The association between sleep and eating disorders in Canada before and during the first wave of the COVID-19 pandemic
Bibliographic record
Abstract
• Sleep disturbances were prevalent in people with EDs before the COVID-19 pandemic. • There was a significant deterioration in sleep quality during the pandemic. • Individuals with remitted EDs remain vulnerable to sleep disruptions. • Mental health practitioners should attend to sleep difficulties in people with EDs. Sleep disturbances are prevalent among individuals with eating disorders (EDs), yet limited research has explored the interplay between EDs and sleep during the COVID-19 pandemic. This study aimed to compare 1) self-reported sleep quality before the pandemic (retrospectively) among individuals with current EDs, remitted EDs, and controls (no psychiatric history); and 2) sleep quality differences among these groups from before to during the pandemic. Participants ( N = 1033) completed the Pittsburgh Sleep Quality Index and reported anxiety and depression symptoms for the month before the pandemic onset (retrospectively) and during the pandemic. One-way ANCOVAs compared sleep quality among groups before the pandemic, adjusting for anxiety and depression symptoms and demographics. Repeated measures ANCOVAs assessed sleep quality differences between before and during the pandemic, controlling for the same covariates. Pre-pandemic, individuals with current EDs reported the highest sleep disturbance levels, followed by those with remitted EDs and controls ( F (2, 955) = 11.01, p < 0.001). During the pandemic, sleep disturbance worsened across all groups, with individuals in current and remitted ED groups experiencing a more significant deterioration than controls, even when accounting for anxiety and depression symptoms ( p < 0.05). The cross-sectional design and retrospective self-reports of sleep quality. Individuals with current and remitted EDs seemed to be vulnerable to sleep disruptions during the pandemic. Sleep disruptions may persist during ED remission. Awareness of these dynamics can enhance mental health practitioners’ attention to sleep disruptions in adults with current or remitted EDs.
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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 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".