New and Pre-existing Eating Disorders Among Adolescents and Young Adults During the COVID-19 Pandemic: A Population-Based Cohort Study
Bibliographic record
Abstract
ObjectivesOur understanding of the contribution of new presentations versus pre-existing eating disorders during the COVID-19 pandemic is limited. This study aims to evaluate rates of emergency department (ED) visits and hospitalizations for eating disorders among adolescents and young adults (YA) new to care and those with pre-existing eating disorders during the pandemic. ApproachWe conducted a population-based cross-sectional study using linked health administrative data for Ontario residents aged 10-26 during the pre-pandemic (Jan. 1, 2017-Feb. 29, 2020) and pandemic periods (Mar. 1, 2020-Jun. 30, 2022). We used Poisson generalized estimating equations models to predict expected overall and monthly rates of eating disorder-related ED visits and hospitalizations among those with a new and pre-existing eating disorder. ResultsCompared with expected rates, ED visits increased during the pandemic among only adolescents with new eating disorders (adolescent RR 2.12, 95% CI [1.84,2.45]). Additionally, both adolescents and YA with pre-existing eating disorders experienced an increase in ED visits (RR 2.78, 95% CI [2.28, 3.38] and RR 1.52, 95% CI [1.25, 1.85], respectively). Similarly, hospitalizations for new presentations increased solely for adolescents (RR 1.48, 95% CI [1.34,1.64]), while hospitalizations for pre-existing eating disorders increased for both adolescents (RR 1.82, 95% CI [1.43,2.32]) and YA (RR 1.12, 95% CI [1.01,1.23]). ConclusionsThere was an increase in acute care visits for eating disorders during the pandemic, especially among adolescents and YA with pre-existing conditions. This differentiation is important in advancing our understanding of the pandemic's effects on adolescents and YA and the healthcare system receiving them.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".