Evaluating the use of eye tracking tasks as language‐ and culturally‐neutral assessments of cognition in a multi‐ethnic cohort of older adults
Bibliographic record
Abstract
Abstract Background Canada and the United States are both aging and becoming increasingly diverse. Despite this demographic shift, non‐White racial/ethnic groups remain underrepresented in research on cognitive impairment and dementia. A major barrier to inclusivity is the lack of cognitive assessments that are valid in individuals with diverse language and cultural backgrounds. Eye tracking tasks can potentially overcome this barrier since they do not require verbal responses and use culturally neutral stimuli. Here, we tested this hypothesis by comparing performance on standard neuropsychological tests and eye tracking tasks across individuals from White and underrepresented ethnic groups (UEG). Method Participants were cognitively unimpaired adults enrolled in the Canadian Multi‐Ethnic Research on Aging (CAMERA) study. Participants completed a battery of standard neuropsychological tests and two well‐characterized eye tracking tasks: the interleaved pro/anti‐saccade task (IPAST), which assesses executive function, and the visual paired comparison task (VPCT), which assesses visual memory. Result We included 54 participants (mean age=68.68±6.91, 70% female) with a Clinical Dementia Rating global score of 0. Among them, 22% of participants self‐identified as White (n=12) and the remaining participants identified as being from an UEG (n=42; 37% East Asian, 37% South Asian, 4% Other). Linear regression models assessed whether ethnic background (White vs. UEG) was associated with task performance after adjusting for age, sex, and years of education. We found that ethnic background influenced performance on several standard neuropsychological tests, including the MoCA (β=0.26, p=0.03), phonemic fluency (β=0.29, p=0.02), category fluency (β=0.38, p=0.003), and Benson Complex Figure delay (β=0.23, p=0.08), such that the UEG group had lower scores. There were no group differences on Trails A and B or the Symbol Digit Modalities Test (p‐values>0.1). Importantly, ethnic background did not influence performance on either eye tracking task (IPAST: β=‐0.17, p=0.17; VPCT: β=0.02, p=0.83). Conclusion Our preliminary results suggest that ethnic background influences performance on several standard neuropsychological tests, but not performance on the IPAST or VPCT. With further validation in larger samples, these eye tracking tasks may provide a brief and language‐free way to screen and monitor cognitive impairment in diverse samples currently underrepresented in dementia research.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".