Stress and selective attention: The interplay of mood, cortisol levels, and emotional information processing
Bibliographic record
Abstract
The effects of a stressful challenge on the processing of emotional words were examined in college students. Stress induction was achieved using a competitive computer task, where the individual either repeatedly lost or won against a confederate. Mood, attention, and cortisol were recorded during the study. There were four findings: (1) Participants in the negative stressor condition were faster to shift attention away from negative words than positive or neutral words; (2) attentional shifts away from negative words were associated with stress-induced mood lowering; (3) participants in the negative stress condition with elevated scores on the Beck Depression Inventory were slow to disengage attention from all stimuli; and (4) elevated depression scores were associated with lower cortisol change from baseline during the experimental phase, and with higher cortisol levels during the recovery phase. These findings point to information-processing strategies as a means to regulate emotion, and to atypical features of cognitive and adrenocortical function that may serve as putative risk markers of depression.
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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 | 0.001 |
| 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".