Trait Mindfulness Is Associated With Less Amyloid, Tau, and Cognitive Decline in Individuals at Risk for Alzheimer’s Disease
Bibliographic record
Abstract
Background: Mindfulness, defined as nonjudgmental awareness of the present moment, has been associated with an array of mental and physical health benefits. Mindfulness may also represent a protective factor for Alzheimer's disease (AD). Here, we tested the potential protective effect of trait mindfulness on cognitive decline and AD pathology in older adults at risk for AD dementia. Methods: Measures of trait mindfulness, longitudinal cognitive assessments, and amyloid-β (Aβ) and tau positron emission tomography scans were collected in 261 nondemented older adults with a family history of AD dementia from the PREVENT-AD (Pre-symptomatic Evaluation of Experimental or Novel Treatments for AD) observational cohort study. Multivariate partial least squares analyses were used to examine relationships between combinations of different facets of trait mindfulness and 1) cognitive decline, 2) Aβ, and 3) tau. Results: Higher levels of mindful nonjudgment, describing, and nonreactivity were associated with less cognitive decline in attention, global cognition, and immediate and delayed memory. Higher levels of mindful nonjudgment and nonreactivity were related to less Aβ positron emission tomography signal in bilateral medial and lateral temporoparietal and frontal regions. Higher levels of mindful acting with awareness, describing, nonjudgment, and nonreactivity were associated with less tau positron emission tomography signal in bilateral medial and lateral temporal regions. Conclusions: Trait mindfulness was associated with less cognitive decline and less Aβ and tau in the brain in older adults at risk for AD dementia. Longitudinal studies examining the temporal relationship between trait mindfulness and AD markers, along with mindfulness intervention studies, will be important for further clarifying the potential protective benefits of mindfulness on AD risk.
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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 | 0.000 | 0.002 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".