette use (n = 543), 40.9 % intended to quit and 24.1 % intended to reduce; non-daily e-cigarette use predicted intention to quit and reduce e-cigarettes (p\'s < 0.03). Among those with sole cannabis use (n = 546), 10.6 % intended to quit and 25.1 % intended to reduce; absence of cannabis cravings predicted intention to reduce cannabis use (p < 0.01). Among those with co-use (n = 816), 26.2 % intended to either quit or reduce (quit/reduce) both substances, 27.5 % intended to quit/reduce e-cigarettes only, and 6.9 % intended to quit/reduce cannabis only. No predictors emerged for intention to change e-cigarette use among those with co-use (p\'s > 0.09), but younger age, lack of poly-tobacco use, and lack of cannabis craving predicted intention to quit/reduce cannabis use (p\'s < 0.04).
CONCLUSIONS: More than half of adolescents with past-month e-cigarette use, regardless of concurrent cannabis use, expressed interest in changing their use. However, only heaviness of e-cigarette use emerged as a predictor of intention to change suggesting. While fewer students expressed interest in changing their cannabis use, cannabis cravings and poly-tobacco use predicted intent to change. Overall, findings emphasize the need to tailor interventions towards adolescents engaging in more problematic substance use patterns.

BACKGROUND: Given that cannabis and e-cigarettes are among the most commonly used substances among young people, there is a need to identify risk factors for concurrent cannabis consumption and nicotine vaping among youth and young adults.
METHODS: Data were obtained from the Truth Longitudinal Cohort, collected from September 2020 to March 2021, among a cohort aged 15-24 years (N = 6379). Chi-square tests were conducted to detect differences in sample characteristics by dual use status (never e-cigarette and never cannabis users, never cannabis and former/noncurrent e-cigarette users, never e-cigarette and former/noncurrent cannabis users, former/noncurrent e-cigarette and cannabis users, current e-cigarette only users, current cannabis only users, and concurrent cannabis and e-cigarette dual users). Multinomial logistic regression was used to determine key demographic variables predicting dual use status.
RESULTS: Household tobacco use (Relative Risk Ratio, RRR = 4.93), higher sensation seeking (RRR = 3.98), and mental health score (RRR = 2.58) were associated with higher risk of dual use. Being 15-17 years (RRR = 0.22), being female (RRR = 0.59) and having parents with an education level of some college or more (RRR = 0.64) were associated with lower risk of dual use.
CONCLUSIONS: Findings suggest the need to carefully monitor cannabis and vaping nicotine among young people. The identification of risk factors provides additional guidance for prevention and treatment efforts, suggesting the need to address use of both substances and target those most at risk.

UNASSIGNED: It is unclear whether cannabis use is associated with adverse health outcomes in patients with COVID-19 when accounting for known risk factors, including tobacco use.
UNASSIGNED: To examine whether cannabis and tobacco use are associated with adverse health outcomes from COVID-19 in the context of other known risk factors.
UNASSIGNED: This retrospective cohort study used electronic health record data from February 1, 2020, to January 31, 2022. This study included patients who were identified as having COVID-19 during at least 1 medical visit at a large academic medical center in the Midwest US.
UNASSIGNED: Current cannabis use and tobacco smoking, as documented in the medical encounter.
UNASSIGNED: Health outcomes of hospitalization, intensive care unit (ICU) admission, and all-cause mortality following COVID-19 infection. The association between substance use (cannabis and tobacco) and these COVID-19 outcomes was assessed using multivariable modeling.
UNASSIGNED: A total of 72 501 patients with COVID-19 were included (mean [SD] age, 48.9 [19.3] years; 43 315 [59.7%] female; 9710 [13.4%] had current smoking; 17 654 [24.4%] had former smoking; and 7060 [9.7%] had current use of cannabis). Current tobacco smoking was significantly associated with increased risk of hospitalization (odds ratio [OR], 1.72; 95% CI, 1.62-1.82; P < .001), ICU admission (OR, 1.22; 95% CI, 1.10-1.34; P < .001), and all-cause mortality (OR, 1.37, 95% CI, 1.20-1.57; P < .001) after adjusting for other factors. Cannabis use was significantly associated with increased risk of hospitalization (OR, 1.80; 95% CI, 1.68-1.93; P < .001) and ICU admission (OR, 1.27; 95% CI, 1.14-1.41; P < .001) but not with all-cause mortality (OR, 0.97; 95% CI, 0.82-1.14, P = .69) after adjusting for tobacco smoking, vaccination, comorbidity, diagnosis date, and demographic factors.
UNASSIGNED: The findings of this cohort study suggest that cannabis use may be an independent risk factor for COVID-19-related complications, even after considering cigarette smoking, vaccination status, comorbidities, and other risk factors.

BACKGROUND: In legal and illegal markets, high-potency cannabis (>10 % delta-9-tetrahydrocannabinol (THC)) is increasingly available. In adult samples higher-potency cannabis has been associated with mental health disorder but no studies have considered associations in adolescence.
METHODS: A population-wide study compared no, low and high potency cannabis using adolescents (aged 13-14 years) self-reported symptoms of probable depression, anxiety, and auditory hallucinations.
RESULTS: Of the 6672 participants, high-potency cannabis was used by 2.6 % (n=171) and low-potency by 0.6 % (n=38). After adjustment for sociodemographic factors, tobacco and alcohol use, in comparison to participants who had never used cannabis, people who had used high-potency but not low-potency cannabis were more likely to report symptoms of depression (odds ratio 1.59 [95 % confidence interval 1.06, 2.39), anxiety (OR 1.45, 95 % CI 0.96, 2.20), and auditory hallucinations (OR 1.56, 95 % CI 0.98, 2.47).
CONCLUSIONS: High-potency cannabis use is associated with an increased risk of probable mental health disorders. Services and programming to minimise drug harms may need to be adapted to pay more attention to cannabis potency.