Psychosocial therapeutic interventions for volatile substance use: a systematic review
Bibliographic record
Abstract
AIMS: Volatile substance use (VSU) is associated with a range of adverse outcomes, including cognitive impairment and death. It occurs disproportionately within young and marginalized populations. A previous international systematic review of VSU treatment identified no relevant studies. This paper reports on a systematic review of a range of study types concerning psychosocial interventions for VSU. METHODS: Search parameters were developed using the Population, Intervention, Professionals, Outcomes, Health care setting and Contexts (PIPOH) tool with input from an expert committee. Included were randomized controlled trials (RCTs), comparative studies with or without concurrent controls, case series studies and grey literature, published in English during 1980-2010. RESULTS: The initial search identified 2344 references. After two screening phases, 23 studies of VSU therapeutic interventions remained. Of these, 19 concerned psychosocial interventions, which we discuss as: case management; counselling; recreation and engagement programmes; and residential treatment. Studies were conducted in Australia, Canada, the United States, United Kingdom and Brazil. No RCTs were identified and studies were generally of low evidentiary levels. CONCLUSIONS: Even when a range of study types are included, clear conclusions for volatile substance use psychological treatment are not supported, but three intervention types merit further examination: family therapy, activity-based programmes and Indigenous-led residential approaches. Future volatile substance use research could be enhanced by developing and validating outcome measurement tools. Robust multi-site studies are also required.
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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 | 0.004 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".