Association between the <scp>COVID</scp>‐19 pandemic and psychiatric symptoms in people with preexisting obsessive‐compulsive, eating, anxiety, and mood disorders: a systematic review and meta‐analysis of before‐after studies
Bibliographic record
Abstract
Aim To determine whether the coronavirus disease 2019 (COVID‐19) pandemic was associated with a change in psychiatric symptoms in people with preexisting obsessive‐compulsive, eating, anxiety, and mood disorders compared to their prepandemic levels. Methods We searched MEDLINE, CINAHL, PsycINFO, and Embase from inception until February 16, 2022. Studies were included if they reported prepandemic and during‐pandemic psychiatric symptoms, using validated scales, in people with preexisting mood, anxiety, eating, or obsessive‐compulsive disorders. Two reviewers independently screened studies, extracted data, and assessed evidence certainty. Random‐effects meta‐analyses were conducted. Effect sizes were reported as standardized mean differences (SMDs) with 95% confidence intervals (CIs). Results Eighteen studies from 10 countries were included. Of the 4465 included participants, 68% were female and the average age was 43 years. Mood and obsessive‐compulsive disorders were the most studied disorders. During‐pandemic psychiatric measurements were usually collected during nationwide lockdown. Obsessive‐compulsive symptoms worsened among people with obsessive‐compulsive and related disorders, with a moderate effect size (N = 474 [six studies], SMD = −0.45 [95% CI, −0.82 to −0.08], I2 = 83%; very low certainty). We found a small association between the COVID‐19 pandemic and reduced anxiety symptoms in people with mood, anxiety, obsessive‐compulsive, and eating disorders (N = 3738 [six studies], SMD = 0.11 [95% CI, 0.02–0.19], I2 = 63%; very low certainty). No change in loneliness, depressive, or problematic eating symptoms was found. Conclusion People with obsessive‐compulsive and related disorders may benefit from additional monitoring during the COVID‐19 pandemic and possibly future pandemics. Other psychiatric symptoms were stable in people with the specific disorders studied. Overall, evidence certainty was very low.
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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 | 0.011 | 0.032 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.028 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".