The vicious cycle of psychopathology and stressful life events: A meta-analytic review testing the stress generation model.
Bibliographic record
Abstract
= .10) stress. We also identified unique patterns of effects across specific types of psychopathology. For example, effects were larger for depression than anxiety. Furthermore, effects were sometimes larger in studies with younger participants, shorter time lags between assessments, checklist measures of stress, and for interpersonal stressors. Finally, a multilevel meta-analytic structural equation model suggested that dependent stress exacerbates psychopathology symptoms over time (β = .04), possibly contributing to chronicity. Interventions targeting the prevention of stress generation may mitigate chronic psychopathology. Conclusions of this study are limited by the predominance of depression effect sizes in the literature and our review of only English language articles. On the other hand, the findings are strengthened by rigorous inclusion criteria, lack of publication bias, and absence of moderating effects by publication year. The latter underscores the replicability of the stress generation effect over the last 30 years. Taken together, the review provides robust evidence that stress generation is a cross-diagnostic phenomenon that contributes to a vicious cycle of increasing stress and psychopathology. (PsycInfo Database Record (c) 2023 APA, all rights reserved).
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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 | 0.016 | 0.038 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.017 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".