title: Gender differences in drug treatment careers among clients in the national Drug Abuse Treatment Outcome Study.
abstract: Gender differences in the factors associated with having a history of drug treatment were examined among 7,652 individuals admitted into the Drug Abuse Treatment Outcome Study (DATOS), a national multisite prospective study. Bivariate relationships were examined between a history of prior drug treatment and variables measuring demographic and background characteristics, addiction career, treatment career parameters, family and social relationships, criminal justice involvement, and mental health status. Stepwise discriminant function analyses (DFAs) were conducted separately for men and women to determine both the common and unique characteristics associated with a history of prior drug treatment. More severe drug use history and criminal behavior were related to prior treatment history for both men and women. Prior drug treatment among men was associated with factors related to family opposition to drug use and support for treatment, whereas for women prior drug treatment was associated with antisocial personality disorder and self-initiation into treatment. Moreover, treatment initiation among men appears to be facilitated by social institutions, such as employment, the criminal justice system, and one's family. In contrast, treatment reentry among women was associated with referral by a social worker, suggesting that contact with family service agencies can facilitate women's treatment entry. The findings suggest that different strategies for increasing treatment utilization may be appropriate for men and women.
authors.affiliation: UCLA Drug Abuse Research Center, Neuropsychiatric Institute, University of California, Los Angeles 90025, USA. grella@ucla.edu
authors.forename: C E
authors.initials: CE
authors.lastname: Grella
authors.forename: V
authors.initials: V
authors.lastname: Joshi
mesh_terms: D000328:Adult; D000704:Analysis of Variance; D003415:Crime / Q000706:statistics & numerical data; D016002:Discriminant Analysis; D005260:Female; D006801:Humans; D016014:Linear Models; D008297:Male; D001523:Mental Disorders / Q000150:complications; D011446:Prospective Studies; D012017:Referral and Consultation / Q000706:statistics & numerical data; D012307:Risk Factors; D012737:Sex Factors; D012944:Social Support; D012959:Socioeconomic Factors; D016320:Substance Abuse Treatment Centers / Q000706:statistics & numerical data*; D019966:Substance-Related Disorders / Q000453:epidemiology* / Q000523:psychology; D014481:United States / Q000453:epidemiology