Journal: Drug and Alcohol Dependence, 2024, doi: 10.1016/j.drugalcdep.2024.112477
Authors: Katelyn F. Romm, Erin A. Vogel, Christina Dyar, Laurie A. Drabble, & Carla J. Berg
Abstract:
Introduction: State policies surrounding sexual minority (SM) rights are associated with tobacco use among SM individuals. Research is scant regarding the role of distinct SM policy categories on SM young adults’ (SMYAs) tobacco use and mechanisms explaining these associations.
Methods: We analyzed 2023 survey data from 1,100 SMYAs (ages 18-34; 14.2% gender minority; 66.1% bisexual+, 29.1% monosexual; 53.2% racial/ethnic minority) with representation across 45 US states and DC. Regression-based models examined: 1) direct associations of residing in states with negative and limited (vs. comprehensive) SM state policies with respect to 7 policy categories (relationship/parent recognition, nondiscrimination, religious exemptions, LGBTQ youth, healthcare, criminal justice, gender identity documents) with minority stress (mental health, internalized stigma, community connectedness); 2) direct associations of policy categories and minority stress with tobacco use (past-month cigarette, e-cigarette, any tobacco use, number of products used); and 3) indirect associations of policy categories with tobacco use through minority stress.
Results: Relative to residing in states with comprehensive policies, residing in states with limited relationship/parent recognition policies indirectly predicted higher odds of e-cigarette use through mental health; weaker nondiscrimination policies indirectly predicted using more tobacco products through internalized stigma; and negative healthcare policies indirectly predicted higher odds of cigarette and any tobacco use through community connectedness.
Conclusions: These novel findings regarding associations among distinct SM policy categories, minority stress mediators, and tobacco use outcomes warrant further examination to better understand these distinct mechanisms, ultimately to inform SM-related policy and advocacy efforts, as well as tobacco prevention and cessation effort.
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Journal: International Journal of Medical Informatics, 2024, doi: 10.1016/j.ijmedinf. 2024.105530
Authors: Sahil Shikalgar, Scott G. Weiner, Gary J. Young, & Md. Noor-E-Alam
Abstract:
Objectives: This study investigates the impact of participation in self-help groups on treatment completion among individuals undergoing medication for opioid use disorder (MOUD) treatment. Given the suboptimal adherence and retention rates for MOUD, this research seeks to examine the association between treatment completion and patient-level factors. Specifically, we evaluated the causal relationship between self-help group participation and treatment completion for patients undergoing MOUD.
Methods: We used the Substance Abuse and Mental Health Services Administration’s (SAMHSA) Treatment Episode Data Set: Discharges (TEDS-D) from 2015 to 2019. The data are filtered by the patient’s opioid use history, demographics, treatment modality, and other relevant information. In this observational study, machine learning models (Lasso Regression, Decision Trees, Random Forest, and XGBoost) were developed to predict treatment completion. Outcome Adaptive Elastic Net (OAENet) was used to select confounders and outcome predictors, and the robust McNemars test was used to evaluate the causal relationship between self-help group participation and MOUD treatment completion.
Results: The machine-learning models showed a strong association between participation in self-help groups and treatment completion. Our causal analysis demonstrated an average treatment effect on treated (ATT) of 0.260 and a p-value < 0.0001 for the robust McNemars test.
Conclusions: Our study demonstrates the importance of participation in self-help groups for MOUD treatment recipients. We found that participation in MOUD along with self-help groups caused higher chances of treatment completion than MOUD alone. This suggests that policymakers should consider further integrating self-help groups into the treatment for OUD to improve the adherence and completion rate.
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Journal: Internet Interventions, 2024, doi: 10.1016/j.invent.2024.100779
Authors: Elizabeth K. Do, Sarah Cha, Shreya Tulsiani, Giselle Edwards, Linda Q. Yu, Michael S. Amato, Megan A. Jacobs, & Elizabeth C. Hair
Abstract:
Background: The evidence-based vaping cessation program, This is Quitting (TIQ), has been found to be effective in promoting abstinence among young people who use e-cigarettes.
Purpose: To estimate acceptability and engagement with Discord among treatment seeking youth and young adults and assess the benefit of adding an online social platform via Discord to TIQ.
Methods: Between February and March 2023, 527 TIQ participants (aged 13-24 years) were invited to join Discord with other TIQ users (TIQ Discord). Participants completed two online surveys, at baseline and 1-month post study enrollment. Descriptive statistics were used to describe acceptability and engagement with TIQ Discord. Chi-square, Fisher’s exact, and t-tests were used to compare changes in confidence in ability to quit and vaping abstinence across those who joined and engaged with TIQ Discord, compared to those receiving TIQ only.
Results: Among the n = 319 who were invited to TIQ Discord and provided follow-up data, 57.4 % joined. Among those who joined (n = 183), 61.7 % engaged with TIQ Discord by contributing at least one message or reaction. The mean number of contributed messages was 4.0 (median = 1, range = 1 to 51) and reactions was 0.31 (median = 0, range = 0 to 14). Engaging with TIQ Discord was positively associated with increased confidence in quitting at follow-up (p-value = 0.02), but vaping abstinence at follow-up did not differ (p-value = 0.87).
Discussion: Over half of participants who were invited to TIQ Discord joined – indicating high acceptability and an uptake rate that is higher than what is typically observed for online cessation communities. Engagement was positively associated with proximal outcomes, but self-selection prevents causal attribution. Pilot study results suggest acceptability of Discord for providing digital cessation support to young people in combination with a text-message cessation intervention.
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Journal: The Lancet Regional Health – Americas, 2024, doi: 10.1016/j.lana. 2024.100898
Authors: Tse Yang Lim, Huiru Dong, Erin Stringfellow, Zeynep Hasgul, Ju Park, Lukas Glos, Reza Kazemi, & Mohammad S. Jalali
Abstract:
Background: Fentanyl and its analogs contribute substantially to drug overdose deaths in the United States. There is concern that people using drugs are being unknowingly exposed to fentanyl, increasing their risk of overdose death. This study examines temporal trends and spatial variations in the co-occurrence of fentanyl with other seized drugs.
Methods: We identified fentanyl co-occurrence (the proportion of samples of non-fentanyl substances that also contain fentanyl) among 9 substances or substance classes of interest: methamphetamine, cannabis, cocaine, heroin, club drugs, hallucinogens, and prescription opioids, stimulants, and benzodiazepines. We used serial cross-sectional data on drug reports across 50 states and the District of Columbia from the National Forensic Laboratory Information System, the largest available database on the U.S. illicit drug supply, from January 2013 to December 2023.
Findings: We analyzed data from 11,940,207 samples. Fentanyl co-occurrence with all examined substances increased monotonically over time (Mann-Kendall p < 0.0001). Nationally, fentanyl co-occurrence was highest among heroin samples (approx. 50%), but relatively low among methamphetamine (≤1%), cocaine (≤4%), and other drug samples. However, co-occurrence rates have grown to over 10% for cocaine and methamphetamine in several Northeast states in 2017-2023.
Interpretation: Fentanyl co-occurs most commonly with heroin, but its presence in stimulant supplies is increasing in some areas, where it may pose a disproportionately high risk of overdose.
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Journal: The Journal of Pain, 2024, doi: 10.1016/j.jpain.2024.104665
Authors: Ryan S. D’Souza, & Richard L. Nahin
Abstract:
Nationally representative rates of incident prescription opioid use in the United States adult population and selected subpopulations are unknown. Using the National Health Interview Survey (2019-2020) longitudinal cohort, a cohort with 1-year follow-up created using random cluster probability sampling of noninstitutionalized civilian U.S. adults, we estimated rates and predictors of incident opioid use. Of 21,161 baseline (2019) participants randomly chosen for follow-up, the final analytic sample included 10,415 who also participated in 2020. Exposure variables were selected per the socio-behavioral model of health care utilization: predisposing characteristics (sex, age, race, etc), enabling characteristics (socioeconomic status, insurance status), health status (pain, disability, comorbidities, etc), and health care use (office visits, emergency room visits, and hospitalizations). Among adults who did not use prescription opioids in 2019, a 1-year cumulative incidence of 4.1% (95% confidence interval [CI]: 3.5-4.6) was seen in 2020, with an incidence rate (IR) of 32.6 cases of new prescription opioid use per 1,000 person-years (PYs). Cumulative incidence, IR, and adjusted relative risk (RR) varied by participant characteristics. We observed the highest IR in those with ineffective pain treatment (81.6 cases per 1,000 PY) and those who visited the emergency room ≥3 times (93.8 cases per 1,000 PY). Participants reporting ≥4 painful conditions had an adjusted RR of 2.9 (95% CI: 2.0-4.1), while the RR for those with sleep problems was 2.3 (95% CI: 1.7-3.1). Overall, this study presents nationally representative rates of incident prescription opioid use and suggests that some participants are using prescription opioids as an early-resort analgesic contrary to best-practice guidelines.
PERSPECTIVE: This longitudinal cohort study presents nationally representative rates of incident prescription opioid use in U.S. adults and selected subpopulations. Our data suggest that some participants are using prescription opioids as a first-line or early-resort analgesic, contrary to best-practice guidelines.
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