A Follow-up Study on the Effects of the COVID-19 Pandemic on Adolescents with Eating Disorders
Bibliographic record
Abstract
Aim: At the onset of the COVID-19 pandemic, we conducted a study to evaluate its early effects on eating disorder behavior and its predictive factors in patients with eating disorders. However, little is known about its long-term effects. The purpose of this second study was to reevaluate the same group. Methods: The sociodemographic characteristics, clinical information, and information on how the pandemic restrictions affected ED behaviours, well-being, and quality of life were evaluated. All participants completed the ED examination questionnaire, Beck Depression Inventory, The State Anxiety Inventory for Children, and The Maudsley Obsessive Compulsive Inventory one-year after the initial assessments. Results: Thirty-seven (97.3%) of the 38 adolescents who participated in the first study were included. There was no difference in eating disorder examination questionnaire scores between the first and second study. ED-related quality of life slightly improved in the later stage. While there was no difference between the studies in terms of depression and obsession scores, whereas anxiety scores increased significantly. In addition, while depression had the highest predictive factor of ED in both studies, there was a significant increase in anxiety as COVID-19 progressed, making it the second most important predictor. Conclusions: Similar to the early study, an exacerbation in ED symptoms during the later stages of the pandemic was not observed. Clinical monitoring before and during the pandemic might have acted protective against the deteriorating effects. In the presence of prolonged social isolation, it is important to monitor adolescents with ED closely for depression and anxiety throughout the disease course.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".