Faculty Bibliography

BACKGROUND:Psilocybin use has increased in the US alongside promising therapeutic potential for depression, raising concerns that individuals may forgo conventional mental health treatment for unsupervised psilocybin use. However, no nationally representative studies have examined whether psilocybin use is associated with differential treatment utilization or perceived unmet need for mental health care among individuals with depression. METHODS:We analyzed data from 6,793 individuals aged ≥ 12 years with a past-year major depressive episode (MDE) from the 2024 National Survey on Drug Use and Health, a nationally representative survey of the noninstitutionalized US population. Sociodemographic and substance use characteristics were first compared by past-year psilocybin use. We then examined associations between past-year psilocybin use and eight past-year mental health treatment outcomes using Poisson regression, adjusting for sociodemographic characteristics, other past-year substance use, psychotherapeutic prescription misuse, and alcohol use disorder. RESULTS:Among individuals with past-year MDE, an estimated 7.3% (95% CI: 6.4-8.3) used psilocybin in the past year. In multivariable models, psilocybin use was not associated with any mental health treatment utilization, including outpatient, inpatient, or telehealth treatment; prescription medication use for mental health; seeing a doctor for depressive feelings; or prescription medication use for depressive feelings. However, psilocybin use was associated with greater perceived unmet treatment need (52.0% vs. 33.9%; aPR = 1.44; 95% CI: 1.04-2.01). CONCLUSIONS:Findings suggest that psilocybin use among individuals with depression co-occurs with perceived unmet need for conventional mental health care but is not associated with lower utilization of any conventional mental health treatments.

BACKGROUND:Psilocybin use has increased in the US alongside promising therapeutic potential for depression, raising concerns that individuals may forgo conventional mental health treatment for unsupervised psilocybin use. However, no nationally representative studies have examined whether psilocybin use is associated with differential treatment utilization or perceived unmet need for mental health care among individuals with depression. METHODS:We analyzed data from 6,793 individuals aged ≥ 12 years with a past-year major depressive episode (MDE) from the 2024 National Survey on Drug Use and Health, a nationally representative survey of the noninstitutionalized US population. Sociodemographic and substance use characteristics were first compared by past-year psilocybin use. We then examined associations between past-year psilocybin use and eight past-year mental health treatment outcomes using Poisson regression, adjusting for sociodemographic characteristics, other past-year substance use, psychotherapeutic prescription misuse, and alcohol use disorder. RESULTS:Among individuals with past-year MDE, an estimated 7.3% (95% CI: 6.4-8.3) used psilocybin in the past year. In multivariable models, psilocybin use was not associated with any mental health treatment utilization, including outpatient, inpatient, or telehealth treatment; prescription medication use for mental health; seeing a doctor for depressive feelings; or prescription medication use for depressive feelings. However, psilocybin use was associated with greater perceived unmet treatment need (52.0% vs. 33.9%; aPR = 1.44; 95% CI: 1.04-2.01). CONCLUSIONS:Findings suggest that psilocybin use among individuals with depression co-occurs with perceived unmet need for conventional mental health care but is not associated with lower utilization of any conventional mental health treatments.

BACKGROUND:Cannabis use among older adults (≥ 65) in the US has increased substantially in recent years. However, physiologic changes associated with aging can complicate cannabis' effects in older populations, particularly as different modes of consumption have distinct pharmacokinetic effects. This study estimates the prevalence of different modes of cannabis use in this population and examines their associations with mental health outcomes. METHODS:We analyzed data from older adults aged ≥ 65 years with past-year cannabis use (N = 1515) from the pooled 2022-2024 National Survey on Drug Use and Health, a nationally representative survey of noninstitutionalized US adults. Four generalized linear models using Poisson and log link examined relationships between modes of cannabis use and cannabis use disorder (CUD), major depressive episode (MDE), serious psychological distress (SPD), and suicidal ideation (SI). The modes examined included smoking, ingested forms (eating/drinking or taking pills), inhaled concentrates (vaping or dabbing), and other routes (use of oral drops/lozenges or topicals). The models adjusted for survey year, sociodemographic characteristics, past-year cannabis use frequency, and other past-year substance use. RESULTS:Smoking (66.0%) was the most common mode of cannabis use, followed by ingested forms (42.1%), inhaled concentrates (17.1%), and other routes (16.8%). Compared to males, females had higher prevalence of ingested forms and other routes, while males had higher prevalence of smoking and inhaled concentrates. In multivariable models, smoking (adjusted prevalence ratio [aPR] = 3.99; 95% CI: 1.92-8.28) and ingested forms (aPR = 1.46; 95% CI: 1.03-2.09) were associated with increased prevalence of CUD. No mode was associated with MDE, SPD, or SI. CONCLUSIONS:Among older adults, smoking and ingested forms were associated with CUD, whereas no mode was associated with depression, distress, or suicidal ideation. These findings may inform targeted screening and harm reduction strategies for adults aged ≥ 65 years using cannabis.

BACKGROUND:Cannabis use among older adults has increased in recent years. Age-related physiological changes, socio-ecological factors, and medications may exacerbate potential adverse effects of cannabis and complicate the detection of cannabis use disorder (CUD) in older adults. However, current estimates of cannabis use are largely limited to national surveys, which may have age-related surveying challenges. METHODS:We conducted an intercept survey of 315 adults aged ≥ 65 in New York City, primarily in public parks and immediately outside older adult centers. The survey asked primarily about drug use with a focus on past-year cannabis use, reasons for use, adverse effects, and CUD. We examined reported cannabis use and delineated correlates of use and of having CUD. RESULTS:22.2% of participants (n = 70) reported past-year cannabis use, and among them, 11.1% (n = 35) reported past 24-h use. Older [adjusted odds ratio (aOR) = 0.90, 95% CI: 0.84-0.95] and female participants were at lower odds for use (aOR = 0.35, 95% CI: 0.17-0.73), and those who smoked cigarettes were at higher odds (aOR = 3.73, 95% CI: 1.65-8.48). Cannabis was most often used to get high (60.0%), relieve tension (55.7%), sleep (52.9%), or relieve chronic pain (30.0%). Dry mouth (41.4%) and drowsiness (18.6%) were the most reported adverse effects. Nearly a third (32.9%) who used cannabis had CUD, with 5.7% having severe CUD. CONCLUSIONS:Findings suggest that cannabis use among older adults may be more common and clinically significant than suggested by prior evidence. Improved screening, clinician education, and harm reduction strategies are needed to confront emerging risks in this population.

OBJECTIVES/OBJECTIVE:To estimate past-year prevalence and correlates of major depressive episode (MDE), characterize mental health treatment utilization, and identify barriers to care among community-dwelling US adults aged ≥50. DESIGN/METHODS:Cross-sectional analysis of a nationally representative survey. SETTING/METHODS:Noninstitutionalized US population. PARTICIPANTS/METHODS:20,580 respondents aged ≥50 from 2022 to 2023 National Survey on Drug Use and Health. MEASUREMENTS/METHODS:We estimated past-year MDE prevalence and delineated demographic and past-year substance use correlates; examined mental health treatment utilization among individuals with MDE; and identified barriers to care among untreated individuals. RESULTS:An estimated 4.6% (95% confidence interval: 4.2-5.2) of adults aged ≥50 experienced past-year MDE. In multivariable analyses, higher odds were estimated among females, divorced/separated or widowed individuals, college-educated individuals, and those with alcohol use disorder, cannabis use (with or without use disorder), and prescription opioid or tranquilizer/sedative misuse. Lower odds were estimated among adults aged ≥65, Non-Hispanic Black individuals, and those with income ≥$50,000. Among those with MDE, 66.2% received any mental health treatment. In bivariable comparisons, adults aged ≥65 were less likely than those aged 50-64 to receive outpatient mental health services (38.7% versus 50.1%, p = 0.032) and to report perceived unmet need for treatment (8.8% versus 23.3%, p = 0.019). Among untreated individuals with perceived unmet need, barriers to treatment were attitudinal (86.2%; e.g., thought could handle without treatment), access-related (73.1%), and financial (48.6%). CONCLUSIONS:MDE is prevalent among older adults with heterogeneity across demographic and substance use factors. Treatment disparities and high barrier rates highlight the need for targeted interventions in this population.

BACKGROUND:Cannabis consumption modalities such as smoking, vaping, and consumption of edibles differ in pharmacokinetics and potency, and vary by demographic characteristics. Data linking real-world consumption modality patterns to use frequency and cannabis use disorder (CUD) remain limited. METHODS:Latent class analysis (LCA) was applied to identify modality-based classes using data from 17,732 adults reporting past 30-day cannabis use on the 2022-2023 National Survey on Drug Use and Health. Multinomial logistic regression delineated associations of class membership with demographic characteristics, cannabis use frequency, and the presence/severity of CUD. RESULTS:LCA yielded four classes based on each modality likelihood: primary smoking (48.2 %), smoking and vaping (20.5 %), mainly edibles (16.9 %), and polymodal use (14.4 %). Compared to adults aged ≥ 50, those aged 18-25 years were more likely to belong to the smoking and vaping (aRRR = 2.52, 95 % CI: 1.77-3.61) or polymodal classes (aRRR = 3.58, 95 % CI: 2.48-5.18). Females were more likely to be in the mainly edibles class (aRRR = 1.78, 95 % CI: 1.48-2.13). Daily cannabis use was more likely among polymodal (aRRR = 2.67, 95 % CI: 2.25-3.17) and less likely among mainly edibles (aRRR = 0.49, 95 % CI: 0.35-0.68) classes, relative to the primary smoking class. Compared to the primary smoking class, risk of having CUD was higher among people in the smoking and vaping class, and in the polymodal class, but lower in the mainly edibles class. CONCLUSIONS:Cannabis use modalities were associated with differences regarding demographic characteristics and severity of use. Future interventions could account for route-specific use to improve prevention and harm reduction efforts.

Synthetic cathinones are a chemically diverse class of novel stimulants that continue to emerge in the U.S. and globally. Trends in overall and specific synthetic cathinone availability in the U.S. (as indicated by seizures) remain poorly characterized. We analyzed annual counts of reports submitted from 2010-2024 to the U.S. Drug Enforcement Administration's National Forensic Laboratory Information System (NFLIS). We grouped reports into chemical subclasses of beta-keto methylenedioxyamphetamines ("-ylones"), pyrrolidinophenones ("pyrros"), and beta-keto amphetamines ("-drones"). Temporal trends in total reports and subclasses were modeled using negative binomial regression spline models. To further contextualize subclass trends, we descriptively examined the contribution of individual synthetic cathinones over time. Between 2010 and 2024, 178,892 synthetic cathinone reports were submitted to NFLIS, of which 73.3% were classified as -ylones, 19.9% as pyrros, 5.2% as -drones, and 1.6% as other. 68.7% of total reports were from the South, with 33.5% from Florida. Nationally, total reports increased sharply in 2010-2013, declined mid-period, rose again from 2019-2020, and then stabilized. Additional regional and temporal heterogeneity was noted across subclasses. We identified patterns of rapid emergence and replacement of individual compounds within subclasses, particularly within the -ylone subclass. Overall, we found substantial temporal, regional, and subclass-specific variation in synthetic cathinone reports to NFLIS from 2010-2024, largely driven by reports from the South and from successive cycles of replacement of -ylones. These findings emphasize the need to strengthen forensic and epidemiological surveillance of the evolving synthetic cathinone landscape in the U.S.

Research is needed to establish optimal cutoffs to determine cocaine use via oral fluid testing while considering the possibility of unintentional exposure. We compared detection of cocaine and its metabolites to self-reported use while considering other drug use to determine optimal cutoffs to determine intentional use. In this study, 1819 adults entering randomly selected nightclubs were surveyed about cocaine and other drug use and had their oral fluid analyzed using liquid chromatography quadrupole time-of-flight mass spectrometry. We compared self-reported use to detected exposure. 13.6% of participants reported past 24-hour cocaine use, 43.7% tested positive for cocaine exposure (≥1 ng/mL), and 11.8% tested positive for at least one metabolite. 28.6% either tested positive for or reported past 24-hour use of other drugs, primarily ketamine. Among those testing positive for cocaine exposure (n = 794), only 29.1% reported past 24-hour use. Among positive cases, the optimal cocaine concentration cut-point for predicting self-report was ≥ 26 ng/mL. When focusing on the full sample and a subsample with data on past 48-hour reported use, optimal cut-points were ≥ 6 ng/mL and ≥ 5 ng/mL, respectively. However, detection of metabolites was the strongest predictor of self-reported use. Using self-report as the gold standard, metabolite detection most accurately classified reported use, over and above detection of cocaine or other drugs; however, relying solely on detection of metabolites or higher cocaine concentration thresholds often led to under-detection. In conclusion, relying on detection of metabolites or higher concentrations most accurately detects intentional use, but these lack sensitivity to detect a portion of use.