The associations of hostility and defensiveness with telomere length are influenced by sex and health status
Bibliographic record
Abstract
BACKGROUND: Shorter telomere length (TL) may indicate premature cellular aging and increased risk for disease. While there is substantial evidence for shorter TL in individuals suffering from psychiatric disorders, data is scarce on maladaptive personality traits related to coronary artery disease (CAD). The purpose of this study was to evaluate the association of TL with hostility and defensiveness in individuals with CAD or other non-cardiovascular illnesses and whether associations were moderated by CAD status and sex. METHODS: = 65.40 ± 6.73 years) with and without CAD completed the Marlowe-Crowne Social Desirability Scale and the Cook-Medley Hostility Scale. Relative TL was measured via quantitative polymerase chain reaction of total genomic DNA samples. Analyses involved hierarchical regressions on TL, performed separately for hostility and defensiveness, controlling for pertinent sociodemographic, behavioural, and medical risk factors. Separate analyses were performed on 25 healthy participants. RESULTS: A hostility by sex interaction emerged (β = - .08, p = .006) in the patient groups, where greater hostility was associated with shorter TL in women only (p < .01). A Defensiveness by CAD status interaction (β = - .06, p = .049) revealed longer TL in more defensive CAD patients only (p = .06). In healthy men, shorter TL was observed in those with greater defensiveness (β = .52, p = .006) but lower hostility (β = - .43, p = .049). CONCLUSION: Hostility and defensiveness are differentially associated with TL as a function of sex and health status. The implication of these results for health remains to be determined, but propose an additional pathway through which the effect of maladaptive personality traits may contribute to CV and other disease.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".