A validation study of the Hong Kong version of Montreal Cognitive Assessment (HK-MoCA) in Chinese older adults in Hong Kong
Bibliographic record
Abstract
OBJECTIVE: To validate the Hong Kong version of Montreal Cognitive Assessment (HK-MoCA) in identification of mild cognitive impairment and dementia in Chinese older adults. DESIGN: Cross-sectional study. SETTING: Cognition clinic and memory clinic of a public hospital in Hong Kong. PARTICIPANTS: A total of 272 participants (dementia, n=130; mild cognitive impairment, n=93; normal controls, n=49) aged 60 years or above were assessed using HK-MoCA. The HK-MoCA scores were validated against expert diagnosis according to the Diagnostic and Statistical Manual of Mental Disorders (4th ed) criteria for dementia and Petersen's criteria for mild cognitive impairment. Statistical analysis was performed using receiver operating characteristic curve and regression analyses. Additionally, comparison was made with the Cantonese version of Mini-Mental State Examination and Global Deterioration Scale. RESULTS: The optimal cutoff score for the HK-MoCA to differentiate cognitive impaired persons (mild cognitive impairment and dementia) from normal controls was 21/22 after adjustment of education level, giving a sensitivity of 0.928, specificity of 0.735, and area under the curve of 0.920. Moreover, the cutoff to detect mild cognitive impairment was 21/22 with a sensitivity of 0.828, specificity of 0.735, and area under the curve of 0.847. Score of the Cantonese version of the Mini-Mental State Examination to detect mild cognitive impairment was 26/27 with a sensitivity of 0.785, specificity of 0.816, and area under the curve of 0.857. At the optimal cutoff of 18/19, HK-MoCA identified dementia from controls with a sensitivity of 0.923, specificity of 0.918, and area under the curve of 0.971. CONCLUSION: The HK-MoCA is a useful cognitive screening instrument for use in Chinese older adults in Hong Kong. A score of less than 22 should prompt further diagnostic assessment. It has comparable sensitivity with the Cantonese version of Mini-Mental State Examination for detection of mild cognitive impairment. It is brief and feasible to conduct in the clinical setting, and can be completed in less than 15 minutes. Thus, HK-MoCA provides an attractive alternative screening instrument to Mini-Mental State Examination which has ceiling effect (ie may fail to detect mild/moderate cognitive impairment in people with high education level or premorbid intelligence) and needs to be purchased due to copyright issues.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".