Hospitalizations for Eating Disorders and Other Mental, Behavioral, and Neurodevelopmental Disorders Before and During COVID-19 in Canada
Bibliographic record
Abstract
PURPOSE: We assessed hospital admission rates for anorexia nervosa (AN)/atypical AN (AAN) relative to other mental, behavioral, and neurodevelopmental disorders across age groups before and 1-year postpandemic onset. METHODS: Using the Canadian Discharge Abstracts Database, we analyzed admissions for AN/AAN and mental, behavioral, and neurodevelopmental disorders in ages 10-84-year-olds, grouped into 10-24, 25-44, and 45+ year olds. Data spanned fiscal years (FY) 2006-2021. RESULTS: AN/AAN admissions increased in the 10-24-year-old group, while remaining stable in older age groups. In FY2019, AN/AAN constituted 2.6% (95% confidence interval 2.4-2.8) of psychiatric admissions, increasing to 4.1% (95% confidence interval 3.9-4.3) in FY2020. Odds ratio for FY2019-FY2020 hospitalizations in 10-24 group was 1.61 (p < .0001), 25-44 was 1.15 (p = .31), and 45+ was 0.61 (p = .03). DISCUSSION: AN/AAN admissions surged among 10-24 year-olds during the pandemic's onset, underscoring the need for early interventions and preparedness to support adolescents and young adults with AN/AAN.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".