IS HEALTHY NEUROTICISM ASSOCIATED WITH MORTALITY? EVIDENCE FROM A 14-STUDY COORDINATED ANALYSIS
Bibliographic record
Abstract
Higher Neuroticism has been consistently linked to higher risk of mortality (Graham et al., 2017). However, several studies showed that, when combined with higher Conscientiousness, higher Neuroticism may in fact be linked to a lowered risk of poorer health, thus rendering the interaction between Neuroticism and Conscientiousness as “Healthy Neuroticism”. Here, we aim to establish the replicability of Healthy Neuroticism in association with mortality. We conducted a coordinated integrative data analysis of 14 prospective cohorts, from 5 countries, with a combined N of nearly 100,000. Overall, there was weak support replicated across studies for higher levels of neuroticism being protective, in terms of mortality risk, when conscientiousness levels were also high. Ours is the first large-scale systematic effort to estimate replicability and generalizability of Healthy Neuroticism. We discuss implications for future research in the field of lifespan personality and health.
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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 | 0.023 | 0.038 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.007 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| 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".