American Journal of Drug and Alcohol Abuse最新文献

Drug checking services provide individuals who use drugs with the ability to test samples of their drugs for the presence of highly potent substances. However, there has been recent concern about whether the existing repertoire of point-of-care drug checking technologies, such as immunoassay strips and Fourier-transform infrared spectroscopy (FTIR), are adequate in identifying substances in the unregulated drug supply. Carfentanil and nitazene opioids, substances that are even more potent than fentanyl in vitro, have been found in the unregulated supply in North America and pose a challenge to our existing drug checking strategy. For example, etizolam has recently permeated the unregulated drug supply in North America, and has demonstrated the ability to evade point-of-care drug checking technologies. In response to the incessantly changing nature of the unregulated supply, we argue that drug checking technologies and service delivery models must continuously adapt alongside constantly changing drug markets. We provide two examples of emerging technologies, paper spray-mass spectrometry and surface-enhanced Raman spectroscopy, which address many of the shortcomings of existing technologies. For both technologies, we discuss their feasibility, where they can be offered, their advantages, and how they address gaps in our existing technologies. We contend that these technologies, and other emerging technologies, can be integrated into a future approach to drug checking that flexibly uses different technologies and service delivery methods to adapt to changes in the drug supply.

Background: The numbers of days people consume alcohol and other drugs over a fixed interval, such as 28 days, are often collected in surveys of substance use. The presence of an upper bound on these variables can result in response distributions with "ceiling effects." Also, if some peoples' substance use behaviors are characterized by weekly patterns of use, summaries of substance days-of-use over longer periods can exhibit multiple modes.Objective: To highlight advantages of ordinal models with a separate level for each distinct survey response, for bounded, and potentially multimodal, count data.Methods: We fitted a Bayesian proportional odds ordinal model to longitudinal cannabis days-of-use reported by 443 individuals who used illicit drugs (206 female, 214 male, 23 non-binary). We specified an ordinal level for each unique response to allow the exact numeric distribution implied by the predicted ordinal response to be inferred. We then compared the fit of the proportional odds model with binomial, negative binomial, hurdle negative binomial and beta-binomial models.Results: Posterior predictive checks and the leave one out information criterion both suggested that the proportional odds model gave a better fit to the cannabis days-of-use data than the other models. Cannabis use among the target population declined during the COVID-19 pandemic in Australia, with the odds of a member of the population exceeding any specified frequency of cannabis use in Wave 4 estimated to be 73% lower than in Wave 1 (median odds ratio 0.27, 90% credible interval 0.19, 0.38).Conclusion: Ordinal models can be suitable for complex count data.

Background: Vaping is an increasingly popular mode of cannabis use. Few studies have characterized the role of flavors in cannabis e-liquids.Objectives: To explore the prevalence of flavored vaping liquids, including differences between countries and correlates of use.Methods: Data were from Wave 4 (2021) of the International Cannabis Policy Study with national samples aged 16-65 in Canada, the United States (US), Australia, and New Zealand. The sample comprised 52,938 respondents, including 6,265 who vaped cannabis e-liquids in the past 12-months (2,858 females, 3,407 males). Logistic regression models examined differences in the use of flavored e-liquids between countries and sociodemographic characteristics.Results: The prevalence of vaping cannabis e-liquids was highest in the US (15.3%) and Canada (10.7%) compared to Australia (4.0%) and New Zealand (3.7%). Among past 12-month cannabis consumers, 57.5% reported using flavored vaping liquids, 34.2% used unflavored vaping products and 8.3% did not know. People who vape in Australia were most likely to report using flavored liquids compared to New Zealand (OR = 2.29), Canada (OR = 3.14), and the US (OR = 3.14) (p < .05 for all). Fruit was the most reported vaping flavor (40.8%), followed by candy/dessert (20.4%) and vanilla (15.2%). Use of flavored vapes was greater among younger, ethnic minorities, female, higher education and income adequacy, and more frequent consumers (p < .05).Conclusion: Many cannabis consumers reported using flavored e-liquids, with highest levels among young people aged 16-35. Given the high prevalence of vaping in legal markets, regulators should consider the role of flavored vaping products in promoting cannabis use among this group.

Background: As more states pass recreational cannabis legalization (RCL), we must understand how RCL affects substance use.Objectives: The current study aims to examine the effect of RCL on lifetime and past-year use of cannabis, alcohol, tobacco, and other drugs, frequency of cannabis, alcohol, and tobacco use, co-use of cannabis with alcohol and tobacco, and consequences from cannabis and alcohol use.Methods: We used a unique, co-twin control design of twin pairs who were discordant for living in a state with RCL between 2018 and 2021. The sample consisted of 3,830 adult twins (41% male), including 232 twin pairs discordant for RCL. Problems from alcohol and cannabis use were assessed via the Brief Marijuana Consequences Questionnaire and the Brief Young Adult Alcohol Consequences Questionnaire.Results: Results indicated that the twin living in an RCL state was more likely to endorse past-year cannabis use (OR = 1.56, p = .009), greater number of cannabis use days in the past 6 months (β = 0.47, p = .019), but not more negative consequences from cannabis use (β = 0.21, p = .456) compared to their co-twin in a non-RCL state. There were no differences within-twin pairs in frequency of alcohol use (β=-0.05, p = .601), but the RCL twin reported fewer negative consequences from alcohol use (β=-0.29, p = .016) compared to their co-twin in a non-RCL state. We did not observe any other differences within-twin pairs on other outcomes.Conclusion: These results suggest that living in an RCL state is associated with greater cannabis frequency but not more negative consequences from cannabis use than living in a non-RCL state.

Background: Medication treatment for opioid use disorder (MOUD) is an instrumental tool in combatting opioid use and overdose. Excess weight gain associated with MOUD initiation is a potential barrier that is not well understood.Objectives: Conduct a scoping review of available studies investigating the effect of MOUD on weight.Methods: Included studies consisted of adults taking any type of MOUD (e.g. methadone, buprenorphine/naloxone, naltrexone) with data on weight or body mass index for at least two time points. Evidence was synthesized using qualitative and descriptive approaches, and predictors of weight gain including demographics, comorbid substance use, and medication dose were examined.Results: Twenty-one unique studies were identified. Most studies were uncontrolled cohort studies or retrospective chart reviews testing the association between methadone and weight gain (n = 16). Studies examining 6 months of methadone treatment reported weight gain ranging from 4.2 to 23.4 pounds. Women appear to gain more weight from methadone than men, while patients using cocaine may gain less. Racial and ethnic disparities were largely unexamined. Only three case reports and two nonrandomized studies examined the effects of either buprenorphine/naloxone or naltrexone, and potential associations with weight gain were not clear.Conclusion: The use of methadone as an MOUD appears to be associated with mild to moderate weight gain. In contrast, there is little data supporting or refuting weight gain with buprenorphine/naloxone or naltrexone. Providers should discuss the potential risk for weight gain with patients as well as prevention and intervention methods for excess weight gain.

An earlier version of this article was published in error. Our prior publication was missing reference to a prior study on this topic. Our prior research has not found an association between recreational cannabis legalization (RCL) and negative psychosocial and psychiatric outcomes. We reported significant associations between RCL with greater cannabis frequency and fewer alcohol use disorder symptoms. The current study expands on our previous research by using a cross-sectional design and different measures of problems from cannabis and alcohol use and including additional substance use variables. The current study found similar results to our previous research.

Background: An exemption to existing U.S. regulation of methadone maintenance therapy after the onset of the COVID-19 pandemic permitted increased take-home doses beginning March 2020.Objectives: We assessed the impact of this exemption on opioid use.Methods: A pre/post study of 187 clients recruited from an OTP who completed a survey and consented to share their urine drug testing (UDT) data. Use of fentanyl, morphine, hydromorphone, codeine, and heroin was assessed via UDT. Receipt of take-home methadone doses was assessed from clinic records for 142 working days pre- and post-COVID exemption. Analysis was conducted using a linear regression model to assess the association between increased take-home doses and use of illicit opioids.Results: In the pre- vs. post-COVID-19 SAMHSA exemption periods, 26.2% vs. 36.3% of UDTs were positive for 6-acetylmorphine respectively, 32.6% vs. 40.6% positive for codeine, 34.2% vs 44.2% positive for hydromorphone, 39.5% vs. 48.1% positive for morphine, 8.0% vs. 14.4% positive for fentanyl (p-value < .001). However, in the unadjusted descriptive data, when grouped by change in substance use, those clients who experienced a decrease in the use of morphine, codeine, and heroin post-COVID-19 were given significantly more take-home doses than the groups that had no change or an increase in the use of these substances. In the adjusted model, there was no significant relationship between change in opioid use and increased receipt of take-home methadone doses.Conclusions: Although take-home doses post-COVID-19 nearly doubled, this increase was not associated with a significant change in use of illicit opioids.

Background: In the US, seventy percent of drug-related deaths are attributed to opioids. In response to the ongoing opioid crisis, New Jersey's (NJ) Medicaid program implemented the MATrx model to increase treatment access for Medicaid participants with opioid use disorder (OUD). The model's goals include increasing the number of office-based treatment providers, enhancing Medicaid reimbursement for certain treatment services, and elimination of prior authorizations for OUD medications.Objectives: To explore office-based addiction treatment providers' experiences delivering care in the context of statewide policy changes and their perspectives on treatment access changes and remaining barriers.Methods: This qualitative study used purposive sampling to recruit office-based New Jersey medications for opioid use disorder (MOUD) providers . Twenty-two providers (11 females, 11 males) discussed treatment experiences since the policy changes in 2019, including evaluations of the current state of OUD care in New Jersey and perceived outcomes of the MATrx model policy changes.Results: Providers reported the MOUD climate in NJ improved as Medicaid implemented policies intended to reduce barriers to care and increase treatment access. Elimination of prior authorizations was noted as important, as it reduced provider burden and allowed greater focus on care delivery. However, barriers remained, including stigma, pharmacy supply issues, and difficulty obtaining injectable or non-generic medication formulations.Conclusion: NJ policies may have improved access to care for Medicaid beneficiaries by reducing barriers to care and supporting providers in prescribing MOUD. Yet, stigma and lack of psychosocial supports still need to be addressed to further improve access and care quality.

Background: Neighborhood-, school-, and peer-contexts play an important role in adolescent alcohol use behaviors. Methodological advances permit simultaneous modeling of these contexts to understand their relative and joint importance. Few empirical studies include these contexts, and studies that do typically: examine each context separately; include contexts for the sole purpose of accounting for clustering in the data; or do not disaggregate by sex.Objectives: This study takes an eco-epidemiologic approach to examine the role of socio-contextual contributions to variance in adolescent alcohol use. The primary parameters of interest are therefore variance rather than beta parameters (i.e. random rather than fixed effects). Sex-stratified models are also used to understand how each context may matter differently for male and female adolescents.Method: Data come from the National Longitudinal Study of Adolescent to Adult Health (n = 8,534 females, n = 8,102 males). We conduct social network analysis and traditional and cross-classified multilevel models (CCMM) in the full and sex-disaggregated samples.Results: In final CCMM, peer groups, schools, and neighborhoods contributed 10.5%, 10.8%, and 0.4%, respectively, to total variation in adolescent alcohol use. Results do not differ widely by gender.Conclusions: Peer groups and schools emerge as more salient contributing contexts relative to neighborhoods in adolescent alcohol use for males and females. These findings have both methodological and practical implications. Multilevel modeling can model contexts simultaneously to prevent the overestimation of variance in youth alcohol use explained by each context. Primary prevention strategies addressing youth alcohol use should focus on schools and peer networks.

Background: Sober living houses are designed for individuals in recovery to live with others in recovery, yet no guidelines exist for the time needed in a sober living house to significantly impact outcomes.Objectives: To examine how the length of stay in sober living houses is related to substance use and related outcomes, focusing on early discontinuation (length of stay less than six months) and stable residence (length of stay six months or longer).Methods: Baseline and 12-month data were collected from 455 sober living house residents (36% female). Longitudinal mixed models tested associations between early discontinuation vs. stable residence and abstinence, recovery capital, psychiatric, and legal outcomes. Final models were adjusted for resident demographics, treatment, 12-step attendance, use in social network, and psychiatric symptoms, with a random effect for house.Results: Both early discontinuers (n = 284) and stable residents (n = 171) improved significantly (Ps ≤ .05) between baseline and 12 months on all outcomes. Compared to early discontinuation, stable residence was related to 7.76% points more percent days abstinent (95% CI: 4.21, 11.31); 0.88 times fewer psychiatric symptoms (95% CI: 0.81, 0.94); 0.84 times fewer depression symptoms (95% CI: 0.76, 0.92); and lower odds of any DSM-SUD (OR = 0.65, 95% CI: 0.47, 0.89) and any legal problems (OR = 0.58, 95% CI: 0.40, 0.86).Conclusion: In this study of sober living houses in California, staying in a sober living house for at least six months was related to better outcomes than leaving before six months. Residents and providers should consider this in long-term recovery planning.