6 Incidence of Eating Disorders During COVID-19: A Retrospective Review
Bibliographic record
Abstract
Abstract Background The COVID-19 pandemic has had marked effects on mental health, including in pediatric populations. Pediatric patients have faced mental health concerns at increased rates including anxiety and depression. Furthermore, patients with eating disorders represent a vulnerable group who have been negatively impacted as well, as a result of lack of support, loss of in-person follow-up and increased relapse. In our centre, and nationally, clinicians have noted a trend towards increased eating disorder referrals and increased hospitalizations during the pandemic. Objectives The objective of this study was to determine the incidence, severity and triggers for eating disorders in the adolescent population during the COVID-19 pandemic and how it compares to the year prior. As well, the subset of patients who were hospitalized for medical stabilization were further analyzed to determine severity of illness. Design/Methods A retrospective chart review compared the first year of the COVID-19 pandemic (March 2020-March 2021), to the previous 12 months. Inclusion criteria included referrals to an eating disorder clinic and inpatient admissions to pediatrics or mental health services during the specified time frame. Data collected included age of onset, triggers, comorbid mental health conditions, and weight measures. Among hospitalized patients, orthostatic vital changes, need for NG feeds, length of medical stabilization and length of mental health hospitalization were included. Results Overall, 76 patients were included in the study. 44 (57.9%) were referred after COVID, which was significantly increased from the prior year (p=0.05). On average, patients presented at a younger age (14.2 ± 2.3 vs. 14.9 ± 1.9; p=0.08). Pre-COVID, approximately 44% of referrals were from family physicians and 19% from pediatrics. During COVID, approximately 39% were from family doctors and 25% from pediatricians. There was an increase in the number of patients requiring hospitalization for treatment (16 vs. 3), with 50% of the post-COVID admissions being direct from the ED Clinic on initial assessment. The reason for hospitalization was unstable vitals/ bradycardia in 68.7% of admissions; self-harm comprised the majority of the other admissions. Conclusion Our results support national and international reports that eating disorder incidence has increased during COVID-19. Patients described loss of routine, anxiety, and isolation as triggers related to the pandemic. Disruptions to daily life including school, sports, recreation, and relationships had profound effects on the mental health of children. The effect of social media on body image has also contributed. It is important for clinicians to screen for mental health conditions, including eating disorders at all available opportunities. Furthermore, this study demonstrates the need for increased services at our centre. Limitations for this study include that it is a single-centre study with a relatively small patient population. As well, it does not capture patients who may have been referred only to psychiatry.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".