Tele neuropsychological exploratory assessment of indicators of mild cognitive impairment and autonomy level in Mexican population over 60 years old
Bibliographic record
Abstract
Due to the cognitive decline associated with aging, it is necessary to determine the variables involved in this process to implement preventive actions to avoid or help slow the progression of cognitive decline to dementia in older adults. This is a priority in the current pandemic situation, due to the consequences of periods of confinement due to COVID-19. To address these challenges, this study was conducted through Information and Communication Technologies (ICTs), by adapting an in-person assessment protocol into an online Tele neuropsychological consultation. The correlation between autonomy and cognitive performance variables is analyzed in 47 Mexican subjects over 60 years of age. The results of the statistical analyses suggest a moderate correlation between the level of autonomy and cognitive performance (with MOCA and Clock Drawing Test), significant correlation values are outlined in some of the variables reviewed, and interesting data were found in the correlation of cognitive reserve with cognitive decline and the educational level from the participants. Finally, future analysis is proposed of the sensitivity of screening tests (CDT) to find indicators of Mild Cognitive Impairment (MCI) in this population that is not detected in classical tests (MOCA). Developing ICT-based screening protocols for the elderly may be a key tool in these coronavirus times or under any given circumstances.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".