The number of substance abuse program admissions for youths in the United States has been rising dramatically, increasing by 46 percent from 1993 to 1998. Despite this growth, little is known about the effectiveness of community-based treatment services for adolescents. Previous studies find that some adolescent outcomes improve after treatment and that outcomes vary across service modalities. These studies, however, are descriptive. They do not examine whether the services youths receive cause the observed functional improvements, or whether these improvements instead are caused by factors unrelated to treatment services, like maturation, the natural course of adolescent psychosocial problems or pretreatment differences in groups. Determining the causal effect attributable to adolescent services is more complex, but policy relevant: unless we know the relative improvement attributable to a particular form of treatment, time-in-treatment or source of referral, we can neither evaluate the relative cost-effectiveness of alternative services nor determine the value in funding such services. The proposed study estimates the causal effects of community-based adolescent services using data collected in NIDA's Drug Abuse Treatment Outcomes Studies for Adolescents (DATOS-A). Innovative statistical methods are planned to distinguish pretreatment group differences from differential treatment effects in the explanation of 12-month post treatment outcomes of youths receiving different service modalities. The study has four specific aims: 1) estimate the causal effects of outpatient, residential and short-term inpatient services on the outcomes of those adolescents most likely to enter each program; 2) for each modality, estimate the causal effects of treatment length; 3) compare the effectiveness of court-referred services to those provided without legal pressure; and 4) develop and evaluate statistical methods required for aims 1 to 3, and compare findings using our new methods to those produced using methods more standard in substance abuse treatment services research. This study will provide the most rigorous and conclusive assessment of the comparative effectiveness of community-based adolescent substance abuse programs yet conducted. In addition, it will develop and disseminate more relevant and robust causal modeling approaches to substance abuse treatment services research than are currently used in our field.

Agency
National Institute of Health (NIH)
Institute
National Institute on Drug Abuse (NIDA)
Type
Research Project (R01)
Project #
5R01DA015697-02
Application #
6730578
Study Section
Human Development Research Subcommittee (NIDA)
Program Officer
Hilton, Thomas
Project Start
2003-04-05
Project End
2006-03-31
Budget Start
2004-04-01
Budget End
2005-03-31
Support Year
2
Fiscal Year
2004
Total Cost
$230,045
Indirect Cost
Name
Rand Corporation
Department
Type
DUNS #
006914071
City
Santa Monica
State
CA
Country
United States
Zip Code
90401
Boruvka, Audrey; Almirall, Daniel; Witkiewitz, Katie et al. (2018) Assessing Time-Varying Causal Effect Moderation in Mobile Health. J Am Stat Assoc 113:1112-1121
Grant, Sean; Agniel, Denis; Almirall, Daniel et al. (2017) Developing adaptive interventions for adolescent substance use treatment settings: protocol of an observational, mixed-methods project. Addict Sci Clin Pract 12:35
Schuler, Megan S; Griffin, Beth Ann; Ramchand, Rajeev et al. (2014) Effectiveness of treatment for adolescent substance use: is biological drug testing sufficient? J Stud Alcohol Drugs 75:358-70
Almirall, Daniel; Griffin, Beth Ann; McCaffrey, Daniel F et al. (2014) Time-varying effect moderation using the structural nested mean model: estimation using inverse-weighted regression with residuals. Stat Med 33:3466-87
Griffin, Beth Ann; Ramchand, Rajeev; Almirall, Daniel et al. (2014) Estimating the causal effects of cumulative treatment episodes for adolescents using marginal structural models and inverse probability of treatment weighting. Drug Alcohol Depend 136:69-78
Schuler, Megan S; Leoutsakos, Jeannie-Marie S; Stuart, Elizabeth A (2014) ADDRESSING CONFOUNDING WHEN ESTIMATING THE EFFECTS OF LATENT CLASSES ON A DISTAL OUTCOME. Health Serv Outcomes Res Methodol 14:232-254
Ramchand, Rajeev; Griffin, Beth Ann; Slaughter, Mary Ellen et al. (2014) Do improvements in substance use and mental health symptoms during treatment translate to long-term outcomes in the opposite domain? J Subst Abuse Treat 47:339-46
McCaffrey, Daniel F; Lockwood, J R; Setodji, Claude M (2013) Inverse probability weighting with error-prone covariates. Biometrika 100:671-680
Almirall, Daniel; McCaffrey, Daniel F; Ramchand, Rajeev et al. (2013) Subgroups analysis when treatment and moderators are time-varying. Prev Sci 14:169-78
McCaffrey, Daniel F; Griffin, Beth Ann; Almirall, Daniel et al. (2013) A tutorial on propensity score estimation for multiple treatments using generalized boosted models. Stat Med 32:3388-414

Showing the most recent 10 out of 20 publications