Measurement and structural invariance of a neuropsychological battery among Middle Eastern/North African, Black, and White older adults.
Bibliographic record
Abstract
OBJECTIVE: There is a lack of guidance on common neuropsychological measures among Arabic speakers and individuals who identify as Middle Eastern/North African (MENA) in the United States. This study evaluated measurement and structural invariance of a neuropsychological battery across race/ethnicity (MENA, Black, White) and language (Arabic, English). METHOD: Six hundred six older adults (128 MENA-English, 74 MENA-Arabic, 207 Black, 197 White) from the Detroit Area Wellness Network were assessed via telephone. Multiple-group confirmatory factor analyses examined four indicators corresponding to distinct cognitive domains: episodic memory (Consortium to Establish a Registry for Alzheimer's Disease [CERAD] Word List), language (Animal Fluency), attention (Montreal Cognitive Assessment [MoCA] forward digit span), and working memory (MoCA backward digit span). RESULTS: Measurement invariance analyses revealed full scalar invariance across language groups and partial scalar invariance across racial/ethnic groups suggesting a White testing advantage on Animal Fluency; yet this noninvariance did not meet a priori criteria for salient impact. Accounting for measurement noninvariance, structural invariance analyses revealed that MENA participants tested in English demonstrated lower cognitive health than Whites and Blacks, and MENA participants tested in Arabic demonstrated lower cognitive health than all other groups. CONCLUSIONS: Measurement invariance results support the use of a rigorously translated neuropsychological battery to assess global cognitive health across MENA/Black/White and Arabic/English groups. Structural invariance results reveal underrecognized cognitive disparities. Disaggregating MENA older adults from other non-Latinx Whites will advance research on cognitive health equity. Future research should attend to heterogeneity within the MENA population, as the choice to be tested in Arabic versus English may reflect immigrant, educational, and socioeconomic experiences relevant to cognitive aging. (PsycInfo Database Record (c) 2023 APA, all rights reserved).
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".