Perfectionistic cognitions, Interleukin-6, and C-Reactive protein: A test of the perfectionism diathesis stress model
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
Previous research has demonstrated that perfectionism is implicated in poorer health and earlier mortality. However, to our knowledge, research has not yet determined how individual differences in perfectionistic cognitions are related to intermediary health markers such as inflammation. Thus, within the theoretical frameworks of the perfectionism diathesis-stress model (Hewitt and Flett, 1993) and the cognitive theory of perfectionism (Flett et al., 2018; Flett et al., 2016) the aims of our study were to test whether individual differences in perfectionistic cognitions were associated with low-grade inflammation via c-reactive CRP and IL-6 biomarkers and whether these relationships varied as a function perceived stress. The sample included 248 Canadian young adults (52% female, Mage = 22.89, SD = 1.53) who completed surveys assessing key constructs such as perfectionistic cognitions and perceived stress along with providing assessments of body fat percentage and serum samples of IL-6 and CRP. Regression analyses indicated that perfectionistic cognitions were not related to IL-6 under any conditions of stress. However, under high levels of stress perfectionistic cognitions were associated with elevated levels of CRP and these findings held after accounting for the effects of smoking status, body fat percentage, and respondent sex. The present work adds to the growing body of evidence supporting links between personality and inflammation. These findings raise the possibility that experiencing more frequent thoughts centered on the need to be perfect when coupled with higher levels of stress may set the stage for greater vulnerability for chronic inflammation.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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