Understanding the inter-relationships among addiction to multiple drugs and between co-occurring substance use and psychiatric disorders is a key priority of NIDA's, given ample research showing extremely high rates of their co-morbidity. Limitations of existing analytic methods impede further progress in these areas, because trajectories describing drug use and co-occurring disorders over time are complex--often nonlinear and based on outcomes with different distributions. Timeline Follow back (TLFB), the most widely utilized and accepted measure for determining drug use outcomes, collects reports of daily use (e.g. used marijuana, yes/no;joints per day) on multiple drugs over specified intervals. But TLFB data are not analyzed as collected (e.g. repeated binomial and Poisson variables). Rather, data are typically collapsed into summaries like total days of use (or abstinence) during a trial, or collapsed over smaller intervals (e.g. monthly sums of days used) in an attempt to create normally distributed variables. Such composite scores sacrifice information, lose efficiency, and are often not normal. Abundant previously collected longitudinal data on outcomes with different distributions like those from TLFB exist, but an inability to analyze them as such prevents satisfactorily addressing scientifically and clinically relevant questions such as: What is the temporal relationship between use of two or more drugs? What is the temporal relationship between change in drug use and change in co-occurring disorders? Do co- occurring psychiatric symptoms remit with reductions in drug use, or do reductions in psychiatric symptoms precede reductions in drug use? At what point does reduction in one occur relative to the other? This project's first two aims propose rigorous theoretical derivation and simulation to develop a multivariate nonlinear mixed model (MvNLMIXED) to simultaneously estimate and compare nonlinear trajectories of substance use and comorbidity outcomes with different distributions over time and between groups (Aim 1), and to evaluate inter- relationships among those jointly modeled trajectories by estimating their association (Aim 2a) and the order of, and time-lag among, change in one relative to the other (Aim 2b).
Aims 3 and 4 will apply MvNLMIXED methods to answer important questions in two pharmacotherapy trials for co-occurring Attention-Deficit Hyperactivity Disorder (ADHD) in adolescents who also received cognitive behavioral therapy for drug use: a trial of atomoxetine and a multi-site trial o Osmotic-Release Methylphenidate in NIDA's Clinical Trials Network. These novel analyses are expected to identify important inter-relationships among use of different drugs with each other (Aim 3) and with ADHD (Aim 4), potentially informing how treatment may be operating. Beyond their importance for evaluating inter-relationships in these two trials and among drug use and comorbidity in general, these novel methods are widely applicable to evaluating temporal relationships among any jointly modeled longitudinal variables, benefiting new research and enhancing the scientific value of existing databases. User-friendly software for these methods will be made available on multiple platforms.

Public Health Relevance

Substance use disorders are a major public health problem, are linked to serious morbidity and mortality, and are strongly linked to other co-occurring psychiatric disorders such as attention deficit hyperactivity disorder (ADHD), depression, and antisocial behaviors that have a highly negative impact on individuals and society. Developing statistical methodology for describing how substance use and other psychiatric disorders change and inter-relate over time will clarify their temporal relationships and may lead to a clearer understanding of how to successfully prevent and treat these conditions. These novel methods will be used to answer important questions about how alcohol, cigarettes, marijuana, and other illicit drugs inter-relate with each other and with ADHD, using data from two clinical trials of adolescents in treatment for ADHD and substance use disorders and more generally, the novel methods will facilitate the understanding of temporal relationships among any longitudinal outcomes with different distributions.

National Institute of Health (NIH)
National Institute on Drug Abuse (NIDA)
Research Project (R01)
Project #
Application #
Study Section
Special Emphasis Panel (ZRG1-PSE-P (55))
Program Officer
Kahana, Shoshana Y
Project Start
Project End
Budget Start
Budget End
Support Year
Fiscal Year
Total Cost
Indirect Cost
University of Colorado Denver
Schools of Medicine
United States
Zip Code
Sakai, Joseph T; Dalwani, Manish S; Mikulich-Gilbertson, Susan K et al. (2017) Imaging decision about whether to benefit self by harming others: Adolescents with conduct and substance problems, with or without callous-unemotionality, or developing typically. Psychiatry Res 263:103-112
Al-Tayyib, Alia; Riggs, Paula; Mikulich-Gilbertson, Susan et al. (2017) Prevalence of Nonmedical Use of Prescription Opioids and Association With Co-occurring Substance Use Disorders Among Adolescents in Substance Use Treatment. J Adolesc Health :
Crowley, Thomas J; Dalwani, Manish S; Sakai, Joseph T et al. (2017) Children's brain activation during risky decision-making: A contributor to substance problems? Drug Alcohol Depend 178:57-65
Sakai, Joseph T; Dalwani, Manish S; Mikulich-Gilbertson, Susan K et al. (2016) A Behavioral Measure of Costly Helping: Replicating and Extending the Association with Callous Unemotional Traits in Male Adolescents. PLoS One 11:e0151678
Coors, Marilyn E; Raymond, Kristen M; Hopfer, Christian J et al. (2016) Adolescents with substance use disorder and assent/consent: Empirical data on understanding biobank risks in genomic research. Drug Alcohol Depend 159:267-71
Sannes, Timothy S; Mikulich-Gilbertson, Susan K; Natvig, Crystal L et al. (2016) Intraindividual Cortisol Variability and Psychological Functioning in Caregivers of Hematopoietic Stem Cell Transplant Patients. Psychosom Med 78:242-7
Boulos, Peter K; Dalwani, Manish S; Tanabe, Jody et al. (2016) Brain Cortical Thickness Differences in Adolescent Females with Substance Use Disorders. PLoS One 11:e0152983
Sakai, Joseph T; Mikulich-Gilbertson, Susan K; Young, Susan E et al. (2016) Adolescent Male Conduct-Disordered Patients in Substance Use Disorder Treatment: Examining the ""Limited Prosocial Emotions"" Specifier. J Child Adolesc Subst Abuse 25:613-625
Coors, Marilyn E; Raymond, Kristen M; McWilliams, Shannon K et al. (2015) What adolescents enrolled in genomic addiction research want to know about conflicts of interest. Drug Alcohol Depend 147:272-5
Dalwani, Manish S; McMahon, Mary Agnes; Mikulich-Gilbertson, Susan K et al. (2015) Female adolescents with severe substance and conduct problems have substantially less brain gray matter volume. PLoS One 10:e0126368

Showing the most recent 10 out of 14 publications