Self-critical perfectionism and depressive and anxious symptoms over 4 years: The mediating role of daily stress reactivity.
Bibliographic record
Abstract
This study of 150 community adults examined heightened emotional reactivity to daily stress as a mediator in the relationships between self-critical (SC) perfectionism and depressive and anxious symptoms over a period of 4 years. Participants completed questionnaires assessing: perfectionism dimensions, general depressive symptoms (i.e., shared with anxiety), specific depressive symptoms (i.e., anhedonia), general anxious symptoms (i.e., shared with depression), and specific anxious symptoms (i.e., somatic anxious arousal) at Time 1; daily stress and affect (e.g., sadness, negative affect) for 14 consecutive days at Month 6 and Year 3; and depressive and anxious symptoms at Year 4. Path analyses indicated that SC perfectionism predicted daily stress-sadness reactivity (i.e., greater increases in sadness in response to increases in stress) across Month 6 and Year 3, which in turn explained why individuals with higher SC perfectionism had more general depressive symptoms, anhedonic depressive symptoms, and general anxious symptoms, respectively, 4 years later. In contrast, daily reactivity to stress with negative affect did not mediate the prospective relation between SC perfectionism and anhedonic depressive symptoms. Findings also demonstrated that higher mean levels of daily stress did not mediate the relationship between SC perfectionism and depressive and anxious symptoms 4 years later. These findings highlight the importance of targeting enduring heightened stress reactivity in order to reduce SC perfectionists' vulnerability to depressive and anxious symptoms over the long term.
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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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".