The Prevalence of Mild Cognitive Impairment in Elders in Chongqing, China
Bibliographic record
Abstract
Mild cognitive impairment (MCI) is a window to detect dementia, and to screen MCI, Montreal Cognitive Assessment (MoCA) is commonly used. This work investigated the prevalence of MCI in Chongqing elderlies by using MoCA as a tool. One hundred fourteen valid data from older adults (≥ 55 years, 51.75% males) were recruited for this research. Twelve demographic information were collected, and each participant did one of the two versions of MoCA tests (Beijing 7.1, and the optimized version). They were developed based on the Beijing 7.1 version, and four test sections were optimized to adapt to the native speaking and cultural background. Five risky demographic factors were found. The incidence of MCI detected by the optimized MoCA version was lowered to 83.3% compared to 94.4% in the original version, and the naming section was significantly improved. The significant decrease in the overall prevalence indicates that the optimization of the MoCA has, to some extent, made it more suitable for Chongqing elders. Accordingly, we suggest further professional and detailed improvements to MoCA.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".