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The effectiveness of a third mRNA COVID-19 vaccine dose (booster dose) against the Omicron (B.1.1.529) variant is uncertain, especially in older, high-risk populations.To determine mRNA booster vaccine effectiveness (VE) against SARS-CoV-2 infection, hospitalization, and death in the Omicron era by booster type, primary vaccine type, time since primary vaccination, age, and comorbidity burden.Retrospective matched cohort study designed to emulate a target trial of booster vaccination versus no booster, conducted from 1 December 2021 to 31 March 2022.U.S. Department of Veterans Affairs health care system.Persons who had received 2 mRNA COVID-19 vaccine doses at least 5 months earlier.Booster monovalent mRNA vaccination (Pfizer-BioNTech's BNT162b2 or Moderna's mRNA-1273) versus no booster.Booster VE.Each group included 490 838 well-matched persons, who were predominantly male (88%), had a mean age of 63.0 years (SD, 14.0), and were followed for up to 121 days (mean, 79.8 days). Booster VE more than 10 days after a booster dose was 42.3% (95% CI, 40.6% to 43.9%) against SARS-CoV-2 infection, 53.3% (CI, 48.1% to 58.0%) against SARS-CoV-2-related hospitalization, and 79.1% (CI, 71.2% to 84.9%) against SARS-CoV-2-related death. Booster VE was similar for different booster types (BNT162b2 or mRNA-1273), age groups, and primary vaccination regimens but was significantly higher with longer time since primary vaccination and higher comorbidity burden.Predominantly male population.Booster mRNA vaccination was highly effective in preventing death and moderately effective in preventing infection and hospitalization for up to 4 months after administration in the Omicron era. Increased uptake of booster vaccination, which is currently suboptimal, should be pursued to limit the morbidity and mortality of SARS-CoV-2 infection, especially in persons with high comorbidity burden.U.S. Department of Veterans Affairs.

Background Drug overdose (OD) deaths in the U.S. continue to rise. After opioids, benzodiazepines (BZD) are the medication most commonly involved in prescription overdoses, yet OD risk factors among those prescribed BZD are not well understood. Our objective was to examine characteristics of BZD, opioid, and other psychotropic prescriptions associated with increased drug OD risk following a BZD prescription. Methods We completed a retrospective cohort study using a 20% sample of Medicare beneficiaries with prescription drug coverage. We identified patients with a BZD prescription (“index”) claim between 1 April 2016 and 31 December 2017. In the 6 months pre-index, those without and with BZD claims comprised incident and continuing cohorts, which were split by age (incident n = 105,737], 65 + [n = 385,951]; continuing n = 240,358], 65 + [n = 508,230]). Exposures of interest were: average daily dose and days prescribed of the index BZD; baseline BZD medication possession ratio (MPR) for the continuing cohort; co-prescribed opioids and psychotropics. Our primary outcome was a treated drug OD event (including accidental, intentional, undetermined, or adverse effect) within 30 days of the index BZD, examined using Cox proportional hazards. Results Among incident and continuing BZD cohorts, 0.78% and 0.56% experienced an OD event. Compared to 14–30 days, a Conclusions In both the incident and continuing cohorts, patients dispensed fewer days' supply were at increased OD risk; those in the continuing cohort with more limited baseline BZD exposure were also at elevated risk. Concurrent medication exposures including opioids, antipsychotics, and antiepileptics were associated with short-term elevated OD risk.

BACKGROUND: High-intensity drinking (HID; 8+ U.S. standard drinks for women, 10+ men) is initiated during adolescence/emerging adulthood, increasing risk for negative outcomes, including blackouts. We examined baseline data from a study of risky drinking youth to identify factors associated with HID. METHODS: Risky drinkers (ages 16-24) were recruited online (positive 3-month AUDIT-C score) as part of a larger study to examine social media interventions for risky drinking. We used baseline survey data to examine HID in relation to demographics, substance use-related variables, and individual and social factors. RESULTS: Among 931 risky drinkers, 29.8% reported past-month HID, and those with HID reported greater substance use and consequences. In multivariable analysis, HID was associated with male sex; greater social motives, impulsivity, and motivation; lower self-efficacy; and greater likelihood of not living with parents, drinking with important peers, and parental disapproval of posting drinking pictures. When examining age group interactions (16-20; 21-24), underage drinkers with high sensation seeking scores and lower parental disapproval of posting drinking pictures on social media reported greater HID. CONCLUSIONS: Among risky drinking youth, male sex, social motives, impulsivity, higher motivation to and lower-self-efficacy to reduce drinking, living away from parents, more frequent drinking with important peers, and lower parental disapproval of posting drinking pictures on social media were positively associated with HID. Further, HID was associated with greater health consequences, underscoring the need for HID interventions. Such interventions may benefit from enhancing motivation and self-efficacy, particularly in social contexts, as well as increasing positive peer and leisure activities to reduce HID.

Background Avoiding use of opioids while alone reduces overdose fatality risk; however, drug use-related stigma may be a barrier to consistently using opioids in the presence of others. Methods We described the frequency of using opioids while alone among 241 people reporting daily heroin use or non-prescribed use of opioid analgesic medications (OAMs) in the month before attending a substance use disorder treatment program in the Midwestern USA. We investigated drug use-related stigma as a correlate of using opioids while alone frequently (very often vs. less frequently or never) and examined overdose risk behaviors associated with using opioids while alone frequently, adjusted for sociodemographic and clinical characteristics. Results The sample was a median age of 30 years, 34% female, 79% white, and nearly all (91%) had experienced an overdose. Approximately 63% had used OAMs and 70% used heroin while alone very often in the month before treatment. High levels of anticipated stigma were associated with using either opioid while alone very often (adjusted PR: 1.20, 95% CI: 1.04–1.38). Drinking alcohol and taking sedatives within two hours of OAMs very often (vs. less often or never) and using OAMs in a new setting very often (vs. less often or never) were associated with using OAMs while alone very often. Taking sedatives within two hours of using heroin and using heroin in a new setting very often (vs. less often or never) were associated with using heroin while alone very often. Conclusion Anticipated stigma, polysubstance use, and use in a new setting were associated with using opioids while alone. These findings highlight a need for enhanced overdose harm reduction options, such as overdose detection services that can initiate an overdose response if needed. Addressing stigmatizing behaviors in communities may reduce anticipated stigma and support engagement and trust in these services.

There is increasing recognition of the long-term health effects of SARS-CoV-2 infection (sometimes called long COVID). However, little is yet known about the clinical diagnosis and management of long COVID within health systems.To describe dominant themes pertaining to the clinical diagnosis and management of long COVID in the electronic health records (EHRs) of patients with a diagnostic code for this condition (International Statistical Classification of Diseases and Related Health Problems, Tenth Revision [ICD-10] code U09.9).This qualitative analysis used data from EHRs of a national random sample of 200 patients receiving care in the Department of Veterans Affairs (VA) with documentation of a positive result on a polymerase chain reaction (PCR) test for SARS-CoV-2 between February 27, 2020, and December 31, 2021, and an ICD-10 diagnostic code for long COVID between October 1, 2021, when the code was implemented, and March 1, 2022. Data were analyzed from February 5 to May 31, 2022.A text word search and qualitative analysis of patients' VA-wide EHRs was performed to identify dominant themes pertaining to the clinical diagnosis and management of long COVID.In this qualitative analysis of documentation in the VA-wide EHR, the mean (SD) age of the 200 sampled patients at the time of their first positive PCR test result for SARS-CoV-2 in VA records was 60 (14.5) years. The sample included 173 (86.5%) men; 45 individuals (22.5%) were identified as Black and 136 individuals (68.0%) were identified as White. In qualitative analysis of documentation pertaining to long COVID in patients' EHRs 2 dominant themes were identified: (1) clinical uncertainty, in that it was often unclear whether particular symptoms could be attributed to long COVID, given the medical complexity and functional limitations of many patients and absence of specific markers for this condition, which could lead to ongoing monitoring, diagnostic testing, and specialist referral; and (2) care fragmentation, describing how post-COVID-19 care processes were often siloed from and poorly coordinated with other aspects of care and could be burdensome to patients.This qualitative study of documentation in the VA EHR highlights the complexity of diagnosing long COVID in clinical settings and the challenges of caring for patients who have or are suspected of having this condition.

Public health surveillance for overdose sometimes depends on nonfatal drug overdoses recorded in health records. However, the proportion of total overdoses identified through health record systems is unclear. Comparison of overdoses from health records to those that are self-reported may provide insight on the proportion of nonfatal overdoses that are not identified.We conducted a cohort study linking survey data on overdose from a national survey of Veterans to United States Department of Veterans Affairs (VA) health records, including community care paid for by VA. Self-reported overdose in the prior 3 years was compared to diagnostic codes for overdoses and substance use disorders in the same time period.The sensitivity of diagnostic codes for overdose, compared to self-report as a reference standard for this analysis, varied by substance: 28.1% for alcohol, 23.1% for sedatives, 12.0% for opioids, and 5.5% for cocaine. There was a notable concordance between substance use disorder diagnoses and self-reported overdose (sensitivity range 17.9%-90.6%).Diagnostic codes in health records may not identify a substantial proportion of drug overdoses. A health record diagnosis of substance use disorder may offer a stronger inference regarding the size of the population at risk. Alternatively, screening for self-reported overdose in routine clinical care could enhance overdose surveillance and targeted intervention.This study suggests that diagnostic codes for overdose are insensitive. These findings support consideration of alternative approaches to overdose surveillance in public health.

Some persons infected with SARS-CoV-2 experience symptoms or impairments many months after acute infection.To determine the rates, clinical setting, and factors associated with documented receipt of COVID-19-related care 3 or more months after acute infection.This retrospective cohort study used data from the US Department of Veterans Affairs health care system. Participants included persons with a positive SARS-CoV-2 test between February 1, 2020, and April 30, 2021, who were still alive 3 months after infection and did not have evidence of reinfection. Data analysis was performed from February 2020 to December 2021.Positive SARS-CoV-2 test.Rates and factors associated with documentation of COVID-19-related International Statistical Classification of Diseases and Related Health Problems, Tenth Revision codes (U07.1, Z86.16, U09.9, and J12.82) 3 or more months after acute infection (hereafter, long-COVID care), with follow-up extending to December 31, 2021.Among 198 601 SARS-CoV-2-positive persons included in the study, the mean (SD) age was 60.4 (17.7) years, 176 942 individuals (89.1%) were male, 133 924 (67.4%) were White, 44 733 (22.5%) were Black, and 19 735 (9.9%) were Hispanic. During a mean (SD) follow-up of 13.5 (3.6) months, long-COVID care was documented in a wide variety of clinics, most commonly primary care and general internal medicine (18 634 of 56 310 encounters [33.1%]), pulmonary (7360 of 56 310 encounters [13.1%]), and geriatrics (5454 of 56 310 encounters [9.7%]). Long-COVID care was documented in 26 745 cohort members (13.5%), with great variability across geographical regions (range, 10.8%-18.1%) and medical centers (range, 3.0%-41.0%). Factors significantly associated with documented long-COVID care included older age, Black or American Indian/Alaska Native race, Hispanic ethnicity, geographical region, high Charlson Comorbidity Index score, having documented symptoms at the time of acute infection (adjusted odds ratio [AOR], 1.71; 95% CI, 1.65-1.78) and requiring hospitalization (AOR, 2.60; 95% CI, 2.51-2.69) or mechanical ventilation (AOR, 2.46; 95% CI, 2.26-2.69). Patients who were fully vaccinated at the time of infection were less likely to receive long-COVID care (AOR, 0.78; 95% CI, 0.68-0.90).Long-COVID care was documented in a variety of clinical settings, with great variability across regions and medical centers and was documented more commonly in older persons, those with higher comorbidity burden, those with more severe acute COVID-19 presentation and those who were unvaccinated at the time of infection. These findings provide support and guidance for health care systems to develop systematic approaches to the evaluation and management of patients who may be experiencing long COVID.

In 2016, the Centers for Disease Control and Prevention (CDC) released the evidence-based Guideline for Prescribing Opioids for Chronic Pain. How the release of this guideline coincided with changes in nonopioid pain medication prescribing rates remains unknown.To evaluate changes in nonopioid pain medication prescribing after the 2016 CDC guideline release and to assess the heterogeneity in these changes as a function of patient demographic and clinical characteristics.This cohort study constructed 7 (4 preguideline and 3 postguideline) annual cohorts using claims data from the national Optum Clinformatics Data Mart Database for the period January 1, 2011, through December 31, 2018. The cohorts included adults with commercial insurance, no cancer or palliative care claims, and 2 years of continuous insurance enrollment. Individuals could qualify for inclusion in multiple cohorts. Each cohort covered a 2-year period, with year 1 as the baseline period used to calculate opioid exposure and other clinical characteristics and year 2 as the follow-up period used to calculate prescribing outcomes. Data were analyzed in March 2022.The CDC guideline, which was released in March 2016.The primary outcome was receipt of any nonopioid pain medication prescriptions (analgesics or antipyretics, anticonvulsants, antidepressants, and nonsteroidal anti-inflammatory drugs) during the follow-up period. This postguideline prescribing pattern was compared with estimates based on the preguideline prescribing pattern, and then the differences were stratified by patient clinical characteristics (chronic pain, recent opioid exposure, substance use disorder, anxiety disorder, and mood disorder).A total of 15 879 241 individuals (2015 mean [SD] age, 50.2 [18.6] years; 8 298 271 female patients [52.3%]) qualified for inclusion in 1 or more cohorts. Logistic regression models showed that nonopioid pain medication prescribing odds were higher by 3.0% (95% CI, 2.6%-3.3%) in postguideline year 1, by 8.7% (95% CI, 8.3%-9.2%) in postguideline year 2, and by 9.7% (95% CI, 9.2%-10.3%) in postguideline year 3 than the preguideline pattern-based estimates. The magnitude of the postguideline departures from the preguideline pattern varied by several clinical characteristics (chronic pain, recent opioid exposure, anxiety disorder, and mood disorder). The largest departure was found among those with chronic pain, with postguideline prescribing being higher than estimated in postguideline year 2 (13.6%; 95% CI, 12.7%-14.6%) and postguideline year 3 (14.9%; 95% CI, 13.8%-16.0%).Results of this study showed increases in nonopioid pain medication prescribing after the release of the 2016 CDC guideline, suggesting that the guideline may be associated with an increase in guideline-concordant care, but additional studies are needed to understand the role of other secular changes in the opioid policy landscape and other sources of nonopioid medication use.

PURPOSE: Unlike in many community-based settings, benzodiazepine (BZD) prescribing to older veterans has decreased. We sought to identify health care system strategies associated with greater facility-level reductions in BZD prescribing to older adults. METHODS: We completed an explanatory sequential mixed methods study of health care facilities in the Veterans Health Administration (N = 140). Among veterans aged ≥75 years receiving long-term BZD treatment, we stratified facilities into relatively high and low performance on the basis of the reduction in average daily dose of prescribed BZD from October 1, 2015 to June 30, 2017. We then interviewed key facility informants (n = 21) who led local BZD reduction efforts (champions), representing 11 high-performing and 6 low-performing facilities. RESULTS: Across all facilities, the age-adjusted facility-level average daily dose in October 2015 began at 1.34 lorazepam-equivalent mg/d (SD 0.17); the average rate of decrease was −0.27 mg/d (SD 0.09) per year. All facilities interviewed, regardless of performance, used passive strategies primarily consisting of education regarding appropriate prescribing, alternatives, and identifying potential patients for discontinuation. In contrast, champions at high-performing facilities described leveraging ≥1 active strategies that included individualized recommendations, administrative barriers to prescribing, and performance measures to incentivize clinicians. CONCLUSIONS: Initiatives to reduce BZD prescribing to older adults that are primarily limited to passive strategies, such as education and patient identification, might have limited success. Clinicians might benefit from additional recommendations, support, and incentives to modify prescribing practices.

OBJECTIVE: To evaluate whether pain management clinic laws and prescription drug monitoring program (PDMP) prescriber check mandates, two state opioid policies with relatively rapid adoption across states, reduced opioid dispensing more or less in Black versus White patients. DATA SOURCES: Pharmacy claims data, US sample of commercially insured adults, 2007–2018. STUDY DESIGN: Stratifying by race, we used generalized estimating equations with an event‐study specification to estimate time‐varying effects of each policy on opioid dispensing, comparing to the four pre‐policy quarters and states without the policy. Outcomes included high‐dosage opioids, overlapping opioid prescriptions, concurrent opioid/benzodiazepines, opioids from >3 prescribers, opioids from >3 pharmacies. DATA EXTRACTION METHODS: We identified all prescription opioid dispensing to Black and White adults aged 18–64 without a palliative care or cancer diagnosis code. PRINCIPAL FINDINGS: Exactly 7,096,592 White and 1,167,310 Black individuals met inclusion criteria. Pain management clinic laws were associated with reductions in two outcomes; their association with high‐dosage receipt was larger among White patients. In contrast, reductions due to PDMP mandates appeared limited to, or larger in, Black patients compared with White patients in four of five outcomes. For example, PDMP mandates reduced high‐dosage receipt in Black patients by 0.7 percentage points (95% CI: 0.36–1.08 ppt.) over 4 years: an 8.4% decrease from baseline; there was no apparent effect in White patients. Similarly, while there was limited evidence that mandates reduced overlapping opioid receipt in White patients, they appeared to reduce overlapping opioid receipt in Black patients by 1.3 ppt. (95% CI: −1.66–−1.01 ppt.) across post‐policy years—a 14.4% decrease from baseline. CONCLUSIONS: PDMP prescriber check mandates but not pain management clinic laws appeared to reduce opioid dispensing more in Black patients than White patients. Future research should discern the mechanisms underlying these disparities and their consequences for pain management.

Background Androgen deprivation therapy (ADT) use is associated with an increased risk of developing depression and anxiety. Little is known about how the mental health of these men is treated. Materials and Methods We identified men with prostate cancer who received ADT between 2001 and 2015 using Optum’s de-identified Clinformatics Data Mart Database. We determined the incidence of depression or anxiety diagnoses, mental health treatments, and the specialty of providers initiating psychotropic medications, after the start of ADT. Outcomes were compared with those of men with prostate cancer not receiving ADT and men without prostate cancer. Results Of 37 388 men with prostate cancer treated with ADT, 3964 (10.6%) received a new diagnosis of depression or anxiety. Of those 3964 men, 1892 (47.7%) did not receive a documented treatment, 10 (0.3%) received psychotherapy, 1321 (33.3%) a selective serotonin reuptake inhibitor, and 744 (18.8%) a benzodiazepine. The median time from initiation of ADT to a depression or anxiety diagnosis was 9.3 months. Primary care physicians were the most common prescribers of psychotropic medications (72.2%). The proportion of men not receiving mental health treatments of interest (47.7%) was similar compared to men without prostate cancer (49.1%), but statistically significantly lower compared to men with prostate cancer not receiving ADT (52.7%). Conclusions In men with prostate cancer receiving ADT with a new diagnosis of depression or anxiety, nearly half are not receiving mental health care while one in five is introduced to a benzodiazepine. Further investigation toward improving the mental health care for men on ADT is needed.

Opioid dosage tapering has emerged as a strategy to reduce harms associated with long-term opioid therapy; however, evidence supporting this approach is limited.To identify the association of opioid tapering or abrupt discontinuation with opioid overdose and suicide events among patients receiving stable long-term opioid therapy without evidence of opioid misuse.This comparative effectiveness study with a trial emulation approach used a large US claims data set of individuals with commercial insurance or Medicare Advantage who were aged 18 years or older and receiving stable long-term opioid therapy without evidence of opioid misuse between January 1, 2010, and December 31, 2018. Statistical analysis was performed from January 17, 2020, through November 12, 2021.Three opioid dosage strategies: stable dosage, tapering (dosage reduction ≥15%), or abrupt discontinuation.Time to opioid overdose or suicide event identified from International Classification of Diseases, Ninth Revision and International Statistical Classification of Diseases and Related Health Problems, Tenth Revision diagnosis codes in medical claims over 11 months of follow-up. Inverse probability weighting was used to adjust for baseline confounders. The primary analysis used an intention-to-treat approach; follow-up after assignment regardless of changes in opioid dose was included. A per-protocol analysis was also conducted, in which episodes were censored for lack of adherence to assigned treatment.A cohort of 199 836 individuals (45.1% men; mean [SD] age, 56.9 [12.4] years; and 57.6% aged 45-64 years) had 415 123 qualifying, long-term opioid therapy episodes; 87.1% of episodes were considered stable, 11.1% were considered a taper, and 1.8% were considered abrupt discontinuation. The adjusted cumulative incidence of opioid overdose or suicide events 11 months after baseline was 0.96% (95% CI, 0.92%-0.99%) with a stable dosage strategy, 1.10% (95% CI, 0.99%-1.22%) with a tapered dosage strategy, and 1.28% (95% CI, 0.93%-1.38%) with an abrupt discontinuation strategy. The risk difference between a taper and a stable dosage was 0.15% (95% CI, 0.03%-0.26%), and the risk difference between abrupt discontinuation and a stable dosage was 0.33% (95% CI, -0.03% to 0.74%). Results were similar using the per-protocol approach.This study identified a small absolute increase in risk of harms associated with opioid tapering compared with a stable opioid dosage. These results do not suggest that policies of mandatory dosage tapering for individuals receiving a stable long-term opioid dosage without evidence of opioid misuse will reduce short-term harm via suicide and overdose.

Background and Objectives We examined use of non-pharmacological treatments for pain in addiction treatment patients. Methods Patients in addiction treatment with chronic pain (N = 501) were classified based on use of non-pharmacological pain treatments. Demographic and clinical correlates were compared. Results A total of 49% (N = 243) of patients used a non-pharmacological treatment in the past year versus 72% (N = 361) who used opioids. Non-pharmacological treatment users were more likely to use opioids and other pain medications. Conclusions Non-pharmacological treatments are less commonly used than opioids by addiction treatment patients. Scientific Significance Findings highlight the need to better understand pain treatment decision-making among addiction treatment patients. (Am J Addict 2017;26:564–567)

Background: Suicides by any method, plus ‘nonsuicide’ fatalities from drug self-intoxication (estimated from selected forensically undetermined and ‘accidental’ deaths), together represent self-injury mortality (SIM)—fatalities due to mental disorders or distress. SIM is especially important to examine given frequent undercounting of suicides amongst drug overdose deaths. We report suicide and SIM trends in the United States of America (US) during 1999–2018, portray interstate rate trends, and examine spatiotemporal (spacetime) diffusion or spread of the drug self-intoxication component of SIM, with attention to potential for differential suicide misclassification. Methods: For this state-based, cross-sectional, panel time series, we used de-identified manner and underlying cause-of-death data for the 50 states and District of Columbia (DC) from CDC's Wide-ranging Online Data for Epidemiologic Research. Procedures comprised joinpoint regression to describe national trends; Spearman's rank-order correlation coefficient to assess interstate SIM and suicide rate congruence; and spacetime hierarchical modelling of the ‘nonsuicide’ SIM component. Findings: The national annual average percentage change over the observation period in the SIM rate was 4.3% (95% CI: 3.3%, 5.4%; p6.0% increase (p

The present clinical case discussion focuses on a patient with comorbid substance use disorder (SUD) and chronic pain, who experienced an overdose of heroin. The case illustrates the complex array of risk factors that contribute to overdose risk, discusses the use of naloxone, and highlights the need for further risk mitigation interventions in patients at risk for overdose.

We examined use of non-pharmacological treatments for pain in addiction treatment patients.Patients in addiction treatment with chronic pain (N = 501) were classified based on use of non-pharmacological pain treatments. Demographic and clinical correlates were compared.A total of 49% (N = 243) of patients used a non-pharmacological treatment in the past year versus 72% (N = 361) who used opioids. Non-pharmacological treatment users were more likely to use opioids and other pain medications.Non-pharmacological treatments are less commonly used than opioids by addiction treatment patients.Findings highlight the need to better understand pain treatment decision-making among addiction treatment patients. (Am J Addict 2017;26:564-567).

To examine efficacy of drug brief interventions (BIs) among adults presenting to a low-income urban emergency department (ED).Randomized controlled trial on drug use outcomes at 3, 6 and 12 months. Participants were assigned to (1) computer-delivered BI (Computer BI), (2) therapist-delivered, computer-guided BI (Therapist BI) or (3) enhanced usual care (EUC-ED) for drug-using adults. Participants were re-randomized after the 3-month assessment to either adapted motivational enhancement therapy (AMET) booster or enhanced usual care booster (EUC-B).Patients recruited from low-income urban emergency departments (ED) in Flint, Michigan, USA.A total of 780 ED patients reporting recent drug use, 44% males, mean age = 31 years.Computer BI consisted of an interactive program guided by a virtual health counselor. Therapist BI included computer guidance. The EUC-ED conditions included review of community health and HIV prevention resources. The BIs and boosters were based on motivational interviewing, focusing on reduction of drug use and HIV risk behaviors.Primary outcome was past 90 days using drugs at 6 and 12 months and secondary outcomes were weighted drug-days and days of marijuana use.Percentage changes in mean days used any drug from baseline to 12 months were: Computer BI + EUC-B: -10.9%, P = 0.0844; Therapist BI + EUC-B: -26.7%, P = 0.0041, for EUC-ED + EUC-B: -20.9, P = 0.0011. In adjusted analyses, there was no significant interaction between ED intervention and booster AMET for primary and secondary outcomes. Compared with EUC-ED, Therapist BI reduced number of days using any drug [95% confidence interval (CI) = -0.41, -0.07, P = 0.0422] and weighted drug-days (95% CI = -0.41, -0.08, P = 0.0283). Both Therapist and Computer BI had significantly fewer number of days using marijuana compared to EUC-ED (Therapist BI: 95% CI = -0.42, -0.06, P = 0.0104, Computer BI: 95% CI = -0.34, -0.01, P = 0.0406). Booster effects were not significant.An emergency department-based motivational brief intervention, delivered by a therapist and guided by computer, appears to reduce drug use among adults seeking emergency department care compared with enhanced usual care.

HIV-seropositive, active injection-drug users (IDUs), compared with other HIV populations, continue to have low rates of highly active antiretroviral therapy (HAART) use, contributing to disparities in their HIV health outcomes. We sought to identify individual-level, interpersonal, and structural factors associated with HAART use among active IDUs to inform comprehensive, contextually tailored intervention to improve the HAART use of IDUs. Prospective data from three semiannual assessments were combined, and logistic general estimating equations were used to identify variables associated with taking HAART 6 months later. Participants were a community sample of HIV-seropositive, active IDUs enrolled in the INSPIRE study, a U.S. multisite (Baltimore, Miami, New York, San Francisco) prevention intervention. The analytic sample included 1,225 observations, and comprised 62% males, 75% active drug users, 75% non-Hispanic blacks, and 55% with a CD4 count

Chronic pain is difficult to treat in individuals with substance use disorders and, when not resolved, can have a negative impact on substance use disorder treatment outcomes. This study tested the efficacy of a psychosocial pain management intervention, ImPAT (improving pain during addiction treatment), that combines pain management with content related to managing pain without substance use.Single-site, parallel-groups randomized controlled trial comparing ImPAT to a supportive psychoeducational control (SPC) condition; follow-up assessments occurred at 3, 6 and 12 months.The Ann Arbor VA Substance Use Disorder treatment program, USA.Veterans Health Administration patients {n = 129; mean [standard deviation (SD)], age = 51.7 (9.5); 115 of 129 (89%) male; ImPAT (n = 65); SPC (n = 64)}.ImPAT combines principles of cognitive-behavioral therapy and acceptance-based approaches to pain management with content related to avoiding the use of substances as a coping mechanism for pain. The SPC used a psychoeducational attention control treatment for alcoholism modified to cover other substances in addition to alcohol.Primary: Pain intensity over 12 months; secondary: pain-related functioning, frequency of alcohol and drug use over 12 months.Primary: randomization to the ImPAT intervention versus SPC predicted significantly lower pain intensity {β [standard error (SE)] = -0.71 (0.29); 95% confidence interval (CI) = -1.29, -0.12}; secondary: relative to the SPC condition, those who received ImPAT also reported improved pain-related functioning [β (SE) = 0.27 (0.11); 95% CI = 0.05, 0.49] and lower frequency of alcohol consumption [β (SE) = -0.77; 95% CI = -1.34, -0.20]. No differences were found between conditions on frequency of drug use over follow-up.For adults with pain who are enrolled in addictions treatment, receipt of a psychological pain management intervention (improving pain during addiction treatment) reduced pain and alcohol use and improves pain-related functioning over 12 months relative to a matched-attention control condition.

OBJECTIVES: Nonmedical prescription opiate use (NPOU) and nonmedical prescription sedative use (NPSU) are serious public health concerns. The objectives of this study were to determine the prevalence and emergency department (ED) visit characteristics and other correlates associated with past-year NPOU and NPSU among adolescents and young adults using the ED. METHODS: Participants aged 14 to 20 presenting to the ED at the University of Michigan Medical Center between September 2010 and September 2011 were systematically recruited. A computerized self-report screening survey with validated items measuring past-year NPOU, NPSU, substance use, and violence was delivered to participants, and a retrospective chart review was performed. RESULTS: Of the 2135 participants (86.0% response rate), 222 (10.4%) reported either NPOU or NPSU. Among the 185 (8.7%) participants that reported NPOU, 14.6% had a current home prescription for an opioid and among the 115 (5.4%) with NPSU, 12.3% had a current home prescription for a sedative. After controlling for demographics (age, gender, race, public assistance), correlates of NPOU or NPSU included other substance use, and drinking and driving or riding with a drinking driver. Additional correlates of NPOU included receiving an intravenous opioid in the ED and for NPSU, dating violence, presenting to the ED for a noninjury complaint, and previous ED visit in the past year. CONCLUSIONS: Nearly 1 in 10 young people who use the ED for care report NPOU or NPSU, and only 12.3% and 14.6% report having current home prescriptions for sedatives and opioids. The ED represents a key location for screening and intervention efforts.

U.S. women have worse HAART and HIV health outcomes compared to U.S. men. The study examined main partner factors associated with women's HAART adherence. The community sample comprised 85% African Americans; 63% had a main partner and 32% relied on their partner for emotional support. Adherence was highest (92%) among those without a main partner, and lowest (57%) among those with an HIV seropositive main partner. In adjusted analysis, adherence was 75% less likely among women with an HIV seropositive main partner, and 78% less likely among those relying on their partner for emotional support. Furthermore, HIV seropositive versus other serostatus main partners were most likely to provide medication taking assistance and to be preferred in helping participants deal with HIV, yet were no more likely to be nominated as the most helpful to them. Findings reveal women's perceived unmet support needs from HIV seropositive main partners in this population, and the need for interventions to promote their HAART adherence. Seroconcordant couples-focused intervention that enhances mutual support of HAART adherence may be an effective approach to improving women's HAART adherence and reducing US gender disparities in HIV health outcomes.

This study examined the prevalence and characteristics of adults with an alcohol use-related problem who receive clergy services. Data come from the National Epidemiologic Survey on Alcohol and Related Conditions. Among persons who sought any services for alcohol-related problems (n = 1,910), 14.7% reported using clergy services. In a multivariable logistic regression model, factors associated with increased likelihood of service use included being Black, aged 35-54 years, a lifetime history of alcohol dependence, major depressive disorder, and personality disorder. Clergy may benefit from training to identify alcohol use problems and serve an important role in making treatment referrals.

Aims While several studies have documented a relationship between initiation of drug use and social network drug use in youth, the direction of this association is not well understood, particularly among adults or for stages of drug involvement beyond initiation. The present study sought to examine two competing theories (social selection and social influence) in the longitudinal relationship between drug use (heroin and/or cocaine) and social network drug use among drug-experienced adults. Design Three waves of data came from a cohort of 1108 adults reporting a life-time history of heroin and/or cocaine use. Setting Low-income neighborhoods with high rates of drug use in Baltimore, Maryland. Participants Participants had weekly contact with drug users and were 18 years of age or older. Measurements Drug use data were self-report. Network drug use was assessed through a social network inventory. Close friends were individuals whom the participant reported seeing daily or rated as having the highest level of trust. Findings Structural equation modeling indicated significant bidirectional influences. The majority of change in network drug use over time was due to change in the composition of the network rather than change in friends' behavior. Drug use by close peers did not influence participant drug use beyond the total network. Conclusions There is evidence of both social selection and social influence processes in the association between drug use and network drug use among drug-experienced adults.