Adaptation and Validation of the Tamil (Sri Lanka) Version ofthe Montreal Cognitive Assessment
Bibliographic record
Abstract
The study aimed to develop the Tamil (Sri Lanka) version of the Montreal Cognitive Assessment (MoCA) and investigate its reliability and validity as a briefscreening tool for mild cognitive impairment (MCI). Tamil-speaking Sri Lankan elderly with normal cognition and MCI were recruited from a neurology clinic.Adaptation of the English MoCA to the Tamil (Sri Lanka) involved context-specific content modification and translation. The content validity, reliability, sensitivity,and specificity of the tool were evaluated. Study participants were 184 older adults, comprising 85 with normal cognition and 99 neurologist-diagnosed MCI.The tool had high internal consistency (Cronbach's alpha = 0.83). Receiver operating characteristic curve analyses showed an area under the curve of 0.87(95% CI = 0.83 - 0.91) for detecting MCI. The optimal cut-off score for detection of MCI was 23/24, yielded a sensitivity and specificity of 84.7% and 76.4%,respectively. The Tamil (Sri Lankan) version of the MoCA maintains its core diagnostic properties rendering it a valid and reliable tool for screening of MCIamong Tamil speaking Sri Lankan older adults.
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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 | 0.006 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 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".