Predictors of treatment receipt among adults with a drug use disorder.
This study used data from the 2000 and 2001 National Household Surveys on Drug Abuse to examine factors that contribute to the receipt of specialty substance abuse treatment, which is defined as treatment in rehabilitation facilities, hospitals, or mental health centers designed to help stop or reduce drug use. The population examined was a nationally representative sample of 3291 adults aged 18 or older with a drug use disorder in the past 12 months. Data were collected by computer-assisted interviews using a combination of computer-assisted personal interviews conducted by the interviewer and audio computer-assisted self-interviewing guided by the computer and respondent. Using descriptive analyses and multivariate logistic regression models, this study compared sociodemographic, substance abuse, and psychosocial characteristics of those receiving treatment with those not receiving treatment; it also examined the factors that influenced treatment receipt while controlling for potential confounders. Characteristics significantly contributing to treatment receipt among adults with a drug use disorder included the following: a woman without social support; a high school graduate with no college education; those receiving insurance through Medicaid or a state Children's Health Insurance Program; those on probation, parole, or supervised release in the past year; a daily smoker of cigarettes; those meeting at least three criteria for drug dependence; those having past year dependence on or abuse of alcohol; and those receiving any mental health treatment or counseling in the past year. Adults associated with the criminal justice system had a different pattern of treatment predictors from those who were not involved with the criminal justice system.
Epstein
Joan F
JF
Office of Applied Studies, Substance Abuse and Mental Health Services Administration, Rockville, Maryland 20857, USA.
Hourani
Laurel L
LL
Heller
David C
DC
D000293:Adolescent; D000328:Adult; D000437:Alcoholism / Q000453:epidemiology / Q000534:rehabilitation*; D003201:Computers; D003415:Crime / Q000523:psychology / Q000706:statistics & numerical data; D005260:Female; D006297:Health Services Accessibility / Q000706:statistics & numerical data*; D006306:Health Surveys; D006801:Humans; D013287:Illicit Drugs; D007406:Interview, Psychological; D016015:Logistic Models; D008297:Male; D008432:Mathematical Computing; D015999:Multivariate Analysis; D011336:Probability; D012017:Referral and Consultation / Q000706:statistics & numerical data*; D012044:Regression Analysis; D040841:Resource Allocation / Q000706:statistics & numerical data*; D012907:Smoking / Q000453:epidemiology; D016540:Smoking Cessation; D012959:Socioeconomic Factors; D016320:Substance Abuse Treatment Centers / Q000706:statistics & numerical data*; D019966:Substance-Related Disorders / Q000453:epidemiology / Q000534:rehabilitation*
D013287:Illicit Drugs