P4‐606: A VALID AND RELIABLE EYE‐TRACKING MEASURE OF COGNITION DISCRIMINATES BETWEEN COGNITIVELY INTACT AND IMPAIRED ADULTS
Bibliographic record
Abstract
In the United States, prevalence of dementia and mild cognitive impairment (MCI) in individuals 65 years or older is 15-20%; moreover, individuals with MCI have a 32% chance of developing Alzheimer's disease (AD) within 5 years. Healthcare costs associated with cognitive decline will continue to increase unless this trend is reversed through early detection with intervention. However, most screening assessments are burdensome to users and are not widely scalable. Therefore, there is a need for scalable and readily accessible cognitive tests. The objective of this study was to examine whether a digital eye-tracking cognitive test could differentiate between cognitively intact and impaired individuals while maintaining stability over time. This prospective study included 57 adult participants (n = 39 females, n = 18 males; 56.4 ± 26.7 years) divided into three cohorts based on Montreal Cognitive Assessment (MoCA) score cutoffs of <26 out of 30: older cognitively intact adults with MCI (65+ years, n = 13), healthy older adults (65+ years, n = 20), and healthy young-middle aged adults (18 – 46 years, n = 24). Participants reported for testing on two separate occasions. The first visit included informed consent, medical history questionnaire, MoCA, and a commercially available 5-min eye tracking test (VPC-5). The second visit occurred at least 14 days later, during which participants completed an alternate form of the VPC-5 to minimize learning effects. A Pearson's r correlation showed a significant correlation between the VPC-5 and the MoCA (r = .46; p = .00). A one-way ANOVA demonstrated significant differences (p =.005) in baseline VPC-5 scores between cohorts. Furthermore, a Tukey's post hoc analysis identified differences between older adults with MCI and young-middle aged adults (p =.006) and between older adults with MCI and healthy older adults (p =.013). A repeated measures ANOVA revealed no significant differences (p =.49) within groups over the two testing sessions, indicating stability over time. The VPC assessment successfully discriminates between cognitively intact and impaired individuals while remaining stable over time. This highly scalable assessment may be a valuable screening tool for individuals at risk for cognitive decline.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.005 | 0.002 |
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".