Personality Traits Predict the Onset of Disease
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
While personality traits have been linked concurrently to health status and prospectively to outcomes such as mortality, it is currently unknown whether traits predict the diagnosis of a number of specific diseases (e.g., lung disease, heart disease, and stroke) that may account for their mortality effects more generally. A sample ( N = 6,904) of participants from the Health and Retirement Study, a longitudinal study of older adults, completed personality measures and reported on current health conditions. Four years later, participants were followed up to see if they developed a new disease. Initial cross-sectional analyses replicated past findings that personality traits differ across disease groups. Longitudinal logistic regression analyses predicting new disease diagnosis suggest that traits are associated with the risk of developing disease—most notably the traits of conscientiousness, neuroticism, and openness. Findings are discussed as a means to identify pathways between personality and health.
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.
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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.008 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 it