Initial development of a brief assessment of cocaine demand.

Cocaine demand is a behavioral economic measure assessing drug reward value and motivation to use drug. The purpose of the current study was to develop a brief assessment of cocaine demand (BACD). Results from the BACD were compared with self-report measures of cocaine use. Participants consisted of treatment-seeking individuals with cocaine use disorder (N = 22). Results revealed that indices of brief demand were significantly associated with various self-report measures of cocaine use. Overall, these results support the utility of a BACD for assessing cocaine demand.

A meta-analysis of tract-based spatial statistics studies examining white matter integrity in cocaine use disorder.

Tract-based spatial statistics (TBSS) of diffusion tensor imaging (DTI) studies have consistently shown diminished white matter (WM) integrity for individuals with cocaine use disorder (CUD). The present study used seed-based d mapping (SDM) to determine the extent to which a systematic difference in the WM integrity of cocaine users may exist (as compared with that of healthy controls). Articles from 2006 (when TBSS was first developed) to present were reviewed, with eight selected for inclusion. Meta-analysis found lower fractional anisotropy (FA) in the genu of the corpus callosum for cocaine users, with a small-to-moderate peak effect size (Hedge's g = -0.331). Sensitivity analyses mostly supported the robustness of the obtained difference. Differences detected at exploratory thresholds for significance suggested insult to WM integrity extending beyond the corpus callosum. The present results compliment a previous region-of-interest (ROI)-based meta-analysis of DTI studies in individuals with CUD. These findings have significant implications for the potential role of neuroprotective agents in the treatment of CUD and merit additional iteration as more studies accrue in the literature.

Patterns of tobacco use among smokers prior to hospitalization for an acute cardiac event: Use of combusted and non-combusted products.

Use of tobacco products before or after a cardiac event increases risk of morbidity and mortality. Unlike cigarette smoking, which is generally screened in the healthcare system, identifying the use of other tobacco products remains virtually unexplored. This study aimed at characterizing the use of other non-combusted tobacco products in addition to combusted products among cardiac patients and identifying a profile of patients who are more likely to use non-combusted products. Patients (N = 168) hospitalized for a coronary event who reported being current cigarette smokers completed a survey querying sociodemographics, cardiac diagnoses, use of other tobacco products, and perceptions towards these products. Classification and regression tree (CART) analysis was used to identify which interrelationships of participants characteristics led to profiles of smoking cardiac patients more likely to also be using non-combusted tobacco products. Results showed that non-combusted tobacco product use ranged from 0% to 47% depending on patient characteristic combinations. Younger age and lower perception that cigarette smoking is responsible for their cardiac condition were the strongest predictive factors for use of non-combusted products. Tobacco product use among cardiac patients extends beyond combusted products (13.7% non-combusted product use), and consequently, screening in health care settings should be expanded to encompass other tobacco product use. This study also characterizes patients likely to be using non-combusted products in addition to combusted, a group at high-risk due to their multiple product use, but also a group that may be amenable to harm reduction approaches and evidence-based tobacco treatment strategies.

Comparison of three measurement models of discounting among individuals with methamphetamine use disorder.

BACKGROUND AND OBJECTIVES: Delay discounting is associated with numerous clinically significant aspects of substance use disorders (SUDs). Recent studies have demonstrated that different models for assessing discounting may result in disparate conclusions. The current study compared two discounting tasks: money now versus money later (M-M) and methamphetamine now versus money later (MA-M) among non-treatment seeking individuals (N = 59) with methamphetamine use disorder (MAUD). Results from each task were assessed using three different models for assessing delay discounting. METHODS: Discounting data were fit to three models of discounting, log k using Mazur's hyperbolic formula, area under the curve (AUC), and an alternative AUC model in which the delay values have been log transformed (AUClog). RESULTS: For both discounting tasks, the distribution of model-related outcomes were normally distributed when using log k and AUClog, but skewed for AUC. Discounting in the MA-M task was significantly greater compared to the M-M task when using log k and AUClog but not AUC. CONCLUSION: To our knowledge, the current study is the first to report significantly greater discounting in a MA-M relative to M-M discounting task among individuals with MAUD, an outcome consistent with other psychomotor stimulants and drugs of abuse. SCIENTIFIC SIGNIFICANCE: The differential results observed across the three discounting models reaffirm potential issues with AUC noted in recent studies and highlight that researchers must be cautious when deciding on their final model of discounting. (Am J Addict 2018;XX:1-8).

A COMPARISON OF MAZUR'S k AND AREA UNDER THE CURVE FOR DESCRIBING STEEP DISCOUNTERS.

Delay discounting describes how a reward loses value as a function of increasing delay to its receipt and has been reliably associated with a variety of vulnerable populations including those with substance use disorders (SUDs). Two commonly used models to assess delay discounting in the field of SUDs include log k derived from Mazur's hyperbolic equation and area under the curve (AUC). In the current study, we compared log k with AUC on delay discounting data obtained from non-treatment seeking, cocaine- and methamphetamine-dependent volunteers. We specifically chose this population in order to obtain a distribution of relatively steep discounters. The results show that the relationship between AUC and log k is better described by a quadratic rather than a linear function. In other words, changes in discounting, as measured by AUC and log k, are reflected differently across a range of obtained responses. Additionally, the distribution of AUC values was skewed, which appears to be more likely among populations exhibiting greater discounting. Finally, closer examination of indifference points revealed that AUC was almost perfectly predicted by the area from the two longest delays, with relatively less input from shorter delays. Given these results, researchers should exercise additional caution when deciding which method to assess discounting data and how final results are to be interpreted, particularly when dealing with relatively high rates of discounting. High rates of discounting are likely in populations with impulsive disorders such as those with SUDs.

Behavioral therapies targeting reward mechanisms in substance use disorders.

Behavioral therapies are considered best practices in the treatment of substance use disorders (SUD) and used as first-line approaches for SUDs without FDA-approved pharmacotherapies. Decades of research on the neuroscience of drug reward and addiction have informed the development of current leading behavioral therapies that, while differing in focus and technique, have in common the overarching goal of shifting reward responding away from drug and toward natural non-drug rewards. This review begins by describing key neurobiological processes of reward in addiction, followed by a description of how various behavioral therapies address specific reward processes. Based on this review, a conceptual 'map' is crafted to pinpoint gaps and areas of overlap, serving as a guide for selecting and integrating behavioral therapies.

Contingency management plus acceptance and commitment therapy for initial cocaine abstinence: Results of a sequential multiple assignment randomized trial (SMART).

BACKGROUND: This study tested an adaptive intervention for optimizing abstinence outcomes over phases of treatment for cocaine use disorder using a SMART design. Phase 1 assessed whether 4 weeks of contingency management (CM) improved response with the addition of Acceptance and Commitment Therapy (ACT). Phase 2 assessed pharmacological augmentation with modafinil (MOD) vs. placebo (PLA) for individuals not achieving abstinence during Phase 1. METHOD: For Phase 1 of treatment, participants (N=118) were randomly allocated to ACT+CM or Drug Counseling (DC+CM), the comparison condition. At week 4, treatment response was defined as the submission of six consecutive cocaine-negative urine drug screens (UDS). Phase 1 non-responders were re-randomized to MOD or PLA as adjunct to their initial treatment. Phase 1 responders continued receiving their initial treatment. Primary outcomes included response rate and proportion of cocaine-negative UDS for Phase 1 and 2. Analyses used Bayesian inference with 80% pre-specified as the posterior probability (PP) threshold constituting moderate evidence that an effect exists. RESULTS: Phase 1 response was higher in the ACT+CM group (24.5%) compared to the DC+CM group (17.5%; PP = 84.5%). In Phase 2, the proportion of cocaine-negative UDS among Phase 1 responders did not differ by initial treatment (PP = 61.8%) but remained higher overall compared to Phase 1 non-responders (PPs > 99%). No evidence of an effect favoring augmentation with MOD was observed. DISCUSSION: Adding ACT to CM increased abstinence initiation. Initial responders were more likely to remain abstinent compared to initial non-responders, for whom modafinil was not an effective pharmacotherapy augmentation strategy.

Opioid Risk Tool, in-hospital opioid exposure, and opioid demand predict pain outcomes following traumatic injury.

Prescribed opioids are a mainstay pain treatment after traumatic injury, but a subgroup of patients may be at risk for continued opioid use. We evaluated the predictive utility of a traditional screening tool, the Opioid Risk Tool (ORT), and two other measures: average in-hospital milligram morphine equivalents (MME) per day and an assessment of opioid demand in predicting pain outcomes. Assessments of pain-related outcomes (pain intensity, interference, injury-related stress, and need for additional pain treatment) were administered at 2 weeks and 12 months post-discharge in a sample of 34 patients hospitalized for traumatic injury. Bayesian linear models were used to evaluate changes in responses over time as a function of predictors. High-risk ORT, higher MME per day, and greater opioid demand predicted less change in outcomes over time. This report provides first evidence that malleable factors of opioid and opioid demand have utility in predicting pain outcomes following traumatic injury.

Comparative assessment of psychometric performance on the adjusting amounts versus the 21-item Monetary Choice Delay Discounting tasks among young adult substance users.

Delay discounting (DD) assessments offer a wide variety of procedures to suit specific clinical and research needs. This study compared the reliability and validity of two DD tasks: (a) an adjusting amounts task presented on a computer (AAC) and (b) the 21-item Monetary Choice Task, which was administered online (MCT). Participants were 1,573 Spanish young-adults reporting past-month substance use. Measures included quantity and severity of drug use (i.e., cigarette smoking, cannabis, alcohol) and two DD assessments (i.e., AAC, MCT). Reliability was assessed using both the classical test and item response theory. Correlations and linear regressions examined the validity of both DD tasks in relation to substance use. The MCT showed higher internal consistency than the AAC (α = .941 vs. α = .748). AAC precision was adequate for moderate levels of discounting (θ values between -2 and +2), but the MCT showed superior reliability at low, moderate, and high levels of discounting (θ values between -1 and +1.5). Both DD tasks showed more significant correlations for alcohol-related measures (|rs| ranged between .053 and .093) compared to cigarettes and cannabis. The incremental validity of DD tasks in relation to nicotine dependence (AUClogd: ß = -.664, 95% CI [-1.256, -.071]) and alcohol problems (AUClogd: ß = -3.098, 95% CI [-5.209, -.988]) was only supported for the AAC. The MCT was more reliable than the AAC for measuring impulsive choice in young adult substance users. Nevertheless, the AAC may serve as a valid marker of nicotine dependence and alcohol problems. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Effects of short-term nicotine deprivation on delay discounting among young, experienced, exclusive ENDS users: An initial study.

Delay discounting describes how rapidly delayed rewards lose value as a function of delay and serves as one measure of impulsive decision-making. Nicotine deprivation among combustible cigarette smokers can increase delay discounting. We aimed to explore changes in discounting following nicotine deprivation among electronic nicotine delivery systems (ENDS) users. Thirty young adults (aged 18-24 years) that exclusively used ENDS participated in two laboratory sessions: one with vaping as usual and another after 16 hr of nicotine deprivation (biochemically assessed). At each session, participants completed a craving measure and three hypothetical delay discounting tasks presenting choices between small, immediate rewards and large, delayed ones (money-money; e-liquid-e-liquid; e-liquid-money). Craving for ENDS significantly increased during short-term nicotine deprivation relative to normal vaping. Delay discounting rates in the e-liquid now versus money later task increased (indicating a shift in preference for smaller, immediate rewards) following short-term nicotine deprivation relative to vaping as usual, but no changes were observed in the other two discounting tasks. Short-term nicotine deprivation increased the preference for smaller amounts of e-liquid delivered immediately over larger, monetary awards available after a delay in this first study of its kind. As similar preference shifts for drug now versus money later have been shown to be indicative of increased desire to use drug as well as relapse risk, the findings support the utility of the current model as a platform to explore interventions that can mitigate these preference shifts. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Naltrexone plus bupropion reduces cigarette smoking in individuals with methamphetamine use disorder: A secondary analysis from the CTN ADAPT-2 trial.

INTRODUCTION: Methamphetamine (MA) use is marked by high rates of comorbid tobacco smoking, which is associated with more severe drug use and worse clinical outcomes compared to single use of either drug. Research has shown the combination of naltrexone plus oral bupropion (NTX-BUP) improves smoking cessation outcomes in non-MA-using populations. In the Accelerated Development of Additive Pharmacotherapy Treatment (ADAPT-2) study, NTX-BUP successfully reduced MA use. Our aim in this secondary data analysis was to examine changes in cigarette smoking among the subgroup of participants reporting comorbid tobacco use in the ADAPT-2 trial. METHODS: The multi-site ADAPT-2 study used a randomized, double blind, sequential parallel comparison design to evaluate treatment with extended-release injectable NTX (380 mg every 3 weeks) combined with once-daily oral extended-release BUP (450 mg/day) vs matching injectable and oral placebo in outpatients with moderate or severe MA use disorder. The study assessed smoking outcomes, based on self-reported timeline followback (TLFB) data, twice/week for 13 weeks. RESULTS: Of the 403 participants in the ADAPT-2 trial, 290 reported being current cigarette smokers (71.9 %). The study found significant differences (p's < 0.0001) for each smoking outcome indicating greater change in the proportion of nonsmoking days, number of cigarettes smoked per week, and consecutive nonsmoking days, all favoring the group receiving NTX-BUP versus placebo. CONCLUSIONS: NTX-BUP was associated with significant reductions in self-reported cigarette smoking in the context of concurrent treatment for MA use disorder. These off-target medication effects warrant prospective investigation using biochemically confirmed measures of smoking abstinence. The development of NTX-BUP as a co-addiction treatment strategy has a potential for high public health impact.

Assessing cocaine motivational value: Comparison of brain reactivity bias toward cocaine cues and cocaine demand.

The behavioral economic measure drug demand and the neural measure late positive potential (LPP) are two measures of motivational value that have been associated with drug relapse risk and treatment outcomes. Despite having overlapping themes, no studies have directly compared drug demand and LPP. Participants (N = 59) included treatment-seeking individuals with cocaine use disorder that had completed both a baseline cocaine demand task and an electroencephalogram (EEG) picture-viewing task of drug-related and pleasant picture cues. Associations between the LPP difference score amplitude (drug-pleasant) and five demand indices (Q0, essential value [EV], Omax, Pmax, and breakpoint [BP]) were evaluated via Bayesian generalized linear modeling. Positive associations (posterior probabilities ≥ 75%) were found between LPP amplitude and four demand indices (Q0, EV, Omax, BP). These results suggest that individuals who attach greater relevance to cocaine cues also exhibit greater valuation of cocaine reward. Implications for incorporating methodology from behavioral science and brain imaging are discussed. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

An opioid-minimizing multimodal pain regimen reduces opioid exposure and pain in trauma-injured patients at high risk for opioid misuse: Secondary analysis from the mast trial.

BACKGROUND: Screening to identify patients at risk for opioid misuse after trauma is recommended but not commonly used to guide perioperative opioid management interventions. The Multimodal Analgesic Strategies for Trauma trial demonstrated that an opioid-minimizing multimodal pain regimen reduced opioid exposure in a heterogeneous trauma patient population. Here, we assess the efficacy of the Multimodal Analgesic Strategies for Trauma multimodal pain regimen in a critical patient subgroup who screened at high risk for opioid misuse. METHODS: The Multimodal Analgesic Strategies for Trauma trial compared an opioid-minimizing multimodal pain regimen (oral acetaminophen, naproxen, gabapentin, lidocaine patch, as-needed opioid) against an original multimodal pain regimen (intravenous followed by oral acetaminophen, 48-hour celecoxib and pregabalin, followed by naproxen and gabapentin, scheduled tramadol, as-needed opioid), in a randomized trial conducted from April 2018 to March 2019. A total of 631 enrolled patients were classified either as low- or high-risk via the Opioid Risk Tool. Bayesian analyses evaluated the moderating influence of Opioid Risk Tool risk (high/low) on the effect of Multimodal Analgesic Strategies for Trauma multimodal pain regimen (versus original) on opioid exposure (morphine milligram equivalents/day), opioids prescribed at discharge, and pain scores. RESULTS: Multimodal Analgesic Strategies for Trauma multimodal pain regimen effectively reduced morphine milligram equivalents/day in low- and high-Opioid Risk Tool risk groups. Moderation was observed for opioids at discharge and pain scores; Multimodal Analgesic Strategies for Trauma multimodal pain regimen was effective in the high-risk group only (opioids at discharge: 63% vs 77%, relative risk = 0.86, 95% Bayesian credible interval [0.66-1.08], posterior probability (relative risk <1) = 90%; pain scores: b = 3.8, 95% Bayesian credible interval [3.2-4.4] vs b = 4.0, 95% Bayesian credible interval [3.4-4.6], posterior probability (b <0) = 87%). CONCLUSION: This study is the first to show the moderating influence of opioid misuse risk on the effectiveness of an opioid-minimizing multimodal pain regimen. The Opioid Risk Tool was useful in identifying high-risk patients for whom the Multimodal Analgesic Strategies for Trauma multimodal pain regimen is recommended for perioperative pain management.

Early pain, stress, and opioid use following traumatic injury.

OBJECTIVE: Prescription opioids are an effective pain treatment strategy but can lead to long-term opioid misuse. Identifying at risk patients during hospitalization can inform the development of prevention interventions post-discharge. Using the Opioid Risk Tool (ORT) as a screening measure, this study predicted factors associated with pain and opioid use at 2 weeks post-discharge in trauma patients. DESIGN: A quality improvement prospective study design was used. SETTING: Participant recruitment took place at an inpatient Level 1 trauma center in Houston, Texas. PARTICIPANTS: Participants (n = 103) were patients admitted to the adult trauma service. Patients completed the ORT in the hospital and a survey at 2 weeks post-discharge. MAIN OUTCOME MEASURE: The survey assessed pain intensity and interference, injury-related stress, medication use, and need for additional pain treatment. Wilcoxon-Mann-Whitney U test, the Spearman rank-order correlation, and chisquare test of independence tested the ORT as a predictor of follow-up outcomes. Post hoc analyses relied on logistic and quantile regression. RESULTS: The ORT identified 15.5 percent of patients at high risk for opioid-related aberrant behavior. Survey results indicated high percentages of patients reporting moderate to severe pain (79.6 percent), pain interference (77.9 percent), taking pain pills (59.6 percent), experiencing stress (76.9 percent), and needing pain treatment (52.4 percent). The ORT predicted injury-related stress with the high-risk category having higher stress levels than low risk (Z = 2.518, p = 0.012). CONCLUSION: Risk of opioid misuse assessed in hospitalized trauma patients was associated with injury-related stress reported post-discharge. This highlights the importance of including stress assessments in follow-up appointments.

Utility of a brief assessment of opioid demand among post-discharge trauma care patients.

Opioid misuse and opioid-related death are a growing public health concern. One population of interest is recent trauma and/or surgery patients, who are at increased risk of developing an opioid use disorder (OUD). Although a variety of assessments have been developed to screen for risk of opioid misuse, each has limitations and prediction needs improvement. One promising measure is drug demand, a behavioral economic measure assessing drug consumption at different price points. In the current proposal, we assessed the utility of a brief assessment of opioid demand. Demand and various pain-related self-report measures among trauma-surgery patients (N = 103) were assessed at 4 weeks post-discharge. Opioid demand was significantly associated with self-report measures of pain and amount of morphine milligram equivalents (MME) received during the hospital stay. The current result support the utility of the opioid demand as an adjunctive and complementary measure to assess risk of opioid misuse. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Assessment of demand for methamphetamine and cigarettes among individuals with methamphetamine use disorder.

Methamphetamine (MA) is a highly addictive stimulant with recent upward trends in prevalence and associated public health problems. Drug demand, as assessed by hypothetical purchasing tasks, has been useful in addictions research and may help our understanding of the factors influencing MA use. However, no studies have assessed MA demand using current models of demand. The purpose of the current study was to assess demand for MA using a hypothetical drug purchasing task. Given high rates of cigarette smoking among MA users, it was of interest also to assess and compare demand for MA relative to cigarettes. Participants consisted of non-treatment-seeking volunteers with MA use disorder (N = 18), of whom 17 reported daily smoking. Results showed the exponentiated demand model provided a good fit to consumption data. Results from Bayesian generalized linear modeling demonstrated multiple positive relationships (posterior probability ≥75%) between self-reported drug use (days MA used in the past 30 days, cigarettes smoked per day) and indices of demand for each drug (Qo, Omax, Pmax, and break point). Comparing MA to cigarettes, results from Bayesian generalized linear mixed modeling revealed greater abuse liability for MA compared to cigarettes (posterior probability ≥99%) based on α and essential value. Overall, the findings of the current study support the feasibility and validity of the exponentiated demand model for assessing demand for drugs among individuals with MA use disorder. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Decreased cocaine demand following contingency management treatment.

A hypothetical cocaine purchasing task (CocPT) was used to assess changes in cocaine demand in the context of contingency management (CM) treatment for cocaine use disorder (CUD). Participants (N = 89) were treatment-seeking individuals with CUD receiving 4 weeks of abstinence-based, high-magnitude CM. Treatment response (vs. non-response) was operationally defined as the submission of 6 consecutive cocaine-negative urine samples across two weeks. The CPT was assessed at baseline, week 2, and week 5. Demand data were well described by the exponentiated demand model, and baseline demand indices (Q0, Pmax, breakpoint, essential value) were significantly associated with self-report measures of cocaine use. The probability of being a zero-responder reporting zero cocaine consumption at all prices significantly increased over the course of treatment, and was greater among treatment responders vs. non-responders. Among non-zero demand data, decreases in Omax, Pmax, breakpoint, and essential value were observed over the course of CM treatment, favoring responders. To our knowledge, this is the first study to assess change in cocaine demand in the context of CM treatment targeting cocaine abstinence. Our results support the utility of cocaine demand as a measure for both identifying individuals with greater treatment need and tracking relapse risk over the course of treatment.

Convolutional Neural Network Addresses the Confounding Impact of CT Reconstruction Kernels on Radiomics Studies.

Achieving high feature reproducibility while preserving biological information is one of the main challenges for the generalizability of current radiomics studies. Non-clinical imaging variables, such as reconstruction kernels, have shown to significantly impact radiomics features. In this study, we retrain an open-source convolutional neural network (CNN) to harmonize computerized tomography (CT) images with various reconstruction kernels to improve feature reproducibility and radiomic model performance using epidermal growth factor receptor (EGFR) mutation prediction in lung cancer as a paradigm. In the training phase, the CNN was retrained and tested on 32 lung cancer patients' CT images between two different groups of reconstruction kernels (smooth and sharp). In the validation phase, the retrained CNN was validated on an external cohort of 223 lung cancer patients' CT images acquired using different CT scanners and kernels. The results showed that the retrained CNN could be successfully applied to external datasets with different CT scanner parameters, and harmonization of reconstruction kernels from sharp to smooth could significantly improve the performance of radiomics model in predicting EGFR mutation status in lung cancer. In conclusion, the CNN based method showed great potential in improving feature reproducibility and generalizability by harmonizing medical images with heterogeneous reconstruction kernels.

Cocaine-specific speed-accuracy trade-off during anti-saccade testing differentiates patients with cocaine use disorder who achieve initial abstinence during treatment.

BACKGROUND: The response time speed-accuracy trade-off (SATO) is an established index of information processing ability, but rarely examined as a variable in association with treatment of substance use disorder (SUD). AIM: The purpose of this study was to test baseline information-processing ability differences between individuals who respond to treatment for cocaine use disorder v. those who do not. METHODS: Eighty patients enrolled in a clinical trial for cocaine use disorder completed a baseline drug-specific eye-tracking (anti-saccade) assessment prior to treatment, which included trials with both cocaine-related and neutral stimuli. SATO functions were computed for treatment responders v. non-responders. RESULTS: Unexpectedly, responders demonstrated statistically different SATO functions, showing poorer accuracy when executing faster response times. This difference was present on trials that presented cocaine stimuli only. CONCLUSIONS: SATO during performance of an eye-movement task may be useful for predicting differential response to substance use disorder treatment. However, in the present study, results were specific to cocaine cues rather than an overall SATO performance decrement.

Social Smoking Environment and Associations With Cardiac Rehabilitation Attendance.

PURPOSE: Continued cigarette smoking after a major cardiac event predicts worse health outcomes and leads to reduced participation in cardiac rehabilitation (CR). Understanding which characteristics of current smokers are associated with CR attendance and smoking cessation will help improve care for these high-risk patients. We examined whether smoking among social connections was associated with CR participation and continued smoking in cardiac patients. METHODS: Participants included 149 patients hospitalized with an acute cardiac event who self-reported smoking prior to the hospitalization and were eligible for outpatient CR. Participants completed a survey on their smoking habits prior to hospitalization and 3 mo later. Participants were dichotomized into two groups by the proportion of friends or family currently smoking ("None-Few" vs "Some-Most"). Sociodemographic, health, secondhand smoke exposure, and smoking measures were compared using t tests and χ2 tests (P < .05). ORs were calculated to compare self-reported rates of CR attendance and smoking cessation at 3-mo follow-up. RESULTS: Compared with the "None-Few" group, participants in the "Some-Most" group experienced more secondhand smoke exposure (P < .01) and were less likely to attend CR at follow-up (OR = 0.40; 95% CI, 0.17-0.93). Participants in the "Some-Most" group tended to be less likely to quit smoking, but this difference was not statistically significant. CONCLUSION: Social environments with more smokers predicted worse outpatient CR attendance. Clinicians should consider smoking within the social network of the patient as an important potential barrier to pro-health behavior change.