Perseverative Negative Thinking, Self-Control, and Executive Functioning in Symptoms of Depression and Anxiety: A Comprehensive Meta-Analysis of Competing Models
Bibliographic record
Abstract
In this meta-analysis, we synthesized existing research on perseverative negative thinking, self-control, and executive functioning to better define their etiologic role in symptoms of depression and anxiety. After a review of leading models of perseverative negative thinking, self-control, executive functioning, and depressive and anxious symptoms, the relevant associations were meta-analyzed as reported in cross-sectional and longitudinal studies. A total of 223 studies met the inclusion criteria, providing 239 independent samples (28 of which provided longitudinal data), N = 50,987. According to both longitudinal and cross-sectional path analyses, self-control deficits predict depression and anxiety symptoms, and these symptoms then predict perseverative negative thinking. In the present research synthesis, we identified evidence that reduced self-control predicts increases in depressive and anxious symptoms, which, in turn, lead to perseverative negative thinking. All in all, this finding suggests an opportunity to treat depression and anxiety through training of self-control and emotional-regulation strategies.
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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 | 0.030 | 0.046 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.012 | 0.064 |
| Bibliometrics | 0.009 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.002 |
| 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".