A preliminary study of application of Montreal Cognitive Assessment among the Uyghur people in Urumqi
Bibliographic record
Abstract
Objective To evaluate the reliability and validity of Uyghur version of the Montreal Cognitive Assessment （MoCA-U）among the Uyghur people in Urumqi, and determine the optimal cutoff score of MoCA-U to detect the cognitive impairment in the Uyghur people. Methods The English MoCA was translated and adapted into the Uyghur version. The MoCA-U, MMSE, CDR and other neuropsychological batteries were administered to 188 Uyghur people who were aged 50-75, 80 of them were in the normal cognitive group, 68 of them were in the mild cognitive impairment（MCI）group and 40 of them were in the dementia group. Results （1）Cronbach′s α of MoCA-U was 0.801, inter-rater reliability ICC was 0.977（95%CI: 0.949-0.990）, test-retest reliability r was 0.987（P<0.001）.（2）The MoCA-U scores of 3 groups were normal cognitive（22.65±2.57）,MCI（18.56±3.08）and dementia（9.43±3.89）, were significantly different among the 3 groups(F=27.991,P<0.001).The correlation coefficients of the scores of MoCA-U with those of MMSE and CDR were r=0.84（P<0.001）and r=-0.77（P<0.001）.（3）MoCA-U scores in the participants with 5 years of education or less, using a cutoff score of 20, the MoCA-U had a sensitivity of 86.4% and a specificity of 84.2% for screening MCI, and using a cutoff score of 13, the MoCA-U had a sensitivity of 94.1% and a specificity of 100% to detect dementia. In the participants within 6-10 years of education, using a cutoff score of 21, the MoCA-U had a sensitivity of 84.6% and a specificity of 94.1% for screening MCI, and using a cutoff score of 15, the MoCA-U had a sensitivity of 100% and a specificity of 92.3% to detect dementia. In the participants with more than 11 years of education, using a cutoff score of 22, the MoCA-U had a sensitivity of 75.8% and a specificity of 70.5% for screening MCI, using a cutoff score of 17, the MoCA-U had a sensitivity of 100% and a specificity of 84.8% to detect dementia. Conclusion The MoCA-U has a good reliability，validity and feasibility, and is suitable for use as a screening tool to screen cognitive function in elderly Uyghur people in Urumqi. The optimal cutoff score for different education years to screen MCI is 20-22, screen dementia is 13-17. Key words: Cognition disorders; Cognition; Reliability; Validity; Montreal cognitive assessment
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".