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Objective: To evaluate the efficacy and safety of osmotic-release methylphenidate (OROS-MPH) compared with placebo for attention-deficit/hyperactivity disorder (ADHD), and the impact on substance treatment outcomes in adolescents concurrently receiving cognitive-behavioral therapy (CBT) for substance use disorders (SUD). Method: This was a 16-week, randomized, controlled, multi-site trial of OROS-MPH + CBT versus placebo + CBT in 303 adolescents (aged 13 through 18 years) meeting "DSM-IV" diagnostic criteria for ADHD and SUD. Primary outcome measures included the following: for ADHD, clinician-administered ADHD Rating Scale (ADHD-RS), adolescent informant; for substance use, adolescent-reported days of use in the past 28 days. Secondary outcome measures included parent ADHD-RS and weekly urine drug screens (UDS). Results: There were no group differences on reduction in ADHD-RS scores (OROS-MPH: -19.2, 95% confidence interval [CI], -17.1 to -21.2; placebo, -21.2, 95% CI, -19.1 to -23.2) or reduction in days of substance use (OROS-MPH: -5.7 days, 95% CI, 4.0-7.4; placebo: -5.2 days, 95% CI, 3.5-7.0). Some secondary outcomes favored OROS-MPH, including lower parent ADHD-RS scores at 8 (mean difference = 4.4, 95% CI, 0.8-7.9) and 16 weeks (mean difference =6.9; 95% CI, 2.9-10.9) and more negative UDS in OROS-MPH (mean = 3.8) compared with placebo (mean = 2.8; p = 0.04). Conclusions: OROS-MPH did not show greater efficacy than placebo for ADHD or on reduction in substance use in adolescents concurrently receiving individual CBT for co-occurring SUD. However, OROS-MPH was relatively well tolerated and was associated with modestly greater clinical improvement on some secondary ADHD and substance outcome measures. Clinical Trial Registration Information-Attention Deficit Hyperactivity Disorder (ADHD) in Adolescents with Substance Use Disorders (SUD); NCT00264797. (Contains 3 figures and 2 tables.)

Objective: To evaluate the effect of atomoxetine hydrochloride versus placebo on attention-deficit/hyperactivity disorder (ADHD) and substance use disorder (SUD) in adolescents receiving motivational interviewing/cognitive behavioral therapy (MI/CBT) for SUD. Method: This single-site, randomized, controlled trial was conducted between December 2005 and February 2008. Seventy adolescents (13 through 19 years of age) with Diagnostic and Statistical Manual of Mental Disorders (Fourth Edition) (DSM-IV) ADHD, a DSM-IV ADHD checklist score greater than or equal to 22, and at least one nontobacco SUD were recruited from the community. All subjects received 12 weeks of atomoxetine hydrochloride + MI/CBT versus placebo + MI/CBT. The main outcome measure for ADHD was self-report DSM-IV ADHD checklist score. For SUD, the main outcome was self-report number of days used nontobacco substances in the past 28 days using the Timeline Followback interview. Results: Change in ADHD scores did not differ between atomoxetine + MI/CBT and placebo + MI/CBT (F4,191 = 1.23, p = 0.2975). Change in days used nonnicotine substances in the last 28 days did not differ between groups (F3,100 = 2.06, p = 0.1103). Conclusions: There was no significant difference between the atomoxetine + MI/CBT and placebo + MI/CBT groups in ADHD or substance use change. The MI/CBT and/or a placebo effect may have contributed to a large treatment response in the placebo group. (Contains 3 figures and 2 tables.)

Objective: To explore change in human immunodeficiency virus (HIV) risk among teens in outpatient treatment for substance use disorders (SUDs). Method: From December 2002 to August 2004, 50 adolescents (13-19 years) with major depressive disorder, conduct disorder, and one or more non-nicotine SUD completed the Teen Health Survey (THS) at the beginning and end of 16 weeks of outpatient cognitive behavioral SUD treatment, which included a one-session HIV intervention. Changes in THS scale scores and specific item responses targeted by the intervention were assessed with paired t tests and Wilcoxon signed rank tests. Results: Pre/post mean THS scores significantly improved for two subscales: Measures of HIV Information (14.8-17.6; p less than 0.001) and Beliefs about Condom Use (17.6-18.5; p less than 0.05). Analyses of specific items showed trends for improvement in intentions to carry condoms and in the number of teens who obtained condoms. Not all of the risks targeted by the intervention showed significant change, but no change was observed in any area that was not specifically targeted. Conclusions: Results from this preliminary study are consistent with the need for specific assessment and targeted intervention to reduce HIV risk in outpatient adolescent SUD treatment. (Contains 3 tables.)

A random clinical trial is conducted among adolescents with co-occurring major depression and substance use disorder to study adolescents for whom the onset of depression is first as compared to those for whom the onset of substance use disorder is first or in the same year as depression. Results reveal some differences in the developmental path towards co-occurring depression and substance use disorder but measures of dependence and severity show remarkable similarity.

Posttraumatic stress disorder (PTSD) in abused and neglected preschool children often leads to extreme and disabling symptoms that require a highly structured treatment program. Clinical results indicate that clonidine, a presynaptic alpha 2-adrenergic agonist, is effective in reducing symptoms of aggression, hyperarousal and sleep difficulties in children with severe PTSD. However, caution is advised when using psychotropic medications in preschool children.

Medical research is often designed to investigate changes in a collection of response variables that are measured repeatedly on the same subjects. The multivariate generalized linear mixed model (MGLMM) can be used to evaluate random coefficient associations (e.g. simple correlations, partial regression coefficients) among outcomes that may be non-normal and differently distributed by specifying a multivariate normal distribution for their random effects and then evaluating the latent relationship between them. Empirical Bayes predictors are readily available for each subject from any mixed model and are observable and hence, plotable. Here, we evaluate whether second-stage association analyses of empirical Bayes predictors from a MGLMM, provide a good approximation and visual representation of these latent association analyses using medical examples and simulations. Additionally, we compare these results with association analyses of empirical Bayes predictors generated from separate mixed models for each outcome, a procedure that could circumvent computational problems that arise when the dimension of the joint covariance matrix of random effects is large and prohibits estimation of latent associations. As has been shown in other analytic contexts, the p-values for all second-stage coefficients that were determined by naively assuming normality of empirical Bayes predictors provide a good approximation to p-values determined via permutation analysis. Analyzing outcomes that are interrelated with separate models in the first stage and then associating the resulting empirical Bayes predictors in a second stage results in different mean and covariance parameter estimates from the maximum likelihood estimates generated by a MGLMM. The potential for erroneous inference from using results from these separate models increases as the magnitude of the association among the outcomes increases. Thus if computable, scatterplots of the conditionally independent empirical Bayes predictors from a MGLMM are always preferable to scatterplots of empirical Bayes predictors generated by separate models, unless the true association between outcomes is zero. [ABSTRACT FROM AUTHOR]

Different types of outcomes (e.g. binary, count, continuous) can be simultaneously modeled with multivariate generalized linear mixed models by assuming: (1) same or different link functions, (2) same or different conditional distributions, and (3) conditional independence given random subject effects. Others have used this approach for determining simple associations between subject-specific parameters (e.g. correlations between slopes). We demonstrate how more complex associations (e.g. partial regression coefficients between slopes adjusting for intercepts, time lags of maximum correlation) can be estimated. Reparameterizing the model to directly estimate coefficients allows us to compare standard errors based on the inverse of the Hessian matrix with more usual standard errors approximated by the delta method; a mathematical proof demonstrates their equivalence when the gradient vector approaches zero. Reparameterization also allows us to evaluate significance of coefficients with likelihood ratio tests and to compare this approach with more usual Wald-type t-tests and Fisher's z transformations. Simulations indicate that the delta method and inverse Hessian standard errors are nearly equivalent and consistently overestimate the true standard error. Only the likelihood ratio test based on the reparameterized model has an acceptable type I error rate and is therefore recommended for testing associations between stochastic parameters. Online supplementary materials include our medical data example, annotated code, and simulation details. [ABSTRACT FROM AUTHOR]