The Relationship between Vaping Cannabis and Frequency of Cannabis Use and Cannabis-Related Problems among Urban High School Students.

Background: Vaping, including vaping cannabis, is increasing among adolescents. In this longitudinal study, we examined the relationship between vaping cannabis and frequency of cannabis use and related problems over 6 months among adolescents. Material and Methods: Data were from 233 participants (46.8% male, 93.1% African American, mean age = 16.4 years) reporting cannabis use. The Alcohol, Smoking and Substance Involvement Screening Test (ASSIST) assessed frequency of past 30-day cannabis use and cannabis-related problems at baseline, 3- and 6-months post-baseline. We used latent growth curve modeling to compare vaping to non-vaping adolescents on trends in cannabis use frequency and ASSIST cannabis scores. Results: Adolescents who vaped cannabis (11.7%) had higher past 30-day frequency (mean = 17.89 days, SD = 10.49) of cannabis use at baseline compared to adolescents who had not vaped (mean = 12.1 days, SD = 10.93), but reported a significantly sharper decline in frequency of cannabis use (b = -0.34, p = 0.017). A significantly steeper decrease existed in the mean cannabis ASSIST scores for the vaping group than for the non-vaping group (b = -0.34, p = 0.014). Mean ASSIST scores on the cannabis subscale between the two groups were significantly different at 6-month follow-up (Vape mean = 6.00, SD = 8.12 vs. Non-vape mean = 9.6, SD = 9.39; p < 0.021). Conclusions: In a sample of cannabis-using adolescents, adolescents with experience vaping cannabis, compared to adolescents without vaping experience, on average reported sharper decreases in frequency of cannabis use and cannabis-related problems such as health or social problems.

Latent class analysis of perceived stigma among older adults receiving medications for opioid use disorder.

RATIONALE: Public stigma surrounds individuals who use medication for their recovery from a substance use disorder. However, we know little about subgroups of individuals with varying levels of perceived stigma and how these levels may be associated with physical and mental health-related quality of life (HRQOL) and social support. METHODS: We used latent class analysis to define subgroups of people aged 50-72 years of age (N = 104) who were enrolled in eight medication for opioid use disorder (MOUD) programs to explore subgroupings and correlates of group membership. RESULTS: We found evidence for three distinct classes of individuals and named the classes 1) the high stigma class, 2) the embarrassed class, and 3) the low stigma class. We found that people in the high-stigma class reported more rejection, more abstinence-based support group involvement, and reduced mental HRQOL. CONCLUSIONS: Results suggest reducing stigma among people on MOUD may help to boost mental HRQOL and improve social support receipt. The results are consistent with iatrogenic effects of AA/NA support groups such that these treatment modalities may increase stigma due to their focus on abstinence-only treatment for substance use disorders.

Mapping prescription drug monitoring program data to self-report measures of non-medical prescription opioid use in community pharmacy settings.

BACKGROUND: Community pharmacists are well-positioned to identify patients engaged in non-medical prescription opioid use (NMPOU) through Prescription Drug Monitoring Program (PDMP) databases. Integrating patient-reported outcomes with PDMP data may improve the interpretability of PDMP information to support clinical decision-making. OBJECTIVE: This study linked patient-reported clinical measures of substance use with PDMP data to examine relationships between average daily opioid dose in morphine milligram equivalents (MME) and visits to multiple pharmacies/prescribers with self-reported NMPOU. METHODS: Data from a cross-sectional health assessment given to patients aged ≥18 years filling opioid prescriptions were linked to PDMP records. NMPOU in the past three months was assessed on a continuous scale (range 0-39) using an adapted version of the Alcohol, Smoking, and Substance Involvement Screening Test (ASSIST). PDMP measures included average daily MME and number of distinct pharmacies/prescribers visited in the past 180 days. Univariable and multivariable zero-inflated negative binomial models estimated associations between PDMP measures and any NMPOU and severity of use. RESULTS: The sample included 1421 participants. In multivariable models adjusted for sociodemographic, mental health, and physical health characteristics, any NMPOU was associated with higher average daily MME (adjusted OR = 1.22, 95% CI = 1.05-1.39) and number of distinct prescribers visited (adjusted OR = 1.15, 95% CI = 1.01-1.30). Higher average daily MME (adjusted mean ratio (MR) = 1.12, 95% CI = 1.08-1.15), number of distinct pharmacies visited (adjusted MR = 1.11, 95% CI = 1.04-1.18), and number of distinct prescribers visited (adjusted MR = 1.07, 95% CI = 1.02-1.11) were associated with increased NMPOU severity. CONCLUSIONS: We observed significant, positive associations between average daily MME and visits to multiple pharmacies/prescribers with any NMPOU and severity of use. This study demonstrates self-report clinical measures of substance use can be cross-walked to PDMP data and translated into clinically interpretable information.