Validation of the Sinhala Version of the Addenbrooke’s Cognitive Examination-Revised for the Detection of Dementia in Sri Lanka: Comparison with the Mini-Mental Status Examination and the Montreal Cognitive Assessment
Bibliographic record
Abstract
BACKGROUND: Sri Lanka is a rapidly aging country, where dementia prevalence will increase significantly in the future. Thus, inexpensive and sensitive cognitive screening tools are crucial. OBJECTIVES: To assess the reliability, validity, and diagnostic accuracy of the Sinhalese version of the Addenbrooke's Cognitive Examination-Revised (ACE-R s). METHOD: The ACE-R was translated into Sinhala with cultural and linguistic adaptations and administered, together with the Sinhala version of the Montreal Cognitive Assessment (MoCA), to 99 patients with dementia and 93 gender-matched controls. RESULTS: The ACE-R s cutoff score for dementia was 80 (sensitivity 91.9%, specificity 76.3%). The areas under the curve for the ACE-R s, Mini-Mental State Examination (MMSE) and MoCA were 0.90, 0.86, and 0.86, respectively. The -ACE-R s had good interrater reliability (intraclass correlation = 0.94), test-retest reliability (intraclass correlation = 0.99), and internal consistency (Cronbach's α = 0.8442). CONCLUSIONS: The ACE-R s is sensitive, specific and reliable to detect dementia in persons aged ≥50 years in a Sinhala-speaking population and its diagnostic accuracy is superior to previously validated tools (MMSE and MoCA).
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".