Clinical, Discharge and Psychosocial Profiles of Adolescents with Substance Use Disorder Accessing Inpatient Psychiatry in Ontario, Canada
Bibliographic record
Abstract
Objective: The aim for this study was to explore the proportion of patients with a Substance Use Disorder (SUD), their proportion of overall admissions, and their psychosocial histories at a regional child and adolescent inpatient psychiatric unit. Methods: A retrospective chart review was conducted on all admissions of patients with a SUD. Abstracted patient data included demographic information, diagnoses, psychosocial histories, living situation at the time of admission, legal involvement and charges, whether an alternate level of care was needed, and discharge plans. Results: From September 2018 to February 2020, of the 540 patients admitted, 126 (23.3%) had a SUD recorded in their charts and accounted for 34.6% of the total number of admissions. Their mean age was 15.85 (SD 1.10; range 13 to 18) years, and most were identified as female (n=81; 64%), which is consistent with the number of female patients admitted during the study period (n=366 female of 540 admitted; X2=0.56, p= 0.45). Common psychiatric diagnoses included mood, trauma, and stressor-related and anxiety disorders. Most patients (124; 98.4%) had a history of psychosocial adversity, 90 (71.4%) patients had a parent with a mental illness or a SUD, 55 (44%) reported being bullied, 54 (43%) reported being sexually assaulted and several (n=41;33%) had experienced precarious living situations. Conclusion: Adolescent inpatients with a SUD were also managing a complex array of clinical and psychosocial challenges. Upon discharge from the hospital, some patients were placed on waitlists, and many patients were referred to specialized treatment far from home, highlighting the need for additional, comprehensive programs for SUD and the constellation of psychosocial problems associated with these disorders.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".