Defensiveness status predicts 3-year incidence of hypertension
Bibliographic record
Abstract
OBJECTIVE: A growing body of research indicates that defensive personality styles (in particular, self-deception) may be related to higher resting blood pressure and stress reactivity levels. This study is the first, however, to examine the value of defensiveness as a prognostic indicator for the development of clinical hypertension. METHODS: Participants were 127 initially normotensive male and female adults who completed a comprehensive protocol including psychological testing, assessment of smoking, physical activity and body fat levels, and 8-12 h ambulatory blood pressure monitoring. Participants returned 3-years later for an identical follow-up protocol. Defensiveness was assessed using the Balanced Inventory of Desirable Responding. RESULTS: At 3-year testing, 15 of 127 participants (12%) met criteria for hypertension (i.e. ambulatory mean blood pressure > 140/90). Comparisons between defensiveness groups showed that 12 of 60 (20%) high defensiveness participants met hypertension criteria, whereas only three of 67 (4.5%) low defensiveness participants were hypertensive. Logistic regression equations adjusted for age, alcohol usage, bodyfat, self-reported exercise levels, smoking, and year-1 ambulatory blood pressure, revealed that membership in the high defensiveness group was associated with more than a sevenfold risk of 3-year hypertension (adjusted risk ratio, 7.5; 95% confidence interval, 1.5-39.2). CONCLUSIONS: These findings link defensive characteristics to an increased prospective risk of hypertension using state of the art ambulatory monitoring techniques, and were robust after controlling for established risk factors. We conclude that the current results add to the hypertension literature by demonstrating associations between personality and clinically relevant blood pressure criteria.
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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 | 0.001 | 0.001 |
| 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 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".