Mood-induced changes on the Implicit Association Test in recovered depressed patients.
Bibliographic record
Abstract
A mood induction paradigm was used to examine dysphoria-related changes in two types of cognitive processing in individuals who had previously experienced depression. Formerly depressed patients (n = 23) and never-depressed controls (n = 27) completed the Dysfunctional Attitudes Scale, a self-report measure of effortful processing, and performed the Implicit Association Test, an automatic-reaction time task that measures evaluative bias, before and after a negative-mood induction. The formerly depressed group showed both an increase in endorsement of dysfunctional attitudes and a more negative evaluative bias for self-relevant information after the induction, relative to controls--however, there was no association between the mood-linked changes observed on these two measures. The shift in evaluative bias shown by the formerly depressed group was similar to that seen in a group of 32 currently depressed individuals. These findings suggest that even a mild negative mood in formerly depressed individuals can reinstate some of the cognitive features observed in depression itself.
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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 | 0.000 | 0.002 |
| 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".