Estimating the causal effects of cumulative treatment episodes for adolescents using marginal structural models and inverse probability of treatment weighting.
BACKGROUND
Substance use treatment is rarely a one-time event for individuals with substance use disorders. Sustained reductions in substance use and its related symptoms may result from multiple treatment episodes.


METHODS
We use a marginal structural model with inverse-probability-of-treatment weighting to estimate the causal effects of cumulative treatment experiences over a period of 9 months on drug use at the end of 1-year among 2870 adolescents receiving care in community-based treatment settings. During the 9 months, adolescents move in and out of outpatient and residential treatment with periods where they only receive biological drug screening (BDS) or no treatment at all. The use of inverse-probability-of-treatment weighting reduces confounding bias due to observed baseline and time-varying measures over the course of follow-up; weights were estimated using generalized boosted models.


RESULTS
Each additional period of treatment (representing at least one day, 1 session, or 1 BDS during the 90 day period between follow-up visits) yielded reductions in average substance use frequency at 1-year relative to no treatment during the 90-day period. For residential treatment it was a 16% decrease (95% CI=-27%, -7%), for outpatient treatment it was a 9% decrease (95% CI=-18%, -0%), and for BDS (with no additional outpatient or residential treatment) it was an 11% decrease (95% CI=-20%, -3%).


CONCLUSIONS
Using robust statistical methods, we find promising (albeit preliminary) evidence that additional periods of outpatient and residential treatment, as well as biological drug screening, lead to reductions in substance use outcomes at one year.
RAND Corporation, United States. Electronic address: bethg@rand.org.
Beth Ann
BA
Griffin
RAND Corporation, United States.
Rajeev
R
Ramchand
Institute for Social Research, United States.
Daniel
D
Almirall
RAND Corporation, United States.
Mary E
ME
Slaughter
RAND Corporation, United States.
Lane F
LF
Burgette
RAND Corporation, United States.
Daniel F
DF
McCaffery
D000293:Adolescent; D000465:Algorithms; D000553:Ambulatory Care; D003627:Data Interpretation, Statistical; D005260:Female; D006801:Humans; D008297:Male; D015233:Models, Statistical; D012114:Residential Treatment; D012959:Socioeconomic Factors; D015813:Substance Abuse Detection; D016320:Substance Abuse Treatment Centers; D019966:Substance-Related Disorders / Q000453:epidemiology / Q000534:rehabilitation*; D016896:Treatment Outcome; D014481:United States
Adolescent treatment; Cumulative treatment effects; Generalized boosted model; Inverse-probability-of-treatment weights; Marginal structural model; Time-varying confounding