Stroop Effects in Alzheimer's Disease: Selective Attention Speed of Processing, or Color-naming? A Meta-Analysis
Bibliographic record
Abstract
Selective attention, an essential part of daily activity, is often impaired in people with Alzheimer's disease (AD). Usually, it is measured by the color-word Stroop test. However, there is no universal agreement whether performance on the Stroop task changes significantly in AD patients; or if so, whether an increase in Stroop effects reflects a decrease in selective attention, a slowing in generalized speed of processing (SOP), or is the result of degraded color-vision. The current study investigated the impact of AD on Stroop performance and its potential sources in a meta-analysis and mathematical modeling of 18 studies, comparing 637 AD patients with 977 healthy age-matched participants. We found a significant increase in Stroop effects for AD patients, across studies. This AD-related change was associated with a slowing in SOP. However, after correcting for a bias in the distribution of latencies, SOP could only explain a moderate portion of the total variance (25%). Moreover, we found strong evidence for an AD-related increase in the latency difference between naming the font-color and reading color-neutral stimuli (r2 = 0.98). This increase in the dimensional imbalance between color-naming and word-reading was found to explain a significant portion of the AD-related increase in Stroop effects (r2 = 0.87), hinting on a possible sensory source. In conclusion, our analysis highlights the importance of controlling for sensory degradation and SOP when testing cognitive performance and, specifically, selective attention in AD patients. We also suggest possible measures and tools to better test for selective attention in AD.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".