American Journal of Drug and Alcohol Abuse最新文献

Background: Rural and frontier communities face high rates of opioid use disorders (OUDs). In 2021, the Rural Addiction Implementation Network (RAIN) sought to establish a rural hospital/clinic-system practice-based research network (RH-PBRN) to facilitate implementation of evidence-based addiction-related prevention, treatment, and recovery (PTR) services to reduce the morbidity of OUD and substance use disorder (SUD) in rural communities.Objective: To describe the goals and implementation of PTR activities of RAIN, a novel RH-PBRN.Methods: RAIN identified teams of external/internal facilitators at four rural hospitals/clinic-networks to achieve at least 15 PTR activities involving OUD and other SUDs. RAIN utilized an implementation-facilitation approach: facilitators assessed the implementation environment and promoted interventions to overcome barriers to PTR implementation. Other interventions included site visits, community of learning calls, and e-communication. RAIN assessed and recorded facilitators and barriers to implementation, milestone attainment, and outcomes of PTR activities. At 18 months, we queried facilitators about the fidelity and implementation of RAIN activities.Results: RAIN established an HP-PBRN in four sites (Idaho, Montana, Utah, and Wyoming). Within the HP-PBRN, 20 PTR activities were established (p = 7, T = 10, R = 3; range 3-7 per site). Barriers to implementation of PTR activities included competing clinical demands, especially due to COVID-19, lack of dedicated effort for staff at sites, and stigma of addiction and its treatment. Facilitators of implementation included the use of trained expert facilitators and communication between the sites.Conclusions: RAIN implemented 20 addiction-related PTR activities in four rural hospitals/clinic-networks. RAIN's intervention model could be replicated to address addiction-related harms in other rural communities.

Background: Although nitrous oxide (N₂O) is increasingly misused recreationally, its use and risks among medical students who have professional access to it are rarely explored.Objectives: To investigate the recreational use of N₂O among medical students in Paris Region (France).Methods: This cross-sectional study used an online questionnaire distributed in 2022 through social networks, to all medical students (undergraduate student from the 2nd year of medical studies to residents until the end of the residency) from the six medical universities in Paris Region. We collected demographic characteristics, patterns of N₂O consumption, co-consumptions, and N₂O training (academic course or self-training). Factors associated with N₂O consumption and complications were analyzed using multivariable logistic regressions.Results: The questionnaires of 444 students (mean age: 25.9 years (SD = 2.69), 75.5% female, and 63.74% residents) were analyzed. Recreational N₂O consumption was reported by 71.85% of students and 20.50% consumed at least monthly. N₂O consumption was associated with being a resident (versus undergraduate student) (adjusted OR (aOR) = 3.07[1.45-6.72]; p < .01), receiving training on N₂O (aOR) = 3.13[1.84-6.24]; p < .01), and consumption of cannabis (aOR = 18.21[3.47-104.26]; p < .01), ecstasy (aOR = NA, p = .048) and poppers (aOR = 13.9[2.64-77.94]; p < .01). Complications (mainly dizziness, paresthesia and burns) were reported in 8.15% of students consuming N₂O. They were associated with consuming more than 10 balloons per intake (aOR = 6.04[1.32-25.00); p < .01) and inversely associated with receiving training (aOR = 0.35[0.14-0.86]; p = .01).Conclusions: Almost three-quarters of medical students experienced recreational N₂O consumption, particularly with poly-drug use. Given that complications were associated with high consumption and lack of education, risk training and screening for N₂O consumption could be beneficial.

Background: Alcoholic liver disease (ALD) significantly contributes to global morbidity and mortality. The role of inflammatory cytokines in alcohol-induced liver injury is pivotal yet not fully elucidated.Objectives: To establish a causal link between inflammatory cytokines and ALD using a Mendelian Randomization (MR) framework.Methods: This MR study utilized genome-wide significant variants as instrumental variables (IVs) for assessing the relationship between inflammatory cytokines and ALD risk, focusing on individuals of European descent. The approach was supported by comprehensive sensitivity analyses and augmented by bioinformatics tools including differential gene expression, protein-protein interactions (PPI), Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis, and analysis of immune cell infiltration.Results: Our findings reveal that increased levels of stem cell growth factor beta (SCGF-β, beta = 0.141, p = .032) and interleukin-7 (IL-7, beta = 0.311, p = .002) are associated with heightened ALD risk, whereas higher levels of macrophage inflammatory protein-1α (MIP-1α, beta = -0.396, p = .004) and basic fibroblast growth factor (bFGF, beta = -0.628, p = .008) are linked to reduced risk. The sensitivity analyses support these robust causal relationships. Bioinformatics analyses around inflammatory cytokine-associated SNP loci suggest multiple pathways through which cytokines influence ALD.Conclusion: The genetic evidence from this study convincingly demonstrates that certain inflammatory cytokines play directional roles in ALD pathogenesis. These findings provide insights into the complex biological pathways involved and underscore the potential for developing targeted therapies that modulate these inflammatory responses, ultimately improving clinical outcomes for ALD patients.

Background: Medication disposal programs have been promoted as one solution to the opioid crisis, but uptake by community members has been minimal.Objectives: To clarify perceptions of medication disposal options among people who have been prescribed an opioid analgesic in North Carolina to inform interventions that can facilitate the disposal of unused opioids.Methods: In 2022, we conducted focus groups with participants who received an opioid medication in the past year to gain information to develop an intervention related to the disposal of unused opioid medication (12 focus group discussions (FGDs); total N = 37; 30 identified as female, 6 as male, and 1 as another gender). Participants were shown a slide with the Food and Drug Administration's recommended disposal options and asked about their perceptions of each option. Themes were derived using an inductive, thematic, qualitative approach.Results: Seven themes about perceptions of medication disposal programs emerged from the data. Four of the themes reflect potential barriers to medication disposal: failed disposal attempts, lack of sufficient education on proper disposal, unclear meaning of specific disposal language, and concerns about existing disposal options. Three of the themes provide insight on potential facilitators of medication disposal: preference of low-cost disposal options, ease and accessibility among disposal methods, and preferred disposal methods.Conclusion: Patients should be provided clear and consistent guidance from prescribers and dispensing pharmacists on when and how to dispose of unused medications and opportunities to dispose of medications at no cost to the patient.

Background: Rural areas in the United States have been severely impacted by recent rises in substance use related mortality and psychosocial consequences. There is a dearth of treatment resources to address substance use disorder (SUD). Rural recovery houses (RRH) are important services that provide individuals with SUD with an environment where they can engage in recovery-oriented activities, but dropout rates are unacceptably high, and evidence-based interventions such as contingency management (CM) may reduce dropout and improve outcomes for RRH residents. In this paper, we describe the results of a national convening of experts that addressed important issues concerning the implementation of CM within the context of RRHs.Methods: Twelve experts (five female) in the areas of CM, RRH and rural health participated in a one-day facilitated meeting that used nominal group technique to identify expert consensus in three areas as they pertain to RRH: (a) facilitators and barriers to CM implementation, (b) elements necessary for successful program building based on group feedback, and (c) recommendations for future implementation of CM.Results: Several RRH- and system-level barriers and facilitators to implementing CM were identified by the panel, and these were categorized based on the level of importance for and ease of implementation. CM funding, staff and resident buy-in, set policies, education on CM, and consistent fidelity to CM procedures and tracking were identified as important requirements for implementing CM in RRH.Conclusions: We provide recommendations for the implementation of CM in RRH that may be useful in this context, as well as more broadly.

Background: Longitudinal Measurement Invariance (LMI) is critically important to evaluate changes in alcohol expectancies over time. However, past research has not explored the longitudinal properties of the Spanish Expectancy Questionnaire Short Form (EQ-SF).Objectives: To examine the reliability, sources of validity (structural, invariance across sex, and concurrent validity), and LMI of the Spanish EQ-SF among young adults who engage in binge drinking.Methods: Participants (n = 279; 48.4% female) completed the EQ-SF and, two months later, completed it again along with measures of alcohol use, drinking motives, and protective behavioral strategies (PBS). We performed confirmatory factor analysis for structural validity and measurement invariance analysis for longitudinal and sex stability.Results: The eight-factor intercorrelated model (i.e. social facilitation, fun, sexual disinhibition, tension reduction, antisocial effects, negative emotional states, negative physical effects, and cognitive impairments) provided the best fit (χ2(df) = 497.29(224), CFI = .962, RMSEA = .064, SRMR = .049). This model was invariant across sex and time. Reliability coefficients (Ordinal alpha) for each dimension were consistently strong at both time points (from .72 to .93 at T1 and .73 to .91 at T2). Positive alcohol expectancies at baseline were positively related to alcohol use and drinking motives and negatively related to PBS at follow-up, demonstrating predictive validity.Conclusion: Our results support the temporal invariance of the EQ-SF scores among Spanish young adults who engage in binge drinking. The evidence supports the suitability of this measure for accurately assessing changes in alcohol expectancies over time in interventions aimed at preventing binge drinking in young adults.

Background: Little is known regarding the extent to which substance use disorder (SUD) treatment facilities adopt comprehensive services to meet patients' medical and social needs.Objective: To examine trends in the availability of comprehensive services within outpatient SUD treatment facilities from 2018 to 2022.Methods: We used data from the Mental Health and Addiction Treatment Tracking Repository, a national database of SUD treatment facilities (n = 13,793). We examined the availability of four domains of comprehensive services and four types of SUD treatment services from 2018 to 2022. We conducted bivariate and multivariate logistic regression predicting the availability of a comprehensive service model (defined as having at least one service from each service domain), controlling for organizational and community characteristics.Results: Comprehensive services were increasingly offered from 2018 to 2022. In unadjusted and adjusted models, facilities which were externally accredited (OR: 1.50; 95%CI: 1.30-1.74), accepted Medicaid (OR: 1.51; 95%CI: 1.30-1.74), performed community outreach (OR: 2.05; 95%CI: 1.80-2.33), provided naloxone and overdose education (OR: 3.50; 95%CI: 3.06-3.99), had a robust SUD treatment infrastructure (OR: 2.33; 95%CI; 2.08-2.62), and were located in a county with a lower percentage of White residents (OR: 0.99; 95%CI: 0.99-0.99), a higher percentage of residents in poverty (OR: 1.02; 95%CI: 1.00-1.03), and the Northeast compared with the South (OR: 1.21; 95%CI: 1.01-1.45), had significantly higher odds of adopting a comprehensive service model.Conclusion: Findings highlight the importance of factors reflecting experience with organizational change efforts and enhanced external support. Policymakers working to enhance the uptake of comprehensive services should focus on obtaining the financial and technical support necessary to develop these models.

Background: Innovative analytic approaches to drug studies are needed to understand better the co-use of opioids with non-opioids among people using illicit drugs. One approach is the Bayesian kernel machine regression (BKMR), widely applied in environmental epidemiology to study exposure mixtures but has received far less attention in substance use research.Objective: To describe the utility of the BKMR approach to study the effects of drug substance mixtures on health outcomes.Methods: We simulated data for 200 individuals. Using the Vale and Maurelli method, we simulated multivariate non-normal drug exposure data: xylazine (mean = 300 ng/mL, SD = 100 ng/mL), fentanyl (mean = 200 ng/mL, SD = 71 ng/mL), benzodiazepine (mean = 300 ng/mL, SD = 55 ng/mL), and nitazene (mean = 200 ng/mL, SD = 141 ng/mL) concentrations. We performed 10,000 MCMC sampling iterations with three Markov chains. Model diagnostics included trace plots, r-hat values, and effective sample sizes. We also provided visual relationships of the univariate and bivariate exposure-response and the overall mixture effect.Results: Higher levels of fentanyl and nitazene concentrations were associated with higher levels of the simulated health outcome, controlling for age. Trace plots, r-hat values, and effective sample size statistics demonstrated BKMR stability across multiple Markov chains.Conclusions: Our understanding of drug mixtures tends to be limited to studies of single-drug models. BKMR offers an innovative way to discern which substances pose a greater health risk than other substances and can be applied to assess univariate, bivariate, and cumulative drug effects on health outcomes.

Background: Ethanol consumption during pregnancy induces enduring detrimental effects in the offspring, manifesting as a spectrum of symptoms collectively termed as Fetal Alcohol Spectrum Disorders (FASD). Presently, there is a scarcity of treatments for FASD.Objectives: To analyze current literature, emphasizing evidence derived from preclinical models, that could potentially inform therapeutic interventions for FASD.Methods: A narrative review was conducted focusing on four prospective treatments: nutritional supplements, antioxidants, anti-inflammatory compounds and environmental enrichment. The review also highlights innovative therapeutic strategies applied during early (e.g. folate administration, postnatal days 4-9) or late (e.g. NOX2 inhibitors given after weaning) postnatal stages that resulted in significant improvements in behavioral responses during adolescence (a critical period marked by the emergence of mental health issues in humans).Results: Our findings underscore the value of treatments centered around nutritional supplementation or environmental enrichment, aimed at mitigating oxidative stress and inflammation, implying shared mechanisms in FASD pathogenesis. Moreover, the review spotlights emerging evidence pertaining to the involvement of novel molecular components with potential pharmacological targets (such as NOX2, MCP1/CCR2, PPARJ, and PDE1).Conclusions: Preclinical studies have identified oxidative imbalance and neuroinflammation as relevant pathological mechanisms induced by prenatal ethanol exposure. The relevance of these mechanisms, which exhibit positive feedback loop mechanisms, appear to peak during early development and decreases in adulthood. These findings provide a framework for the future development of therapeutic avenues in the development of specific clinical treatments for FASD.

Background: X-ray absorption spectroscopy (XAS) is a widely used substance analysis technique. It bases on the different absorption coefficients at different energy level to achieve material identification. Additionally, the combination of spectral technology and deep learning can achieve auto detection and high accuracy in material identification.Objectives: Current methods are difficult to identify drugs quickly and nondestructively. Therefore, we explore a novel approach utilizing XAS for the detection of prohibited drugs with common X-ray tube source and photon-counting (PC) detector.Method: To achieve automatic, rapid, and accurate detection of drugs. A CdTe detector and a common X-ray source were used to collect data, then dividing the data into training and testing sets. Finally, the improved transformer encoder model was used for classification. LSTM and ResU-net models are selected for comparation.Result: Fifty substances, which are isomers or compounds with similar molecular formulas of drugs, were selected for experiment substances. The results showed that the improved transformer model achieving 1.4 hours for training time and 96.73% for accuracy, which is better than the LSTM (2.6 hours and 65%) and ResU-net (1.5 hours and 92.7%).Conclusion: It can be concluded that the attention mechanism is more accurate for spectral material identification. XAS combined with deep learning can achieve efficient and accurate drug identification, offering promising application in clinical drug testing and drug enforcement.