Mental Health and Cognitive Outcomes in Patients Six Months After Testing Positive Compared with Matched Patients Testing Negative for COVID-19 in a Non-Hospitalized Sample: A Matched Retrospective Cohort Study
Bibliographic record
Abstract
We aimed to determine the mental health and cognitive outcomes at six months in people who had not been hospitalized with COVID-19 and who had tested positive or negative for COVID-19 in Eastern Ontario, Canada. Participants were matched 1:1 six months following their COVID-19 polymerase chain reaction test. X2, t-test, and Mann–Whitney U tests were conducted to compare self-report and observer-rated mental health and cognitive outcomes between the two groups. We also conducted an age and gender-adjusted logistic regression analysis to explore risk factors associated with depression, anxiety, and cognitive impairment among those who had tested positive for COVID-19. A total of 324 participants were enrolled (n = 162 per arm). Overall, 40.7% of those in the COVID-positive group were men, with an average age of 37.9 (SD 13.2) years. In the COVID-negative group, 41.4% were men, with an average age of 36.7 (SD 12.8). There were no statistically significant differences in mental health outcomes between the groups. On cognitive testing, while 21% of the COVID-positive participants and 14% of the COVID-negative participants had scores indicating significant cognitive impairment, the difference between groups was not significant, though this warrants further investigation in future research. In non-hospitalized patients who have tested positive for COVID-19, there is no evidence of an increase in mental health disorders compared to people who tested negative. Any increases in mental health disorders during the pandemic may be the effect of social changes rather than an effect of the virus itself. The exception may be the cognitive changes in those who tested positive.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".