Protocol for harmonization of randomized trials testing the addition of behavioral therapy to buprenorphine for opioid use disorder.

Background: Although buprenorphine is an effective treatment for opioid use disorder (OUD), much remains to be understood about treatment non-response and methods for improving treatment retention. The addition of behavioral therapies to buprenorphine has not yielded consistent benefits for opioid outcomes, on average. However, several studies suggest that certain subgroups may benefit from the combination of buprenorphine and behavioral therapy, highlighting the potential for personalized approaches to treatment. Furthermore, little is known about whether behavioral therapies improve buprenorphine retention or non-opioid (e.g., functional) outcomes. Methods: The objective of this project is to harmonize four previously conducted clinical trials testing the addition of behavioral therapy to buprenorphine maintenance for OUD and to use this larger dataset to answer critical clinical questions about the role of behavioral therapy in this population. Study aims include identifying potential moderators of the effect of the addition of behavioral therapy and quantifying the effect of behavioral therapy on buprenorphine retention and functional outcomes. Results: Analyses will consider outcomes of weeks of opioid use, weeks of retention in buprenorphine treatment, and functional outcomes as measured by the Addiction Severity Index. Analyses will include an indicator for each study to account for heterogeneity of samples and design. Conclusion: Results will help to inform clinical and research efforts to optimize the use of behavioral therapies in the treatment of OUD.

Cognitive behavioral therapy for anxiety and opioid use disorder: Development and pilot testing.

INTRODUCTION: Anxiety disorders are highly prevalent among people with opioid use disorder (OUD), and they have a negative impact on disorder course and treatment outcomes. The objective of this Stage 1 A/1B behavioral treatment development trial was to develop a novel cognitive-behavioral therapy (CBT) protocol for co-occurring anxiety disorders and OUD. METHODS: Following a period of iterative manual development involving patient interviews and feedback from content experts, we tested a 12-session individual CBT protocol in a small, open pilot trial (N = 5). This was followed by a small, randomized controlled trial (N = 32), comparing the new protocol to 12 sessions of manualized Individual Drug Counseling. All participants also received medication for OUD. RESULTS: Overall, support for feasibility and acceptability was strong, based on recruitment and retention rates and patient satisfaction ratings. Within-subjects results identified 11-point reductions in anxiety symptom severity (on a 0-56 point scale); these gains were sustained through 3 months of follow-up. However, these changes did not differ between randomized conditions. With respect to opioid outcomes, 85 % of participants were abstinent in the prior month at the end of treatment. Opioid use outcomes also did not differ by treatment condition. CONCLUSIONS: These results support the feasibility and acceptability of a CBT protocol for co-occurring anxiety and OUD. However, in this small pilot trial results do not show an initial benefit over an evidence-based psychosocial treatment targeted to OUD alone, in combination with medication for OUD.

Permutation Tests for Assessing Potential Non-Linear Associations between Treatment Use and Multivariate Clinical Outcomes.

In many psychometric applications, the relationship between the mean of an outcome and a quantitative covariate is too complex to be described by simple parametric functions; instead, flexible nonlinear relationships can be incorporated using penalized splines. Penalized splines can be conveniently represented as a linear mixed effects model (LMM), where the coefficients of the spline basis functions are random effects. The LMM representation of penalized splines makes the extension to multivariate outcomes relatively straightforward. In the LMM, no effect of the quantitative covariate on the outcome corresponds to the null hypothesis that a fixed effect and a variance component are both zero. Under the null, the usual asymptotic chi-square distribution of the likelihood ratio test for the variance component does not hold. Therefore, we propose three permutation tests for the likelihood ratio test statistic: one based on permuting the quantitative covariate, the other two based on permuting residuals. We compare via simulation the Type I error rate and power of the three permutation tests obtained from joint models for multiple outcomes, as well as a commonly used parametric test. The tests are illustrated using data from a stimulant use disorder psychosocial clinical trial.

The 8-Year Course of Acute Physical Pain Reported by Patients With Borderline Personality Disorder and Comparison Subjects With Other Personality Disorders.

The present study examines the 8-year course of physical pain and its interference with functioning in patients with borderline personality disorder (BPD) and a comparison group of patients with other personality disorders (other-PD). Participants completed the Brief Pain Inventory (BPI) at five assessments, each separated by 2 years. Results showed that across all 13 domains assessed, participants with BPD reported significantly higher levels of acute physical pain and its functional interference than other-PD comparison subjects. The severity of physical pain and its interference with multiple domains of functioning were relatively stable over 8 years of assessment for both study groups. Within the BPD group, pain was significantly associated with older age, comorbid major depressive disorder (MDD), and history of a physically violent partner. Taken together, these results suggest that physical pain is a serious health issue for individuals with BPD that interferes with functioning across a wide spectrum of areas.

Longitudinal Description and Prediction of Smoking Among Borderline Patients: An 18-Year Follow-Up Study.

Objective: The objectives of this study were (1) to compare smoking between recovered and non-recovered patients with borderline personality disorder (BPD) over the course of 18 years and (2) to assess baseline predictors of tobacco use in patients with BPD.Methods: A total of 264 borderline patients were interviewed concerning their smoking history beginning at the 6-year follow-up wave in a longitudinal study of the course of BPD (McLean Study of Adult Development) and re-interviewed at 2-year intervals over the next 18 years. Initial data collection of the larger study happened between June 1992 and December 1995, and the DSM-III-R and the Revised Diagnostic Interview for Borderlines (DIB-R) were used as the diagnostic instruments for BPD.Results: Recovered patients had a 48% lower prevalence of smoking than non-recovered patients at 6-year follow-up (a significant difference; P = .01). Also, the rate of decline in smoking for the recovered group was 68% and was significantly faster (P = .008) than for the non-recovered group over the subsequent 18 years. Alcohol abuse or dependence (relative risk [RR] = 1.22; 95% CI, 1.06-1.40; P = .005), lower levels of education (RR = 1.28; 95% CI, 1.15-1.42; P < .001), and higher levels of the defense mechanism of denial (RR = 1.08; 95% CI, 1.03-1.13; P = .002) were significant predictors of smoking in borderline patients in multivariate analyses.Conclusions: Taken together, the results of this study suggest that recovery status was an important element in the prevalence of smoking among borderline patients over time. They also suggest that smoking was predicted by 3 factors: prior psychopathology, demographics, and psychological maturity.

Pathways to Health Reported by Patients With Borderline Personality Disorder With a Good Overall Outcome Versus a Fair-Poor Outcome Over 24 Years of Prospective Follow-Up.

Our objective was to determine pathways to health reported by patients with borderline personality disorder (BPD) who had and had not attained a good overall outcome over 24 years of prospective follow-up. Overall outcome symptomatically and psychosocially and 11 pathways to health related to vocation, relationships, activities, and psychiatric treatment that patients reported were helpful to their functioning or feeling better about themselves were assessed at 12 contiguous 2-year follow-up periods using a semistructured interview. Good outcome patients reported significantly higher rates of pathways related to work performance, relationships with friends, relationship with a partner/spouse, and athletic activities. In contrast, patients with a fair-poor outcome reported significantly higher rates of psychotherapy and psychotropic medication as pathways. Taken together, the results of this study suggest that a good overall outcome is significantly associated with reported vocational, interpersonal, and activity pathways, while a fair-poor outcome is significantly associated with reported treatment-related pathways.

Multiple imputation for non-monotone missing not at random data using the no self-censoring model.

Although approaches for handling missing data from longitudinal studies are well-developed when the patterns of missingness are monotone, fewer methods are available for non-monotone missingness. Moreover, the conventional missing at random assumption-a natural benchmark for monotone missingness-does not model realistic beliefs about the non-monotone missingness processes (Robins and Gill, 1997). This has provided the impetus for alternative non-monotone missing not at random mechanisms. The "no self-censoring" model is such a mechanism and assumes the probability an outcome variable is missing is independent of its value when conditioning on all other possibly missing outcome variables and their missingness indicators. As an alternative to "weighting" methods that become computationally demanding with increasing number of outcome variables, we propose a multiple imputation approach under no self-censoring. We focus on the case of binary outcomes and present results of simulation and asymptotic studies to investigate the performance of the proposed imputation approach. We describe a related approach to sensitivity analysis to departure from no self-censoring. We discuss the relationship between missing at random and no self-censoring and prove that one is not a special case of the other. Finally, we discuss extensions to non-binary data settings. The proposed methods are illustrated with application to a substance use disorder clinical trial.

Methods for handling missing binary data in substance use disorder trials.

Missing data are a ubiquitous problem in longitudinal substance use disorder (SUD) clinical trials. In particular, the rates of missingness are often high and study participants often intermittently skip their scheduled outcome assessments, leading to so-called "non-monotone" missing data patterns. Moreover, when the primary outcome is a measure of substance use, study investigators often have strong prior beliefs based on their clinical experience that those participants with missing data are more likely to be using substances at those occasions, i.e., data are missing not at random (MNAR). Although approaches for handling missing data are well-developed when the missing data patterns are monotone, arising primarily from study participants withdrawing from the trial prematurely, fewer methods are available for non-monotone missingness. In this paper we review some conventional, as well as more novel, methods for handling non-monotone missingness in SUD trials when the repeatedly measured outcome variable is binary (e.g., denoting presence/absence of substance use). We compare and contrast the different approaches using data from a longitudinal clinical trial of four psychosocial treatments from the Collaborative Cocaine Treatment Study. We conclude by making some recommendations to the SUD research community concerning how more principled methods for handling missing data can be incorporated in the analysis and reporting of trial results.

Defining Prescription Drug Misuse: A Naturalistic Evaluation of National Survey on Drug Use and Health Data From 2012-2014 to 2015-2017.

OBJECTIVES: Prescription drug misuse (PDM) is a significant public health problem. As research has evolved, the definitions of misuse have varied over time, yet the implications of this variability have not been systematically studied. The objective of this study was to leverage a change in the measurement of PDM in a large population survey to identify its impact on the prevalence and correlates of this behavior. METHODS: Data from the National Survey on Drug Use and Health were compared before and after a change in the definition of PDM from one that restricted the source and motive for use to one that captured any misuse other than directed by a prescriber. Three-year cohorts were constructed, representing a restricted definition of PDM (2012-2014) and a broad definition of PDM (2015-2017). RESULTS: Segmented logistic regression models indicated a significant increase in PDM prevalence for all 3 drug types examined (opioids, tranquilizers, and sedatives). Although the magnitude of differences varied somewhat based on drug type, the broader definition was generally associated with older age, higher prevalence of health insurance, and higher odds of misusing one's own prescription. Some worsening of mental health indicators was observed, but results indicated few other clinical or substance use differences. CONCLUSIONS: Definitions of prescription drug misuse have a substantial impact on the prevalence of misuse and some impact on the characteristics of the population. Further research is needed to understand the optimal strategy for measuring this behavior, based on the scientific or public health question or interest.

Dissociative experiences of adolescents with borderline personality disorder: description and prediction.

AIMS: The first purpose of this study was to assess the severity of dissociative experiences reported by adolescent inpatients with borderline personality disorder (BPD). The second purpose was to compare the severity of their dissociative symptoms to those reported by a sample of adult inpatients with BPD. The third purpose of this study was to assess a range of clinically meaningful predictors of the severity of dissociation in adolescents and adults with BPD. METHODS: The Dissociative Experiences Scale (DES) was administered to a total of 89 hospitalized girls and boys aged 13-17 with BPD and 290 adult inpatients with BPD. Predictors of the severity of dissociation in adolescents and adults with BPD were assessed using the Revised Childhood Experiences Questionnaire (a semi-structured interview), the NEO, and the SCID I. RESULTS: Borderline adolescents and adults had non-significant differences on their overall DES scores and subscale scores. They also had a non-significant distribution of low, moderate, and high scores. In terms of multivariate predictors, neither temperament nor childhood adversity was a significant predictor of the severity of dissociative symptoms in adolescents. However, co-occurring eating disorders were found in multivariate analyses to be the only bivariate predictor to significantly predict this outcome. In adults with BPD, however, both the severity of childhood sexual abuse and co-occurring PTSD were significantly related to the severity of dissociative symptoms in multivariate analyses. CONCLUSIONS: Taken together, the results of this study suggest that the severity of dissociation is not significantly different in adolescents and adults with BPD. However, the etiological factors differ substantially.

Impact of pediatric versus adult colonoscope on terminal ileum intubation: a retrospective study.

Background: Various possible predictors of successful terminal ileal intubation (TII) have been explored but the role of the type of colonoscope is unclear. Methods: We carried out a retrospective review of a prospectively collected database of all colonoscopies performed at a single endoscopy unit between May 2015 and July 2020. The primary outcome measure was successful TII in patients with specific indications for ileal examination. The primary predictor was the type of endoscope, pediatric or adult, used during the procedure. Univariate and multivariate analyses were performed. Results: In 5845 colonoscopies fulfilling the study criteria, the overall TII rate was 67.8%. In univariate analysis, the use of a pediatric colonoscope was associated with a higher TII rate (72.1% vs. 58.8%, P<0.001). Other variables associated with successful TII based on univariate analysis included the patient's age, male sex, body mass index, endoscopists' specialty, place of training, shorter colonoscope insertion time, shorter duration of the procedure, longer withdrawal time, procedures performed in the afternoon, type of sedation administered during colonoscopy, and cleanliness of the colon. Multivariate analysis yielded an adjusted odds ratio (OR) of 1.40 (95% confidence interval [CI] 1.21-1.62) for the use of a pediatric colonoscope. Propensity score-matching analysis also showed superiority of the pediatric colonoscope in achieving TII compared to an adult colonoscope, OR 1.35 (95%CI 1.17-1.57). Conclusions: Pediatric colonoscope increases the success of TII during colonoscopy. For endoscopists performing colonoscopy with intent to examine the terminal ileum, it is recommended to choose a pediatric colonoscope to maximize the success rate.

Elevated striatal glutamate + glutamine in recreational cannabis users during abstinence.

Cannabis withdrawal symptoms contribute to relapse, but the underlying mechanism remains unclear. We hypothesize that cannabis withdrawal may be associated with a reset of regional γ-amino butyric acid (GABA) and glutamate concentrations secondary to changes in the endocannabinoid system during abstinence and conducted a study on this issue. We used magnetic resonance spectroscopy (MRS) to detect the associated changes of these neurochemicals in twenty-six frequent, recreational cannabis users and eleven age-matched non-using controls. Twenty users (8F/12M) and ten control (5F/5M) participants completed a verified 21-day abstinence period. Striatal GABA and glutamine concentrations were measured at baseline and on abstinence days 7 and 21 in conjunction with measures of cannabis withdrawal symptoms and mood state. Cannabis users reported increased self-reported ratings of cannabis-withdrawal-symptoms on abstinence day 7 relative to controls. Striatal glutamate + glutamine (Glx) group concentrations were elevated in cannabis users at baseline and abstinence days 7 and 21 (F = 7.16, p = 0.012), and changes in GABA concentration and withdrawal symptoms between baseline and abstinence day 7 were positively correlated (r = 0.550, p = 0.010). In addition, baseline striatal GABA concentrations were negatively correlated with withdrawal symptoms on abstinence day 7 (r = -0.680, p = 0.003). Our data demonstrate that striatal Glx was elevated in cannabis users and baseline striatal GABA correlated with withdrawal during the abstinence. In addition, striatal GABA may temporally correlate with self-reported withdrawal symptoms during the initial days of abrupt cannabis abstinence. These findings provide preliminary evidence that striatal GABA and Glx are associated with the severity of cannabis withdrawal.

Associations between patterns of modifiable risk factors in mid-life to late life and longevity: 36 year prospective cohort study.

Objective: To examine the associations between patterns of mid-life to late life modifiable risk factors and longevity. Design: Prospective cohort study. Setting: Data collected from the Nurses' Health Study starting in 1984 and the Health Professionals Follow-up Study starting in 1986. Participants: 85 346 participants from the Nurses' Health Study and the Health Professionals Follow-up Study. Main outcome measures: Death from any cause by 31 October 2020 for the Nurses' Health Study and Health Professionals Follow-up Study. Risk factors investigated were body mass index, physical activity, alcohol intake, smoking status, and quality of diet. Trajectories of each risk factor and trajectories of changes in the risk factor were identified from baseline with smoothing mixture models, and the joint group memberships of participants was used to most efficiently capture patterns of the factor over time. For each risk factor, three trajectories (patterns with high, medium, and low values) and three trajectories of change in the risk factor (patterns with increase, no change, and decrease in the factor from baseline) were assumed, giving nine joint patterns: high-stable, high-increase, high-decrease, medium-stable, medium-increase, medium-decrease, low-stable, low-increase, and low-decrease. Associations between patterns of modifiable risk factors and longevity (age at death ≥85 years) and life expectancy were examined with logistic regression and accelerated failure time models, respectively. Results: The analysis included 85 346 participants, with 46 042 participants achieving longevity and 25 322 participants achieving healthy longevity (those who did not have a diagnosis of cardiovascular disease, type 2 diabetes, or cancer). Mean age at baseline was 56 years (standard deviation 5 years). Maximum longevity was achieved in participants with a low-stable pattern for body mass index (compared with a medium-stable pattern, odds ratio of longevity of 1.05, 95% confidence interval 1.00 to 1.10); those with a medium-increase pattern for physical activity (compared with a medium-stable pattern, odds ratio 1.08, 1.01 to 1.15); those with a medium-stable pattern for alcohol intake (high-increase v medium-stable pattern, odds ratio 0.83, 0.74 to 0.93); those who never smoked (low-stable v medium-stable pattern, odds ratio 3.09, 2.84 to 3.37); and those who with a high-increase pattern for quality of diet (compared with a medium-stable pattern, odds ratio 1.09, 1.01 to 1.18). The associations between each factor and life expectancy and healthy longevity (no diagnosis of cardiovascular disease, type 2 diabetes, or cancer) were similar to those for longevity. Conclusions: During mid-life and late life, maximum longevity was achieved in participants who maintained a normal body mass index, never smoked, ate a healthy diet, and had physical activity levels and alcohol consumption that met public health recommendations.

A note on median regression for complex surveys.

There is a great need for statistical methods for analyzing skewed responses in complex sample surveys. Quantile regression is a logical option in addressing this problem but is often accompanied by incorrect variance estimation. We show how the variance can be estimated correctly by including the survey design in the variance estimation process. In a simulation study, we illustrate that the variance of the median regression estimator has a very small relative bias with appropriate coverage probability. The motivation for our work stems from the National Health and Nutrition Examination Survey where we demonstrate the impact of our results on iodine deficiency in females compared with males adjusting for other covariates.

Temporal patterns of suicide and circulatory system disease-related mortality are inversely correlated in several countries.

BACKGROUND: Nearly 800,000 suicides occur worldwide annually and suicide rates are increasing faster than population growth. Unfortunately, the pathophysiology of suicide remains poorly understood, which has hindered suicide prevention efforts. However, mechanistic clues may be found by studying effects of seasonality on suicide and other mortality causes. Suicides tend to peak in spring-summer periods and nadir in fall-winter periods while circulatory system disease-related mortality tends to exhibit the opposite temporal trends. This study aimed to determine for the first time whether monthly temporal cross-correlations exist between suicide and circulatory system disease-related mortality at the population level. If so and if common biological factors moderate risks for both mortality types, such factors may be discoverable and utilized to improve suicide prevention. METHODS: We conducted time series analyses of monthly mortality data from northern (England and Wales, South Korea, United States) and southern (Australia, Brazil) hemisphere countries during the period 2009-2018 (N = 41.8 million all-cause mortality cases). We used a Poisson regression variant of the standard cosinor model to determine peak months of mortality. We also estimated cross-correlations between monthly mortality counts from suicide and from circulatory system diseases. RESULTS: Suicide and circulatory disease-related mortality temporal patterns were negatively correlated in Australia (- 0.32), Brazil (- 0.57), South Korea (- 0.32), and in the United States (- 0.66), but no temporal correlation was discernable in England and Wales. CONCLUSIONS: The negative temporal cross-correlations between these mortality types we found in 4 of 5 countries studied suggest that seasonal factors broadly and inversely moderate risks for circulatory disease-related mortality and suicide, but not in all regions, indicating that the effect is not uniform. Since the seasonal factors of temperature and light exert opposite effects on suicide and circulatory disease-related mortality in several countries, we propose that physiologically-adaptive circulatory system responses to heat and light may increase risk for suicide and should be studied to determine whether they affect suicide risk. For example, heat and light increase production and release of the bioactive gas nitric oxide and reduce circulatory system disease by relaxing blood vessel tone, while elevated nitric oxide levels are associated with suicidal behavior, inverse effects that parallel the inverse temporal mortality patterns we detected.

Childhood Gender Nonconformity and Intimate Partner Violence in Adolescence and Young Adulthood.

Childhood gender nonconformity has been associated with numerous adverse experiences, including peer bullying and homophobic violence. However, little is known about gender nonconformity in the context of intimate relationships, independent of sexual orientation. This study aimed to examine associations between childhood gender nonconformity and intimate partner violence (IPV) in adolescence and early adulthood. Using data from the 2007 wave of the U.S. Growing Up Today Study (N = 7,641, mean age = 22.8 years), we estimated risk ratios (RRs) for the association of gender nonconformity up to age 11 years and lifetime IPV victimization and perpetration. Models were adjusted for demographic characteristics, including sexual orientation identity. We assessed effect modification by gender and examined whether childhood abuse mediated the association between nonconformity and IPV. Males in the top decile of nonconformity were at elevated risk of IPV victimization (RR = 1.40, 95% confidence interval [CI] = [1.15, 1.71]) and IPV perpetration (RR = 2.34, 95% CI = 1.54, 3.56) compared with those below median nonconformity, adjusting for sexual orientation and demographic characteristics. There was no evidence of a similar association for females in the top decile of gender nonconformity. Childhood abuse did not mediate IPV disparities by gender nonconformity. We identify gender nonconformity as an important risk indicator for IPV victimization and perpetration among young adult males, independent of sexual orientation. Findings highlight the vulnerability of boys and men who do not conform to societal gender norms and the importance of studying gender expression as a determinant of violence. IPV prevention efforts may be improved with more explicit focus on socially constructed gender norms and support for diverse gender expressions. Further research into the pathways between nonconformity and IPV and in more diverse populations is needed to build a more comprehensive understanding of the unique experiences gender nonconforming youth face.

Development of a mixture model allowing for smoothing functions of longitudinal trajectories.

In the health and social sciences, two types of mixture models have been widely used by researchers to identify participants within a population with heterogeneous longitudinal trajectories: latent class growth analysis and the growth mixture model. Both methods parametrically model trajectories of individuals, and capture latent trajectory classes, using an expectation-maximization algorithm. However, parametric modeling of trajectories using polynomial functions or monotonic spline functions results in limited flexibility for modeling trajectories; as a result, group membership may not be classified accurately due to model misspecification. In this paper, we propose a smoothing mixture model allowing for smoothing functions of trajectories using a modified algorithm in the M step. Specifically, participants are reassigned to only one group for which the estimated trajectory is the most similar to the observed one; trajectories are fitted using generalized additive mixed models with smoothing functions of time within each of the resulting subsamples. The smoothing mixture model is straightforward to implement using the recently released "gamm4" package (version 0.2-6) in R 3.5.0. It can incorporate time-varying covariates and be applied to longitudinal data with any exponential family distribution, e.g., normal, Bernoulli, and Poisson. Simulation results show favorable performance of the smoothing mixture model, when compared to latent class growth analysis and growth mixture model, in recovering highly flexible trajectories. The proposed method is illustrated by its application to body mass index data on individuals followed from adolescence to young adulthood and its relationship with incidence of cardiometabolic disease.

Meta-analysis of Total Effect Decomposition in the Presence of Multiple Mediators: The Example of Schizophrenia Treatment.

BACKGROUND: Causal mediation analysis addresses mechanistic questions by decomposing and quantifying effects operating through different pathways. Because most individual studies are underpowered to detect mediating effects, we outlined a parametric approach to meta-analyzing causal mediation and interaction analyses with multiple mediators, compared it with a bootstrap-based alternative, and discussed its limitations. METHODS: We employed fixed- and random-effects multivariate meta-analyses to integrate evidence on treatment-mediators and mediators-outcome associations across trials. We estimated path-specific effects as functions of meta-analyzed regression coefficients; we obtained standard errors using the delta method. We evaluated the performance of this approach in simulations and applied it to assess the mediating roles of positive symptoms of schizophrenia and weight gain in the treatment effect of paliperidone ER on negative symptoms across four efficacy trials. RESULTS: Both simulations and the application showed that the meta-analytic approaches increased statistical power. In the application, we observed substantial mediating effects of positive symptoms (proportions mediated from fixed-effects meta-analysis: (Equation is included in full-text article.)). Weight gain may have beneficial mediating effects; however, such benefit may disappear at high doses when metabolic side effects were excessive. CONCLUSIONS: Meta-analyzing causal mediation analysis combines evidence from multiple sources and improves power. Targeting positive symptoms may be an effective way to reduce negative symptoms that are challenging to treat. Future work should focus on extending the existing methods to allow for more flexible modeling of mediation.

The Treatment Ambassador Program: A Highly Acceptable and Feasible Community-Based Peer Intervention for South Africans Living with HIV Who Delay or Discontinue Antiretroviral Therapy.

We conducted a novel pilot randomized controlled trial of the Treatment Ambassador Program (TAP), an 8-session, peer-based, behavioral intervention for people with HIV (PWH) in South Africa not on antiretroviral therapy (ART). PWH (43 intervention, 41 controls) completed baseline, 3- and 6-month assessments. TAP was highly feasible (90% completion), with peer counselors demonstrating good intervention fidelity. Post-intervention interviews showed high acceptability of TAP and counselors, who supported autonomy, assisted with clinical navigation, and provided psychosocial support. Intention-to-treat analyses indicated increased ART initiation by 3 months in the intervention vs. control arm (12.2% [5/41] vs. 2.3% [1/43], Fisher exact p-value = 0.105; Cohen's h = 0.41). Among those previously on ART (off for > 6 months), 33.3% initiated ART by 3 months in the intervention vs. 14.3% in the control arm (Cohen's h = 0.45). Results suggest that TAP was highly acceptable and feasible among PWH not on ART.

Using Multiple Imputation with GEE with Non-monotone Missing Longitudinal Binary Outcomes.

This paper considers multiple imputation (MI) approaches for handling non-monotone missing longitudinal binary responses when estimating parameters of a marginal model using generalized estimating equations (GEE). GEE has been shown to yield consistent estimates of the regression parameters for a marginal model when data are missing completely at random (MCAR). However, when data are missing at random (MAR), the GEE estimates may not be consistent; the MI approaches proposed in this paper minimize bias under MAR. The first MI approach proposed is based on a multivariate normal distribution, but with the addition of pairwise products among the binary outcomes to the multivariate normal vector. Even though the multivariate normal does not impute 0 or 1 values for the missing binary responses, as discussed by Horton et al. (Am Stat 57:229-232, 2003), we suggest not rounding when filling in the missing binary data because it could increase bias. The second MI approach considered is the fully conditional specification (FCS) approach. In this approach, we specify a logistic regression model for each outcome given the outcomes at other time points and the covariates. Typically, one would only include main effects of the outcome at the other times as predictors in the FCS approach, but we explore if bias can be reduced by also including pairwise interactions of the outcomes at other time point in the FCS. In a study of asymptotic bias with non-monotone missing data, the proposed MI approaches are also compared to GEE without imputation. Finally, the proposed methods are illustrated using data from a longitudinal clinical trial comparing four psychosocial treatments from the National Institute on Drug Abuse Collaborative Cocaine Treatment Study, where patients' cocaine use is collected monthly for 6 months during treatment.