Predictors of substance abuse treatment retention among women and men in an HMO

Alcohol Clin Exp Res. 2000 Oct;24(10):1525-33.

Abstract

Background: Although prior research has examined predictors of treatment retention in public alcohol and drug treatment programs, little is known about factors that influence treatment retention in an insured outpatient population. Because there is growing evidence that the factors which influence treatment retention may differ by gender, we identify sex-specific predictors.

Methods: We recruited all eligible intakes to a health maintenance organization's outpatient alcohol and drug treatment program during a 2-year period and obtained a sample of 317 women and 599 men. The programs, day hospital and traditional outpatient modalities, were abstinence based. We separated our sample by sex and used least squares and logistic regression to identify independent predictors of length of stay and program completion, respectively.

Results: One general pattern of predictors of increased retention was shared by women and men in this alcohol and drug treatment program--fewer and less severe drug problems. However, most predictors were sex-specific. Among women, retention was predicted by having higher incomes, belonging to ethnic categories other than African American, being unemployed, being married, and having lower levels of psychiatric severity. Among men, predictors of higher retention included being older, receiving employer suggestions to enter treatment, and having abstinence goals.

Conclusions: These findings highlight the importance of examining aspects of the course of treatment separately by sex. They also suggest treatment factors that may enhance retention among insured populations, including employer referrals, psychiatric services, and drug-related services.

Publication types

  • Comparative Study
  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Adult
  • Age Factors
  • Educational Status
  • Employment
  • Ethnicity
  • Female
  • Health Maintenance Organizations*
  • Humans
  • Income
  • Logistic Models
  • Male
  • Middle Aged
  • Patient Compliance
  • Patient Dropouts*
  • Sex Characteristics
  • Substance-Related Disorders / therapy*