[P1–500]: DEVELOPMENT AND VALIDATION OF THE HONG KONG MONTREAL COGNITIVE ASSESSMENT (HK‐MOCA) ALTERNATE VERSIONS FOR SCREENING OF MILD COGNITIVE IMPAIRMENT
Bibliographic record
Abstract
The Montreal Cognitive Assessment (MoCA) is a valid and widely used cognitive test in clinical and research settings. However, repeated testing in same individuals results in practice effect which may mask true cognitive changes when evaluating treatment efficacy. The objective of this study is to develop two alternate versions of the Hong Kong version of MoCA (HK-MoCA), together with two alternate versions of the 5-minute protocol and to investigate the validity and reliability of the alternate versions in elderly persons with normal cognition and mild cognitive impairment (MCI) patients. The availability of alternate versions of the HK-MoCA will significantly improve the accuracy in measuring cognitive changes in clinical and research settings. Thirty normal controls and 30 patients with MCI were tested with each alternate version (namely V1-HK-MoCA and V2-HK-MoCA) and the original version one month apart of each other. Twenty subjects were further administered the same alternate version one month later to assess test-retest reliability. Correlational and Bland-Altman analyses for the original and alternate versions of HK-MoCA were performed. Criterion validity was assessed by ability to differentiate MCI from controls using receiver operation curve (ROC) analysis. One-month test-retest reliability was indexed by the intra-class correlation coefficient. The original HK-MoCA and the two alternate versions were highly correlated (V1-HK-MoCA, Pearson r=.87, p<.001; V2-MoCA, Pearson r=.79, p<.001). The alternate versions both showed excellent test-retest reliability (V1-MoCA, Intra-class r=.92, p<.001; V2-MoCA, Intra-class r=.82, p<.001), together with good internal consistency (V1-MoCA: α=.79; V2-MoCA: α=.75). The alternate versions also showed excellent to good ability to detect MCI from normal (ROC area under curve: V1-MoCA=0.92; V2-MoCA=0.72). Bland-Altman analysis of the alternate versions showed a high level of agreement with the original HK-MoCA with no proportional bias.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".