Causal inference under interference with prognostic scores for dynamic group therapy studies

Group therapy is a common treatment modality for behavioral health conditions. Patients often enter and exit groups on an ongoing basis, leading to dynamic therapy groups. Examining the effect of high versus low session attendance on patient outcomes is a research question of interest. However, there are several challenges to identifying causal effects in this setting, including the lack of randomization, interference among patients, and the interrelatedness of patient participation. Dynamic therapy groups motivate a unique causal inference scenario, as the treatment statuses are completely defined by the patient attendance record for the therapy session, which is also the structure inducing interference. We adopt the Rubin causal model framework to define the causal effect of high versus low session attendance of group therapy at both the individual patient and peer levels. We propose a strategy to identify individual, peer, and total effects of high attendance versus low attendance on patient outcomes by the prognostic score stratification. We examine performance of our approach via simulation and apply it to data from a group cognitive behavioral therapy trial for treating depression among patients in a substance use disorders treatment setting.

Appropriate analyses of bimodal substance use frequency outcomes: a mixture model approach

Background: In addiction research, outcome measures are often characterized by bimodal distributions. One mode can be for individuals with low substance use and the other mode for individuals with high substance use. Applying standard statistical procedures to bimodal data may result in invalid inference. Mixture models are appropriate for bimodal data because they assume that the sampled population is composed of several underlying subpopulations.Objectives: To introduce a novel mixture modeling approach to analyze bimodal substance use frequency data.Methods: We reviewed existing models used to analyze substance use frequency outcomes and developed multiple alternative variants of a finite mixture model. We applied all methods to data from a randomized controlled study in which 30-day alcohol abstinence was the primary outcome. Study data included 73 individuals (38 men and 35 women). Models were implemented in the software packages SAS, Stata, and Stan.Results: Shortcomings of existing approaches include: 1) inability to model outcomes with multiple modes, 2) invalid statistical inferences, including anti-conservative p-values, 3) sensitivity of results to the arbitrary choice to model days of substance use versus days of substance abstention, and 4) generation of predictions outside the range of common substance use frequency outcomes. Our mixture model variants avoided all of these shortcomings.Conclusions: Standard models of substance use frequency outcomes can be problematic, sometimes overstating treatment effectiveness. The mixture models developed improve the analysis of bimodal substance use frequency.

Understanding the characteristics of Latino individuals with first-time DUI offenses to facilitate effective interventions

Literature shows that Latinos who drink are more likely to experience alcohol-related consequences and less likely to seek care for alcohol misuse than Whites. We aim to understand characteristics, consumption patterns, and openness to treatment among Latino first-time offenders driving under the influence. Latino participants were significantly younger (29.0 years) than non-Latinos (37.7 years). In adjusted models, Latino participants were significantly more likely than non-Latinos to binge drink, but there were no significant group differences in amount of alcohol consumed in a typical week. There was no significant difference in incidence of alcohol-related consequences, readiness to change drinking, and driving behaviors in this sample.

Longitudinal effects of social network changes on drinking outcomes for individuals with a first-time DUI

BACKGROUND

Social networks are important predictors of alcohol-related outcomes, especially among those with a DUI where riskier social networks are associated with increased risk of drinking and driving. Social networks are increasingly a target for intervention; however, no studies have examined and measured whether longitudinal changes in social networks are associated with reductions in impaired driving.

OBJECTIVE

The current study first examines longitudinal changes in social networks among participants receiving services following a first-time DUI, and then examines the association between network change and drinking outcomes at 4- and 10-month follow-up.

METHODS

The study surveyed a subsample of participants (N = 94) enrolled in a clinical trial of individuals randomized to cognitive behavioral therapy (CBT) or usual care (UC) on an iPad using EgoWeb 2.0-an egocentric social network data collection software-about pre-DUI and post-DUI networks and their short- and long-term drinking behaviors.

RESULTS

Participants were 65% male, 48% Hispanic, and an average of 32.5 years old. Overall, participants significantly reduced the proportion of network members with whom they drank from 0.41 to 0.30 (p = .001) and with whom they drank more alcohol than they wanted to from 0.15 to 0.07 (p = .0001) from two weeks prior to the DUI (measured at baseline) to 4-month follow-up. Furthermore, decreases in proportion of drinking partners over time were associated with reduced drinks per week, self-reported driving after drinking, and intentions to drive after drinking at 4-month follow-up. Participants who reported decreases in proportion of drinking partners also reported significantly less binge drinking at 10-month follow-up. Finally, increases in emotional support were associated with decreases in binge drinking at 4-month follow-up. The study found no differences in the changes in composition of networks between CBT and UC groups.

CONCLUSIONS

These results suggest that individuals receiving services in DUI programs significantly reduced risky network members over time and that these social network changes were associated with reduced drinking and other indicators of risk for DUI recidivism. Clinical interventions that target reductions in risky network members may improve outcomes for those enrolled in a DUI program.

Social Networks of Clients in First-Time DUI Programs

OBJECTIVE

Social networks play an important role in the development of and recovery from problem drinking behaviors; however, few studies have measured the social networks of individuals convicted of driving under the influence (DUI) or assessed the relationship between social network characteristics and risk for DUI relapse and recidivism. The goal of this study is to describe the social network characteristics of a first-time DUI population in the 2 weeks before the DUI incident; examine demographic differences in social network characteristics by age, ethnicity, and gender; and assess the relationship between social network characteristics and risk factors for DUI.

METHOD

We collected personal (egocentric) social network survey data from 94 participants (65% male) enrolled in a randomized clinical trial comparing the effects of cognitive behavioral therapy with usual care for individuals convicted of a first-time DUI. Multivariate models were used to assess the relationship between pre-DUI personal network characteristics and risk factors for DUI measured at baseline interview.

RESULTS

Results indicate that the proportion of drinking partners in one's personal network was positively associated with drinks per week, binge drinking, alcohol use, marijuana use, and alcohol-related consequences. Several dimensions of personal network support were inversely associated with risk factors for DUI.

CONCLUSIONS

The pre-DUI composition of personal networks has a strong relationship to baseline risk factors for DUI; networks composed of more risky individuals (e.g., drinking partners) were associated with greater substance use and drinking and driving behaviors. Networks with greater levels of social support were associated with lower likelihood of self-reported driving after drinking and intentions to drive after drinking. Interventions that target positive and negative aspects of personal networks may enhance clinical treatments.

Social Networks of Clients in First-Time DUI Programs

OBJECTIVE

Social networks play an important role in the development of and recovery from problem drinking behaviors; however, few studies have measured the social networks of individuals convicted of driving under the influence (DUI) or assessed the relationship between social network characteristics and risk for DUI relapse and recidivism. The goal of this study is to describe the social network characteristics of a first-time DUI population in the 2 weeks before the DUI incident; examine demographic differences in social network characteristics by age, ethnicity, and gender; and assess the relationship between social network characteristics and risk factors for DUI.

METHOD

We collected personal (egocentric) social network survey data from 94 participants (65% male) enrolled in a randomized clinical trial comparing the effects of cognitive behavioral therapy with usual care for individuals convicted of a first-time DUI. Multivariate models were used to assess the relationship between pre-DUI personal network characteristics and risk factors for DUI measured at baseline interview.

RESULTS

Results indicate that the proportion of drinking partners in one's personal network was positively associated with drinks per week, binge drinking, alcohol use, marijuana use, and alcohol-related consequences. Several dimensions of personal network support were inversely associated with risk factors for DUI.

CONCLUSIONS

The pre-DUI composition of personal networks has a strong relationship to baseline risk factors for DUI; networks composed of more risky individuals (e.g., drinking partners) were associated with greater substance use and drinking and driving behaviors. Networks with greater levels of social support were associated with lower likelihood of self-reported driving after drinking and intentions to drive after drinking. Interventions that target positive and negative aspects of personal networks may enhance clinical treatments.

Study design to evaluate a group-based therapy for support persons of adults on buprenorphine/naloxone

Background

Opioid use disorders (OUDs) have devastating effects on individuals, families, and communities. While medication treatments for OUD save lives and are increasingly utilized, rates of treatment dropout are very high. In addition, most existing medication treatments for OUD may often neglect the impact of untreated OUD on relationships and ignore the potential role support persons (SPs) could have on encouraging long-term recovery, which can also impact patient treatment retention.

Methods/design

The current study adapts Community Reinforcement and Family Training (CRAFT) for use with SPs (family member, spouse or friend) of patients using buprenorphine/naloxone (buprenorphine) in an outpatient community clinic setting. The study will evaluate whether the adapted intervention, also known as integrating support persons into recovery (INSPIRE), is effective in increasing patient retention on buprenorphine when compared to usual care. We will utilize a two-group randomized design where patients starting or restarting buprenorphine will be screened for support person status and recruited with their support person if eligible. Support persons will be randomly assigned to the INSPIRE intervention, which will consist of 10 rolling group sessions led by two facilitators. Patients and SPs will each be assessed at baseline, 3 months post-baseline, and 12 months post-baseline. Patient electronic medical record data will be collected at six and 12 months post-baseline. We will examine mechanisms of intervention effectiveness and also conduct pre/post-implementation surveys with clinic staff to assess issues that would affect sustainability.

Discussion

Incorporating the patient’s support system may be an important way to improve treatment retention in medication treatments for OUD. If SPs can serve to support patient retention, this study would significantly advance work to help support the delivery of effective treatments that prevent the devastating consequences associated with OUD.

Trial registration This study was registered with ClinicalTrials.gov, NCT04239235. Registered 27 January 2020, https://clinicaltrials.gov/ct2/show/NCT04239235.

Randomized Clinical Trial Examining Cognitive Behavioral Therapy for Individuals With a First-Time DUI Offense

BACKGROUND

Driving under the influence (DUI) programs are a unique setting to reduce disparities in treatment access to those who may not otherwise access treatment. Providing evidence-based therapy in these programs may help prevent DUI recidivism.

METHODS

We conducted a randomized clinical trial of 312 participants enrolled in 1 of 3 DUI programs in California. Participants were 21 and older with a first-time DUI offense who screened positive for at-risk drinking in the past year. Participants were randomly assigned to a 12-session manualized cognitive behavioral therapy (CBT) or usual care (UC) group and then surveyed 4 and 10 months later. We conducted intent-to-treat analyses to test the hypothesis that participants receiving CBT would report reduced impaired driving, alcohol consumption (drinks per week, abstinence, and binge drinking), and alcohol-related negative consequences. We also explored whether race/ethnicity and gender moderated CBT findings.

RESULTS

Participants were 72.3% male and 51.7% Hispanic, with an average age of 33.2 (SD = 12.4). Relative to UC, participants receiving CBT had lower odds of driving after drinking at the 4- and 10-month follow-ups compared to participants receiving UC (odds ratio [OR] = 0.37, p = 0.032, and OR = 0.29, p = 0.065, respectively). This intervention effect was more pronounced for females at 10-month follow-up. The remaining 4 outcomes did not significantly differ between UC versus CBT at 4- and 10-month follow-ups. Participants in both UC and CBT reported significant within-group reductions in 2 of 5 outcomes, binge drinking and alcohol-related consequences, at 10-month follow-up (p < 0.001).

CONCLUSIONS

In the short-term, individuals receiving CBT reported significantly lower rates of repeated DUI than individuals receiving UC, which may suggest that learning cognitive behavioral strategies to prevent impaired driving may be useful in achieving short-term reductions in impaired driving.

Group Cohesion and Climate in Cognitive Behavioral Therapy for Individuals with a First-Time DUI

Few studies have examined group cohesion and climate in the substance use disorder treatment literature. We examined whether group cohesion and climate are associated with increased self-efficacy outcomes and reduced drinks per week, binge drinking and DUI behaviors, in a sample of individuals with a first-time DUI receiving either cognitive behavioral therapy (CBT) or usual care. Additionally, we examined whether CBT moderates these relationships. Group measures and drinking outcomes were not significantly associated. This study is the first to provide an in-depth analysis on group processes in DUI settings, and as such, provides important insights into how group processes may differ in a mandated DUI context.

Sample selection in the face of design constraints: Use of clustering to define sample strata for qualitative research

OBJECTIVE

To sample 40 physician organizations stratified on the basis of longitudinal cost of care measures for qualitative interviews in order to describe the range of care delivery structures and processes that are being deployed to influence the total costs of caring for patients.

DATA SOURCES

Three years of physician organization-level total cost of care data (n = 156 in California) from the Integrated Healthcare Association's value-based pay-for-performance program.

STUDY DESIGN

We fit total cost of care data using mixture and K-means clustering algorithms to segment the population of physician organizations into sampling strata based on 3-year cost trajectories (ie, cost curves).

PRINCIPAL FINDINGS

A mixture of multivariate normal distributions can classify physician organization cost curves into clusters defined by total cost level, shape, and within-cluster variation. K-means clustering does not accommodate differing levels of within-cluster variation and resulted in more clusters being allocated to unstable cost curves. A mixture of regressions approach focuses overly on anomalous trajectories and is sensitive to model coding.

CONCLUSIONS

Statistical clustering can be used to form sampling strata when longitudinal measures are of primary interest. Many clustering algorithms are available; the choice of the clustering algorithm can strongly impact the resulting strata because various algorithms focus on different aspects of the observed data.

Reducing disparities requires multiple strategies

Disparities in care are a complex issue requiring multiple strategies to solve, including approaches to improve the measurement of quality and reporting stratified performance estimates.

Differences in alcohol cognitions, consumption, and consequences among first-time DUI offenders who co-use alcohol and marijuana

BACKGROUND

A significant portion of alcohol-related DUI offenders engage in co-use of alcohol and marijuana (AM). Given expanding marijuana legalization and the impaired driving risks associated with co-use, it is of increased importance to understand how characteristics of AM co-users compare to those who use alcohol only (AO) in order to inform DUI interventions and prevent recidivism.

METHODS

Participants were 277 first-time DUI offenders enrolled in a first-time DUI offender program across three locations. Using well-established measures, we evaluated differences in alcohol-related cognitions (positive expectancies and self-efficacy), frequency and quantity of alcohol consumption, and alcohol-related consequences between AO users and AM co-users by running a series of multivariate generalized linear models.

RESULTS

Compared to AO users, AM co-users reported lower self-efficacy to achieve abstinence and avoid DUI. Differences in abstinence self-efficacy largely explain higher relative rates of average and peak drinking quantity and higher odds of binge drinking among AM co-user. Despite lower self-efficacy and higher drinking quantity, there were no significant differences between AM and AO-users on alcohol-related consequences and past month reports of drinking and driving.

CONCLUSIONS

Our results provide preliminary evidence that DUI offenders who co-use alcohol and marijuana have higher alcohol use and lower self-efficacy than AO-users, and long-term consequences for this group should be monitored in future research. DUI programs may screen and identify co-users and consider tailoring their interventions to build self-efficacy to address the risks associated with AM co-use uniquely.

Shifting From Passive Quality Reporting to Active Nudging to Influence Consumer Choice of Health Plan

Comparative quality information on health plan and provider performance is increasingly available in the form of quality report cards, but consumers rarely make use of these passively provided decision support tools. In 2012-2013, the Centers for Medicare & Medicaid Services (CMS) initiated quality-based nudges designed to encourage beneficiaries to move into higher quality Medicare Advantage (MA) plans. We assess the impacts of CMS' targeted quality-based nudges with longitudinal analysis of 2009-2014 MA plan enrollment trends. Nudges are associated with 17% reductions in enrollment in the lowest-performing plans and 3% increases in enrollment in the highest performing plans (annually, p < .01 for both), occurring at the time of nudge implementation and relative to trends for plans with moderate performance that were not targeted by nudges. These findings suggest that quality-based nudges can successfully steer consumers into higher quality plans and provide opportunities for purchasers and payers to increase consumers' use of quality information.

Adjusting Medicare Advantage star ratings for socioeconomic status and disability

OBJECTIVES

Studies have identified potential unintended effects of not adjusting clinical performance measures in value-based purchasing programs for socioeconomic status (SES) factors. We examine the impact of SES and disability adjustments on Medicare Advantage (MA) plans' and prescription drug plans' (PDPs') contract star ratings. These analyses informed the development of the Categorical Adjustment Index (CAI), which CMS implemented with the 2017 star ratings.

STUDY DESIGN

Retrospective analyses of MA and PDP performance using 2012 Medicare beneficiary-level characteristics and performance data from the Star Rating Program.

METHODS

We modeled within-contract associations of beneficiary SES (Medicaid and Medicare dual eligibility [DE] or receipt of a low-income subsidy [LIS]) and disability with performance on 16 clinical measures. We estimated variability in contract-level DE/LIS and disability disparities using mixed-effects regression models. We simulated the impact of applying the CAI to adjust star ratings for DE/LIS and disability to construct the 2017 star ratings.

RESULTS

DE/LIS was negatively associated with performance for 12 of 16 measures and positively associated for 2 of 16 measures. Disability was negatively associated with performance for 11 of 15 measures and positively associated for 3 of 15 measures. Adjusting star ratings using the CAI resulted in half-star rating increases for 8.5% of MA and 33.3% of PDP contracts that exceeded 50% DE/LIS beneficiaries.

CONCLUSIONS

Increases in star ratings following adjustment of clinical performance for SES and disability using the CAI focused on contracts with higher percentages of DE/LIS beneficiaries. Adjustment for enrollee characteristics may improve the accuracy of quality measurement and remove incentives for providers to avoid caring for more challenging patient populations.

Bayesian models for semicontinuous outcomes in rolling admission therapy groups

Alcohol and other drug abuse are frequently treated in a group therapy setting. If participants are allowed to enroll in therapy on a rolling basis, irregular patterns of participant overlap can induce complex correlations of participant outcomes. Previous work has accounted for common session attendance by modeling random effects for each therapy session, which map to participant outcomes via a multiple membership construction when modeling normally distributed outcome measures. We build on this earlier work by extending the models to semicontinuous outcomes, or outcomes that are a mixture of continuous and discrete distributions. This results in multivariate session effects, for which we allow temporal dependencies of various orders. We illustrate our methods using data from a group-based intervention to treat substance abuse and depression, focusing on the outcome of average number of drinks per day. Alcohol and other drug abuse are frequently treated in a group therapy setting. If 2 clients attend the some of the same sessions, we might expect that-on average-their posttreatment outcomes would be more similar than if they had not attended any sessions together. Hence, if participants are allowed to enroll in therapy on a rolling basis, irregular patterns of session attendance can induce complex relationships between participant outcomes. Statistical methods have been developed previously to account for rolling admission group therapy when the outcomes are normally distributed. In the case of alcohol and other drug use interventions, however, a substantial fraction of participants often report zero use after treatment. We extend previous work to build models that accommodate semicontinuous outcomes, which are a mixture of continuous and discrete distributions, for such situations. We find that modern Bayesian statistical methods and software allow users to efficiently estimate nonstandard models such as these. We illustrate our methods using data from a group-based intervention to treat substance abuse and depression, focusing on the outcome of average number of drinks per day. We find that the intervention is associated with a drop in the probability of any drinking, but find no evidence of a change in the amount of drinking, conditional on some drinking. (PsycINFO Database Record

Quality of Care for PTSD and Depression in the Military Health System: Final Report

The U.S. Department of Defense (DoD) strives to maintain a physically and psychologically healthy, mission-ready force, and the care provided by the Military Health System (MHS) is critical to meeting this goal. Attention has been directed to ensuring the quality and availability of programs and services for posttraumatic stress disorder (PTSD) and depression. This study is a comprehensive assessment of the quality of care delivered by the MHS in 2013-2014 for over 38,000 active-component service members with PTSD or depression. The assessment includes performance on 30 quality measures to evaluate the receipt of recommended assessments and treatments. These measures draw on multiple data sources including administrative encounter data, medical record review data, and patient self-reported outcome monitoring data. The assessment identified strengths and areas for improvement for the MHS. In particular, the MHS excels at screening for suicide risk and substance use, but rates of appropriate follow-up for service members with suicide risk are lower. Most service members received at least some psychotherapy, but less than half of psychotherapy delivered was evidence-based. In analyses focused on Army soldiers, outcome monitoring increased notably over time, yet preliminary analyses suggest that more work is needed to ensure that services are effective in reducing symptoms. When comparing performance between 2012-2013 and 2013-2014, most measures demonstrated slight improvement, but targeted efforts will be needed to support further improvements. RAND provides recommendations for strategies to improve the quality of care delivered for these conditions.

Delivering Clinical Practice Guideline-Concordant Care for PTSD and Major Depression in Military Treatment Facilities

Providing accessible, high-quality care for psychological health (PH) conditions, such as posttraumatic stress disorder (PTSD) and major depressive disorder (MDD), is important to maintaining a healthy, mission-ready force. It is unclear whether the current system of care meets the needs of service members with PTSD or MDD, and little is known about the barriers to delivering guideline-concordant care. RAND used existing provider workforce data, a provider survey, and key informant interviews to (1) provide an overview of the PH workforce at military treatment facilities (MTFs), (2) examine the extent to which care for PTSD and MDD in military treatment facilities is consistent with Department of Veterans Affairs/Department of Defense clinical practice guidelines, and (3) identify facilitators and barriers to providing this care. This study provides a comprehensive assessment of providers' perspectives on their capacity to deliver PH care within MTFs and presents detailed results by provider type and service branch. Findings suggest that most providers report using guideline-concordant psychotherapies, but use varied by provider type. The majority of providers reported receiving at least minimal training and supervision in at least one recommended psychotherapy for PTSD and for MDD. Still, more than one-quarter of providers reported that limits on travel and lack of protected time in their schedule affected their ability to access additional professional training. Finally, most providers reported routinely screening patients for PTSD and MDD with a validated screening instrument, but fewer providers reported using a validated screening instrument to monitor treatment progress.

Association Between Process-Based Quality Indicators and Mortality for Patients With Substance Use Disorders

OBJECTIVE

Substance use disorders (SUDs) are associated with elevated rates of mortality. Little is known about whether receiving appropriate care is associated with lower mortality for patients with SUDs. This study examined the association between the receipt of care for SUDs and subsequent 12- and 24-month mortality.

METHOD

This was a retrospective cohort study of veterans who received care for SUDs paid for by the Veterans Health Administration during October 2006- September 2007 (n = 339,966). Logistic regressions were used to examine the association between quality indicators measuring receipt of care and mortality while controlling for patient characteristics and facility service area.

RESULTS

There were four quality indicators: SUD treatment initiation, SUD treatment engagement, SUD-related psychosocial treatment, and SUD-related psychotherapy. Outcomes measured were mortality 12 and 24 months after the end of the observation period, through September 2009. Receipt of indicated care ranged from 26.5% to 58.6%, and 12- and 24-month mortality rates were 3% and 6%, respectively. Adjusted odds ratios [95% CI] of 12-month mortality by indicator were: initiation, 0.86 [0.79, 0.93]; engagement, 0.65 [0.58, 0.74]; psychosocial treatment, 0.88 [0.84, 0.92]; and psychotherapy, 0.84 [0.79, 0.89]. For the 24-month mortality outcome, adjusted odds ratios were: initiation, 0.88 [0.84, 0.93]; engagement, 0.78 [0.71, 0.85]; psychosocial treatment, 0.91 [0.88, 0.94]; and psychotherapy, 0.87 [0.83, 0.91]. Results were similar when controlling for facility service area.

CONCLUSIONS

Receiving appropriate care is associated with lower mortality for patients with SUDs. Significant overall and within-facility service area associations of quality indicators and mortality support their use in encouraging providers to deliver the indicated care. These indicators should be prioritized above others lacking comparably strong process-outcome associations.

Medicare Advantage and Fee-for-Service Performance on Clinical Quality and Patient Experience Measures: Comparisons from Three Large States

OBJECTIVE

To compare performance between Medicare Advantage (MA) and Fee-for-Service (FFS) Medicare during a time of policy changes affecting both programs.

DATA SOURCES/STUDY SETTING

Performance data for 16 clinical quality measures and 6 patient experience measures for 9.9 million beneficiaries living in California, New York, and Florida.

STUDY DESIGN

We compared MA and FFS performance overall, by plan type, and within service areas associated with contracts between CMS and MA organizations. Case mix-adjusted analyses (for measures not typically adjusted) were used to explore the effect of case mix on MA/FFS differences.

DATA COLLECTION/EXTRACTION METHODS

Performance measures were submitted by MA organizations, obtained from the nationwide fielding of the Medicare Consumer Assessment of Healthcare Providers and Systems (MCAHPS) Survey, or derived from claims.

PRINCIPAL FINDINGS

Overall, MA outperformed FFS on all 16 clinical quality measures. Differences were large for HEDIS measures and small for Part D measures and remained after case mix adjustment. MA enrollees reported better experiences overall, but FFS beneficiaries reported better access to care. Relative to FFS, performance gaps were much wider for HMOs than PPOs. Excluding HEDIS measures, MA/FFS differences were much smaller in contract-level comparisons.

CONCLUSIONS

Medicare Advantage/Fee-for-Service differences are often large but vary in important ways across types of measures and contracts.

Association Between Quality Measures and Perceptions of Care Among Patients With Substance Use Disorders

OBJECTIVE

This study evaluated whether eight quality measures assessing care for patients with a substance use disorder were associated with patient perceptions of their care, including perceived improvement and global rating of behavioral health care.

METHODS

Secondary data analyses were conducted of administrative and patient survey data collected as part of a national evaluation of Veterans Health Administration (VHA) mental health and substance use services. Data for patients who received care for substance use disorders during October 2006-September 2007 paid for by the VHA and who participated in a telephone interview about their care (N=2,074) were included. Measures of patient perceptions of care included perceived improvement and global rating of behavioral health care. Eight quality measures based on administrative data assessed initiation and engagement in substance use disorder care, receipt of psychotherapy or psychosocial treatment, and follow-up after hospitalization. Regression models were conducted in which each quality measure predicted each outcome, with analyses adjusting for patient characteristics and functioning.

RESULTS

Treatment engagement, two measures of psychotherapy receipt, and psychosocial treatment were significantly associated with perceived improvement, whereas treatment initiation and follow-up after hospitalization (seven and 30 days) were not. Psychotherapy receipt and follow-up after hospitalization (seven and 30 days) were significantly associated with global rating of behavioral health care.

CONCLUSIONS

Some quality measures assessing care for substance use disorders were significantly associated with patient perceptions of care. Results provide additional support for these quality measures and suggest that patient perceptions of care are an important outcome in assessing care.

Association between process measures and mortality in individuals with opioid use disorders

BACKGROUND

Individuals with opioid use disorders have high rates of mortality relative to the general population. The relationship between treatment process and mortality is unknown.

AIM

To examine the association between 7 process measures and 12- and 24-month mortality.

METHODS

Retrospective cohort study of patients with opioid use disorders who received care from the Veterans Administration between October 2006 and September 2007. Logistic regression models were used to examine the association between 12 and 24-month mortality and 7 patient-level process measures, while risk-adjusting for patient characteristics. Process measures included quarterly physician visits, any opioid use disorder pharmacotherapy, continuous pharmacotherapy, psychosocial treatment, Hepatitis B/C and HIV screening, and no prescriptions for benzodiazepines or opioids. We conducted sensitivity analyses to examine the robustness of our findings to an unobserved confounder.

RESULTS

Among individuals with opioid use disorders, not being prescribed opioids or benzodiazepines, receipt of any psychosocial treatment and quarterly physician visits were significantly associated with lower mortality at both 12 and 24 months, but Hepatitis and HIV screening, and measures related to opioid use disorder pharmacotherapy were not. Sensitivity analyses indicated that the difference in the prevalence of an unobserved confounder would have to be unrealistically large given the observed data, or there would need to be a large effect of the confounder, to render these findings non-significant.

CONCLUSIONS AND RELEVANCE

This is the first study to show an association between process measures and mortality in patients with opioid use disorders and provides initial evidence for their use as quality measures.

Misclassification Risk of Tier-Based Physician Quality Performance Systems

OBJECTIVE

There is increasing interest in identifying high-quality physicians, such as whether physicians perform above or below a threshold level. To evaluate whether current methods accurately distinguish above- versus below-threshold physicians, we estimate misclassification rates for two-category identification systems.

DATA SOURCES

Claims data for Medicare fee-for-service beneficiaries residing in Florida or New York in 2010.

STUDY DESIGN

Estimate colorectal cancer, glaucoma, and diabetes quality scores for 23,085 physicians. Use a beta-binomial model to estimate physician score reliabilities. Compute the proportion of physicians whose performance tier would be misclassified under three scoring systems.

PRINCIPAL FINDINGS

In the three scoring systems, misclassification ranges were 8.6-25.7 percent, 6.4-22.8 percent, and 4.5-21.7%. True positive rate ranges were 72.9-97.0 percent, 83.4-100.0 percent, and 34.7-88.2 percent. True negative rate ranges were 68.5-91.6 percent, 10.5-92.4 percent, and 81.1-99.9 percent. Positive predictive value ranges were 70.5-91.6 percent, 77.0-97.3 percent, and 55.2-99.1 percent.

CONCLUSIONS

Current methods for profiling physicians on quality may produce misleading results, as the number of eligible events is typically small. Misclassification is a policy-relevant measure of the potential impact of tiering on providers, payers, and patients. Quantifying misclassification rates should inform the construction of high-performance networks and quality improvement initiatives.

Quality of Care for PTSD and Depression in the Military Health System: Phase I Report

The U.S. Department of Defense (DoD) strives to maintain a physically and psychologically healthy, mission-ready force, and the care provided by the Military Health System (MHS) is critical to meeting this goal. Given the rates of posttraumatic stress disorder (PTSD) and depression among U.S. service members, attention has been directed to ensuring the quality and availability of programs and services targeting these and other psychological health (PH) conditions. Understanding the current quality of care for PTSD and depression is an important step toward improving care across the MHS. To help determine whether service members with PTSD or depression are receiving evidence-based care and whether there are disparities in care quality by branch of service, geographic region, and service member characteristics (e.g., gender, age, pay grade, race/ethnicity, deployment history), DoD's Defense Centers of Excellence for Psychological Health and Traumatic Brain Injury (DCoE) asked the RAND Corporation to conduct a review of the administrative data of service members diagnosed with PTSD or depression and to recommend areas on which the MHS could focus its efforts to continuously improve the quality of care provided to all service members. This study characterizes care for service members seen by MHS for diagnoses of PTSD and/or depression and finds that while the MHS performs well in ensuring outpatient follow-up following psychiatric hospitalization, providing sufficient psychotherapy and medication management needs to be improved. Further, quality of care for PTSD and depression varied by service branch, TRICARE region, and service member characteristics, suggesting the need to ensure that all service members receive high-quality care.

Association Between Quality Measures and Mortality in Individuals With Co-Occurring Mental Health and Substance Use Disorders

IMPORTANCE

Individuals with co-occurring mental and substance use disorders have increased rates of mortality relative to the general population. The relationship between measures of treatment quality and mortality for these individuals is unknown.

OBJECTIVE

To examine the association between 5 quality measures and 12- and 24-month mortality.

DESIGN, SETTING AND PARTICIPANTS

Retrospective cohort study of patients with co-occurring mental illness (schizophrenia, bipolar disorder, post-traumatic stress disorder and major depression) and substance use disorders who received care for these disorders paid for by the Veterans Administration between October 2006 and September 2007. Logistic regression models were used to examine the association between 12 and 24-month mortality and 5 patient-level quality measures, while risk-adjusting for patient characteristics. Quality measures included receipt of psychosocial treatment, receipt of psychotherapy, treatment initiation and engagement, and a measure of continuity of care. We also examined the relationship between number of diagnosis-related outpatient visits and mortality, and conducted sensitivity analyses to examine the robustness of our findings to an unobserved confounder.

MAIN OUTCOMES MEASURE

Mortality 12 and 24 months after the end of the observation period.

RESULTS

All measures except for treatment engagement at 24 months were significantly associated with lower mortality at both 12 and 24 months. At 12 months, receiving any psychosocial treatment was associated with a 21% decrease in mortality; psychotherapy, a 22% decrease; treatment initiation, a 15% decrease, treatment engagement, a 31% decrease; and quarterly, diagnosis-related visits a 28% decrease. Increasing numbers of visits were associated with decreasing mortality. Sensitivity analyses indicated that the difference in the prevalence of an unobserved confounder would have to be unrealistically large given the observed data, or there would need to be a large effect of an unobserved confounder, to render these findings non-significant.

CONCLUSIONS AND RELEVANCE

This is the first study to show an association between process-based quality measures and mortality in patients with co-occurring mental and substance use disorders, and provides initial support for the predictive validity of the measures. By devising strategies to improve performance on these measures, health care systems may be able to decrease the mortality of this vulnerable population.

Evaluating the Implementation of the Re-Engineering Systems of Primary Care Treatment in the Military (RESPECT-Mil)

A RAND team conducted an independent implementation evaluation of the Re-Engineering Systems of Primary Care Treatment in the Military (RESPECT-Mil) Program, a system of care designed to screen, assess, and treat posttraumatic stress disorder and depression among active duty service members in the Army's primary care settings. Evaluating the Implementation of the Re-Engineering Systems of Primary Care Treatment in the Military (RESPECT-Mil) presents the results from RAND's assessment of the implementation of RESPECT-Mil in military treatment facilities and makes recommendations to improve the delivery of mental health care in these settings. Analyses were based on existing program data used to monitor fidelity to RESPECT-Mil across the Army's primary care clinics, as well as discussions with key stakeholders. During the time of the evaluation, efforts were under way to implement the Patient Centered Medical Home, and uncertainties remained about the implications for the RESPECT-Mil program. Consideration of this transition was made in designing the evaluation and applying its findings more broadly to the implementation of collaborative care within military primary care settings.

A pilot study comparing in-person and web-based motivational interviewing among adults with a first-time DUI offense

Background

Driving under the influence (DUI) is a significant problem, and there is a pressing need to develop interventions that reduce future risk.

Methods

We pilot-tested the acceptance and efficacy of web-motivational interviewing (MI) and in-person MI interventions among a diverse sample of individuals with a first-time DUI offense. Participants (N = 159) were 65 percent male, 40 percent Hispanic, and an average age of 30 (SD = 9.8). They were enrolled at one of three participating 3-month DUI programs in Los Angeles County and randomized to usual care (UC)-only (36-h program), in-person MI plus UC, or a web-based intervention using MI (web-MI) plus UC. Participants were assessed at intake and program completion. We examined intervention acceptance and preliminary efficacy of the interventions on alcohol consumption, DUI, and alcohol-related consequences.

Results

Web-MI and in-person MI participants rated the quality of and satisfaction with their sessions significantly higher than participants in the UC-only condition. However, there were no significant group differences between the MI conditions and the UC-only condition in alcohol consumption, DUI, and alcohol-related consequences. Further, 67 percent of our sample met criteria for alcohol dependence, and the majority of participants in all three study conditions continued to report alcohol-related consequences at follow-up.

Conclusions

Participants receiving MI plus UC and UC-only had similar improvements, and a large proportion had symptoms of alcohol dependence. Receiving a DUI and having to deal with the numerous consequences related to this type of event may be significant enough to reduce short-term behaviors, but future research should explore whether more intensive interventions are needed to sustain long-term changes.

Bayesian restricted spatial regression for examining session features and patient outcomes in open-enrollment group therapy studies

Group-based interventions have been developed for treating patients across a range of health conditions. Enrollment into such groups often occurs on an open (or rolling) basis. Conditional autoregression modeling of random session effects has been proposed to account for the expected correlation in session effects associated with the overlap in patient participation session to session. However, when the analytic objective is to examine the relationship between a fixed-effect session feature and a patient outcome using conditional autoregression, confounding might arise if the fixed session feature of interest and the random session effects vary across sessions in similar ways, resulting in bias and inflated standard errors of a fixed-effect session feature of interest. Motivated by the goal of examining the relationships between outcomes and the session features of leader and session module theme, we applied restricted spatial regression to the analysis of patient outcomes collected from 132 participants in an open-enrollment group for treating depression among patients of a residential alcohol and other drug treatment program, adapting the approach to the multilevel data structure of open-enrollment group data. As compared with standard conditional autoregression, the restricted regression approach resulted in more precise estimates of regression coefficients of the module theme and leader predictor variables. The restricted regression approach provides an important analytic tool for group therapy researchers who are investigating the relationship between key components of open-enrollment group therapy interventions and patient outcomes.

Bayesian Semi- and Non-parametric Models for Longitudinal Data with Multiple Membership Effects in R

We introduce growcurves for R that performs analysis of repeated measures multiple membership (MM) data. This data structure arises in studies under which an intervention is delivered to each subject through the subject's participation in a set of multiple elements that characterize the intervention. In our motivating study design under which subjects receive a group cognitive behavioral therapy (CBT) treatment, an element is a group CBT session and each subject attends multiple sessions that, together, comprise the treatment. The sets of elements, or group CBT sessions, attended by subjects will partly overlap with some of those from other subjects to induce a dependence in their responses. The growcurves package offers two alternative sets of hierarchical models: 1. Separate terms are specified for multivariate subject and MM element random effects, where the subject effects are modeled under a Dirichlet process prior to produce a semi-parametric construction; 2. A single term is employed to model joint subject-by-MM effects. A fully non-parametric dependent Dirichlet process formulation allows exploration of differences in subject responses across different MM elements. This model allows for borrowing information among subjects who express similar longitudinal trajectories for flexible estimation. growcurves deploys "estimation" functions to perform posterior sampling under a suite of prior options. An accompanying set of "plot" functions allow the user to readily extract by-subject growth curves. The design approach intends to anticipate inferential goals with tools that fully extract information from repeated measures data. Computational efficiency is achieved by performing the sampling for estimation functions using compiled C++.

Veterans' perceptions of behavioral health care in the veterans health administration: a national survey

OBJECTIVE

This study provided national estimates of perceptions of behavioral health care services among patients of the Veterans Health Administration (VHA) with a diagnosis of bipolar I disorder, major depression, posttraumatic stress disorder, schizophrenia, or substance use disorder.

METHODS

A stratified random sample of 6,190 patients completed telephone interviews from November 2008 through August 2009. Patients (N=5,185) who reported receiving VHA behavioral health care in the prior 12 months were asked about their need for housing and employment services, timeliness and recovery orientation of their care, satisfaction with care, and perceived improvement.

RESULTS

Half of patients reported always receiving routine appointments as soon as requested, and 42% were highly satisfied with their VHA mental health care. Approximately 74% of patients reported being helped by the treatment they received, yet only 32% reported that their symptoms had improved. After controlling for covariates, the analyses showed that patients with a substance use disorder reported lower satisfaction with care and perceived their treatment to be less helpful compared with patients without a substance use disorder.

CONCLUSIONS

Although matched sample comparison data were not available, the results showed that overall patient perceptions of VHA mental health care were favorable, but there was significant room for improvement across all areas of assessment. A majority reported being helped by treatment, but few reported symptom improvement. Variations in perceptions among patients with different disorders suggest the potential importance of psychiatric diagnosis, particularly substance use disorder, in assessing patient perceptions of care.

Does group cognitive-behavioral therapy module type moderate depression symptom changes in substance abuse treatment clients?

Little is known about the effect of group therapy treatment modules on symptom change during treatment and on outcomes post-treatment. Secondary analyses of depressive symptoms collected from two group therapy studies conducted in substance use treatment settings were examined (n=132 and n=44). Change in PHQ-9 scores was modeled using longitudinal growth modeling combined with random effects modeling of session effects, with time-in-treatment interacted with module theme to test moderation. In both studies, depressive symptoms significantly decreased during the active treatment phase. Symptom reductions were not significantly moderated by module theme in the larger study. However, the smaller pilot study's results suggest that future examination of module effects is warranted, given the data are compatible with differential reductions in reported symptoms being associated with attending people-themed module sessions versus thoughts-themed sessions.

Statistical benchmarks for health care provider performance assessment: a comparison of standard approaches to a hierarchical Bayesian histogram-based method

OBJECTIVE

Examine how widely used statistical benchmarks of health care provider performance compare with histogram-based statistical benchmarks obtained via hierarchical Bayesian modeling.

DATA SOURCES

Publicly available data from 3,240 hospitals during April 2009-March 2010 on two process-of-care measures reported on the Medicare Hospital Compare website.

STUDY DESIGN

Secondary data analyses of two process-of-care measures comparing statistical benchmark estimates and threshold exceedance determinations under various combinations of hospital performance measure estimates and benchmarking approaches.

PRINCIPAL FINDINGS

Statistical benchmarking approaches for determining top 10 percent performance varied with respect to which hospitals exceeded the performance benchmark; such differences were not found at the 50 percent threshold. Benchmarks derived from the histogram of provider performance under hierarchical Bayesian modeling provide a compromise between benchmarks based on direct (raw) estimates, which are overdispersed relative to the true distribution of provider performance and prone to high variance for small providers, and posterior mean provider performance, for which over-shrinkage and under-dispersion relative to the true provider performance distribution is a concern.

CONCLUSIONS

Given the rewards and penalties associated with characterizing top performance, the ability of statistical benchmarks to summarize key features of the provider performance distribution should be examined.

The cost-effectiveness of depression treatment for co-occurring disorders: a clinical trial

The authors aimed to determine the economic value of providing on-site group cognitive behavioral therapy (CBT) for depression to clients receiving residential substance use disorder (SUD) treatment. Using a quasi-experimental design and an intention-to-treat analysis, the incremental cost-effectiveness and cost-utility ratio of the intervention were estimated relative to usual care residential treatment. The average cost of a treatment episode was $908, compared to $180 for usual care. The incremental cost effectiveness ratio was $131 for each point improvement of the BDI-II and $49 for each additional depression-free day. The incremental cost-utility ratio ranged from $9,249 to $17,834 for each additional quality adjusted life year. Although the intervention costs substantially more than usual care, the cost effectiveness and cost-utility ratios compare favorably to other depression interventions. Health care reform should promote dissemination of group CBT to individuals with depression in residential SUD treatment.

Do client attributes moderate the effectiveness of a group cognitive behavioral therapy for depression in addiction treatment?

The study goal was to determine whether client attributes were associated with outcomes from group cognitive behavioral therapy for depression (GCBT-D) as delivered in community-based addiction treatment settings. Data from 299 depressed residential clients assigned to receive either usual care (N = 159) or usual care plus GCBT-D (N = 140) were examined. Potential moderators included gender, race/ethnicity, education, referral status, and problem substance use. Study outcomes at 6 months post-baseline included changes in depressive symptoms, mental health functioning, negative consequences from substance use, and percentage of days abstinent. Initial examination indicated that non-Hispanic Whites had significantly better outcomes than other racial/ethnic groups on two of the four outcomes. After correcting for multiple testing, none of the examined client attributes moderated the treatment effect. GCBT-D appears effective; however, the magnitude and consistency of treatment effects indicate that it may be less helpful among members of racial/ethnic minority groups and is worthy of future study.

Bayesian Hierarchical Semiparametric Modelling of Longitudinal Post-treatment Outcomes from Open Enrolment Therapy Groups

There are several challenges to testing the effectiveness of group therapy-based interventions in alcohol and other drug use (AOD) treatment settings. Enrollment into AOD therapy groups typically occurs on an open (rolling) basis. Changes in therapy group membership induce a complex correlation structure among client outcomes, with relatively small numbers of clients attending each therapy group session. Primary outcomes are measured post-treatment, so each datum reflects the effect of all sessions attended by a client. The number of post-treatment outcomes assessments is typically very limited. The first feature of our modeling approach relaxes the assumption of independent random effects in the standard multiple membership model by employing conditional autoregression (CAR) to model correlation in random therapy group session effects associated with clients' attendance of common group therapy sessions. A second feature specifies a longitudinal growth model under which the posterior distribution of client-specific random effects, or growth parameters, is modeled non-parametrically. The Dirichlet process prior helps to overcome limitations of standard parametric growth models given limited numbers of longitudinal assessments. We motivate and illustrate our approach with a data set from a study of group cognitive behavioral therapy to reduce depressive symptoms among residential AOD treatment clients.

Intervening with practitioners to improve the quality of prevention: one-year findings from a randomized trial of assets-getting to outcomes

There continues to be a gap in prevention outcomes achieved in research trials versus those achieved in "real-world" practice. This article reports interim findings from a randomized controlled trial evaluating Assets-Getting To Outcomes (AGTO), a two-year intervention designed to build prevention practitioners' capacity to implement positive youth development-oriented practices in 12 community coalitions in Maine. A survey of coalition members was used to assess change on individual practitioners' prevention capacity between baseline and one year later. Structured interviews with 32 program directors (16 in the intervention group and 16 in the control group) were used to assess changes in programs' prevention practices during the same time period. Change in prevention capacity over time did not differ significantly between the intervention and control groups. However, in secondary analyses of only those assigned to the AGTO intervention, users showed greater improvement in their self-efficacy to conduct Assets-based programming and increases in the frequency with which they engaged in AGTO behaviors, whereas among non-users, self-efficacy to conduct Assets-based programming declined. Interview ratings showed improvement in several key areas of performance among intervention programs. Improvement was associated with the number of technical assistance hours received. These results suggest that, after one year, AGTO is beginning to improve the capacity of community practitioners who make use of it.

Bayesian Non-Parametric Hierarchical Modeling for Multiple Membership Data in Grouped Attendance Interventions

We develop a dependent Dirichlet process (DDP) model for repeated measures multiple membership (MM) data. This data structure arises in studies under which an intervention is delivered to each client through a sequence of elements which overlap with those of other clients on different occasions. Our interest concentrates on study designs for which the overlaps of sequences occur for clients who receive an intervention in a shared or grouped fashion whose memberships may change over multiple treatment events. Our motivating application focuses on evaluation of the effectiveness of a group therapy intervention with treatment delivered through a sequence of cognitive behavioral therapy session blocks, called modules. An open-enrollment protocol permits entry of clients at the beginning of any new module in a manner that may produce unique MM sequences across clients. We begin with a model that composes an addition of client and multiple membership module random effect terms, which are assumed independent. Our MM DDP model relaxes the assumption of conditionally independent client and module random effects by specifying a collection of random distributions for the client effect parameters that are indexed by the unique set of module attendances. We demonstrate how this construction facilitates examining heterogeneity in the relative effectiveness of group therapy modules over repeated measurement occasions.

The Carrot and the Stick: A Cross-Sectional Study of the Influences on Responsible Merchant Practices to Reduce Underage Drinking

Alcohol merchants (N=331) completed a cross-sectional survey assessing their attitudes and beliefs about underage drinking, its likely consequences, requirements for responsible beverage service (RBS) training, and performance of RBS practices and checking IDs. Merchants requiring more rigorous RBS training (i.e., state-approved versus in-house or none) have stronger beliefs that outlets who sell to minors will get cited and that their employees know RBS practices. Also, merchants who engage in more RBS practices require more rigorous RBS training, and believe more strongly that outlets who sell to minors are more likely to face, and deserve, stricter sanctions. Merchants who check IDs more strictly conduct more RBS practices and believe more strongly that underage drinking is serious and will result in stronger consequences if caught selling to minors. These findings about the attitudes, practices, and enforcement of alcohol merchants suggests ways communities can better target their limited resources to prevent underage drinking.

Treating depression and substance use: a randomized controlled trial

Few integrated substance use and depression treatments have been developed for delivery in outpatient substance abuse treatment settings. To meet the call for more "transportable" interventions, we conducted a pilot study to test a group cognitive-behavioral therapy (CBT) for depression and substance use that was designed for delivery by outpatient substance abuse treatment counselors. Seventy-three outpatient clients were randomized to usual care enhanced with group CBT or usual care alone and assessed at three time points (baseline and 3 and 6 months postbaseline). Our results demonstrated that the treatment was acceptable and feasible for delivery by substance abuse treatment staff despite challenges with recruiting clients. Both depressive symptoms and substance use were reduced by the intervention but were not significantly different from the control group. These results suggest that further research is warranted to enhance the effectiveness of treatment for co-occurring disorders in these settings.

An Epidemiological Model for Examining Marijuana Use over the Life Course

Trajectories of drug use are usually studied empirically by following over time persons sampled from either the general population (most often youth and young adults) or from heavy or problematic users (e.g., arrestees or those in treatment). The former, population-based samples, describe early career development, but miss the years of use that generate the greatest social costs. The latter, selected populations, help to summarize the most problematic use, but cannot easily explain how people become problem users nor are they representative of the population as a whole. This paper shows how microsimulation can synthesize both sorts of data within a single analytical framework, while retaining heterogeneous influences that can impact drug use decisions over the life course. The RAND Marijuana Microsimulation Model is constructed for marijuana use, validated, and then used to demonstrate how such models can be used to evaluate alternative policy options aimed at reducing use over the life course.

The moderating effects of group cognitive-behavioral therapy for depression among substance users

This study examined the prospective longitudinal relationship between changes in depressive symptoms on alcohol and/or drug (i.e., substance) use among addiction participants in treatment, and whether group cognitive-behavioral therapy for depression (GCBT-D) moderated the relationship. Using a quasi-experimental intent-to-treat design, 299 residential addiction treatment clients with depressive symptoms (Beck Depression Inventory-II, BDI-II scores > 17; Beck, Steer, & Brown, 1996) were assigned to either usual care (n = 159) or usual care plus a 16-session GCBT-D intervention (n = 140). Two follow-up interviews were conducted, one 3 months after the baseline interview corresponding to the end of the intervention, and then one 3 months later. Parallel-process growth modeling was used to examine changes in depressive symptoms and the associated changes in abstinence and negative consequences from substance use over time. Treatment group was included as a moderator of the association. Participants in the GCBT-D condition showed a greater increase in abstinence and greater decreases in depressive symptoms and negative consequences over time. There were significant interaction effects, such that the associations between depressive symptoms, negative consequences, and abstinence changes were larger in the usual-care condition than in the GCBT-D condition. The results suggest that the intervention may be effective by attenuating the association between depressive symptoms and substance use outcomes. These findings contribute to the emerging literature on the prospective longitudinal associations between depressive symptoms and substance use changes by being the first to examine them among a sample receiving GCBT-D in an addiction treatment setting.

Emotional distress and cognitive functioning of older couples: a dyadic analysis

OBJECTIVE

This article examines the relationship between cognitive functioning and emotional distress in a sample of 2,684 married couples from the 2006 and 2008 Korean Longitudinal Study of Aging.

METHOD

Using the Center for Epidemiologic Studies Depression (CESD) scale and the Mini-Mental State Exam (MMSE), we analyze the interrelation between emotional and cognitive health for individuals and spouses with with dyadic regression models. We test how emotional distress and cognitive impairment affect each other within individuals and from one spouse to another.

RESULTS

We find emotional distress contributes to cognitive impairment for wives but not for husbands. We also find emotional distress and cognitive impairment in one spouse affects that in the other. We find no evidence that emotional distress effects spouse's cognitive impairment or that the cognitive ability impacts spouses' emotional distress.

DISCUSSION

We discuss the results within the context of existing literature, focusing on the socioeconomic and clinical factors that explain these interrelations.

The premises is the premise: understanding off- and on-premises alcohol sales outlets to improve environmental alcohol prevention strategies

Environmental strategies to prevent the misuse of alcohol among youth--e.g., use of public policies to restrict minors' access to alcohol--have been shown to reduce underage drinking. However, implementation of policy changes often requires public and private partnerships. One way to support these partnerships is to better understand the target of many of the environmental strategies, which is the alcohol sales outlet. Knowing more about how off-premises outlets (e.g., liquor and convenience stores) and on-premises outlets (e.g., bars and restaurants) are alike and different could help community-based organizations better tailor, plan, and implement their environmental strategies and strengthen partnerships between the public and commercial sectors. We conducted a survey of managerial or supervisory staff and/or owners of 336 off- and on-premises alcohol outlets in six counties in South Carolina, comparing these two outlet types on their preferences regarding certain alcohol sales practices, beliefs toward underage drinking, alcohol sales practices, and outcomes. Multilevel logistic regression showed that while off- and on-premises outlets did have many similarities, off-premises outlets appear to engage in more practices designed to prevent sales of alcohol to minors than on-premises outlets. The relationship between certain Responsible Beverage Service (RBS) practices and outcomes varied by outlet type. This study furthers the understanding of the differences between off- and on-premises alcohol sales outlets and offers options for increasing and tailoring environmental prevention efforts to specific settings.