Race, Purpose and Meaning of Life, and Markers of Brain Health for Alzheimer’s Disease
Bibliographic record
Abstract
Abstract Background Meaning and purpose in life (M&P) represents goal direction and meaning for an individual. Literature has shown associations between higher M&P and better global cognition. However, papers included either predominantly White or Black samples. We aim to replicate these results in a sample with roughly equal Black and White participants and assess racial differences in the association between M&P and markers of brain health (global cognition and amyloid). We hypothesize that higher M&P scores will be associated with better markers of brain health and that the association will be stronger among Black compared to White individuals. Methods 263 adults aged 50‐89 years (Table 1) from the Pittsburgh Human Connectome Project were included. M&P was measured by the NIH Toolbox questionnaire. Brain health was characterized as general cognitive function by the Montreal Cognitive Assessment (MoCA) and amyloid burden from positron emission tomography with Pittsburgh compound B (PiB) using a global region of interest. Race was self‐reported as either White or Black/African American; individuals of other races (n = 6) were not included in these analyses. The association of M&P with brain outcomes was assessed by linear regression adjusted for years of education, sex, and age. Effect modification by race was assessed with inclusion of an interaction term in the models. Analyses were conducted in the whole sample and then again, in only those considered cognitively normal. Results There was no association between M&P and either marker of brain health (global amyloid: β = 0.0008, p = 0.52; cognition: β = 0.019, p = 0.28). There was no statistically significant effect modification by race for either outcome (all p for interaction>0.1). When restricting to those considered cognitively normal, results remained the same. Conclusion In contrast to prior findings, we found no association between M&P and markers of brain health in contrast to other studies. This difference is not likely due to racial composition as we found no differences by race but may be due to differences in measurements used. Further research should explore potential differences in associations based on cognitive domain.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.004 | 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".