Race, Meaning and Purpose in Life, and Markers of Brain Health for Alzheimer’s Disease
Bibliographic record
Abstract
Introduction: Meaning and purpose in life (M&P) represents goal direction and meaning for individuals. Higher M&P is related to better global cognition. However, papers included either predominantly White or Black samples. We aimed to test the association of M&P with brain health markers in a roughly equal Black and White sample to assess racial differences. We hypothesized that higher M&P scores would be associated with better markers of brain health and that the association would be stronger among Black compared to White individuals. Methods: 206 adults (50-89 years) were included. M&P was measured by the National Institutes of Health Toolbox. Brain health was characterized as general cognition by the Montreal Cognitive Assessment, cortical thickness from magnetic resonance imaging, and beta-amyloid (Aβ) burden from positron emission tomography scans with Pittsburgh compound B. Race was self-reported as either White or Black/African American. The association of M&P with brain outcomes was assessed by linear regression adjusted for years of education, sex, age, and separately, depressive symptoms. Effect modification by race was assessed with inclusion of a race*M&P interaction term and race-stratified models when the interaction p<0.10. Results: While there was no association between M&P and two markers of brain health– global Aβ and cortical thickness (both p>0.10)– among cognitively normal participants, there was an association between higher M&P scores and better global cognition (β=0.090, p=0.022). Further, in the whole sample, the results varied by race (interaction p=0.073), with higher M&P scores associated with better global cognition for Black (β=0.11, p=0.011), but not White participants (β=0.0081, p=0.83). There was no effect modification for amyloid or cortical thickness (p’s for interaction all>0.10). Conclusion: Greater M&P is associated with better global cognition in Black older adults. Studies should assess whether other brain health markers are related to M&P and if and how promoting M&P may improve brain health outcomes and enhance brain health equity, thus providing a significant public health impact.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".