Illicit drug toxicity from opioid, stimulant or sedative use in adolescents: results of a Canadian one-time cross-sectional study
Bibliographic record
Abstract
Background: Illicit drug toxicity is an escalating public health emergency. Usually framed as an adult issue, adolescents are significantly impacted. Little is currently known about the interface between Canadian paediatric physicians and adolescents experiencing severe health events from illicit drug toxicity. Objectives: (1) To determine the proportion of paediatricians in Canada who care for young people between 12 and 18 years who have managed cases of illicit drug toxicity; (2) to identify the characteristics of paediatricians that provide this care; and (3) to describe respondents' awareness of substance use-oriented services for youth in their home communities. Methods: A one-time descriptive cross-sectional study was conducted from May to June 2022. Clinicians self-reported cases of illicit drug toxicity from opioids, stimulants and sedatives for adolescents 12 to 18 years old over the preceding 24-month period. Respondents also self-reported their knowledge of substance use-focussed services for children and adolescents in their communities. Results: = 934, 91%) reported providing medical care to children and youth 12 years of age and over. 128/934 (13.7%) reported caring for at least one case of illicit drug toxicity. The majority of case reporters were general paediatricians (43%). Overall awareness of substance-related services was limited. Conclusion: A considerable proportion of respondents provided care for illicit drug toxicity over 24 months. This contrasts with a relatively low level of awareness of services for substance use in this population. Further research and education can support patients and physicians alike in the care of adolescent illicit drug toxicity.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".