Disentangling the cognitive, physical, and mental health sequelae of COVID-19
Bibliographic record
Abstract
As COVID-19 cases exceed hundreds of millions globally, many survivors face cognitive challenges and prolonged symptoms. However, important questions about the cognitive effects of COVID-19 remain unresolved. In this cross-sectional online study, 478 adult volunteers who self-reported a positive test for COVID-19 (mean = 30 days since most recent test) perform significantly worse than pre-pandemic norms on cognitive measures of processing speed, reasoning, verbal, and overall performance, but not short-term memory, suggesting domain-specific deficits. Cognitive differences are even observed in participants who did not require hospitalization. Factor analysis of health- and COVID-related questionnaires reveals two clusters of symptoms-one that varies mostly with physical symptoms and illness severity, and one with mental health. Cognitive performance is positively correlated with the global measure encompassing physical symptoms, but not the one that broadly describes mental health, suggesting that the subjective experience of "long COVID" relates to physical symptoms and cognitive deficits, especially executive dysfunction.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".