Associations between attentional biases for emotional images and rumination in depression
Bibliographic record
Abstract
Rumination is a key feature of depression and contributes to its onset, maintenance, and recurrence. Researchers have proposed that biases in the attentional processing of emotional information may underlie rumination, and particularly, the brooding component. This investigation evaluated associations between attentional biases for emotional images and rumination, including both brooding and reflection, in currently and never depressed participants. In two separate studies, participants viewed sets of four emotional images (happy, sad, threatening, and neutral) for 8 s in a free-viewing eye-tracking paradigm. In both studies, currently depressed individuals attended to happy face images and happy naturalistic images significantly less than never depressed individuals. In Study 2, currently depressed individuals attended to sad naturalistic images significantly more than never depressed individuals. There were no statistically significant associations between attentional biases and any of the forms of rumination, independent of their shared relationship with depression symptoms. These findings call into question the robustness of the link between attentional biases and rumination.
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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 | 0.009 |
| 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".