COVID‐19 pandemic: Quantifying the effects of the first lockdown on behavioral and cognitive measures using TASIC
Bibliographic record
Abstract
Abstract Background Following the rapid spread of the COVID‐19 virus throughout Quebec, the TRIAD cohort, a longitudinal observational study, evaluated the effects of COVID‐19 on it’s aging and vulnerable population and their caregivers. This study aims at investigating the behavioural and psychological effects of COVID‐19 and social isolation on the aging population. The TRIAD Assessment of Social Isolation and Cognition (TASIC) was developed to assess these effects on participants of observational trials. Method Pre‐pandemic data including, demographical information, Clinical Dementia Rating (CDR), Mini‐Mental State Examination (MMSE), Geriatric Depression Scale (GDS), Montreal Cognitive Assessment (MoCA) and a Social Support Questionnaire, were collected during in‐person visits and take‐home questionnaires. Following the onset of COVID‐19, TASIC was created to include additional COVID‐19 specific scales developed by Dr. Rosa‐Neto and Dr. King that include Knowledge of COVID‐19 scale, the Montreal Assessment of Stress related to COVID‐19 (MASC), as well as the Impact of Events Scale (IESR), the Peritraumatic Distress Inventory (PDI), the Peritraumatic Dissociative Experiences Questionnaire (PDEQ) for COVID‐19. Assessments were conducted via telephone interviews with TRIAD participants (n=292) and their informants (n=243) by eight trained research assistants from April through June 2020. All participants enrolled in previous TRIAD studies, deemed eligible through detailed screening criteria were contacted. Result As a result of this study, and previous work done by the cohort, a culmination of information is available, with 90% of TRIAD participants having completed the COVID‐19 study also having plasma collected. 80% of participants from the COVID‐19 study have PET imaging using [18F]AZD4694 and [18F]MK6240 and MRI sequencing. Conclusion The COVID‐19 study conducted by TRIAD provides a unique opportunity to understand the effects of a global pandemic on our aging population as well as caregiver burden. This data, in conjunction with other measures available in the cohort, can make important strides in finding ways to help, and better understand those most impacted by the crisis.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.000 |
| Open science | 0.001 | 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".