Memory and metamemory performance in individuals with and without post-COVID-19 subjective cognitive symptoms
Bibliographic record
Abstract
Background Metamemory is the awareness of and ability to evaluate one’s own cognitive abilities. This study examined impaired metamemory as a possible mechanism contributing to persistent cognitive symptoms after COVID-19.Methods Individuals with previous COVID-19 illness were recruited. Participants completed questionnaires regarding physical health, mental health, and their COVID-19 illness. To assess memory and metamemory performance, participants were presented with 50 words and then completed a two-alternative forced choice recognition memory task with a confidence rating after each trial. This was repeated for 3 blocks of 50 trials each. A signal detection theory framework was applied to derive metrics of memory performance (d’), metamemory performance (meta-d’), and metamemory efficiency (M-ratio). We compared participants who self-reported persistent cognitive symptoms at the time of their metamemory assessment (n = 47) to participants who denied persistent cognitive symptoms (n = 87). We used a general linear model to compare groups, covarying for age and days between COVID-19 and metamemory assessment.Results Participants with and without self-reported persistent cognitive symptoms did not differ on memory performance (d’: p = .24, β = 0.22 95% CI [−0.1, 0.6]), metamemory performance (meta-d’: p = .28, β = 0.20 95% CI [−0.2, 0.6]), or metamemory efficiency (M-ratio: p = .85, β = −0.04 95% CI [−0.4, 0.3]). Those with persistent cognitive symptoms reported a higher degree of depression (p < 0.001, β = 0.83 95% CI [0.5, 1.2]), anxiety (p = 0.016, β = 0.50 95% CI [0.2, 0.9]), and somatic symptom scores (p < 0.001, β = 0.92 95% CI [0.5, 1.3]).Conclusions Patients with and without self-reported persistent cognitive symptoms had similar memory accuracy and both demonstrated good (synchronous) awareness of their memory test performance. While both cognitive and metacognitive impairment appear unlikely to drive cognitive symptoms after COVID-19, psychological distress (particularly anxiety) remains a compelling candidate perpetuating factor. Future mechanistic research is necessary to understand if and how psychological distress contributes to cognitive symptoms, and vice versa.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".