Cognitive health mediates the effect of hippocampal volume on COVID‐19‒related knowledge or anxiety change during the COVID‐19 pandemic
Bibliographic record
Abstract
Abstract Background Individuals with cognitive/memory impairments may be more vulnerable to COVID19 due to having poor knowledge of COVID19 and how to protect themselves under current policies. Here, we aimed to show cognitive/memory impairment is associated with less knowledge or less anxiety change related to COVID19. We hypothesized that the effect of hippocampal volume on COVID19‐related knowledge or anxiety change during the pandemic is mediated by cognitive health. Method A total of 247 participants (162 cognitively normal (CN) and 85 cognitively impaired (CI)) from the Montreal TRIAD cohort underwent a structural MRI and cognition and anxiety assessments using CDRSOB and GAD score, respectively before the COVID19 pandemic. During the first wave of COVID19, the participants were assessed for anxiety using GAD score and knowledge related to COVID19. Hippocampal volume was measured using Freesurfer, and the anxiety was evaluated as the rate of change in the GAD score: (follow‐up – baseline)/time difference. Then, the effect of hippocampal volume on the rate of change in the anxiety or knowledge on COVID19 was evaluated based on a mediation analysis with CDRSOB as a mediator, 2000 bootstrapping, and age, sex, education, and APOEe4 as covariates. Result The CI group showed significantly less knowledge of COVID19, or less anxiety change compared to the CN group, while hippocampal volume showed a significant association with knowledge of COVID19 or the rate of change in anxiety. Upon further examination, we revealed that the effect of hippocampal volume on COVID19 knowledge or the rate of change in anxiety was significantly mediated by cognitive health, indicated by CDRSOB (Figure 1). Conclusion Our finding highlights the poorer knowledge of COVID19 and related risks in individuals with cognitive/memory impairments; the CDRSOB, indicative of cognitive health, significantly mediated the effect of hippocampal volume on the rate of change in anxiety or knowledge on COVID19 in our cohort. This study urges for a more effective strategy and policy about informing and educating the individual with cognitive/memory impairment on COVID19 and related risks.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".