The role of functional social support in treatment retention and outcomes among outpatient adult substance abusers
Bibliographic record
Abstract
AIMS: The goals of this study were: (1) to compare patients with high and low functional social support at intake and 6 months later on various risk factors; (2) to test the stress-buffering role of functional social support on treatment outcomes, and (3) to determine whether levels of functional social support at intake predicted treatment retention. DESIGN: Consecutive admissions to an outpatient treatment program were assessed at intake (n = 206) and at 6 month follow-up (n = 172) using the Addition Severity Index (ASI). Patients completed questionnaires pertaining to social support, stress and psychological functioning both at intake and at 6 months. FINDINGS: Both high and low social support groups experienced marked declines in negative affect and in the severity of substance abuse over time. There were some group differences: for example, symptoms of depression and psychological distress were higher among patients with low social support at intake and at 6 months. Patients with low social support at intake reported higher severity of alcohol and drug abuse at 6 months. Hierarchical regression analyses showed that functional social support was a modest predictor of reductions in the severity of alcohol abuse at follow-up, after controlling for the number of days in treatment. Higher levels of social support explained a modest (6%) proportion of the variance in alcohol-related outcomes, but did not predict reductions in drug abuse. Survival analysis demonstrated that the rate of dropping out of treatment was significantly higher for patients with low social support. CONCLUSIONS: Higher functional social support at intake is a positive predictor of retention in treatment, and a modest predictor of reductions in alcohol intake, but not in drug use. Overall, social support accounts for a small percentage of the variance in drug/alcohol-related outcomes, underscoring the need for further research into variables accounting for treatment success and failure.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".