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BACKGROUND: Both increases and decreases in patients prescribed daily opioid dose have been linked to increased overdose risk, but associations between 30-day dose trajectories and subsequent overdose risk have not been systematically examined. OBJECTIVE: To examine the associations between 30-day prescribed opioid dose trajectories and fatal opioid overdose risk during the subsequent 15 days. DESIGN: Statewide cohort study using linked prescription drug monitoring program and death certificate data. We constructed a multivariable Cox proportional hazards model that accounted for time-varying prescription-, prescriber-, and pharmacy-level factors. PARTICIPANTS: All patients prescribed an opioid analgesic in California from March to December, 2013 (5,326,392 patients). MAIN MEASURES: Dependent variable: fatal drug overdose involving opioids. Primary independent variable: a 16-level variable denoting all possible opioid dose trajectories using the following categories for current and 30-day previously prescribed daily dose: 0-29, 30-59, 60-89, or ≥90 milligram morphine equivalents (MME). KEY RESULTS: Relative to patients prescribed a stable daily dose of 0-29 MME, large (≥2 categories) dose increases and having a previous or current dose ≥60 MME per day were associated with significantly greater 15-day overdose risk. Patients whose dose decreased from ≥90 to 0-29 MME per day had significantly greater overdose risk compared to both patients prescribed a stable daily dose of ≥90 MME (aHR 3.56, 95%CI 2.24-5.67) and to patients prescribed a stable daily dose of 0-29 MME (aHR 7.87, 95%CI 5.49-11.28). Patients prescribed benzodiazepines also had significantly greater overdose risk; being prescribed Z-drugs, carisoprodol, or psychostimulants was not associated with overdose risk. CONCLUSIONS: Large (≥2 categories) 30-day dose increases and decreases were both associated with increased risk of fatal opioid overdose, particularly for patients taking ≥90 MME whose opioids were abruptly stopped. Results align with 2022 CDC guidelines that urge caution when reducing opioid doses for patients taking long-term opioid for chronic pain.

A growing body of literature has documented high rates of adverse childhood experiences (ACEs) and their effects on behavioral health among adolescents impacted by the juvenile legal system. Most research with justice-impacted youth assesses the ten standard ACEs, encompassing abuse, neglect, and household dysfunction. This body of work has largely ignored the five expanded ACEs which assess social and community level adversity. Justice-impacted youth commonly experience expanded ACEs (racial discrimination, placement in foster care, living in a disadvantaged neighborhood, witnessing violence, bullying), and inclusion of these adversities may enhance predictive utility of the commonly used ACEs score. The current study examined the prospective impact of total ACEs (standard and expanded) on alcohol and cannabis use, substance-related consequences, and psychiatric symptoms during the year following first ever contact with the juvenile court. Results indicate justice-impacted youth experience multiple expanded ACEs prior to first court contact. The expanded ACEs did not predict any of the behavioral health outcomes assessed, over and above the standard ACEs. Inclusion of expanded ACEs in the standard ACEs score may not increase utility in identifying prospective behavioral health outcomes among youth in first time contact with the juvenile legal system.

BACKGROUND AND AIMS: Low outcome prevalence, often observed with opioid-related outcomes, poses an underappreciated challenge to accurate predictive modeling. Outcome class imbalance, where non-events (i.e. negative class observations) outnumber events (i.e. positive class observations) by a moderate to extreme degree, can distort measures of predictive accuracy in misleading ways, and make the overall predictive accuracy and the discriminatory ability of a predictive model appear spuriously high. We conducted a simulation study to measure the impact of outcome class imbalance on predictive performance of a simple SuperLearner ensemble model and suggest strategies for reducing that impact. DESIGN, SETTING, PARTICIPANTS: Using a Monte Carlo design with 250 repetitions, we trained and evaluated these models on four simulated data sets with 100 000 observations each: one with perfect balance between events and non-events, and three where non-events outnumbered events by an approximate factor of 10:1, 100:1, and 1000:1, respectively. MEASUREMENTS: We evaluated the performance of these models using a comprehensive suite of measures, including measures that are more appropriate for imbalanced data. FINDINGS: Increasing imbalance tended to spuriously improve overall accuracy (using a high threshold to classify events vs non-events, overall accuracy improved from 0.45 with perfect balance to 0.99 with the most severe outcome class imbalance), but diminished predictive performance was evident using other metrics (corresponding positive predictive value decreased from 0.99 to 0.14). CONCLUSION: Increasing reliance on algorithmic risk scores in consequential decision-making processes raises critical fairness and ethical concerns. This paper provides broad guidance for analytic strategies that clinical investigators can use to remedy the impacts of outcome class imbalance on risk prediction tools.

Justice-involved youth with clinically significant co-occurring psychiatric and substance-related problems are at increased risk for recidivism. Less is known about how psychiatric symptoms (i.e., internalizing and externalizing) and substance-related problems (i.e., alcohol and cannabis) interact to predict recidivism, especially at first court contact. Among 361 first-time justice-involved youth aged 12 to 18, we used nested multivariate negative binomial regression models to examine the association between psychiatric symptoms, substance-related problems and 24-month recidivism while accounting for demographic and legal covariates. Clinically significant externalizing symptoms and alcohol-related problems predicted recidivism. Moderation analyses revealed that alcohol-related problems drove recidivism for youth without clinically significant psychiatric symptoms and externalizing symptoms predicted recidivism, regardless of alcohol-related problems. After accounting for other predictors, Latinx, Black non-Latinx, and multiracial non-Latinx youth were more likely to recidivate at follow-up than White non-Latinx youth. Systematic screening, referral, and linkage to treatment for psychiatric and substance-related problems are needed to reduce recidivism risk among first-time justice-involved youth. Differences in recidivism rates by race/ethnicity not attributable to behavioral health needs suggest it is imperative to concurrently deploy large-scale structural interventions designed to combat systemic racial bias and overrepresentation of ethnoracial minoritized youth within the juvenile justice system.

Helping people with HIV (PWH) and without HIV (PWoH) understand the relationship between physical symptoms and alcohol use might help motivate them to decrease use. In surveys collected in the Veterans Aging Cohort Study from 2002 to 2018, PWH and PWoH were asked about 20 common symptoms and whether they thought any were caused by alcohol use. Analyses were restricted to current alcohol users (AUDIT-C > 0). We applied generalized estimating equations. The outcome was having any Symptoms Attributed to Alcohol use (SxAA). Primary independent variables were each of the 20 symptoms and HIV status. Compared to PWoH, PWH had increased odds of SxAA (OR 1.54; 95% CI 1.27, 1.88). Increased AUDIT-C score was also associated with SxAA (OR 1.32; 95% CI 1.28, 1.36), as were trouble remembering, anxiety, and weight loss/wasting. Evidence that specific symptoms are attributed to alcohol use may help motive people with and without HIV decrease their alcohol use.

Purpose We aimed to synthesize insights from systems science approaches applied to domestic and gender-based violence. Methods We conducted a systematic review of systems science studies (systems thinking, group model-building, agent-based modeling [ABM], system dynamics [SD] modeling, social network analysis [SNA], and network analysis [NA]) applied to domestic or gender-based violence, including victimization, perpetration, prevention, and community responses. We used blinded review to identify papers meeting our inclusion criteria (i.e., peer-reviewed journal article or published book chapter that described a systems science approach to domestic or gender-based violence, broadly defined) and assessed the quality and transparency of each study. Results Our search yielded 1,841 studies, and 74 studies met our inclusion criteria (45 SNA, 12 NA, 8 ABM, and 3 SD). Although research aims varied across study types, the included studies highlighted social network influences on risks for domestic violence, clustering of risk factors and violence experiences, and potential targets for intervention. We assessed the quality of the included studies as moderate, though only a minority adhered to best practices in model development and dissemination, including stakeholder engagement and sharing of model code. Conclusions Systems science approaches for the study of domestic and gender-based violence have shed light on the complex processes that characterize domestic violence and its broader context. Future research in this area should include greater dialogue between different types of systems science approaches, consideration of peer and family influences in the same models, and expanded use of best practices, including continued engagement of community stakeholders., Author(s): Melissa Tracy [sup.1] , Li Shen Chong [sup.2] , Kate Strully [sup.3] , Elana Gordis [sup.2] , Magdalena Cerdá [sup.4] , Brandon D. L. Marshall [sup.5] Author Affiliations: (1) [...]

BackgroundUnderstanding the sources of HIV transmission provides a basis for prioritizing HIV prevention resources in specific geographic regions and populations. This study estimated the number, proportion, and rate of HIV transmissions attributable to individuals along the HIV care continuum within different HIV transmission risk groups in 6 US cities.MethodsWe used a dynamic, compartmental HIV transmission model that draws on racial behavior-specific or ethnic behavior-specific and risk behavior-specific linkage to HIV care and use of HIV prevention services from local, state, and national surveillance sources. We estimated the rate and number of HIV transmissions attributable to individuals in the stage of acute undiagnosed HIV, nonacute undiagnosed HIV, HIV diagnosed but antiretroviral therapy (ART) naïve, off ART, and on ART, stratified by HIV transmission group for the 2019 calendar year.ResultsIndividuals with undiagnosed nonacute HIV infection accounted for the highest proportion of total transmissions in every city, ranging from 36.8% (26.7%-44.9%) in New York City to 64.9% (47.0%-71.6%) in Baltimore. Individuals who had discontinued ART contributed to the second highest percentage of total infections in 4 of 6 cities. Individuals with acute HIV had the highest transmission rate per 100 person-years, ranging from 76.4 (58.9-135.9) in Miami to 160.2 (85.7-302.8) in Baltimore.ConclusionThese findings underline the importance of both early diagnosis and improved ART retention for ending the HIV epidemic in the United States. Differences in the sources of transmission across cities indicate that localized priority setting to effectively address diverse microepidemics at different stages of epidemic control is necessary.

Constitutional mandates require access to medical testing and treatment in correctional settings, including sexual and reproductive health (SRH) care services. These same mandates do not apply to youth supervised in the community, who represent the majority of justice-involved youth. Waiting until youth are in detention settings to provide access to SRH services misses an opportunity to improve health outcomes for youth who have earlier points of contact with the system. This mixed-methods study explored structural intervention development and policy geared toward increasing access to and uptake of SRH prevention, treatment, care, and support services for court-involved, nonincarcerated (CINI) youth. Data were collected from a nationwide survey (N = 226) and qualitative interviews (N = 18) with juvenile justice (JJ) and public health (PH) system stakeholders between December 2015 and January 2017. Results suggest both PH and JJ stakeholders perceive CINI youth as having substantial, largely unmet SRH care needs due to a lack of services, policies, or procedures to address these needs. Barriers to implementing programs and policies to improve SRH services for this population include limited resources (e.g., staffing, time); perceived irrelevance for juvenile court, probation, or other community supervision settings; and concerns about confidentiality, privacy, and information sharing. Recommendations for effective intervention included colocating services, justice-to-community referrals, and service linkages (e.g., through a community health navigator), and staff education around youth SRH confidentiality and information-sharing practices. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Introduction: Urolithiasis causes severe acute pain and is commonly treated with opioid analgesics in the emergency department (ED). We examined opioid analgesic use after episodes of acute pain.  Methods: Using data from a longitudinal trial of ED patients with urolithiasis, we constructed multivariable models to estimate the adjusted probability of opioid analgesic use 3, 7, 30, and 90 days after ED discharge. We used multiple imputation to account for missing data and weighting to account for the propensity to be prescribed an opioid analgesic at ED discharge. We used weighted multivariable regression to compare longitudinal opioid analgesic use for those prescribed vs not prescribed an opioid analgesic at discharge, stratified by reported pain at ED discharge.  Results: Among 892 adult ED patients with urolithiasis, 79% were prescribed an opioid analgesic at ED discharge. Regardless of reporting pain at ED discharge, those who were prescribed an opioid analgesic were significantly more likely to report using it one, three, and seven days after the visit in weighted multivariable analysis. Among those who were not prescribed an opioid analgesic, an estimated 21% (not reporting pain at ED discharge) and 30% (reporting pain at discharge) reported opioid analgesic use at day three. Among those prescribed an opioid analgesic, 49% (no pain at discharge) and 52% (with pain at discharge) reported using an opioid analgesic at day three.  Conclusion: Urolithiasis patients who received an opioid analgesic at ED discharge were more likely to continue using an opioid analgesic than those who did not receive a prescription at the initial visit, despite the time-limited nature of urolithiasis.

BackgroundLimiting the incidence of opioid-naïve patients who transition to long-term opioid use (i.e., continual use for > 90 days) is a key strategy for reducing opioid-related harms.ObjectiveTo identify variables constructed from data routinely collected by prescription drug monitoring programs that are associated with opioid-naïve patients' likelihood of transitioning to long-term use after an initial opioid prescription.DesignStatewide cohort study using prescription drug monitoring program data PARTICIPANTS: All opioid-naïve patients in California (no opioid prescriptions within the prior 2 years) age ≥ 12 years prescribed an initial oral opioid analgesic from 2010 to 2017.Methods and main measuresMultiple logistic regression models using variables constructed from prescription drug monitoring program data through the day of each patient's initial opioid prescription, and, alternatively, data available up to 30 and 60 days after the initial prescription were constructed to identify probability of transition to long-term use. Model fit was determined by the area under the receiver operating characteristic curve (C-statistic).Key resultsAmong 30,569,125 episodes of patients receiving new opioid prescriptions, 1,809,750 (5.9%) resulted in long-term use. Variables with the highest adjusted odds ratios included concurrent benzodiazepine use, ≥ 2 unique prescribers, and receipt of non-pill, non-liquid formulations. C-statistics for the day 0, day 30, and day 60 models were 0.81, 0.88, and 0.94, respectively. Models assessing opioid dose using the number of pills prescribed had greater discriminative capacity than those using milligram morphine equivalents.ConclusionsData routinely collected by prescription drug monitoring programs can be used to identify patients who are likely to develop long-term use. Guidelines for new opioid prescriptions based on pill counts may be simpler and more clinically useful than guidelines based on days' supply or milligram morphine equivalents.

BackgroundTools are needed to aid clinicians in estimating their patients' risk of transitioning to long-term opioid use and to inform prescribing decisions.ObjectiveThe objective of this study was to develop and validate a model that predicts previously opioid-naive patients' risk of transitioning to long-term use.Research designThis was a statewide population-based prognostic study.SubjectsOpioid-naive (no prescriptions in previous 2 y) patients aged 12 years old and above who received a pill-form opioid analgesic in 2016-2018 and whose prescriptions were registered in the California Prescription Drug Monitoring Program (PDMP).MeasuresA multiple logistic regression approach was used to construct a prediction model with long-term (ie, >90 d) opioid use as the outcome. Models were developed using 2016-2017 data and validated using 2018 data. Discrimination (c-statistic), calibration (calibration slope, intercept, and visual inspection of calibration plots), and clinical utility (decision curve analysis) were evaluated to assess performance.ResultsDevelopment and validation cohorts included 7,175,885 and 2,788,837 opioid-naive patients with outcome rates of 5.0% and 4.7%, respectively. The model showed high discrimination (c-statistic: 0.904 for development, 0.913 for validation), was well-calibrated after intercept adjustment (intercept, -0.006; 95% confidence interval, -0.016 to 0.004; slope, 1.049; 95% confidence interval, 1.045-1.053), and had a net benefit over a wide range of probability thresholds.ConclusionsA model for the transition from opioid-naive status to long-term use had high discrimination and was well-calibrated. Given its high predictive performance, this model shows promise for future integration into PDMPs to aid clinicians in formulating opioid prescribing decisions at the point of care.

BackgroundSevere acute pain is still commonly treated with opioid analgesics in the United States, but this practice could prolong the duration of pain.ObjectivesEstimate the risk of experiencing persistent pain after opioid analgesic use after emergency department (ED) discharge among patients with suspected urolithiasis.MethodsWe analyzed data collected for a longitudinal, multicenter clinical trial of ED patients with suspected urolithiasis. We constructed multilevel models to estimate the odds ratios (ORs) of reporting pain at 3, 7, 30, or 90 days after ED discharge, using multiple imputation to account for missing outcome data. We controlled for clinical, demographic, and institutional factors and used weighting to account for the propensity to be prescribed an opioid analgesic at ED discharge.ResultsAmong 2413 adult ED patients with suspected urolithiasis, 62% reported persistent pain 3 days after discharge. Participants prescribed an opioid analgesic at discharge were OR 2.51 (95% confidence interval [CI] 1.82-3.46) more likely to report persistent pain than those without a prescription. Those who reported using opioid analgesics 3 days after discharge were OR 2.24 (95% CI 1.77-2.84) more likely to report pain at day 7 than those not using opioid analgesics at day 3, and those using opioid analgesics at day 30 had OR 3.25 (95% CI 1.96-5.40) greater odds of pain at day 90.ConclusionsOpioid analgesic prescription doubled the odds of persistent pain among ED patients with suspected urolithiasis. Limiting opioid analgesic prescribing at ED discharge for these patients might prevent persistent pain in addition to limiting access to these medications.

ContextSupervised injection facilities are harm reduction interventions that allow people who inject drugs to use previously obtained substances under the supervision of health professionals. Although currently considered illegal under U.S. federal law, several U.S. cities are considering implementing supervised injection facilities anyway as a response to the escalating overdose crisis. The objective of this review is to determine the effectiveness of supervised injection facilities, compared with that of control conditions, for harm reduction and community outcomes.Evidence acquisitionStudies were identified from 2 sources: a high-quality, broader review examining supervised injection facility-induced benefits and harms (from database inception to January 2014) and an updated search using the same search strategy (January 2014‒September 2019). Systematic review methods developed by the Guide to Community Preventive Services were used (screening and analysis, September 2019‒December 2020).Evidence synthesisA total of 22 studies were included in this review: 16 focused on 1 supervised injection facility in Vancouver, Canada. Quantitative synthesis was not conducted given inconsistent outcome measurement across the studies. Supervised injection facilities in the included studies (n=number of studies per outcome category) were mostly associated with significant reductions in opioid overdose morbidity and mortality (n=5), significant improvements in injection behaviors and harm reduction (n=7), significant improvements in access to addiction treatment programs (n=7), and no increase or reductions in crime and public nuisance (n=7).ConclusionsFor people who inject drugs, supervised injection facilities may reduce the risk of overdose morbidity and mortality and improve access to care while not increasing crime or public nuisance to the surrounding community.

BackgroundGirls have unique developmental pathways to substance use and justice system involvement, warranting gender-responsive intervention. We tested the efficacy of VOICES (a 12-session, weekly trauma-informed, gender-responsive substance use intervention) in reducing substance use and HIV/STI risk behaviors among justice- and school-referred girls.MethodsParticipants were 113 girls (Mage = 15.7 years, SD = 1.4; 12 % White, 19 % Black, 15 % multi-racial; 42 % Latinx) with a history of substance use referred from juvenile justice (29 %) and school systems (71 %). Study assessments were completed at baseline, 3-, 6- and 9-months follow-up. Primary outcomes included substance use and HIV/STI risk behaviors; secondary outcomes included psychiatric symptoms (including posttraumatic stress) and delinquent acts. We hypothesized that girls randomized to the VOICES (n = 51) versus GirlHealth (attention control; n = 62) condition would report reduced alcohol, cannabis and other substance use, HIV/STI risk behaviors, psychiatric symptoms, and delinquent acts.ResultsGirls randomized to VOICES reported significantly less cannabis use over 9-month follow-up relative to the control condition (time by intervention, p < .01), but there were no between group differences over time in HIV/STI risk behavior. Girls in both conditions reported fewer psychiatric symptoms and delinquent acts over time.ConclusionsData support the use of a trauma-informed, gender-responsive intervention to reduce cannabis use among girls with a substance use history and legal involvement; reducing cannabis use in this population has implications for preventing future justice involvement and improving public health outcomes for girls and young women, who are at disproportionate health and legal risk relative to their male counterparts.

ObjectiveCombination strategies generate health benefits through improved health outcomes among people living with HIV (PLHIV) and prevention of new infections. We aimed to determine health benefits attributable to improved health among PLHIV versus HIV prevention for a set of combination strategies in six US cities.DesignA dynamic HIV transmission model.MethodsUsing a model calibrated for Atlanta, Baltimore, Los Angeles, Miami, New York City (NYC) and Seattle, we assessed the health benefits of city-specific optimal combinations of evidence-based interventions implemented at publicly documented levels and at ideal (90% coverage) scale-up (2020-2030 implementation, 20-year study period). We calculated the proportion of health benefit gains (measured as quality-adjusted life-years) resulting from averted and delayed HIV infections; improved health outcomes among PLHIV; and improved health outcomes due to medication for opioid use disorder (MOUD).ResultsThe HIV-specific proportion of total benefits ranged from 68.3% (95% credible interval: 55.3-80.0) in Seattle to 98.5% (97.5-99.3) in Miami, with the rest attributable to MOUD. The majority of HIV-specific health benefits in five of six cities were attributable HIV prevention, and ranged from 33.1% (26.1-41.1) in NYC to 83.1% (79.6-86.6) in Atlanta. Scaling up to ideal service levels resulted in three to seven-fold increases in additional health benefits, mostly from MOUD, with HIV-specific health gains primarily driven by HIV prevention.ConclusionOptimal combination strategies generated a larger proportion of health benefits attributable to HIV prevention in five of six cities, underlining the substantial benefits of antiretroviral therapy engagement for the prevention of HIV transmission through viral suppression. Understanding to whom benefits accrue may be important in assessing the equity and impact of HIV investments.

We examined the effects of family functioning and beliefs regarding peers' cannabis use among minority (n = 112) and non-minority (n = 275) sexual orientation and gender identity (SOGI), first-time court-involved adolescents. We examined longitudinally the effects of baseline general family functioning and peer cannabis use beliefs on self-reported cannabis use and cannabis-related consequences after 12 months. At baseline, 39.2 percent of adolescents reported using cannabis. Minority SOGI adolescents reported worse family functioning (p = .017) and higher peer cannabis use beliefs (p = .047). Higher peer cannabis use beliefs at baseline predicted recent cannabis use at the 12-month assessment for both minority and non-minority SOGI adolescents. Better family functioning predicted a lower likelihood of recent cannabis use at 12 months for non-minority SOGI adolescents, but not for minority SOGI adolescents. Baseline peer cannabis use beliefs and family functioning predicted cannabis-related consequences for both cohorts at 12 months when accounting for intermediate (i.e., four-month and eight-month) data. Among all first-time court-involved adolescents, those who believed greater cannabis use among their peers reported more subsequent cannabis use themselves. Conversely, higher general family functioning may be less of a protective factor for minority SOGI adolescents. These results suggest the utility of feedback interventions to modify peer norm beliefs among first-time court-involved adolescents.

BackgroundIn the USA, Black and Hispanic or Latinx individuals continue to be disproportionately affected by HIV. Applying a distributional cost-effectiveness framework, we estimated the cost-effectiveness and epidemiological impact of two combination implementation approaches to identify the approach that best meets the dual objectives of improving population health and reducing racial or ethnic health disparities.MethodsWe adapted a dynamic, compartmental HIV transmission model to characterise HIV micro-epidemics in six US cities: Atlanta, Baltimore, Los Angeles, Miami, New York, and Seattle. We considered combinations of 16 evidence-based interventions to diagnose, treat, and prevent HIV transmission according to previously documented levels of scale-up. We then identified optimal combination strategies for each city, with the distribution of each intervention implemented according to existing service levels (proportional services approach) and the racial or ethnic distribution of new diagnoses (between Black, Hispanic or Latinx, and White or other ethnicity individuals; equity approach). We estimated total costs, quality-adjusted life-years (QALYs), and incremental cost-effectiveness ratios of strategies implemented from 2020 to 2030 (health-care perspective; 20-year time horizon; 3% annual discount rate). We estimated three measures of health inequality (between-group variance, index of disparity, Theil index), incidence rate ratios, and rate differences for the selected strategies under each approach.FindingsIn all cities, optimal combination strategies under the equity approach generated more QALYs than those with proportional services, ranging from a 3·1% increase (95% credible interval [CrI] 1·4-5·3) in New York to more than double (101·9% [75·4-134·6]) in Atlanta. Compared with proportional services, the equity approach delivered lower costs over 20 years in all cities except Los Angeles; cost reductions ranged from $22·9 million (95% CrI 5·3-55·7 million) in Seattle to $579·8 million (255·4-940·5 million) in Atlanta. The equity approach also reduced incidence disparities and health inequality measures in all cities except Los Angeles.InterpretationEquity-focused HIV combination implementation strategies that reduce disparities for Black and Hispanic or Latinx individuals can significantly improve population health, reduce costs, and drive progress towards Ending the HIV Epidemic goals in the USA.FundingNational Institute on Drug Abuse.

BackgroundJustice-involved youth use cannabis at higher rates than their same-aged peers increasing likelihood of adverse behavioral health consequences and continued legal involvement. This study examined individual level predictors of early onset use cannabis use (

OBJECTIVE: Justice-involved youth report high rates of adverse childhood experiences (ACEs; abuse, neglect, household dysfunction) and are at high risk for elevated behavioral health needs (i.e., substance use, psychiatric symptoms). Research with broad samples of adolescents shows ACEs predict behavioral health outcomes, yet most research on the impact of ACEs among justice-involved youth focuses on recidivism. The present study addresses this gap by examining the prospective association between ACEs and psychiatric symptoms, substance use, and substance-related problems (i.e., consequences of use) among first-time justice-involved youth. METHOD: First-time justice-involved youth (n = 271; 54.3% male; M age = 14.5 years; 43.5% Latinx; non-Latinx: 34.2% White, 8.6% Black, 7.1% Other, 6.7% Multiracial) and their caregivers were assessed at youths first court contact and 4- and 12-month follow-ups. Youth and caregivers reported youths exposure to ACEs through a series of instruments at baseline and 4-months (e.g., Childhood Trauma Questionnaire Short-Form; Traumatic Life Events Inventory). Primary outcomes included youth alcohol and cannabis use (Adolescent Risk Behavior Assessment), consequences of use (Brief Young Adult Alcohol Consequences Questionnaire; Brief Marijuana Consequences Scale), and psychiatric symptoms (Behavior Assessment System for Children; National Stressful Events Survey PTSD Short Scale). RESULTS: Youth were exposed to three ACEs, on average, prior to first justice contact (M = 3). Exposure to more ACEs, particularly abuse, predicted substance use and psychiatric outcomes. Gender differences emerged for cannabis use and internalizing symptoms. CONCLUSIONS: Implications for trauma-responsive juvenile justice reform are discussed, including screening for ACEs and their sequelae at first court contact and considering the role of masculine norms. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

BackgroundWidespread viral and serological testing for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) may present a unique opportunity to also test for human immunodeficiency virus (HIV) infection. We estimated the potential impact of adding linked, opt-out HIV testing alongside SARS-CoV-2 testing on the HIV incidence and the cost-effectiveness of this strategy in 6 US cities.MethodsUsing a previously calibrated dynamic HIV transmission model, we constructed 3 sets of scenarios for each city: (1) sustained current levels of HIV-related treatment and prevention services (status quo); (2) temporary disruptions in health services and changes in sexual and injection risk behaviors at discrete levels between 0%-50%; and (3) linked HIV and SARS-CoV-2 testing offered to 10%-90% of the adult population in addition to Scenario 2. We estimated the cumulative number of HIV infections between 2020-2025 and the incremental cost-effectiveness ratios of linked HIV testing over 20 years.ResultsIn the absence of linked, opt-out HIV testing, we estimated a total of a 16.5% decrease in HIV infections between 2020-2025 in the best-case scenario (50% reduction in risk behaviors and no service disruptions), and a 9.0% increase in the worst-case scenario (no behavioral change and 50% reduction in service access). We estimated that HIV testing (offered at 10%-90% levels) could avert a total of 576-7225 (1.6%-17.2%) new infections. The intervention would require an initial investment of $20.6M-$220.7M across cities; however, the intervention would ultimately result in savings in health-care costs in each city.ConclusionsA campaign in which HIV testing is linked with SARS-CoV-2 testing could substantially reduce the HIV incidence and reduce direct and indirect health care costs attributable to HIV.

BackgroundThe estimated 2.2 million people who inject drugs (PWID) in the USA experience significant gaps in preventive healthcare and a high burden of infectious, psychiatric, and other chronic diseases. Many PWID rely on emergency medical services, which are costly and not designed to deliver preventive services, manage chronic conditions, or address social needs.ObjectiveThe objective of this study was to explore barriers and facilitators to primary care utilization from the perspectives of PWID in New England, a region highly affected by the overdose crisis.DesignParticipants completed semi-structured qualitative interviews exploring substance use and healthcare utilization patterns.ParticipantsWe recruited 78 PWID through community-based organizations (e.g., syringe service programs) in 16 urban and non-urban communities throughout Massachusetts and Rhode Island.ApproachThematic analysis identified barriers and facilitators to primary care utilization at the individual, interpersonal, and systemic levels.Key resultsAmong 78 PWID, 48 described recent primary care experiences; 33 had positive experiences and 15 described negative experiences involving discrimination or mistrust. Individual-level barriers to primary care utilization included perceived lack of need and competing priorities (e.g., avoiding opioid withdrawal, securing shelter beds). Interpersonal-level barriers included stigma and perceived low quality of care for PWID. Systemic-level barriers included difficulty navigating healthcare systems, inadequate transportation, long wait times, and frequent provider turnover. Participants with positive primary care experiences explained how appointment reminders, flexible hours, addiction medicine-trained providers, case management services, and transportation support facilitated primary care utilization and satisfaction.ConclusionsFindings regarding the multilevel barriers and facilitators to accessing primary care among PWID identify potential targets for programmatic interventions to improve primary care utilization in this population. Based on these findings, we make recommendations for improving the engagement of PWID in primary care as a means to advance individual and public health outcomes.

Alcohol use increases non-adherence to antiretroviral therapy (ART) among persons living with HIV (PLWH). Dynamic longitudinal associations are understudied. Veterans Aging Cohort Study (VACS) data 2/1/2008-7/31/16 were used to fit linear regression models estimating changes in adherence (% days with ART medication fill) associated with changes in alcohol use based on annual clinically-ascertained AUDIT-C screening scores (range - 12 to + 12, 0 = no change) adjusting for demographics and initial adherence. Among 21,275 PLWH (67,330 observations), most reported no (48%) or low-level (39%) alcohol use initially, with no (55%) or small (39% ≤ 3 points) annual change. Mean initial adherence was 86% (SD 21%), mean annual change was - 3.1% (SD 21%). An inverted V-shaped association was observed: both increases and decreases in AUDIT-C were associated with greater adherence decreases relative to stable scores [p

We estimated human immunodeficiency virus incidence and incidence rate ratios (IRRs) for black and Hispanic vs white populations in 6 cities in the United States (2020-2030). Large reductions in incidence are possible, but without elimination of disparities in healthcare access, we found that wide disparities persisted for black compared with white populations in particular (lowest IRR, 1.69 [95% credible interval, 1.19-2.30]).

: Using a dynamic HIV transmission model calibrated for six USA cities, we projected HIV incidence from 2020 to 2040 and estimated whether an established UNAIDS HIV epidemic control target could be met under ideal implementation of optimal combination strategies previously defined for each city. Four of six cities (Atlanta, Baltimore, New York City and Seattle) were projected to achieve epidemic control by 2040 and we identified differences in reaching epidemic control across racial/ethnic groups.