Post-Treatment Outcomes Among Adjudicated Adolescent Males and Females in Modified Therapeutic Community Treatment
Bibliographic record
Abstract
Identifying effective targeted interventions for substance using delinquent populations has remained an important objective for researchers and clinicians alike. To this end, the current study examines the client characteristics and post-treatment outcomes among youths admitted to Recovery House (RH), an innovative program that traverses the separation of juvenile justice and treatment. Data for the current analyses derive from a National Institute on Drug Abuse-funded 5-year post-treatment outcome study (NIDA #P50-DA-0770) of N = 938 adolescent clients admitted to therapeutic community (TC) programs in the United States and Canada during the period April 1992 to April 1994. Note the year The subsample of N = 200 males and N = 82 females from the two RH facilities is the focus of the current study. The 5-year follow-up sample contained 57.9% or N = 70 of the original sample of RH males and 62.2% or N = 51 or the original RH females. Chi-square statistics, one-way analysis of variance, and the Wilcoxon Signed Rank test was used to examine pretreatment, admissions, and outcome variables and to assess within person differences pre- to post-treatment. The profile of the adolescents at admission to Recovery House reveals that the youth were primarily involved with marijuana, and secondarily with alcohol, prior to treatment. The sample yielded multiple psychiatric disorders, the single most prevalent diagnosis being Conduct Disorder They also revealed extensive involvement in criminal activity (e.g., drug sales, violent crimes, and property crimes). Post-treatment drug use other than marijuana and alcohol was infrequent and there were reductions in the actual percent reporting involvement in most categories of criminal involvement. Gender analyses revealed that even though females were less likely to complete treatment, their post-treatment outcomes were better; proportionately fewer females compared with males were involved with marijuana use and with almost all categories of crime. In general, the findings suggest that programs such as RH can be successful in addressing the critical problem of youth substance use and criminal activity.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".