Brain Health Screening in Israel’s Diverse Population
Bibliographic record
Abstract
BACKGROUND: Israeli population is primarily comprised of Jews (74%) and Arabs (21%). Previous studies suggested a higher incidence of cerebrovascular risk factors (CVRF) and dementia among Israeli Arabs. We evaluated potential cognitive disparities between community-dwelling Arabs and Jews diagnosed with at least one CVRF. METHOD: 96 participants (age: 66.6± 5.3; education: 14.8± 4.1), 52 Arabs (age: 64.4± 5; education: 15.3±2.6), and 44 Jews (age: 69.1± 4.4; education: 14.8± 4.1) without known cognitive impairment and with at least one CVRF were prospectively enrolled. All participant 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, including the TabCAT Favorites (associative memory), Match (executive functions and processing speed) and Line Orientation (visuospatial skills) tasks. Demographic and clinical characteristics were analyzed using the Student's t-test for continuous variables and Chi-squared tests for categorical data. RESULTS: Arab participants were younger (p≤0.001) than Jews, education was similar (p = 0.26). Cognitive complaints were reported by 32 (33%) participants, (24% Arab,9% Jews). Participants with cognitive complaints exhibited significantly lower scores on Match (p = 0.005), but not on Favorites (p = 0.28), Line Orientation (p = 0.48), and MoCA (p = 0.62). Arabs scored significantly worse on Match (p = 0.006) while Jews scored worse on Line Orientation (p = 0.004). Performance was similar on the Favorites (p = 0.4) and MoCA (p = 0.2). When focusing on participants with cognitive complaints Arabs exhibited significantly lower scores on Match (p = 0.036) while Jews had lower scores on Line Orientation (p = 0.06). No significant differences were observed on Favorites (p = 0.4) or MoCA (p = 0.2). Among participants without cognitive complaints no significant differences were observed between Jews and Arabs on Match (p = 0.29), Favorites (p = 0.99) or MoCA (p = 0.65). Jews had lower scores on Line Orientation (p = 0.04). CONCLUSION: TabCAT-BHA proved superior to MoCA in depicting subtle cognitive impairment in people with CVRF. Despite being younger, Arabs exhibited higher prevalence of cognitive complaints and were more impaired on executive functions while Jews on visuospatial tasks.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".