TabCAT Brain Health Assessment: Preliminary validation in a multicultural Israeli population
Bibliographic record
Abstract
BACKGROUND: The Israeli population, primarily comprised of Israeli Jews (74%) and Arabs (21%), is one of the most diverse aging societies around the world. The need for brief, accurate, and culturally appropriate cognitive measures in Israel is high, as they can facilitate early detection of cognitive disorders across clinical settings. We examined the discrimination accuracy and concurrent validity of the brief Tablet-based Cognitive Assessment Tool (TabCAT) Brain Health Assessment (BHA) battery in a multicultural Israeli sample. METHODS: Participants were 79 Hebrew and Arabic speaking older adults (age: 67±6; 58% female; education: 15±4). Clinically normal participants (n = 63) were community-dwelling individuals with no self- or informant-reported cognitive symptoms or functional decline. Cognitively impaired participants (n = 16) with diagnoses of mild cognitive impairment (n = 15) or dementia (n = 1) were recruited from a large neurology center. Diagnoses were based on the published clinical criteria, and all patients underwent comprehensive neurological and neuropsychological evaluations independent of study procedures. All participants completed the TabCAT-BHA and the Montreal Cognitive Assessment (MoCA) in their primary language. Logistic regressions with ROC curves were used to examine discrimination accuracy, controlling for age, sex, education, and testing language. Concurrent validity was evaluated against the MoCA indices for the same domains. RESULTS: The TabCAT-BHA battery showed excellent discrimination accuracy (AUC = .99, sensitivity = .81, and specificity = .95) outperforming the MoCA (AUC = .94, sensitivity = .63, specificity = 0.97). Moderate associations were observed between TabCAT Favorites (associative memory) and MoCA Memory Index (r = .49, P < .001), and between TabCAT Match (executive functions) and MoCA Executive Index (r = .64, P < .001). Weaker associations were found between TabCAT Line Orientation (visuospatial skills) and MoCA Visuospatial Index (r = -.27, P = .02). CONCLUSIONS: Our preliminary findings support the validity of the 10-minute TabCAT-BHA battery in culturally diverse Israeli older adults. The battery exhibited excellent performance in detecting cognitive impairment in our sample outperforming a widely used brief cognitive assessment tool, the MoCA. Future studies, including development of Israel-specific normative data and replication of these results in larger samples, are ongoing.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".