The Mediating Role of Automatic Thoughts in the Personality–Event–Affect Relationship
Bibliographic record
Abstract
Although cognitive theory gives automatic thoughts a causal role in the onset of negative mood and depressive symptoms, little research has directly tested this relationship, and no research has examined whether automatic thoughts explain the effects of personality factors, life events, and positive mood on negative affect. Accordingly, automatic thoughts were prospectively tested as a mediator of the effects of personality vulnerability factors, positive affect, and hassles on mood. Measures of self-criticism and dependency were administered at baseline, and measures of automatic thoughts, hassles, and positive and negative affect were administered once per week for 4 weeks to 102 college students. Automatic thoughts fully mediated the effects of self-criticism and partially mediated the effects of dependency and hassles on mood. Findings suggest that negative thoughts only partially account for the relationship among personality, hassles, and mood. Results also showed that the impact of positive affect on negative affect may be mediated by the presence or absence of automatic thoughts.
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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 | 0.002 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.003 | 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".