Benzodiazepine Use Disorder Observed and Diagnosed in a Tertiary Care Pediatric Specialty Clinic: A Descriptive Retrospective Chart Review
Bibliographic record
Abstract
Aims Objectives: In youth and young adults, it is common to encounter non-medical use of benzodiazepines, defined as use without a prescription or use for reasons other than that for which the medication is intended. Benzodiazepine use disorder remains understudied and overlooked, especially in youth and young adults. The primary objective of our study was to highlight the proportion of youth and young adults with aberrant use of benzodiazepines and diagnosed with benzodiazepine use disorder in a single centre. The secondary objective was to determine factors associated with aberrant benzodiazepine use and benzodiazepine use disorder in that sample. Methods This retrospective chart review screened for benzodiazepine use in 310 adolescent patients aged 12–19 seen for the first time in a concurrent disorders clinic, at a tertiary care clinic in Canada. Of those 310 patients, 167 were included in the final chart review. Results 97.6% of patients who used benzodiazepines demonstrated aberrant use, and 39.3% of patients received a diagnosis of benzodiazepine use disorder. Conclusion This review showed that a substantial percentage of youth and young adults in a concurrent disorders clinic in Canada are presenting with aberrant benzodiazepine use and are being diagnosed with benzodiazepine use disorder. Despite this prevalence, there is little by way of literature to guide treatment of benzodiazepine use disorder in this population.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".