Validity of the <scp>C</scp>antonese <scp>C</scp>hinese <scp>M</scp>ontreal <scp>C</scp>ognitive <scp>A</scp>ssessment in <scp>S</scp>outhern <scp>C</scp>hinese
Why this work is in the frame
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Bibliographic record
Abstract
AIM: The objective of the present study was to investigate the reliability and the validity of the Cantonese Chinese Montreal Cognitive Assessment (MoCA) as a brief screening tool of amnestic mild cognitive impairment (aMCI) and Alzheimer's disease (AD) in Southern Chinese older adults. METHODS: Cognitively normal, aMCI and AD Cantonese-speaking Chinese older adults were recruited from a memory clinic and the community. The English MoCA was translated into Cantonese Chinese and then back-translated. We then evaluated the content validity, reliability, sensitivity and specificity of the Chinese Cantonese MoCA. RESULTS: We recruited 115 cognitively normal controls, 87 aMCI and 64 AD patients. Only education was positively correlated with the Cantonese MoCA score (r = 0.46, P < 0.001). The Chinese Cantonese MoCA had a high internal consistency with a Cronbach's alpha of 0.85. In the test-retest reliability assessment, the intraclass correlation coefficient (ICC) was 0.95 (P < 0.001). The ICC for the interrater reliability was 0.96 (P < 0.001). Receiving operating characteristic curve analyses showed an area under the curve of 0.85 and 0.99 for aMCI and AD, respectively (both P < 0.001). The optimal cut-off score for detection of aMCI was 22/23, which yielded a sensitivity and specificity of 78% and 73%, respectively. The optimal cut-off score for detection of AD was 19/20, which gave sensitivity and specificity of 94% and 92%, respectively. CONCLUSION: The Cantonese Chinese MoCA is a consistent and reliable instrument. In terms of its validity, the MoCA is better in the detection of AD than aMCI in Cantonese-speaking Chinese persons. It is only fair for the screening of aMCI.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.067 |
| Meta-epidemiology (narrow) | 0.004 | 0.004 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.006 | 0.004 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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 it