DISPARITIES IN MOCA AND MMSE SCORES AMONG DIVERSE OLDER ADULTS: A CASE ANALYSIS OF CREOLE-SPEAKING PARTICIPANTS
Bibliographic record
Abstract
Abstract Almost 11% of older adults in the US have Alzheimer’s or related dementia. Most studies suggest that those who are Black or Hispanic are at higher risk. A culturally diverse sample, including Haitian older adults, was recruited from South Florida communities to participate in a longitudinal study, “In-Vehicle Sensors to Detect Change in Cognition of Older Drivers.” An extensive cognitive battery was administered for comparison with driving behaviors. No validated translations in Creole were available, so three Haitian-born examiners translated and back-translated test items into Creole. Two additional bilingual examiners verified the results. An analysis of variance (ANCOVA) comparing Haitian participants (N=12) and European Americans (N=135) on the MoCA controlling for age and education indicated the European American group scored higher (M = 25.78, SD = 2.57) than the Haitian Group (M =24.17, SD = 3.01), a significant difference in test performance, F (1, 124) = 6.11, P= .015. Results on four subscales of the MoCA evidenced significantly higher scores for the European American group: Visual EX Total, F (1, 124) = 22.52, p < .001; Serial-7, F (1, 124) = 12.09, p <.001; Attention Total, F (1, 124) = 5.10, p <.001; Letter Score F (1, 124) = 13.09, p <.001. No differences in language, abstract, delayed recall, or orientation were found. These preliminary results suggest cultural influences may account for differences in test performance. Further investigation with a larger sample of Haitian older adults is needed to explain differences in performance on this widely used test.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".