Research News Roundup: December 19, 2024

Journal: Addiction, 2024, doi: 10.1111/add.16663

Authors: Seema Choksy Pessar, Rosanna Smart, Tim Naimi, Marlene Lira, Jason Blanchette, Anne Boustead, & Rosalie Liccardo Pacula

Abstract:

Aims: To measure the association between state cannabis policies and use among adults and youth in the United States from 2002 to 2019, given rapid policy liberalization and complex state cannabis policy environments.

Design: Repeated cross-sectional time series analysis. Three sets of models assessed the linear association between the Cannabis Policy Scale (CPS), an aggregate measure of 17 state cannabis policy areas that weights each policy by its efficacy and implementation rating, and prevalence of cannabis use. The first included year and state fixed effects; the second added state-level controls; the third replaced state fixed effects with state random effects. Standard errors were clustered at the state level in all models.

Setting and participants: United States.

Measurements: Past-month prevalence of cannabis use is from the National Survey on Drug Use and Health Small Area Estimates, a nationally and state-representative cross-sectional survey of household population ages 12 and older for years 2002-2003 to 2018-2019. Exposure data include the CPS.

Findings: A 10 percentage-point increase in the CPS (i.e. greater cannabis policy restrictiveness) was associated with lower past-month use prevalence by 0.81 (95% confidence interval [CI] = -1.05 to -0.56) to 0.97 (95% CI = -1.19 to -0.75) percentage-points for the population ages 12 years and older. When models were stratified by age, a 10 percentage-point increase in the CPS was associated with a 0.87 (95% CI = -1.13 to -0.61) to 1.04 percentage-point (95% CI = -1.03 to -0.84) reduction in past-month use prevalence for adults ages 18 years and older, and a 0.17 (95% CI = -0.24 to -0.09) to 0.21 percentage-point (95% CI = -0.35 to -0.07) reduction for youth ages 12-17 years.

Conclusions: More restrictive US cannabis policies appear to be associated with reduced cannabis use for both adults and youth.

To read the full text of the article, please visit the publisher’s website.

Journal: Journal of Substance Use & Addiction Treatment, 2024, doi: 10.1016/j.josat. 2024.209562

Authors: Tammy Chung, Brian Suffoletto, & Trishnee Bhurosy

Abstract:

Introduction: Effective interventions show heterogeneity in treatment response. Addressing this heterogeneity involves identifying which intervention works best for whom. One method to address this heterogeneity identifies treatment-subgroup interactions to determine which of two interventions has greater effect for certain individuals based on their profile of pre-treatment characteristics. This secondary analysis of a randomized clinical trial (RCT) to address binge drinking examined whether two of the RCT’s interventions, GOAL and COMBO, which produced similar reductions in drinking outcomes, might have involved treatment-subgroup interactions. Identifying treatment-subgroup interactions can inform efficient patient-treatment matching that optimizes individual outcomes.

Methods: These secondary analyses included young adults (n = 344; 68.6 % female, ages 18-25) randomized to GOAL or COMBO 12-week alcohol text message interventions and who completed 3-month follow-up (end of intervention). GOAL provided weekly support for drinking limit goals. COMBO included all GOAL features, in addition to pre-event feedback on drinking plans and post-event feedback on alcohol consumption. QUINT, a tree-based algorithm, aimed to identify treatment-subgroup interactions using 21 pre-treatment (baseline) characteristics (e.g., demographics, perceived risk of binge-drinking related harm, perceived number of peers drinking to intoxication) that predicted the primary outcome of binge drinking at follow-up.

Results: The algorithm used five pre-treatment characteristics (sex, race, perceived risk of binge drinking-related harm, perceived number of peers drinking to intoxication, and any cannabis use in the past 3 months) to identify 7 treatment-subgroup interactions. COMBO had greater effectiveness than GOAL, for example, for females who reported lower risk of binge-drinking related harm and no cannabis use in the past 3 months, whereas GOAL had greater effectiveness for females who reported higher risk of binge-drinking related harm and more peers who drank to intoxication. In comparison, GOAL had greater effectiveness than COMBO among White males, whereas males of other racial backgrounds benefitted more from COMBO than GOAL.

Conclusions: The identified treatment-subgroup interactions involving GOAL and COMBO indicated which intervention had greater effectiveness for which subgroups of individuals based on pre-treatment characteristics. These findings can help efficiently match individuals to effective interventions, bringing the field closer to personalized, precision care.

To read the full text of the article, please visit the publisher’s website.

Journal: Social Science & Medicine, 2024, doi: 10.1016/j.socscimed.2024.117433

Authors: Natrina L. Johnson, Corinne A. Beaugard, Daneiris Heredia-Perez, Kaku So-Armah, Phillip Reason, Amy M. Yule, … Miriam Komaromy

Abstract:

In the United States, Black people face harsher health and social consequences of addiction compared to people who are not Black. These differential consequences are largely attributable to systemic racism. While addiction treatment may mitigate health disparities related to substance use, Black people also experience structural barriers and direct interpersonal racism which contribute to inequitable access and treatment outcomes. Improvements in addiction treatment for Black people are urgently needed, but there is little guidance or consensus on how to achieve this. Our interdisciplinary work group is comprised of 16 researchers and clinicians from one urban safety-net hospital in the Northeast US, and 9 community members with lived experience of substance use disorder (SUD) who came together from 2022 to 2024 for a community-engaged initiative to identify how to make addiction treatment more appealing, effective, and equitable for Black people. This paper’s objective is two-fold. First, we provide a broad overview of the project, which included 6 scoping literature reviews, 7 focus groups, and 4 day-long convenings which included an additional 30 experts on addiction treatment for Black patients, drawn primarily from the Northeast U.S. Altogether, we engaged more than 70 people with expertise in substance use and treatment, the majority of whom identify as Black. Second, we present major findings from the convenings, where we identified actions that can be taken now to improve the care of Black people and challenge the racist features of our addiction treatment system. Making addiction treatment more appealing, effective, and equitable will help to achieve health equity for Black people who use substances.

To read the full text of the article, please visit the publisher’s website.

Journal: Addiction, 2024, doi: 10.1111/add.16684

Authors: Gary J. Young, Tianjie Zhu, Mahmudul Hasan, Farbod Alinezhad, Leonard D. Young, & Noor-E-Alam

Abstract:

Background and aims: Opioid use disorder (OUD) is treatable with buprenorphine / naloxone (buprenorphine), but many patients discontinue treatment prematurely. The aim of this study was to assess the influence of patient- and prescriber-level characteristics relative to several patient outcomes following the initiation of buprenorphine treatment for OUD.

Design: This was a retrospective observational investigation. We used the Public Health Data Warehouse from the Massachusetts Department of Public Health to construct a sample of patients who initiated buprenorphine treatment between 2015 and 2019. We attributed each patient to a prescriber based on information from prescription claims. We used multilevel models to assess the influence of patient- and prescriber-level characteristics on each outcome.

Setting: Massachusetts, USA.

Participants: The study cohort comprised 37 955 unique patients and 2146 prescribers. Among patients, 64.6% were male, 52.6% were under the age of 35 and 82.2% were White, non-Hispanic. For insurance coverage, 72.1% had Medicaid.

Measurements: The outcome measures were poor medication continuity, treatment discontinuation and opioid overdose, all assessed within a 12-month follow-up period that began with a focal prescription for buprenorphine. Each patient had a single follow-up period. Poor medication continuity was defined as medication gaps totaling more than 7 days during the initial 180 days of buprenorphine treatment and treatment discontinuation was defined as having a medication gap for 2 consecutive months within the 12-month follow-up period.

Findings: The patient-level rates for poor medication continuity, treatment discontinuation and opioid overdose were 59.7% [95% confidence interval (CI) = 59.2-60.2], 57.4% (95% CI = 56.9-57.9) and 10.3% (95% CI = 10.0-10.6), respectively, with 1.1% (95% CI = 1.0-1.2) experiencing a fatal opioid overdose. At the patient level, after adjustment for covariates, adverse outcomes were associated with race/ethnicity as both Black, non-Hispanic and Hispanic patients had worse outcomes than did White, non-Hispanic patients (Black, non-Hispanic — poor continuity: 1.50, 95% CI = 1.34-1.68; discontinuation: 1.44, 95% CI = 1.30-1.60; Hispanic — poor continuity: 1.21, 95% CI = 1.12-1.31; discontinuation: 1.38, 95% CI = 1.28-1.48). Patients with insurance coverage through Medicaid also had worse outcomes than those with commercial insurance (poor continuity: 1.18, 95% CI = 1.11-1.26; discontinuation: 1.09, 95% CI = 1.03-1.16; overdose: 1.98, 95% CI = 1.75-2.23). Pre-treatment mental health conditions and other types of chronic illness were also associated with worse outcomes (History of mental health conditions — poor continuity: 1.11, 95% CI = 1.06-1.17; discontinuation: 1.05, CI = 1.01-1.10; overdose: 1.47, 95% CI = 1.36-1.60; Chronic health conditions — poor continuity: 1.15, 95% CI = 1.05-1.27; discontinuation: 1.15, 95% CI = 1.05-1.26; overdose: 1.83, 95% CI = 1.60-2.10; History of substance use disorder other than for opioids — poor continuity: 1.54, 95% CI = 1.46-1.62; discontinuation: 1.54, 95% CI = 1.47-1.62; overdose: 1.93, 95% CI = 1.80-2.07). At the prescriber level, after adjustments for covariates, adverse outcomes were associated with clinical training, as primary care physicians had higher rates of adverse outcomes than psychiatrists (poor continuity: 1.12, 95% CI = 1.02-1.23; discontinuation: 1.04, 95% CI = 1.01-1.09). A larger prescriber panel size, based on number of patients being prescribed buprenorphine, was also associated with higher rates of adverse outcomes (poor continuity: 1.36, 95% CI = 1.27-1.46; discontinuation: 1.21, 95% CI = 1.14-1.28; overdose: 1.10, 95% CI = 1.01-1.19). Between 9% and 15% of the variation among patients for the outcomes was accounted for at the prescriber level.

Conclusions: Patient- and prescriber-level characteristics appear to be associated with patient outcomes following buprenorphine treatment for opioid use disorder. In particular, patients’ race/ethnicity and insurance coverage appear to be associated with substantial disparities in outcomes, and prescriber characteristics appear to be most closely associated with medication continuity during early treatment.

To read the full text of the article, please visit the publisher’s website.