Biomarkers of Metabolic Adaptation to High Dietary Fats in a Mouse Model of Obesity Resistance.

Obesity-resistant (non-responder, NR) phenotypes that exhibit reduced susceptibility to developing obesity despite being exposed to high dietary fat are crucial in exploring the metabolic responses that protect against obesity. Although several efforts have been made to study them in mice and humans, the individual protective mechanisms are poorly understood. In this exploratory study, we used a polygenic C57BL/6J mouse model of diet-induced obesity to show that NR mice developed healthier fat/lean body mass ratios (0.43 ± 0.05) versus the obesity-prone (super-responder, SR) phenotypes (0.69 ± 0.07, p < 0.0001) by upregulating gene expression networks that promote the accumulation of type 2a, fast-twitch, oxidative muscle tissues. This was achieved in part by a metabolic adaptation in the form of blood glucose sparing, thus aggravating glucose tolerance. Resistance to obesity in NR mice was associated with 4.9-fold upregulated mitoferrin 1 (Slc25a37), an essential mitochondrial iron importer. SR mice also showed fecal volatile metabolite signatures of enhanced short-chain fatty acid metabolism, including increases in detrimental methyl formate and ethyl propionate, and these effects were reversed in NR mice. Continued research into obesity-resistant phenotypes can offer valuable insights into the underlying mechanisms of obesity and metabolic health, potentially leading to more personalized and effective approaches for managing weight and related health issues.

Nurse Care Management for Opioid Use Disorder Treatment: The PROUD Cluster Randomized Clinical Trial.

Importance: Few primary care (PC) practices treat patients with medications for opioid use disorder (OUD) despite availability of effective treatments. Objective: To assess whether implementation of the Massachusetts model of nurse care management for OUD in PC increases OUD treatment with buprenorphine or extended-release injectable naltrexone and secondarily decreases acute care utilization. Design, Setting, and Participants: The Primary Care Opioid Use Disorders Treatment (PROUD) trial was a mixed-methods, implementation-effectiveness cluster randomized clinical trial conducted in 6 diverse health systems across 5 US states (New York, Florida, Michigan, Texas, and Washington). Two PC clinics in each system were randomized to intervention or usual care (UC) stratified by system (5 systems were notified on February 28, 2018, and 1 system with delayed data use agreement on August 31, 2018). Data were obtained from electronic health records and insurance claims. An implementation monitoring team collected qualitative data. Primary care patients were included if they were 16 to 90 years old and visited a participating clinic from up to 3 years before a system's randomization date through 2 years after. Intervention: The PROUD intervention included 3 components: (1) salary for a full-time OUD nurse care manager; (2) training and technical assistance for nurse care managers; and (3) 3 or more PC clinicians agreeing to prescribe buprenorphine. Main Outcomes and Measures: The primary outcome was a clinic-level measure of patient-years of OUD treatment (buprenorphine or extended-release injectable naltrexone) per 10 000 PC patients during the 2 years postrandomization (follow-up). The secondary outcome, among patients with OUD prerandomization, was a patient-level measure of the number of days of acute care utilization during follow-up. Results: During the baseline period, a total of 130 623 patients were seen in intervention clinics (mean [SD] age, 48.6 [17.7] years; 59.7% female), and 159 459 patients were seen in UC clinics (mean [SD] age, 47.2 [17.5] years; 63.0% female). Intervention clinics provided 8.2 (95% CI, 5.4-∞) more patient-years of OUD treatment per 10 000 PC patients compared with UC clinics (P = .002). Most of the benefit accrued in 2 health systems and in patients new to clinics (5.8 [95% CI, 1.3-∞] more patient-years) or newly treated for OUD postrandomization (8.3 [95% CI, 4.3-∞] more patient-years). Qualitative data indicated that keys to successful implementation included broad commitment to treat OUD in PC from system leaders and PC teams, full financial coverage for OUD treatment, and straightforward pathways for patients to access nurse care managers. Acute care utilization did not differ between intervention and UC clinics (relative rate, 1.16; 95% CI, 0.47-2.92; P = .70). Conclusions and Relevance: The PROUD cluster randomized clinical trial intervention meaningfully increased PC OUD treatment, albeit unevenly across health systems; however, it did not decrease acute care utilization among patients with OUD. Trial Registration: ClinicalTrials.gov Identifier: NCT03407638.

Implementation of substance use screening in rural federally-qualified health center clinics identified high rates of unhealthy alcohol and cannabis use among adult primary care patients.

BACKGROUND: Screening for substance use in rural primary care clinics faces unique challenges due to limited resources, high patient volumes, and multiple demands on providers. To explore the potential for electronic health record (EHR)-integrated screening in this context, we conducted an implementation feasibility study with a rural federally-qualified health center (FQHC) in Maine. This was an ancillary study to a NIDA Clinical Trials Network study of screening in urban primary care clinics (CTN-0062). METHODS: Researchers worked with stakeholders from three FQHC clinics to define and implement their optimal screening approach. Clinics used the Tobacco, Alcohol, Prescription Medication, and Other Substance (TAPS) Tool, completed on tablet computers in the waiting room, and results were immediately recorded in the EHR. Adult patients presenting for annual preventive care visits, but not those with other visit types, were eligible for screening. Data were analyzed for the first 12 months following implementation at each clinic to assess screening rates and prevalence of reported unhealthy substance use, and documentation of counseling using an EHR-integrated clinical decision support tool, for patients screening positive for moderate-high risk alcohol or drug use. RESULTS: Screening was completed by 3749 patients, representing 93.4% of those with screening-eligible annual preventive care visits, and 18.5% of adult patients presenting for any type of primary care visit. Screening was self-administered in 92.9% of cases. The prevalence of moderate-high risk substance use detected on screening was 14.6% for tobacco, 30.4% for alcohol, 10.8% for cannabis, 0.3% for illicit drugs, and 0.6% for non-medical use of prescription drugs. Brief substance use counseling was documented for 17.4% of patients with any moderate-high risk alcohol or drug use. CONCLUSIONS: Self-administered EHR-integrated screening was feasible to implement, and detected substantial alcohol, cannabis, and tobacco use in rural FQHC clinics. Counseling was documented for a minority of patients with moderate-high risk use, possibly indicating a need for better support of primary care providers in addressing substance use. There is potential to broaden the reach of screening by offering it at routine medical visits rather than restricting to annual preventive care visits, within these and other rural primary care clinics.

Prevalence of Cannabis Use Disorder and Reasons for Use Among Adults in a US State Where Recreational Cannabis Use Is Legal.

Importance: Medical and nonmedical cannabis use and cannabis use disorders (CUD) have increased with increasing cannabis legalization. However, the prevalence of CUD among primary care patients who use cannabis for medical or nonmedical reasons is unknown for patients in states with legal recreational use. Objective: To estimate the prevalence and severity of CUD among patients who report medical use only, nonmedical use only, and both reasons for cannabis use in a state with legal recreational use. Design, Setting, and Participants: This cross-sectional survey study took place at an integrated health system in Washington State. Among 108 950 adult patients who completed routine cannabis screening from March 2019 to September 2019, 5000 were selected for a confidential cannabis survey using stratified random sampling for frequency of past-year cannabis use and race and ethnicity. Among 1688 respondents, 1463 reporting past 30-day cannabis use were included in the study. Exposure: Patient survey-reported reason for cannabis use in the past 30 days: medical use only, nonmedical use only, and both reasons. Main Outcomes and Measures: Patient responses to the Composite International Diagnostic Interview-Substance Abuse Module for CUD, corresponding to Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition CUD severity (0-11 symptoms) were categorized as any CUD (≥2 symptoms) and moderate to severe CUD (≥4 symptoms). Adjusted analyses were weighted for survey stratification and nonresponse for primary care population estimates and compared prevalence of CUD across reasons for cannabis use. Results: Of 1463 included primary care patients (weighted mean [SD] age, 47.4 [16.8] years; 748 [weighted proportion, 61.9%] female) who used cannabis, 42.4% (95% CI, 31.2%-54.3%) reported medical use only, 25.1% (95% CI, 17.8%-34.2%) nonmedical use only, and 32.5% (95% CI, 25.3%-40.8%) both reasons for use. The prevalence of CUD was 21.3% (95% CI, 15.4%-28.6%) and did not vary across groups. The prevalence of moderate to severe CUD was 6.5% (95% CI, 5.0%-8.6%) and differed across groups: 1.3% (95% CI, 0.0%-2.8%) for medical use, 7.2% (95% CI, 3.9%-10.4%) for nonmedical use, and 7.5% (95% CI, 5.7%-9.4%) for both reasons for use (P = .01). Conclusions and Relevance: In this cross-sectional study of primary care patients in a state with legal recreational cannabis use, CUD was common among patients who used cannabis. Moderate to severe CUD was more prevalent among patients who reported any nonmedical use. These results underscore the importance of assessing patient cannabis use and CUD symptoms in medical settings.

Strategies for specialty training of healthcare professionals in low-resource settings: a systematic review on evidence from stroke care.

BACKGROUND: The greatest mortality and disability from stroke occurs in low- and middle-income countries. A significant barrier to implementation of best stroke care practices in these settings is limited availability of specialized healthcare training. We conducted a systematic review to determine the most effective methods for the provision of speciality stroke care education for hospital-based healthcare professionals in low-resource settings. METHODS: We followed the PRISMA guidelines for systematic reviews and searched PubMed, Web of Science and Scopus for original clinical research articles that described or evaluated stroke care education for hospital-based healthcare professionals in low-resource settings. Two reviewers screened titles/abstracts and then full text articles. Three reviewers critically appraised the articles selected for inclusion. RESULTS: A total of 1,182 articles were identified and eight were eligible for inclusion in this review; three were randomized controlled trials, four were non-randomized studies, and one was a descriptive study. Most studies used several approaches to education. A "train-the-trainer" approach to education was found to have the most positive clinical outcomes (lower overall complications, lengths of stay in hospital, and clinical vascular events). When used for quality improvement, the "train-the-trainer" approach increased patient reception of eligible performance measures. When technology was used to provide stroke education there was an increased frequency in diagnosis of stroke and use of antithrombotic treatment, reduced door-to-needle times, and increased support for decision making in medication prescription was reported. Task-shifting workshops for non-neurologists improved knowledge of stroke and patient care. Multidimensional education demonstrated an overall care quality improvement and increased prescriptions for evidence-based therapies, although, there were no significant differences in secondary prevention efforts, stroke reoccurrence or mortality rates. CONCLUSIONS: The "train the trainer" approach is likely the most effective strategy for specialist stroke education, while technology is also useful if resources are available to support its development and use. If resources are limited, basic knowledge education should be considered at a minimum and multidimensional training may not be as beneficial. Research into communities of practice, led by those in similar settings, may be helpful to develop educational initiatives with relevance to local contexts.

Effectiveness of interventions by non-professional community-level workers or family caregivers to improve outcomes for physical impairments or disabilities in low resource settings: systematic review of task-sharing strategies.

BACKGROUND: In low-resource settings, access to basic rehabilitation could be supplemented by community-level interventions provided by community health workers, health volunteers, or family caregivers. Yet, it is unclear whether basic physical rehabilitation interventions delivered to adults by non-professional alternative resources in the community, under task-shifting or task-sharing approaches, are effective as those delivered by skilled rehabilitation professionals. We aim to synthesize evidence on the effectiveness of community-level rehabilitation interventions delivered by non-professional community-level workers or informal caregivers to improve health outcomes for persons with physical impairments or disabilities. METHODS: We performed a systematic review with a PROSPERO registration. Eight databases were searched for (PubMed, CINAHL, Global Health, PDQ Evidence, Scopus, ProQuest, CENTRAL, and Web of Science), supplemented by snowballing and key-informant recommendations, with no time restrictions, applied. Controlled and non-controlled experiments were included if reporting the effects of interventions on mobility, activities of daily living (ADLs), quality of life, or social participation outcomes. Two independent investigators performed the eligibility decisions, data extraction, risk of bias, and assessed the quality of the evidence using the GRADE approach. RESULTS: Ten studies (five randomized controlled trials [RCTs]) involving 2149 participants were included. Most common targeted stroke survivors (n = 8); family caregivers were most frequently used to deliver the intervention (n = 4); and the intervention was usually provided in homes (n = 7), with training initiated in the hospital (n = 4). Of the four RCTs delivered by family caregivers, one demonstrated a statistically significant improvement in mobility (effect size: 0.3; confidence interval [CI] 121.81-122.19; [p = 0.04]) and another one in ADLs (effect size: 0.4; CI 25.92-35.08; [p = 0.03]). Of the five non-RCT studies by community health workers or volunteers, one demonstrated a statistically significant improvement in mobility (effect size: 0.3; CI 10.143-16.857; [p < 0.05]), while two demonstrated improved statistically significant improvement in ADLs (effect size: 0.2; CI 180.202-184.789 [p = 0.001]; 0.4; CI - 7.643-18.643; [p = 0.026]). However, the quality of evidence, based on GRADE criteria, was rated as low to very low. CONCLUSIONS: While task-sharing is a possible strategy to meet basic rehabilitation needs in low-resource settings, the current evidence on the effectiveness of delivering rehabilitation interventions by non-professional community-level workers and informal caregivers is inconclusive. We can use the data and experiences from existing studies to better design studies and improve the implementation of interventions. Trial registration PROSPERO registration number: CRD42022319130.

A patient-centered nurse-supported primary care-based collaborative care program to treat opioid use disorder and depression: Design and protocol for the MI-CARE randomized controlled trial.

BACKGROUND: Opioid use disorder (OUD) contributes to rising morbidity and mortality. Life-saving OUD treatments can be provided in primary care but most patients with OUD don't receive treatment. Comorbid depression and other conditions complicate OUD management, especially in primary care. The MI-CARE trial is a pragmatic randomized encouragement (Zelen) trial testing whether offering collaborative care (CC) to patients with OUD and clinically-significant depressive symptoms increases OUD medication treatment with buprenorphine and improves depression outcomes compared to usual care. METHODS: Adult primary care patients with OUD and depressive symptoms (n ≥ 800) from two statewide health systems: Kaiser Permanente Washington and Indiana University Health are identified with computer algorithms from electronic Health record (EHR) data and automatically enrolled. A random sub-sample (50%) of eligible patients is offered the MI-CARE intervention: a 12-month nurse-driven CC intervention that includes motivational interviewing and behavioral activation. The remaining 50% of the study cohort comprise the usual care comparison group and is never contacted. The primary outcome is days of buprenorphine treatment provided during the intervention period. The powered secondary outcome is change in Patient Health Questionnaire (PHQ)-9 depression scores. Both outcomes are obtained from secondary electronic healthcare sources and compared in "intent-to-treat" analyses. CONCLUSION: MI-CARE addresses the need for rigorous encouragement trials to evaluate benefits of offering CC to generalizable samples of patients with OUD and mental health conditions identified from EHRs, as they would be in practice, and comparing outcomes to usual primary care. We describe the design and implementation of the trial, currently underway. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT05122676. Clinical trial registration date: November 17, 2021.

Cannabis and nicotine co-use among primary care patients in a state with legal cannabis access.

The aim of this exploratory analysis was to evaluate cannabis exposure, reasons for use and problematic cannabis use among adult primary care patients in Washington state (United States) who co-use cannabis and nicotine (tobacco cigarettes and/or nicotine vaping) compared to patients who endorse current cannabis use only. As part of a NIDA Clinical Trials Network (CTN) parent study, patients who completed a cannabis screen as part of routine primary care were randomly sampled (N = 5,000) to a receive a confidential cannabis survey. Patients were stratified and oversampled based on the frequency of past-year cannabis use and for Black, indigenous, or other persons of color. Patients who endorsed past 30-day cannabis use are included here (N = 1388). Outcomes included; prevalence of cannabis use, days of cannabis use per week and times used per day, methods of use, THC:CBD content, non-medical and/or medical use, health symptoms managed, and cannabis use disorder (CUD) symptom severity. We conducted unadjusted bivariate analyses comparing outcomes between patients with cannabis and current nicotine co-use to patients with cannabis-only use. Nicotine co-use (n = 352; 25.4 %) was associated with differences in method of cannabis use, THC:CBD content, days of use per week and times used per day, number of health symptoms managed, and CUD severity (all p < 0.001), compared to primary care patients with cannabis-only use (n = 1036). Interventions targeting cannabis and nicotine co-use in primary care are not well-established and further research is warranted given findings of more severe cannabis use patterns and the adverse health outcomes associated with co-use.

Baseline representativeness of patients in clinics enrolled in the PRimary care Opioid Use Disorders treatment (PROUD) trial: comparison of trial and non-trial clinics in the same health systems.

BACKGROUND: Pragmatic primary care trials aim to test interventions in "real world" health care settings, but clinics willing and able to participate in trials may not be representative of typical clinics. This analysis compared patients in participating and non-participating clinics from the same health systems at baseline in the PRimary care Opioid Use Disorders treatment (PROUD) trial. METHODS: This observational analysis relied on secondary electronic health record and administrative claims data in 5 of 6 health systems in the PROUD trial. The sample included patients 16-90 years at an eligible primary care visit in the 3 years before randomization. Each system contributed 2 randomized PROUD trial clinics and 4 similarly sized non-trial clinics. We summarized patient characteristics in trial and non-trial clinics in the 2 years before randomization ("baseline"). Using mixed-effect regression models, we compared trial and non-trial clinics on a baseline measure of the primary trial outcome (clinic-level patient-years of opioid use disorder (OUD) treatment, scaled per 10,000 primary care patients seen) and a baseline measure of the secondary trial outcome (patient-level days of acute care utilization among patients with OUD). RESULTS: Patients were generally similar between the 10 trial clinics (n = 248,436) and 20 non-trial clinics (n = 341,130), although trial clinics' patients were slightly younger, more likely to be Hispanic/Latinx, less likely to be white, more likely to have Medicaid/subsidized insurance, and lived in less wealthy neighborhoods. Baseline outcomes did not differ between trial and non-trial clinics: trial clinics had 1.0 more patient-year of OUD treatment per 10,000 patients (95% CI: - 2.9, 5.0) and a 4% higher rate of days of acute care utilization than non-trial clinics (rate ratio: 1.04; 95% CI: 0.76, 1.42). CONCLUSIONS: trial clinics and non-trial clinics were similar regarding most measured patient characteristics, and no differences were observed in baseline measures of trial primary and secondary outcomes. These findings suggest trial clinics were representative of comparably sized clinics within the same health systems. Although results do not reflect generalizability more broadly, this study illustrates an approach to assess representativeness of clinics in future pragmatic primary care trials.

INTERBLEED: Design of an International Study of Risk Factors for Gastrointestinal Bleeding and Cardiovascular Events After Gastrointestinal Bleeding.

Background: Bleeding is the most common adverse event in those with cardiovascular (CV) disease receiving antithrombotic therapy, and it most commonly occurs in the gastrointestinal (GI) tract. Clinicians often dismiss bleeding as an adverse event that is reversible with effective antithrombotic therapy, but bleeding is associated with substantial morbidity and mortality, most likely mediated through an increased risk of CV events. Reducing the burden of bleeding requires knowledge of the potentially modifiable risk factors for bleeding and the potentially modifiable risk factors for adverse outcomes after bleeding. Methods: INTERBLEED is an international, multicentre, 2-component, observational study, with an incident case-control study examining the risk factors for GI bleeding, and a prospective cohort study of risk factors for CV events after GI bleeding. Cases either have CV disease and present to the hospital with GI bleeding or develop GI bleeding during hospitalization. Controls have CV disease, but no history of GI bleeding. We use a questionnaire to obtain detailed information on known and potential risk factors for GI bleeding and for CV events and outcomes after bleeding. We obtain CV and anthropometric measurements, perform functional and cognitive assessments, and follow participants at 3 months and 12 months. Results: As of April 1, 2022, the study is ongoing in 10 countries at 31 centres and has recruited 2407 cases and 1478 controls. Conclusions: Knowledge of risk factors for bleeding, and risk factors for CV events and functional decline after bleeding, will help develop strategies to prevent bleeding and subsequent complications.

Contexte: L'hémorragie est l'effet indésirable le plus fréquent chez les patients atteints de maladies cardiovasculaires (CV) qui reçoivent un traitement antithrombotique, et elle survient le plus souvent dans le tractus gastro-intestinal (GI). Les cliniciens considèrent souvent l'hémorragie comme une simple manifestation indésirable réversible par un traitement antithrombotique efficace, mais une morbidité et une mortalité considérables y sont associées, probablement en raison d'un risque accru d'événements CV. Une réduction du fardeau de l'hémorragie nécessite une connaissance des facteurs de risque potentiellement modifiables tant de l'hémorragie que des événements indésirables qui surviennent après l'hémorragie. Méthodologie: INTERBLEED est une étude internationale, observationnelle et multicentrique à deux volets; le premier volet est une étude cas-témoins incidents visant à examiner les facteurs de risque d'hémorragie GI, alors que le second volet est une étude de cohorte prospective visant à examiner les facteurs de risque d'événements CV après une hémorragie GI. Les cas sont des patients atteints de maladies CV qui consultent les services hospitaliers pour une hémorragie GI ou qui présentent une hémorragie GI en cours d'hospitalisation. Les témoins sont des patients atteints de maladies CV, mais sans antécédents d'hémorragie GI. Un questionnaire est utilisé pour obtenir des renseignements détaillés au sujet de facteurs de risque connus et potentiels d'hémorragie GI et d'événements CV et d'autres résultats de santé après une hémorragie. Des mesures cardiovasculaires et anthropométriques ainsi que des évaluations fonctionnelles et cognitives sont réalisées, et les participants sont revus après trois mois et 12 mois. Résultats: En date du 1er avril 2022, l'étude est en cours dans 10 pays et 31 établissements de santé; 2 407 cas et 1 478 témoins ont été recrutés. Conclusions: La connaissance des facteurs de risque d'hémorragie, ainsi que des facteurs de risque d'événements CV et de déclin fonctionnel à la suite d'une hémorragie, aidera à mettre en place des stratégies pour prévenir les hémorragies et les complications qui peuvent en découler.

A modified Delphi process to identify experts' perceptions of the most beneficial and harmful laws to reduce opioid-related harm.

BACKGROUND: States have enacted multiple types of laws, with a variety of constituent provisions, in response to the opioid epidemic, often simultaneously. This temporal proximity and variation in state-to-state operationalization has resulted in significant challenges for empirical research on their effects. Thus, expert consensus can be helpful to classify laws and their provisions by their degree of helpfulness and impact. METHODS: We conducted a four-stage modified policy Delphi process to identify the top 10 most helpful and 5 most harmful provisions from eight opioid-related laws. This iterative consultation with six types of opioid experts included a preliminary focus group (n=12), two consecutive surveys (n=56 and n=40, respectively), and a final focus group feedback session (n=5). RESULTS: On a scale of very harmful (0) to very helpful (4), overdose Good Samaritan laws received the highest average helpfulness rating (3.62, 95% CI: 3.48-3.75), followed by naloxone access laws (3.37, 95% CI: 3.22-3.51), and pain management clinic laws (3.08, 95% CI: 2.89-3.26). Drug-induced homicide (DIH) laws were rated the most harmful (0.88, 95% CI: 0.66-1.11). Impact ratings aligned similarly, although Medicaid laws received the second highest overall impact rating (3.71, 95% CI: 3.45, 3.97). The two most helpful provisions were naloxone standing orders (3.94, 95% CI: 3.86-4.02) and Medicaid coverage of medications for opioid use disorder (MOUD) (3.89, 95% CI: 3.82). Mandatory minimum DIH laws were the most harmful provision (0.73, 95% CI 0.53-0.93); followed by requiring prior authorization for Medicaid coverage of MOUD (1.00 95% CI: 0.72-1.27). CONCLUSION: Overall, experts rated laws and provisions that facilitated harm reduction efforts and access to MOUD as most helpful. Laws and provisions rated as most harmful criminalized substance use and placed restrictions on access to MOUD. These ratings provide a foundation for evaluating the overall overdose policy environment for each state.

Use of an Inverted Synthetic Control Method to Estimate Effects of Recent Drug Overdose Good Samaritan Laws, Overall and by Black/White Race/Ethnicity.

Overdose Good Samaritan laws (GSLs) aim to reduce mortality by providing limited legal protections when a bystander to a possible drug overdose summons help. Most research into the impact of these laws is dated or potentially confounded by coenacted naloxone access laws. Lack of awareness and trust in GSL protections, as well as fear of police involvement and legal repercussions, remain key deterrents to help-seeking. These barriers may be unequally distributed by race/ethnicity due to racist policing and drug policies, potentially producing racial/ethnic disparities in the effectiveness of GSLs for reducing overdose mortality. We used 2015-2019 vital statistics data to estimate the effect of recent GSLs on overdose mortality, overall (8 states) and by Black/White race/ethnicity (4 states). Given GSLs' near ubiquity, few unexposed states were available for comparison. Therefore, we generated an "inverted" synthetic control method (SCM) to compare overdose mortality in new-GSL states with that in states that had GSLs throughout the analytical period. The estimated relationships between GSLs and overdose mortality, both overall and stratified by Black/White race/ethnicity, were consistent with chance. An absence of effect could result from insufficient protection provided by the laws, insufficient awareness of them, and/or reticence to summon help not addressable by legal protections. The inverted SCM may be useful for evaluating other widespread policies.

The stigma system: How sociopolitical domination, scapegoating, and stigma shape public health.

Stigma is a fundamental driver of adverse health outcomes. Although stigma is often studied at the individual level to focus on how stigma influences the mental and physical health of the stigmatized, considerable research has shown that stigma is multilevel and structural. This paper proposes a theoretical approach that synthesizes the literature on stigma with the literature on scapegoating and divide-and-rule as strategies that the wealthy and powerful use to maintain their power and wealth; the literatures on racial, gender, and other subordination; the literature on ideology and organization in sociopolitical systems; and the literature on resistance and rebellion against stigma, oppression and other forms of subordination. we develop a model of the "stigma system" as a dialectic of interacting and conflicting structures and processes. Understanding this system can help public health reorient stigma interventions to address the sources of stigma as well as the individual problems that stigma creates. On a broader level, this model can help those opposing stigma and its effects to develop alliances and strategies with which to oppose stigma and the processes that create it.

Screening for Unhealthy Alcohol and Drug Use in General Medicine Settings.

Unhealthy alcohol and drug use are among the top 10 causes of preventable death in the United States, but they are infrequently identified and addressed in medical settings. Guidelines recommend screening adult primary care patients for alcohol and drug use, and routine screening should be a component of high-quality clinical care. Brief, validated screening tools accurately detect unhealthy alcohol and drug use, and their thoughtful implementation can facilitate adoption and optimize the quality of screening results. Recommendations for implementation include patient self-administered screening tools, integration with electronic health records, and screening during routine primary care visits.

Sensory Descriptor Analysis of Whisky Lexicons through the Use of Deep Learning.

This paper is concerned with extracting relevant terms from a text corpus on whisk(e)y. "Relevant" terms are usually contextually defined in their domain of use. Arguably, every domain has a specialized vocabulary used for describing things. For example, the field of Sensory Science, a sub-field of Food Science, investigates human responses to food products and differentiates "descriptive" terms for flavors from "ordinary", non-descriptive language. Within the field, descriptors are generated through Descriptive Analysis, a method wherein a human panel of experts tastes multiple food products and defines descriptors. This process is both time-consuming and expensive. However, one could leverage existing data to identify and build a flavor language automatically. For example, there are thousands of professional and semi-professional reviews of whisk(e)y published on the internet, providing abundant descriptors interspersed with non-descriptive language. The aim, then, is to be able to automatically identify descriptive terms in unstructured reviews for later use in product flavor characterization. We created two systems to perform this task. The first is an interactive visual tool that can be used to tag examples of descriptive terms from thousands of whisky reviews. This creates a training dataset that we use to perform transfer learning using GloVe word embeddings and a Long Short-Term Memory deep learning model architecture. The result is a model that can accurately identify descriptors within a corpus of whisky review texts with a train/test accuracy of 99% and precision, recall, and F1-scores of 0.99. We tested for overfitting by comparing the training and validation loss for divergence. Our results show that the language structure for descriptive terms can be programmatically learned.

Good Samaritan laws and overdose mortality in the United States in the fentanyl era.

BACKGROUND: As of July 2018, 45 United States (US) states and the District of Columbia have enacted an overdose Good Samaritan law (GSL). These laws, which provide limited criminal immunity to individuals who request assistance during an overdose, may be of importance in the current wave of the overdose epidemic, which is driven primarily by illicit opioids including heroin and fentanyl. There are substantial differences in the structures of states' GSL laws which may impact their effectiveness. This study compared GSLs which have legal provisions protecting from arrest and laws which have more limited protections. METHODS: Using national county-level overdose mortality data from 3109 US counties, we examined the association of enactment of GSLs with protection from arrest and GSLs with more limited protections with subsequent overdose mortality between 2013 and 2018. Since GSLs are often enacted in conjunction with Naloxone Access Laws (NAL), we examined the effect of GSLs separately and in conjunction with NAL. We conducted these analyses using hierarchical Bayesian spatiotemporal Poisson models. RESULTS: GSLs with protections against arrest enactment in conjunction with a NAL were associated with 7% lower rates of all overdose deaths (rate ratio (RR): 0.93% Credible Interval (CI): 0.89-0.97), 10% lower rates in opioid overdose deaths (RR: 0.90; CI: 0.85-0.95) and 11% lower rates of heroin/synthetic overdose mortality (RR: 0.89; CI: 0.82-0.96) two years after enactment, compared to rates in states without these laws. Significant reductions in overdose mortality were not seen for GSLs with protections for charge or prosecution. CONCLUSION: GSLs with more expansive legal protections combined with a NAL, were associated with lower rates of overdose deaths, although these risk reductions take time to manifest. Policy makers should consider enacting and implementing more expansive GSLs with arrest protections to increase the likelihood people will contact emergency services in the event of an overdose.

Comparison of Methods for Alcohol and Drug Screening in Primary Care Clinics.

Importance: Guidelines recommend that adult patients receive screening for alcohol and drug use during primary care visits, but the adoption of screening in routine practice remains low. Clinics frequently struggle to choose a screening approach that is best suited to their resources, workflows, and patient populations. Objective: To evaluate how to best implement electronic health record (EHR)-integrated screening for substance use by comparing commonly used screening methods and examining their association with implementation outcomes. Design, Setting, and Participants: This article presents the outcomes of phases 3 and 4 of a 4-phase quality improvement, implementation feasibility study in which researchers worked with stakeholders at 6 primary care clinics in 2 large urban academic health care systems to define and implement their optimal screening approach. Site A was located in New York City and comprised 2 clinics, and site B was located in Boston, Massachusetts, and comprised 4 clinics. Clinics initiated screening between January 2017 and October 2018, and 93 114 patients were eligible for screening for alcohol and drug use. Data used in the analysis were collected between January 2017 and October 2019, and analysis was performed from July 13, 2018, to March 23, 2021. Interventions: Clinics integrated validated screening questions and a brief counseling script into the EHR, with implementation supported by the use of clinical champions (ie, clinicians who advocate for change, motivate others, and use their expertise to facilitate the adoption of an intervention) and the training of clinic staff. Clinics varied in their screening approaches, including the type of visit targeted for screening (any visit vs annual examinations only), the mode of administration (staff-administered vs self-administered by the patient), and the extent to which they used practice facilitation and EHR usability testing. Main Outcomes and Measures: Data from the EHRs were extracted quarterly for 12 months to measure implementation outcomes. The primary outcome was screening rate for alcohol and drug use. Secondary outcomes were the prevalence of unhealthy alcohol and drug use detected via screening, and clinician adoption of a brief counseling script. Results: Patients of the 6 clinics had a mean (SD) age ranging from 48.9 (17.3) years at clinic B2 to 59.1 (16.7) years at clinic B3, were predominantly female (52.4% at clinic A1 to 64.6% at clinic A2), and were English speaking. Racial diversity varied by location. Of the 93,114 patients with primary care visits, 71.8% received screening for alcohol use, and 70.5% received screening for drug use. Screening at any visit (implemented at site A) in comparison with screening at annual examinations only (implemented at site B) was associated with higher screening rates for alcohol use (90.3%-94.7% vs 24.2%-72.0%, respectively) and drug use (89.6%-93.9% vs 24.6%-69.8%). The 5 clinics that used a self-administered screening approach had a higher detection rate for moderate- to high-risk alcohol use (14.7%-36.6%) compared with the 1 clinic that used a staff-administered screening approach (1.6%). The detection of moderate- to high-risk drug use was low across all clinics (0.5%-1.0%). Clinics with more robust practice facilitation and EHR usability testing had somewhat greater adoption of the counseling script for patients with moderate-high risk alcohol or drug use (1.4%-12.5% vs 0.1%-1.1%). Conclusions and Relevance: In this quality improvement study, EHR-integrated screening was feasible to implement in all clinics and unhealthy alcohol use was detected more frequently when self-administered screening was used at any primary care visit. The detection of drug use was low at all clinics, as was clinician adoption of counseling. These findings can be used to inform the decision-making of health care systems that are seeking to implement screening for substance use. Trial Registration: ClinicalTrials.gov Identifier: NCT02963948.

Critical Factors Influencing Interorganizational Relationships Between Juvenile Probation and Behavioral Health Agencies.

Although interorganizational relationships (IORs) are essential to the effective delivery of human services, very little research has examined relationships between juvenile justice agencies and behavioral health providers, and few studies have identified the most critical organizational and individual-level characteristics influencing IORs. Across 36 sites, juvenile probation officials (n = 458) and community behavioral health providers (n = 91) were surveyed about characteristics of their agencies, themselves, and IORs with each other. Generalized Linear Mixed Models were used to analyze the data. The strongest predictors included Perceived Organizational Support and individual Adaptability. Implications for research, theory and practice are discussed.

Early implementation of screening for substance use in rural primary care: A rapid analytic qualitative study.

Background: Few primary care patients are screened for substance use. As part of a phased feasibility study examining the implementation of electronic health record-integrated screening with the Tobacco, Alcohol, and Prescription Medication Screening (TAPS) Tool and clinical decision support (CDS) in rural primary care clinics, focus groups were conducted to identify early indicators of success and challenges to screening implementation. Method: Focus groups (n = 6) were conducted with medical assistants (MAs: n = 3: 19 participants) and primary care providers (PCPs: n = 3: 13 participants) approximately one month following screening implementation in three Federally Qualified Health Centers in Maine. Rapid analysis and matrix analysis using Proctor's Taxonomy of Implementation Outcomes were used to explore implementation outcomes. Results: There was consensus that screening is being used, but use of the CDS was lower, in part due to limited positive screens. Fidelity was high among MAs, though discomfort with the CDS surfaced among PCPs, impacting adoption and fidelity. The TAPS Tool's content, credibility and ease of workflow integration were favorably assessed. Challenges include screening solely at annual visits and self-administered screening for certain patients. Conclusions: Results reveal indicators of implementation success and strategies to address challenges to screening for substance use in primary care.

A Critical Review of the Social and Behavioral Contributions to the Overdose Epidemic.

More than 750,000 people in the United States died from an overdose between 1999 and 2018; two-thirds of those deaths involved an opioid. In this review, we present trends in opioid overdose rates during this period and discuss how the proliferation of opioid prescribing to treat chronic pain, changes in the heroin and illegally manufactured opioid synthetics markets, and social factors, including deindustrialization and concentrated poverty, contributed to the rise of the overdose epidemic. We also examine how current policies implemented to address the overdose epidemic may have contributed to reducing prescription opioid overdoses but increased overdoses involving illegal opioids. Finally, we identify new directions for research to understand the causes and solutions to this critical public health problem, including research on heterogeneous policy effects across social groups, effective approaches to reduce overdoses of illegal opioids, and the role of social contexts in shaping policy implementation and impact.