Personality Vulnerabilities to Psychopathology: Relations Between Trait Structure and Affective-Cognitive Processes
Bibliographic record
Abstract
The present research examined (a) the relations among various affective-cognitive vulnerabilities to psychopathology, (b) the relations between vulnerabilities and dispositional traits, and (c) the mediating role of vulnerabilities between dispositional traits and psychopathological symptoms. Self-report questionnaires were administered to two independent samples in Study 1 (total N=274), whereas a longitudinal experience-sampling method was employed in Study 2 (N=100). All samples consisted of college students. Results suggested that affective-cognitive vulnerabilities showed a pattern of intercorrelations consistent with a 2-factor model representing general vulnerability to internalizing and externalizing psychopathology, respectively. The vulnerabilities also revealed common and unique aspects when mapped onto the trait structure represented by the Five-Factor Model. Most important, affective-cognitive vulnerabilities were found to constitute proximal-specific mechanisms that mediated between distal-broad dispositional vulnerabilities, such as Neuroticism, and different psychopathological symptoms. Our data support a model of personality-psychopathology relations that benefits from an integration of both the dispositional trait and social-cognitive approaches.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".