Neuroticism facets and mortality risk in adulthood: A systematic review and narrative synthesis
Bibliographic record
Abstract
ObjectiveThis systematic review sought to comprehensively summarize the research investigating the association between facets of neuroticism and mortality risk. MethodsA systematic review of prospective cohort studies utilizing rigorous reporting methods was conducted. Six electronic bibliographic databases, MEDLINE [Ovid], Embase, PsycINFO, CINAHL, Web of Science, and SCOPUS, were searched for eligible studies using keywords encompassing personality traits and mortality. Articles from inception to January 2023 were reviewed. The risk of bias was assessed using a modified Newcastle-Ottawa Scale.ResultsFive of the 2,358 identified studies met the inclusion criteria for extraction. Included studies had 333,853 participants, of whom 3.25% died. Participants ages at baseline ranged from 20 to 102, and 54% were female. Four of the five studies reported statistically significant associations between facets of neuroticism and mortality risk. Impulsiveness was found to potentially have a protective effect when controlling for demographic and health information. Conflicting findings were reported for the facets related to anxiety and vulnerability. One study found that the 'worried-vulnerable' facet was protective of mortality risk. The remaining two studies found that the vulnerability and 'pessimistic, anxious, depressive' facet was associated with mortality in models adjusted for demographic information. ConclusionsThe findings of this systematic review suggest that various facets related to neuroticism may be associated with an increased or decreased risk of mortality risk, highlighting the variability in this field. Based on the findings, recommendations are provided to improve the quality and comparability of future cohort studies focusing on personality facets and mortality risk.Keywords: Personality, Neuroticism, Facet, Mortality, Systematic Review, Big Five
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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 | 0.015 | 0.065 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.008 |
| Bibliometrics | 0.012 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| 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".