Educational Bias in Cognitive Screening of Adults with Sickle Cell Disease: A Bilingual Multisite Observational Study
Bibliographic record
Abstract
Cognitive impairment is a common and dreaded complication of sickle cell disease (SCD), profoundly affecting patients’ quality of life, education, and employment. Despite its significance, there is a striking lack of guidance on optimal screening strategies, with existing tools often skewed by biases related to language proficiency and educational background, leaving many patients undiagnosed and unsupported. The Rowland Universal Dementia Assessment Scale (RUDAS) was specifically designed for cognitive screening in multicultural populations. We hypothesized that in adults with SCD, RUDAS performance is less influenced by educational attainment when compared to the Montreal Cognitive Assessment (MoCA). We conducted a cross-sectional study of adults with SCD who underwent cognitive screening at the Henri-Mondor Hospital using RUDAS and MoCA. Educational attainment was scored as the years of schooling for the highest completed diploma (HLE). Abnormal RUDAS (<28) and MoCA (<26) scores were found in 55/73 (75.3%) and 52/73 (71.2%). Both scores increased significantly with HLE (p < 0.001). Adding 1 point for those with the HLE < 12 years significantly mitigated the effect of education on RUDAS but only partially for MoCA (p = 0.26 and p = 0.003). In an independent cohort of 252 adults, this adjustment for HLE significantly lessened the effect of education on RUDAS. These results suggest there is an educational bias in neurocognitive screening of adults with SCD. We propose that the RUDAS adjusted for HLE is a promising novel strategy to systematically identify those in need of comprehensive neurocognitive assessment.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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 teacher head, 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".