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Richard N Rosenthal,1 Viral V Goradia2 1Department of Psychiatry, Addiction Institute at Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, 2Department of Psychiatry, Upstate Medical University, Syracuse, NY, USA Abstract: Opioid use disorders (OUDs) have long been a global problem, but the prevalence rates have increased over 20 years to epidemic proportions in the US, with concomitant increases in morbidity and all-cause mortality, but especially opioid overdose. These increases are in part attributable to a several-fold expansion in the prescription of opioid pain medications over the same time period. Opioid detoxification and psychosocial treatments alone have each not yielded sufficient efficacy for OUD, but μ-opioid receptor agonist, partial agonist, and antagonist medications have demonstrated the greatest overall benefit in OUD treatment. Buprenorphine, a μ-opioid receptor partial agonist, has been used successfully on an international basis for several decades in sublingual tablet and film preparations for the treatment of OUD, but the nature of formulation, which is typically self-administered, renders it susceptible to nonadherence, diversion, and accidental exposure. This article reviews the clinical trial data for novel buprenorphine delivery systems in the form of subcutaneous depot injections, transdermal patches, and subdermal implants for the treatment of OUD and discusses both the clinical efficacy of longer-acting formulations through increasing consistent medication exposure and their potential utility in reducing diversion. These new delivery systems also offer new dosing opportunities for buprenorphine and strategies for dosing intervals in the treatment of OUD. Keywords: opioid use disorder, buprenorphine, drug diversion, drug implants, depot medications, maintenance therapy, treatment adherence

This column describes the nonproprietary software Talker, used to adapt screening instruments to audio computer-assisted self-interviewing (ACASI) systems for low-literacy populations and other populations. Talker supports ease of programming, multiple languages, on-site scoring, and the ability to update a central research database. Key features include highly readable text display, audio presentation of questions and audio prompting of answers, and optional touch screen input. The scripting language for adapting instruments is briefly described as well as two studies in which respondents provided positive feedback on its use. [ABSTRACT FROM AUTHOR]

Abstract: The directors of the National Institute on Drug Abuse and the National Institute on Alcohol Abuse and Alcoholism have proposed new efforts to enable earlier identification and intervention for harmful substance use and its consequences. As editors of The ASAM Principles of Addiction Medicine, we fully support this goal. The word "preaddiction" has been suggested as a diagnostic label to describe individuals who would be targeted for early intervention. In this commentary, we offer that "unhealthy substance use" would be a better descriptor than "preaddiction" and review several potential barriers to be addressed in order to maximize the impact of introducing this new paradigm., Competing Interests: The authors report no conflicts of interest., (Copyright © 2024 American Society of Addiction Medicine.)

Class imbalance issues are prevalent in the medical field and significantly impact the performance of clinical predictive models. Traditional techniques to address this challenge aim to rebalance class proportions. They generally assume that the rebalanced proportions are derived from the original data, without considering the intricacies of the model utilized. This study challenges the prevailing assumption and introduces a new method that ties the optimal class proportions to model complexity. This approach allows for individualized tuning of class proportions for each model. Our experiments, centered on the opioid overdose prediction problem, highlight the performance gains achieved by this approach. Furthermore, rigorous regression analysis affirms the merits of the proposed theoretical framework, demonstrating a statistically significant correlation between hyperparameters controlling model complexity and the optimal class proportions., (©2024 AMIA - All rights reserved.)

Importance: Injectable extended-release (XR)-naltrexone is an effective treatment option for opioid use disorder (OUD), but the need to withdraw patients from opioid treatment prior to initiation is a barrier to implementation., Objective: To compare the effectiveness of the standard procedure (SP) with the rapid procedure (RP) for XR-naltrexone initiation., Design, Setting, and Participants: The Surmounting Withdrawal to Initiate Fast Treatment with Naltrexone study was an optimized stepped-wedge cluster randomized trial conducted at 6 community-based inpatient addiction treatment units. Units using the SP were randomly assigned at 14-week intervals to implement the RP. Participants admitted with OUD received the procedure the unit was delivering at the time of their admission. Participant recruitment took place between March 16, 2021, and July 18, 2022. The last visit was September 21, 2022., Interventions: Standard procedure, based on the XR-naltrexone package insert (approximately 5-day buprenorphine taper followed by a 7- to 10-day opioid-free period and RP, defined as 1 day of buprenorphine at minimum necessary dose, 1 opioid-free day, and ascending low doses of oral naltrexone and adjunctive medications (eg, clonidine, clonazepam, antiemetics) for opioid withdrawal., Main Outcomes and Measures: Receipt of XR-naltrexone injection prior to inpatient discharge (primary outcome). Secondary outcomes included opioid withdrawal scores and targeted safety events and serious adverse events. All analyses were intention-to-treat., Results: A total of 415 participants with OUD were enrolled (mean [SD] age, 33.6 [8.48] years; 205 [49.4%] identified sex as male); 54 [13.0%] individuals identified as Black, 91 [21.9%] as Hispanic, 290 [69.9%] as White, and 22 [5.3%] as multiracial. Rates of successful initiation of XR-naltrexone among the RP group (141 of 225 [62.7%]) were noninferior to those of the SP group (68 of 190 [35.8%]) (odds ratio [OR], 3.60; 95% CI, 2.12-6.10). Withdrawal did not differ significantly between conditions (proportion of days with a moderate or greater maximum Clinical Opiate Withdrawal Scale score (>12) for RP vs SP: OR, 1.25; 95% CI, 0.62-2.50). Targeted safety events (RP: 12 [5.3%]; SP: 4 [2.1%]) and serious adverse events (RP: 15 [6.7%]; SP: 3 [1.6%]) were infrequent but occurred more often with RP than SP., Conclusions and Relevance: In this trial, the RP of XR-naltrexone initiation was noninferior to the standard approach and saved time, although it required more intensive medical management and safety monitoring. The results of this trial suggest that rapid initiation could make XR-naltrexone a more viable treatment for patients with OUD., Trial Registration: ClinicalTrials.gov Identifier: NCT04762537.

The COVID pandemic placed a spotlight on alcohol use and the hardships of working within the food and beverage industry, with millions left jobless. Following previous studies that have found elevated rates of alcohol problems among bartenders and servers, here we studied the alcohol use of bartenders and servers who were employed during COVID. From February 12-June 16, 2021, in the midst of the U.S. COVID national emergency declaration, survey data from 1,010 employed bartender and servers were analyzed to quantify rates of excessive or hazardous drinking along with regression predictors of alcohol use as assessed by the 10-item Alcohol Use Disorders Identification Test (AUDIT). Findings indicate that more than 2 out of 5 (44%) people surveyed reported moderate or high rates of alcohol problem severity (i.e., AUDIT scores of 8 or higher)-a rate 4 to 6 times that of the heavy alcohol use rate reported pre- or mid-pandemic by adults within and outside the industry. Person-level factors (gender, substance use, mood) along with the drinking habits of one's core social group were significantly associated with alcohol use. Bartenders and servers reported surprisingly high rates of alcohol problem severity and experienced risk factors for hazardous drinking at multiple ecological levels. Being a highly vulnerable and understudied population, more studies on bartenders and servers are needed to assess and manage the true toll of alcohol consumption for industry employees., Competing Interests: The authors have declared that no competing interests exist., (Copyright: This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.)

Background: Unhealthy alcohol consumption is a severe public health problem. But low to moderate alcohol consumption is associated with high subjective well-being, possibly because alcohol is commonly consumed socially together with friends, who often are important for subjective well-being. Disentangling the health and social complexities of alcohol behavior has been difficult using traditional rating scales with cross-section designs. We aim to better understand these complexities by examining individuals' everyday affective subjective well-being language, in addition to rating scales, and via both between- and within-person designs across multiple weeks., Method: We used daily language and ecological momentary assessment on 908 US restaurant workers (12692 days) over two-week intervals. Participants were asked up to three times a day to "describe your current feelings", rate their emotions, and report their alcohol behavior in the past 24 hours, including if they were drinking alone or with others., Results: Both between and within individuals, language-based subjective well-being predicted alcohol behavior more accurately than corresponding rating scales. Individuals self-reported being happier on days when drinking more, with language characteristic of these days predominantly describing socializing with friends. Between individuals (over several weeks), subjective well-being correlated much more negatively with drinking alone (r = -.29) than it did with total drinking (r = -.10). Aligned with this, people who drank more alone generally described their feelings as sad, stressed and anxious and drinking alone days related to nervous and annoyed language as well as a lower reported subjective well-being., Conclusions: Individuals' daily subjective well-being, as measured via language, in part, explained the social aspects of alcohol drinking. Further, being alone explained this relationship, such that drinking alone was associated with lower subjective well-being., Competing Interests: The authors have declared that no competing interests exist., (Copyright: This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.)

Opioid overdose (OD) has become a leading cause of accidental death in the United States, and overdose deaths reached a record high during the COVID-19 pandemic. Combating the opioid crisis requires targeting high-need populations by identifying individuals at risk of OD. While deep learning emerges as a powerful method for building predictive models using large scale electronic health records (EHR), it is challenged by the complex intrinsic relationships among EHR data. Further, its utility is limited by the lack of clinically meaningful explainability, which is necessary for making informed clinical or policy decisions using such models. In this paper, we present LIGHTED, an integrated deep learning model combining long short term memory (LSTM) and graph neural networks (GNN) to predict patients' OD risk. The LIGHTED model can incorporate the temporal effects of disease progression and the knowledge learned from interactions among clinical features. We evaluated the model using Cerner's Health Facts database with over 5 million patients. Our experiments demonstrated that the model outperforms traditional machine learning methods and other deep learning models. We also proposed a novel interpretability method by exploiting embeddings provided by GNNs to cluster patients and EHR features respectively, and conducted qualitative feature cluster analysis for clinical interpretations. Our study shows that LIGHTED can take advantage of longitudinal EHR data and the intrinsic graph structure of EHRs among patients to provide effective and interpretable OD risk predictions that may potentially improve clinical decision support., Competing Interests: Declaration of competing interest The authors do not have any conflicts of interest to disclose., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Benevolent intersubjectivity developed in parent-infant interactions and compassion toward friend and foe alike are non-violent interventions to group behavior in conflict. Based on a dyadic active inference framework rooted in specific parental brain mechanisms, we suggest that interventions promoting compassion and intersubjectivity can reduce stress, and that compassionate mediation may resolve conflicts.

Background: Opioid addiction and overdose have a large burden of disease and mortality in New York State (NYS). The medication naloxone can reverse an overdose, and buprenorphine can treat opioid use disorder. Efforts to increase the accessibility of both medications include a naloxone standing order and a waiver program for prescribing buprenorphine outside a licensed drug treatment program. However, only a slim majority of NYS pharmacies are listed as participating in the naloxone standing order, and less than 7% of prescribers in NYS have a buprenorphine waiver. Therefore, there is a significant opportunity to increase access., Objective: Identifying the geographic regions of NYS that are farthest from resources can help target interventions to improve access to naloxone and buprenorphine. To maximize the efficiency of such efforts, we also sought to determine where these underserved regions overlap with the largest numbers of actual patients who have experienced opioid overdose., Methods: We used address data to assess the spatial distribution of naloxone pharmacies and buprenorphine prescribers. Using the home addresses of patients who had an opioid overdose, we identified geographic locations of resource deficits. We report findings at the high spatial granularity of census tracts, with some neighboring census tracts merged to preserve privacy., Results: We identified several hot spots, where many patients live far from the nearest resource of each type. The highest density of patients in areas far from naloxone pharmacies was found in eastern Broome county. For areas far from buprenorphine prescribers, we identified subregions of Oswego county and Wayne county as having a high number of potentially underserved patients., Conclusions: Although NYS is home to thousands of naloxone pharmacies and potential buprenorphine prescribers, access is not uniform. Spatial analysis revealed census tract areas that are far from resources, yet contain the residences of many patients who have experienced opioid overdose. Our findings have implications for public health decision support in NYS. Our methods for privacy can also be applied to other spatial supply-demand problems involving sensitive data., (©Kayley Abell-Hart, Sina Rashidian, Dejun Teng, Richard N Rosenthal, Fusheng Wang. Originally published in JMIR Public Health and Surveillance (https://publichealth.jmir.org), 12.04.2022.)

Objective: The United States is experiencing an opioid epidemic. In recent years, there were more than 10 million opioid misusers aged 12 years or older annually. Identifying patients at high risk of opioid use disorder (OUD) can help to make early clinical interventions to reduce the risk of OUD. Our goal is to develop and evaluate models to predict OUD for patients on opioid medications using electronic health records and deep learning methods. The resulting models help us to better understand OUD, providing new insights on the opioid epidemic. Further, these models provide a foundation for clinical tools to predict OUD before it occurs, permitting early interventions., Methods: Electronic health records of patients who have been prescribed with medications containing active opioid ingredients were extracted from Cerner's Health Facts database for encounters between January 1, 2008, and December 31, 2017. Long short-term memory models were applied to predict OUD risk based on five recent prior encounters before the target encounter and compared with logistic regression, random forest, decision tree, and dense neural network. Prediction performance was assessed using F1 score, precision, recall, and area under the receiver-operating characteristic curve., Results: The long short-term memory (LSTM) model provided promising prediction results which outperformed other methods, with an F1 score of 0.8023 (about 0.016 higher than dense neural network (DNN)) and an area under the receiver-operating characteristic curve (AUROC) of 0.9369 (about 0.145 higher than DNN)., Conclusions: LSTM-based sequential deep learning models can accurately predict OUD using a patient's history of electronic health records, with minimal prior domain knowledge. This tool has the potential to improve clinical decision support for early intervention and prevention to combat the opioid epidemic., (© The Author(s) 2021. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

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.

Background: Opioid overdose-related deaths have increased dramatically in recent years. Combating the opioid epidemic requires better understanding of the epidemiology of opioid poisoning (OP) and opioid use disorder (OUD)., Objective: We aimed to discover geospatial patterns in nonmedical opioid use and its correlations with demographic features related to despair and economic hardship, most notably the US presidential voting patterns in 2016 at census tract level in New York State., Methods: This cross-sectional analysis used data from New York Statewide Planning and Research Cooperative System claims data and the presidential voting results of 2016 in New York State from the Harvard Election Data Archive. We included 63,958 patients who had at least one OUD diagnosis between 2010 and 2016 and 36,004 patients with at least one OP diagnosis between 2012 and 2016. Geospatial mappings were created to compare areas of New York in OUD rates and presidential voting patterns. A multiple regression model examines the extent that certain factors explain OUD rate variation., Results: Several areas shared similar patterns of OUD rates and Republican vote: census tracts in western New York, central New York, and Suffolk County. The correlation between OUD rates and the Republican vote was .38 (P<.001). The regression model with census tract level of demographic and socioeconomic factors explains 30% of the variance in OUD rates, with disability and Republican vote as the most significant predictors., Conclusions: At the census tract level, OUD rates were positively correlated with Republican support in the 2016 presidential election, disability, unemployment, and unmarried status. Socioeconomic and demographic despair-related features explain a large portion of the association between the Republican vote and OUD. Together, these findings underscore the importance of socioeconomic interventions in combating the opioid epidemic., (©Anthony Xiang, Wei Hou, Sina Rashidian, Richard N Rosenthal, Kayley Abell-Hart, Xia Zhao, Fusheng Wang. Originally published in JMIR Public Health and Surveillance (https://publichealth.jmir.org), 21.04.2021.)

The US is experiencing an opioid epidemic, and opioid overdose is causing more than 100 deaths per day. Early identification of patients at high risk of Opioid Overdose (OD) can help to make targeted preventative interventions. We aim to build a deep learning model that can predict the patients at high risk for opioid overdose and identify most relevant features. The study included the information of 5,231,614 patients from the Health Facts database with at least one opioid prescription between January 1, 2008 and December 31, 2017. Potential predictors (n = 1185) were extracted to build a feature matrix for prediction. Long Short-Term Memory (LSTM) based models were built to predict overdose risk in the next hospital visit. Prediction performance was compared with other machine learning methods assessed using machine learning metrics. Our sequential deep learning models built upon LSTM outperformed the other methods on opioid overdose prediction. LSTM with attention mechanism achieved the highest F-1 score (F-1 score: 0.7815, AUCROC: 0.8449). The model is also able to reveal top ranked predictive features by permutation important method, including medications and vital signs. This study demonstrates that a temporal deep learning based predictive model can achieve promising results on identifying risk of opioid overdose of patients using the history of electronic health records. It provides an alternative informatics-based approach to improving clinical decision support for possible early detection and intervention to reduce opioid overdose., (Copyright © 2021 Elsevier Inc. All rights reserved.)

Opioid overdose related deaths have increased dramatically in recent years. Combating the opioid epidemic requires better understanding of the epidemiology of opioid poisoning (OP). To discover trends and patterns of opioid poisoning and the demographic and regional disparities, we analyzed large scale patient visits data in New York State (NYS). Demographic, spatial, temporal and correlation analyses were performed for all OP patients extracted from the claims data in the New York Statewide Planning and Research Cooperative System (SPARCS) from 2010 to 2016, along with Decennial US Census and American Community Survey zip code level data. 58,481 patients with at least one OP diagnosis and a valid NYS zip code address were included. Main outcome and measures include OP patient counts and rates per 100,000 population, patient level factors (gender, age, race and ethnicity, residential zip code), and zip code level social demographic factors. The results showed that the OP rate increased by 364.6%, and by 741.5% for the age group > 65 years. There were wide disparities among groups by race and ethnicity on rates and age distributions of OP. Heroin and non-heroin based OP rates demonstrated distinct temporal trends as well as major geospatial variation. The findings highlighted strong demographic disparity of OP patients, evolving patterns and substantial geospatial variation.

Background: In recent years, both suicide and overdose rates have been increasing. Many individuals who struggle with opioid use disorder are prone to suicidal ideation; this may often result in overdose. However, these fatal overdoses are difficult to classify as intentional or unintentional. Intentional overdose is difficult to detect, partially due to the lack of predictors and social stigmas that push individuals away from seeking help. These individuals may instead use web-based means to articulate their concerns., Objective: This study aimed to extract posts of suicidality among opioid users on Reddit using machine learning methods. The performance of the models is derivative of the data purity, and the results will help us to better understand the rationale of these users, providing new insights into individuals who are part of the opioid epidemic., Methods: Reddit posts between June 2017 and June 2018 were collected from r/suicidewatch, r/depression, a set of opioid-related subreddits, and a control subreddit set. We first classified suicidal versus nonsuicidal languages and then classified users with opioid usage versus those without opioid usage. Several traditional baselines and neural network (NN) text classifiers were trained using subreddit names as the labels and combinations of semantic inputs. We then attempted to extract out-of-sample data belonging to the intersection of suicide ideation and opioid abuse. Amazon Mechanical Turk was used to provide labels for the out-of-sample data., Results: Classification results were at least 90% across all models for at least one combination of input; the best classifier was convolutional neural network, which obtained an F 1 score of 96.6%. When predicting out-of-sample data for posts containing both suicidal ideation and signs of opioid addiction, NN classifiers produced more false positives and traditional methods produced more false negatives, which is less desirable for predicting suicidal sentiments., Conclusions: Opioid abuse is linked to the risk of unintentional overdose and suicide risk. Social media platforms such as Reddit contain metadata that can aid machine learning and provide information at a personal level that cannot be obtained elsewhere. We demonstrate that it is possible to use NNs as a tool to predict an out-of-sample target with a model built from data sets labeled by characteristics we wish to distinguish in the out-of-sample target., (©Hannah Yao, Sina Rashidian, Xinyu Dong, Hongyi Duanmu, Richard N Rosenthal, Fusheng Wang. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 27.11.2020.)

Opioid addiction in the United States has come to national attention as opioid overdose (OD) related deaths have risen at alarming rates. Combating opioid epidemic becomes a high priority for not only governments but also healthcare providers. This depends on critical knowledge to understand the risk of opioid overdose of patients. In this paper, we present our work on building machine learning based prediction models to predict opioid overdose of patients based on the history of patients' electronic health records (EHR). We performed two studies using New York State claims data (SPARCS) with 440,000 patients and Cerner's Health Facts database with 110,000 patients. Our experiments demonstrated that EHR based prediction can achieve best recall with random forest method (precision: 95.3%, recall: 85.7%, F1 score: 90.3%), best precision with deep learning (precision: 99.2%, recall: 77.8%, F1 score: 87.2%). We also discovered that clinical events are among critical features for the predictions., (©2019 AMIA - All rights reserved.)

Opioid use disorder (OUD) is epidemic in the United States. In addition to medical, economic, and social impairments, risk of overdose fatality is high. In 2017, there were 14,958 deaths from natural or semisynthetic opioids, 15,958 from heroin, and 29,406 from synthetic opioids, such as fentanyl. Psychosocial interventions do not add substantial efficacy to medical OUD treatments, and thus making evidence-based OUD treatments more accessible is urgent. However, considerable diversion of oral and transmucosal opioid maintenance medications has been documented. Delivery systems that reduce risks of nonadherence through diversion or altered self-administration may increase buprenorphine's effectiveness for clinical stabilization via increased treatment exposure. The article presents findings from multisite efficacy studies of two subcutaneous depot buprenorphine formulations and a long-acting implant. Novel delivery systems show promise in providing improved outcomes through intermediate- and long-acting exposure to medication while reducing the risk of medication nonadherence, diversion, and accidental exposure., (Copyright © 2019by the American Psychiatric Association.)

Background: Several single-site alcohol treatment clinical trials have demonstrated efficacy for immediate-release (IR) gabapentin in reducing drinking outcomes among individuals with alcohol dependence. The purpose of this study was to conduct a large, multisite clinical trial of gabapentin enacarbil extended-release (GE-XR) (HORIZANT ® ), a gabapentin prodrug formulation, to determine its safety and efficacy in treating alcohol use disorder (AUD)., Methods: Men and women (n = 346) who met DSM-5 criteria for at least moderate AUD were recruited across 10 U.S. clinical sites. Participants received double-blind GE-XR (600 mg twice a day) or placebo and a computerized behavioral intervention (Take Control) for 6 months. Efficacy analyses were prespecified for the last 4 weeks of the treatment period., Results: The GE-XR and placebo groups did not differ significantly on the primary outcome measure, percentage of subjects with no heavy drinking days (28.3 vs. 21.5, respectively, p = 0.157). Similarly, no clinical benefit was found for other drinking measures (percent subjects abstinent, percent days abstinent, percent heavy drinking days, drinks per week, drinks per drinking day), alcohol craving, alcohol-related consequences, sleep problems, smoking, and depression/anxiety symptoms. Common side-effects were fatigue, dizziness, and somnolence. A population pharmacokinetics analysis revealed that patients had lower gabapentin exposure levels compared with those in other studies using a similar dose but for other indications., Conclusions: Overall, GE-XR at 600 mg twice a day did not reduce alcohol consumption or craving in individuals with AUD. It is possible that, unlike the IR formulation of gabapentin, which showed efficacy in smaller Phase 2 trials at a higher dose, GE-XR is not effective in treating AUD, at least not at doses approved by the U.S. Food and Drug Administration for treating other medical conditions., (Published 2018. This article is a U.S. Government work and is in the public domain in the USA.)

Background: Alcohol and drug use are leading causes of morbidity and mortality that frequently go unidentified in medical settings. As part of a multi-phase study to implement electronic health record-integrated substance use screening in primary care clinics, we interviewed key clinical stakeholders to identify current substance use screening practices, barriers to screening, and recommendations for its implementation., Methods: Focus groups and individual interviews were conducted with 67 stakeholders, including patients, primary care providers (faculty and resident physicians), nurses, and medical assistants, in two urban academic health systems. Themes were identified using an inductive approach, revised through an iterative process, and mapped to the Knowledge to Action (KTA) framework, which guides the implementation of new clinical practices (Graham et al. in J Contin Educ Health Prof 26(1):13-24, 2006)., Results: Factors affecting implementation based on KTA elements were identified from participant narratives. Identifying the problem: Participants consistently agreed that having knowledge of a patient's substance use is important because of its impacts on health and medical care, that substance use is not properly identified in medical settings currently, and that universal screening is the best approach. Assessing barriers: Patients expressed concerns about consequences of disclosing substance use, confidentiality, and the individual's own reluctance to acknowledge a substance use problem. Barriers identified by providers included individual-level factors such as lack of clinical knowledge and training, as well as systems-level factors including time pressure, resources, lack of space, and difficulty accessing addiction treatment. Adapting to the local context: Most patients and providers stated that the primary care provider should play a key role in substance use screening and interventions. Opinions diverged regarding the optimal approach to delivering screening, although most preferred a patient self-administered approach. Many providers reported that taking effective action once unhealthy substance use is identified is crucial., Conclusions: Participants expressed support for substance use screening as a valuable part of medical care, and identified individual-level as well as systems-level barriers to its implementation. These findings suggest that screening programs should clearly communicate the goals of screening to patients and proactively counteract stigma, address staff concerns regarding time and workflow, and provide education as well as treatment resources to primary care providers.

Smoking is highly prevalent in patients with schizophrenia and exerts a negative impact on cardiovascular mortality in these patients. Smoking has complex interactions with monoamine metabolism through the ability of cigarette smoke to suppress Type 1 T helper cell (Th1) type immunity, the immunophenotype that is implicated in phenylalanine hydroxylase (PAH) dysfunction and tryptophan (Trp) breakdown to kynurenine (Kyn) via indoleamine 2,3-dioxygenase. Nicotine also induces tyrosine hydroxylase (TH) gene expression, leading to increased synthesis of catecholamines. Furthermore, there is evidence for PAH dysfunction in schizophrenia. This study aimed to compare the plasma levels of selected monoamine precursors and their metabolites in smokers vs. non-smokers in a large sample of patients with schizophrenia. We measured plasma phenylalanine (Phe), tyrosine (Tyr), Trp, and Kyn levels using high-performance liquid chromatography and calculated Phe:Tyr and Kyn:Trp ratios in 920 patients with schizophrenia. Analysis of variance and linear regression analyses were used to compare these endpoints between three groups of patients with schizophrenia: (1) current smokers, (2) past smokers, and (3) non-smokers. There were significant differences among the three groups with regards to Tyr levels [F (2,789) = 3.77, p = 0.02], with current smokers having lower Tyr levels when compared with non-smokers (p = 0.02). Kyn levels and Kyn:Trp ratio were different among the three groups [F (2,738) = 3.17, p = 0.04, F (2,738) = 3.61, p = 0.03] with current smokers having lower Kyn levels (p = 0.04) and higher Kyn:Trp ratio (p = 0.02) when compared with past smokers. These findings need to be replicated with protocols that include healthy controls to further elucidate the neurobiological underpinnings of altered Tyr and Kyn levels in smokers. Results do suggest potential molecular links between schizophrenia and smoking that may represent biomarkers and treatment targets for reducing an important modifiable cause of general morbidity and mortality in patients with schizophrenia.

Importance: The effectiveness of buprenorphine treatment of opioid dependence is limited by suboptimal medication adherence, abuse, and diversion., Objective: To determine whether 6-month buprenorphine implants are noninferior to daily sublingual buprenorphine as maintenance treatment for opioid-dependent patients with stable abstinence., Design, Setting, and Participants: Outpatient, randomized, active-controlled, 24-week, double-blind, double-dummy study conducted at 21 US sites from June 26, 2014, through May 18, 2015. Outpatients were prescribed daily sublingual buprenorphine for 6 months or more, were abstinent while taking 8 mg/d or less of sublingual buprenorphine for 90 days or longer, and were determined to be clinically stable by their physician., Interventions: Participants were randomized to receive sublingual buprenorphine plus 4 placebo implants or sublingual placebo plus four 80-mg buprenorphine hydrochloride implants (expected efficacy, 24 weeks)., Main Outcome Measure: The primary end point was between-group difference in proportion of responders (≥4 of 6 months without opioid-positive urine test result [monthly and 4 times randomly] and self-report). The noninferiority established for the lower bound of the 95% confidence interval was greater than -0.20 (P < .025). Secondary end points included cumulative percentage of negative opioid urine results, abstinence, and time to first illicit opioid use. Safety was assessed by adverse event reporting., Results: Of 177 participants (mean age, 39 years; 40.9% female), 90 were randomized to sublingual buprenorphine with placebo implants and 87 to buprenorphine implants with sublingual placebo; 165 of 177 (93.2%) completed the trial. Eighty-one of 84 (96.4%) receiving buprenorphine implants and 78 of 89 (87.6%) receiving sublingual buprenorphine were responders, an 8.8% difference (1-sided 97.5% CI, 0.009 to ∞; P < .001 for noninferiority). Over 6 months, 72 of 84 (85.7%) receiving buprenorphine implants and 64 of 89 (71.9%) receiving sublingual buprenorphine maintained opioid abstinence (hazard ratio, 13.8; 95% CI, 0.018-0.258; P = .03). Non-implant-related and implant-related adverse events occurred in 48.3% and 23% of the buprenorphine implant group and in 52.8% and 13.5% of participants in the sublingual buprenorphine group, respectively., Conclusions and Relevance: Among adults with opioid dependence maintaining abstinence with a stable dose of sublingual buprenorphine, the use of buprenorphine implants compared with continued sublingual buprenorphine did not result in an inferior likelihood of remaining a responder. However, the study population had an exceptionally high response rate in the control group, and further studies are needed in broader populations to assess the efficacy in other settings., Trial Registration: clinicaltrials.gov Identifier: NCT02180659.

Aims: To evaluate the safety and efficacy of buprenorphine implants (BI) versus placebo implants (PI) for the treatment of opioid dependence. A secondary aim compared BI to open-label sublingual buprenorphine/naloxone tablets (BNX)., Design: Randomized, double-blind, placebo-controlled trial. Subjects received either four buprenorphine implants (80 mg/implant) (n = 114), four placebo implants (n = 54) or open-label BNX (12-16 mg/day) (n = 119)., Setting: Twenty addiction treatment centers., Participants: Adult out-patients (ages 18-65) with DSM-IV-TR opioid dependence., Measurements: The primary efficacy end-point was the percentage of urine samples negative for opioids collected from weeks 1 to 24, examined as a cumulative distribution function (CDF)., Findings: The BI CDF was significantly different from placebo (P < 0.0001). Mean [95% confidence interval (CI)] proportions of urines negative for opioids were: BI = 31.2% (25.3, 37.1) and PI = 13.4% (8.3, 18.6). BI subjects had a higher study completion rate relative to placebo (64 versus 26%, P < 0.0001), lower clinician-rated (P < 0.0001) and patient-rated (P < 0.0001) withdrawal, lower patient-ratings of craving (P < 0.0001) and better subjects' (P = 0.031) and clinicians' (P = 0.022) global ratings of improvement. BI also resulted in significantly lower cocaine use (P = 0.0016). Minor implant-site reactions were comparable in the buprenorphine [27.2% (31 of 114)] and placebo groups [25.9% (14 of 54)]. BI were non-inferior to BNX on percentage of urines negative for opioids [mean (95% CI) = 33.5 (27.3, 39.6); 95% CI for the difference of proportions = (-10.7, 6.2)]., Conclusions: Compared with placebo, buprenorphine implants result in significantly less frequent opioid use and are non-inferior to sublingual buprenorphine/naloxone tablets., (© 2013 Society for the Study of Addiction.)

Background: Cannabis use can frequently have adverse affects in those that use it and these can be amplified by various characteristics of an individual, from demographic and environmental variations to familial predisposition for mental illnesses., Methods: The current study of 100 individuals, who were cannabis users during their adolescence and may still be users, was a survey of the self perceived effects of cannabis and their correlates. A reliable family member was also interviewed for determination of family history of various major mental illnesses and substance use., Results: As many as 40% of cannabis users had paranoid feelings (suspiciousness) when using cannabis, although the most frequent effect was feeling relaxed (46%). Having a familial background for mental illnesses such as depression or schizophrenia did not determine the effects of cannabis nor its pattern of use, although the number of subjects with such a history was small. An age at which an individual began using cannabis did have an effect on how heavily it was used and the heavier the cannabis use, the more likely the individual was also to have had psychotic symptoms after use. There were no sex differences in effects of cannabis. These results are tempered by the reliance on self-report for many of the variables ascertained., Conclusion: Cannabis can frequently have negative effects in its users, which can be amplified by certain demographic and/or psychosocial factors. Thus, users with a specific profile may be at a higher risk of unpleasant effects from cannabis use and caution should be noted when cannabis is administered to young people for medicinal purposes.

The authors conducted systematic searches in standard databases using key search terms related to epidemiology, prevalence, and co-occurring substance use and other mental disorders (COD), as well as specific combinations of drug and mental disorders. The authors targeted high-quality, large sample epidemiological surveys so as to utilize studies of high methodological rigor in the construction of recommendations for clinical identification. Further refined searches to identify these studies revealed common themes and related research gaps. Findings suggest that clinicians should have increased expectation that a patient with a substance use disorder (SUD) has a co-occurring mental disorder if the SUD is relatively severe, if the patient began using substances (including tobacco) at an early age, is female, is dependent on nicotine, or has a drug use disorder. Patients identified as having at least one SUD and one co-occurring mental disorder should be assessed to identify other likely CODs, because disorders are not normally distributed and tend to cluster in relatively few individuals., (Copyright © American Academy of Addiction Psychiatry.)

Context: Limitations of existing pharmacological treatments for opioid dependence include low adherence, medication diversion, and emergence of withdrawal symptoms., Objective: To determine the efficacy of buprenorphine implants that provide a low, steady level of buprenorphine over 6 months for the treatment of opioid dependence., Design, Setting, and Participants: A randomized, placebo-controlled, 6-month trial conducted at 18 sites in the United States between April 2007 and June 2008. One hundred sixty-three adults, aged 18 to 65 years, diagnosed with opioid dependence. One hundred eight were randomized to receive buprenorphine implants and 55 to receive placebo implants., Intervention: After induction with sublingual buprenorphine-naloxone tablets, patients received either 4 buprenorphine implants (80 mg per implant) or 4 placebo implants. A fifth implant was available if a threshold for rescue use of sublingual buprenorphine-naloxone treatment was exceeded. Standardized individual drug counseling was provided to all patients., Main Outcome Measure: The percentage of urine samples negative for illicit opioids for weeks 1 through 16 and for weeks 17 through 24., Results: The buprenorphine implant group had significantly more urine samples negative for illicit opioids during weeks 1 through 16 (P = .04). Patients with buprenorphine implants had a mean percentage of urine samples that tested negative for illicit opioids across weeks 1 through 16 of 40.4% (95% confidence interval [CI], 34.2%-46.7%) and a median of 40.7%; whereas those in the placebo group had a mean of 28.3% (95% CI, 20.3%-36.3%) and a median of 20.8%. A total of 71 of 108 patients (65.7%) who received buprenorphine implants completed the study vs 17 of 55 (30.9%) who received placebo implants (P < .001). Those who received buprenorphine implants also had fewer clinician-rated (P <.001) and patient-rated (P = .004) withdrawal symptoms, had lower patient ratings of craving (P <.001), and experienced a greater change on clinician global ratings of severity of opioid dependence (P<.001) and on the clinician global ratings of improvement (P < .001) than those who received placebo implants. Minor implant site reactions were the most common adverse events: 61 patients (56.5%) in the buprenorphine group and 29 (52.7%) in the placebo group., Conclusion: Among persons with opioid dependence, the use of buprenorphine implants compared with placebo resulted in less opioid use over 16 weeks as assessed by urine samples., Trial Registration: clinicaltrials.gov Identifier: NCT00447564.

Background: Opiate-dependent individuals are prone to dysphoria that may contribute to treatment failure. Methadone-maintenance therapy (MMT) may mitigate this vulnerability, but controversy surrounds its long-term use. Little is known about the neurobiology of mood dysregulation in individuals receiving or removed from MMT., Methods: Fifteen opiate-abstinent and 12 methadone-maintained, opiate-dependent subjects, who lacked other Axis I pathology, and 13 control subjects were compared on the Cornell Dysthymia Rating Scale (CDRS) and regional cerebral glucose metabolism (rCMRglc) using [(18)F]fluorodeoxyglucose positron emission tomography., Results: CDRS scores showed no group differences. Opiate-abstinent subjects had lower rCMRglc than control subjects in the bilateral perigenual anterior cingulate cortex (ACC), left mid-cingulate cortex, left insula and right superior frontal cortex. Methadone-maintained subjects exhibited lower rCMRglc than control subjects in the left insula and thalamus. In opiate-abstinent subjects, rCMRglc in the left perigenual ACC and mid-cingulate cortex correlated positively with CDRS scores., Conclusions: In remitted heroin dependence, opiate-abstinence is associated with more widespread patterns of abnormal cortical activity than MMT. Aberrant mood processing in the left perigenual ACC and mid-cingulate cortex, seen in opiate-abstinent individuals, is absent in those receiving MMT, suggesting that methadone may improve mood regulation in this population.

The genetic predisposition to addiction to opioids and other substances is transmitted as a complex genetic trait, which investigators are attempting to characterize using genetic linkage and association. We now report a high-density genome-wide linkage study of opioid dependence. We ascertained 305 DSM-IV opioid dependent affected sibling pairs from an ethnically mixed population of methadone maintained subjects and genotyped their DNA using Affymetrix 10K v2 arrays. Analysis with MERLIN identified a region on chromosome 14q with a non-parametric lod (NPL) of 3.30. Secondary analyses indicated that this locus was relatively specific to the self-identified Puerto Rican subset, as the NPL increased from 3.30 to 5.00 (NPL(Caucasian) = 0.05 and NPL(African Amer.) = 0.15). The 14q peak encompasses the NRXN3 gene (neurexin 3), which was previously identified as a potential candidate gene for addiction. Secondary analyses also identified several regions with gender-specific NPL scores greater than 2.00. The most significant was a peak on (10q) that increased from 0.90 to 3.22 when only males were considered (NPL(female) = 0.05). Our linkage data suggest specific chromosomal loci for future fine-mapping genetic analysis and support the hypothesis that ethnic and gender specific genes underlie addiction susceptibility.

Gabapentin was compared with phenobarbital for the treatment of alcohol withdrawal in a randomized, open-label, controlled trial in 27 inpatients. There were no significant differences in the proportion of treatment completers between treatment groups or the proportion of patients in each group requiring rescue medication for breakthrough signs and symptoms of alcohol withdrawal. There were no significant treatment differences in withdrawal symptoms or psychological distress, nor were there serious adverse events. These findings suggest that gabapentin may be as effective as phenobarbital in the treatment of alcohol withdrawal. Given gabapentin's favorable pharmacokinetic profile, further study of its effectiveness in treating alcohol withdrawal is warranted.

This final article, coauthored by a chronobiology consultant, a sports psychologist who applied a chronobiology-based program to an Olympic national team, a clinical neurologist, a performance data analyst, a training-conditioning coach from a major league baseball team who applied chronobiology principles to major league pitchers, and a substance abuse expert, discusses practical aspects of a sports chronobiology consultation, including the goals and current arsenal of available interventions. Short vignettes of actual cases are presented for edification, and references are made to appropriate reviews found elsewhere in this issue.

Although alcohol use disorders are commonly associated with co-morbid drug use and psychiatric disorders, such co-morbidity is frequently underdiagnosed and inadequately treated. This paper reviews the epidemiological, diagnostic, and treatment literature on the co-morbidity of alcoholism, with a focus on the most common co-morbid disorders: drug abuse, mood disorders, anxiety disorders, and antisocial personality disorder. The paper goes on to describe a number of promising approaches to the treatment of these common co-morbid disorders in alcoholics. Despite the difficulties inherent in treating dual diagnosis patients, the clinician must recognize that it is possible to derive valid diagnoses and deliver efficacious treatment to such patients.

Over the past decade, several studies have attempted to determine whether integrating psychiatric and substance abuse treatment leads to better outcome for patients with comorbid schizophrenia and substance use disorders. A recent (1999) Cochrane Review (1) analyzed the effectiveness of prospective randomized studies of integrated treatment approaches, and concluded that there was no clear evidence for superiority of integrated treatment. This paper describes one such integrated treatment approach, in Beth Israel Medical Center's COPAD (Combined Psychiatric and Addictive Disorders) program. We summarize findings from an initial outcome study and a recent replication study; and describe clinical and research issues relevant to this population. Our data suggests the benefits of integrated treatment for patients with addictive disorders and schizophrenia, at least with regard to treatment retention. Clinical issues for such patients include identification of patients at risk, proper assessment and treatment planning, decision-making about mainstreaming vs. referral to specialized programs, and the importance of initial engagement and ongoing reengagement in successful treatment.

Objective: It is proposed that the pruritus of cholestasis is, in part, centrally mediated by endogenous opioid peptides. The expression of these peptides and their receptors on neurons displays a circadian rhythm, as does the scratching activity in patients with cholestasis and pruritus. Because light has regulatory effects on circadian rhythms via retinothalamic pathways, we hypothesized that bright-light therapy (BLT) reflected toward the eyes might alter the pruritus of cholestasis. To test this hypothesis, we studied the effect of BLT on this form of pruritus., Methods: Eight patients with chronic liver disease of different etiologies and pruritus were studied in an open-label, pilot study of 8-wk duration. BLT (10,000 lux) was administered for up to 60 min twice a day. Pruritus was assessed subjectively by a visual analog scale from which a visual analog score (VAS) was derived, and objectively, by a scratching activity monitoring system that recorded hourly scratching activity (HSA)., Results: In seven of the eight patients studied, the mean HSA was lower during BLT. BLT was associated with a mean decrease in HSA of 32.2% (p = 0.123). The mean VAS for pruritus was lower in six patients during BLT; the mean VAS score derived from the eight patients studied decreased by 42% (p = 0.05) during treatment., Conclusions: The results of this short-term study suggest that the pruritus of cholestasis is responsive to bright light reflected toward the eyes and that in some patients, BLT may ameliorate this form of pruritus.

Patients with dysthymia have been shown to respond to treatment with antidepressant medications, and to some degree to psychotherapy. Even patients successfully treated with medication often have residual symptoms and impaired psychosocial functioning. The authors describe a prospective randomized 36-week study of dysthymic patients, comparing continued treatment with antidepressant medication (fluoxetine) alone and medication with the addition of group therapy treatment. After an 8-week trial of fluoxetine, medication-responsive subjects were randomly assigned to receive either continued medication only or medication plus 16 sessions of manualized group psychotherapy. Results provide preliminary evidence that group therapy may provide additional benefit to medication-responding dysthymic patients, particularly in interpersonal and psychosocial functioning.

The authors describe the use of gabapentin in the treatment of 4 outpatients with dementia-associated agitation. On the basis of clinical case reports and the Overt Agitation Severity Scale, all 4 patients had reduced agitation with gabapentin. Three of 4 patients were successfully titrated to a full dose of 2,400mg/day. These findings suggest a possible role for gabapentin in the behavioral management of patients with dementia.

Background: The long-term effects of opiate use on human brain are not known. The goal of this preliminary study was to determine whether human subjects with histories of opiate dependence have persistent differences in brain function as compared with individuals without substance use disorders, and whether methadone maintenance reverses or ameliorates the potential abnormality., Method: Positron emission tomographic (PET) [18F]fluorodeoxyglucose (FDG) method was used to compare the regional cerebral metabolic rate for glucose(rCMRglc) in three groups: four opiate-dependent subjects currently receiving methadone maintenance therapy (MM), four opiate-dependent subjects not receiving methadone maintenance therapy (MW), and a comparison group of five subjects without substance use disorders., Results: A significant difference in rCMRglc in the anterior cingulate gyrus was found between the MW and Control groups (Mann-Whitney U=2.0, p=0.05). Generally speaking, rCMRglc's in MM subjects were intermediate between those of MW and Control groups, although the difference did not reach statistical significance., Conclusions: The results of this study suggest that neurobiological abnormalities can persist in the brain of a chronic opiate user several years after detoxification from methadone. Future research is needed to replicate these results and to determine whether the observed rCMRglc differences are related to opiate use or to neurochemical abnormalities that play a role in developing addictive behavior.

Objective: The purpose of the current study was to examine the relation between regional cerebral blood flow (rCBF) and negative symptoms (NS) in patients with dementia of Alzheimer type (DAT)., Background: Negative symptoms in neuropsychiatric disorders were associated with altered rCBF in frontal cortex., Methods: Twenty-five subjects with a diagnosis of DAT were administered the Scale for the Assessment of Negative Symptoms (SANS), the Positive and Negative Symptom Scale, the Hamilton Rating Scale for Depression, and the Mini-Mental State Examination. The subjects were divided into two groups by means of a median split with regard to NS severity (high NS group, N = 12; low NS group, N = 13). Each patient underwent a single photon emission tomography scan using 99mTc-HMPAO at rest. Cortical and subcortical regions of interest were symmetrically defined in each hemisphere. Cortical-to-cerebellar perfusion ratios were established quantitatively using ADAC software., Results: High NS group subjects had a significantly lower rCBF than low NS group subjects in the frontal cortex and cingulate gyrus (MANOVA: p = 0.022) as a result of differences in the dorsolateral prefrontal cortex bilaterally (right: F = 12.12, p = 0.002; left: F = 6.55, p = 0.02) and in the frontal cortex, mainly in the right hemisphere (right: F = 6.33, p = 0.02; left: F = 3.26, p = 0.08). For all the subjects (N = 25), there were negative correlations between the SANS total score and rCBF, most prominently in the dorsolateral prefrontal cortex bilaterally (right: r = -0.48, p <0.01; left: r = -0.49, p = 0.01). No significant correlation was found between rCBF in any of the regions of interest and either the Mini-Mental State Examination or the Hamilton Rating Scale for Depression scores., Conclusions: This study indicates that decreased perfusion in the frontal cortex is associated with NS severity but not with measures of cognitive impairment or depressive symptoms in DAT patients. These results support the hypothesis that the frontal lobes may be involved in the cause of NS in DAT, and they underscore the importance of NS evaluation in neuroimaging studies.

As a substudy of a manual-based outcome study of the Beth Israel Brief Psychotherapy Program, the authors studied the efficacy of supportive psychotherapy in personality change, with particular attention to changes that outlast the period of treatment. They examined results from the Inventory of Interpersonal Problems (IIP) at intake, 40th-session termination, and 6-month follow-up in the first 20 subjects randomized to the supportive group. Eight subjects (40%) dropped out, but their initial IIP scores did not differ from those of follow-up completers. Six of 10 subjects with complete 6-month follow-up data showed significant improvement in interpersonal problems (4 cases P < 0.001; 2 cases P < 0.05). In a case method design, using the IIP mapped to an interpersonal circumplex model, the authors graphically demonstrate lasting positive changes in interpersonal functioning in subjects treated with supportive psychotherapy.