Underdiagnosis and Ethnic Differences in Community‐Based Brain Health Screening
Bibliographic record
Abstract
BACKGROUND: In Israel, Arabs experience higher mortality rates from cerebrovascular disease and greater prevalence of vascular cognitive impairment compared to Jews. This study evaluated cognitive disparities between community-dwelling Arabs and Jews with comparable cerebrovascular risk factors (CVRF). METHOD: We enrolled 115 participants (age: 67.07 ± 5.95; education: 15.28 ± 4.16), including 59 Arabs (age: 64.17 ± 5.38; education: 14.76 ± 5.07) and 56 Jews (age: 70.16 ± 4.91; education: 15.82 ± 2.84), all withouxt known cognitive impairment but with at least one CVRF. Participants completed a cognitive symptoms questionnaire in their primary language and underwent the Montreal Cognitive Assessment (MoCA) and the Tablet-based Cognitive Assessment Tool (TabCAT) Brain Health Assessment (BHA) battery, which included Birdwatch (visial associative memory), Match (executive function and processing speed), and Line Orientation (visuospatial skills) tasks. Clinical characteristics were analyzed using Student's t-test, Mann-Whitney U test, and Chi-squared tests as appropriate. Participants reported the number of days they engaged in ≥30 minutes of physical activity in the prior week. RESULTS: Cognitive symptoms were reported by 41 participants (35%), including 28 Arabs (68%) and 13 Jews (32%) (p = 0.007). Arabs were younger than Jews (p < 0.001), with no significant differences in sex or education between groups (p = 0.45 and p = 0.17, respectively). Participants with and without cognitive symptoms were similar in age, sex, and education (p = 0.73, p = 0.90, and p = 0.30, respectively). Those with cognitive complaints scored lower on the Match task (p = 0.002) but not on Birdwatch (p = 0.32), Line Orientation (p = 0.18), or MoCA (p = 0.27). CVRF prevalence, including hypertension, diabetes, hyperlipidemia, and smoking, was similar between participants with and without cognitive symptoms. Participants without cognitive symptoms reported more physical activity days in the previous week (p = 0.01). CONCLUSION: In our community-based health screening, the majority of individuals reporting cognitive symptoms were Arabs. Participants with cognitive symptoms exhibited poorer performance on an executive function task, suggesting the possibility of underdiagnosed cognitive disorders. Additionally, greater physical activity was associated with fewer cognitive symptoms, emphasizing the crucial role of exercise in supporting brain health.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".