Vascular Health Modifies Theory of Mind Performance in Older Adults
Bibliographic record
Abstract
OBJECTIVES: Age reductions in theory of mind (ToM) are well documented, though underlying mechanisms are poorly understood. Research suggests that traditional cognitive abilities underlie ToM in part; however, whether age-associated health modifiers also predict ToM remains unknown. We investigated the role of pulse pressure (PP), an age-related marker of vascular risk, in modifying ToM performance. METHOD: Sixty-six community-dwelling older adults (65-92 years) completed a short story paradigm assessing ToM. Participants also completed measures assessing blood pressure and cognitive abilities empirically linked to ToM. We used hierarchical regression to test our prediction that high PP would adversely influence associations between ToM and cognition. RESULTS: Reduced ToM was associated with older age and decreased verbal memory, processing speed, and working memory; however, associations between ToM and working memory were attenuated when PP was included in the regression model. Importantly, associations between ToM, memory, and processing speed were qualified by vascular health, in that participants with elevated PP showed stronger associations between reduced ToM and lower memory/speed. DISCUSSION: This is the first study to demonstrate that vascular risk modifies the strength of associations between ToM and age-sensitive cognitive resources. Results add to current perspectives on mechanisms influencing reduced ToM in older age.
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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 | 0.001 | 0.004 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".