Efficacy of extensive intervention models for substance use disorders: A systematic review
Bibliographic record
Abstract
ISSUES: Despite a growing trend towards considering addiction as a chronic disease, the development of intervention models addressing the chronicity of substance use disorder is relatively new, and no literature review on this topic is available. The aim of this systematic review is to evaluate the efficacy of intervention models designed within the perspective of addiction as a chronic disease and those tailored to persons with substance use disorder who revolve in and out of treatment. APPROACH: Electronic databases were searched to identify articles published between 2000 and 2015 reporting an empirical study of an intervention model with data on its effectiveness. Study selection, data extraction and quality appraisal were performed independently by two reviewers. KEY FINDINGS: The selection process yielded 16 studies meeting all the inclusion criteria. The intervention models were classified into four groups according to the duration, frequency and components of the interventions. In general, the models showed potential therapeutic effects. The outcomes tended to be positive immediately after the end of the treatment. However, months after, the benefits obtained during treatment did not persist. IMPLICATIONS AND CONCLUSION: The review highlights that models designed specifically for persons with multiple treatment re-entries are scarce, but promising. Further research is needed to determine the best match between the clinical profile of persons with substance use disorder and a model's components, intensity and duration. [Simoneau H, Kamgang E, Tremblay J, Bertrand K, Brochu S, FleuryM-J. Efficacy of extensive interventionmodels for substance use disorders: A systematic review. Drug Alcohol Rev 2017;00:000-000].
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.008 | 0.003 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".