Construction of a short version of the Montreal Cognitive Assessment (MoCA) rating scale for the Thai population using Partial Least Squares analysis
Bibliographic record
Abstract
BACKGROUND: The Montreal Cognitive Assessment (MoCA) rating scale is frequently used to assess cognitive impairments in amnestic mild cognitive impairment (aMCI) and Alzheimer's disease (AD). OBJECTIVES: The aims of this study were to a) evaluate the construct validity of the MoCA and its subdomains or whether the MoCA can be improved by feature reduction, and b) develop a short version of the MoCA (MoCA-Brief) for the Thai population. METHODS: We recruited 181 participants, namely 60 healthy controls, 61 aMCI, and 60 AD patients. RESULTS: < 0.001) and shows adequate concurrent, test-retest, and inter-rater validity. CONCLUSION: The construct validity of the MoCA may be improved by deleting five items. The new MoCA-Brief rating scale deserves validation in independent samples and especially in other countries.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".