Towards an International Consensus on the Prevention, Treatment, and Management of High-Risk Substance Use and Overdose among Youth
Bibliographic record
Abstract
Background and Objectives: Now more than ever, there is an obvious need to reduce the overall burden of disease and risk of premature mortality that are associated with mental health and substance use disorders among young people. However, the current state of research and evidence-based clinical care for high-risk substance use among youth is fragmented and scarce. The objective of the study is to establish consensus for the prevention, treatment, and management of high-risk substance use and overdose among youth (10 to 24 years old). Materials and Methods: A modified Delphi technique was used based on the combination of scientific evidence and clinical experience of a group of 31 experts representing 10 countries. A semi-structured questionnaire with five domains (clinical risks, target populations, intervention goals, intervention strategies, and settings/expertise) was shared with the panelists. Based on their responses, statements were developed, which were subsequently revised and finalized through three iterations of feedback. Results: Among the five major domains, 60 statements reached consensus. Importantly, experts agreed that screening in primary care and other clinical settings is recommended for all youth, and that the objectives of treating youth with high-risk substance use are to reduce harm and mortality while promoting resilience and healthy development. For all substance use disorders, evidence-based interventions should be available and should be used according to the needs and preferences of the patient. Involuntary admission was the only topic that did not reach consensus, mainly due to its ethical implications and resulting lack of comparable evidence. Conclusions: High-risk substance use and overdoses among youth have become a major challenge. The system’s response has been insufficient and needs substantial change. Internationally devised consensus statements provide a first step in system improvement and reform.
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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 | 0.277 | 0.179 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.007 | 0.004 |
| Science and technology studies | 0.006 | 0.010 |
| Scholarly communication | 0.012 | 0.010 |
| Open science | 0.010 | 0.021 |
| Research integrity | 0.018 | 0.022 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".