Recidivism and indices of drug abuse treatment effectiveness.
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Biomedical subjects
Publications and source records attributed to G W Joe.
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Relationships between age at initial marijuana use and selected behavioral measures representing education, arrests, employment, alcohol use, and other drug use were examined for a sample of 370 male veterans. Younger age at marijuana use was found to be associated with less education, more arrests, and more other drug use prior to entering the service. A factor analysis of the correlates of age at initial marijiana use suggested three factors of delinquent activities: drug use, school delinquency, and other propensities for delinquency.
Preliminary findings for the first cohort of a national follow-up study of drug users admitted to treatment in the Drug Abuse Reporting Program (DARP) during 1969-1971 are reported. From a sample of 1,853 selected for follow-up, 87% were located and interviews were completed for 77%. Gross tabulations are shown comparing several outcome measures based on pre-DARP treatment, the posttreatment period, and for the 2 months before interview. Sixty-one percent of all patients returned to treatment at some time after DARP termination. Decreases in drug use, expecially of opioids, were substantial and were generally accompanied by improvements in other outcome measures as well. Plans for more detailed and informative analysis of these and related DARP data are addressed.
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It was hypothesized that node-link mapping a tool for visually representing client issues during drug abuse counseling, would reduce communication barriers between counselors and their African American and Mexican American clients. Three hundred twenty daily opioid users participated in methadone maintenance treatment programs in three cities for 6 months or longer following random assignments to mapping-enhanced or standard counseling. Clients in the mapping condition had fewer drug-positive urines (with respect to opiates and cocaine), missed fewer scheduled counseling sessions, and were rated more positively by their counselors on rapport, motivation, and self-confidence during the first 6 months of treatment. Significant interactions involving ethnicity and counseling condition suggested that mapping is more effective for African Americans and Mexican Americans than for Whites. The use of mapping appears to help reduce cultural, racial, and class communication barriers by providing a visual supplement and a common language that enhances counselor-client interchanges.
Clients in a community-based methadone treatment program earned stars for attending counseling sessions as scheduled and for providing clean urines. These stars were later redeemed for contingent rewards (food or gas coupons or bus tokens) according to one of three randomly assigned reward schedules, including high reward (four stars per prize), low reward (eight stars per prize), or delayed reward (those who had to wait 3 months to earn a prize). Clients in the high-reward condition showed a pattern of increasing the number of stars earned for group sessions and clean urines across the 3-month intervention. All clients, independent of reward condition, attended significantly more group counseling sessions during the months that contingent reinforcers were available than in the months prior to, and after, the intervention. Finally, urinalysis data indicated that, in the postintervention period, high-reward clients had fewer dirty urines than did low-reward or delayed-reward clients. This study suggests that a simple system of recognizing client progress with stars and modest prizes for performing specific behaviors can be an effective tool in increasing clinic attendance rates and reducing positive urines.
This study of methadone-maintenance clients interviewed approximately 1 year after discharge from treatment revealed that outcomes differed between heavy-drinking clients who are alcohol dependent and those who are not. Alcohol-dependent clients seem to benefit more from treatment but continue to have severe cocaine-use problems, suggesting they also may be cocaine dependent. The results emphasized the value in differentiating between these types of drinking clients, and they suggest that failure to do so may account for earlier contradictory results about the role alcohol consumption has in treatment outcomes for methadone-maintenance clients.
Integrative models containing client and treatment components were tested in a sample of 396 daily opioid users from three methadone maintenance treatment sites. Measures included client motivation at intake as well as repeated assessments of therapeutic engagement (relationships between clients and their counselors, session attendance, and results of urine testing) during the first 6 months of treatment. There was a positive effect of pretreatment motivation on greater engagement and a reciprocal positive relationship between components of engagement and their effects on lowering drug use throughout treatment. Further analyses addressed differential effects of group versus individual counseling and showed that group session attendance was associated with higher rates of drug-negative urines.
BACKGROUND: Longer retention has been the most consistent predictor of favorable drug abuse treatment outcomes, but key therapeutic and patient engagement indicators of treatment process need to be more clearly established. METHODS: An integrative model representing treatment dynamics was tested for explaining long-term program retention. It was based on a multisite sample of 527 daily opioid users who remained in methadone maintenance a minimum of 3 months. All had been assigned randomly to a counseling condition at admission (i.e., cognitively enhanced or standard), and information obtained from patient files, as well as periodic assessments completed by patients and their counselors in the first 90 days after admission were the sources of predictors. RESULTS: Counseling enhancements (using node-link mapping, a visual representation tool for improving communication and problem solving) contributed to stronger therapeutic relationships between counselor and patient, which in turn had a positive reciprocal relationship with patient engagement (session attendance). Pretreatment motivation measured at intake was also related to higher engagement. More positive therapeutic relationships (in months 1 and 2) led to lower levels of during-treatment drug use (defined from urinalysis results in months 2 and 3), and better session attendance and therapeutic relationships both predicted longer retention. In addition, lower drug use during treatment was related to longer retention. CONCLUSIONS: Major conceptual domains of drug abuse treatment process were identified in community-based programs and their interrelationships with retention specified. As intermediate (during treatment) criteria, they can help guide functional improvements in program effectiveness as illustrated with our counseling enhancements.
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Recidivism rates and recidivism proportions for return to a state of daily opioid use following discharge from drug abuse treatment were studied for a sample of Black and White male daily opioid users. The rates and proportions were analyzed by treatment type and time in treatment. Significantly higher recidivism proportions were found for shorter tenure clients.
Follow-up studies of drug user treatment generally find significant improvements in client functioning, but information about the therapeutic components associated with client behavioral changes over time is limited. An integrative model developed previously to predict treatment retention was expanded and applied to post-treatment outcomes. This study is based on 321 daily opioid users treated in three methadone treatment clinics. Effects of pre-treatment motivation, treatment process measures representing therapeutic relationship, counseling session attendance, and length of treatment are examined in relation to measures of family relations, peer deviancy, return to treatment, drug use, and criminality in the year after treatment. Models were tested in two stages. The first was built on a during-treatment process model for predicting time in treatment to include post-treatment outcomes. The second model was expanded further to include the effects of intervening social support variables as predictors of post-treatment drug and criminality outcomes. The results supported both models and emphasize the importance of considering social influences and related community contextual factors that affect recovery dynamics.