High Level of Trait Anxiety Leads to Salience-Driven Distraction and Compensation
Bibliographic record
Abstract
Individuals with high levels of anxiety are hypothesized to have impaired executive control functions that would otherwise enable efficient filtering of irrelevant information. Pinpointing specific deficits is difficult, however, because anxious individuals may compensate for deficient control functions by allocating greater effort. Here, we used event-related-potential indices of attentional selection (the N2pc) and suppression (the P D ) to determine whether high trait anxiety is associated with a deficit in preventing the misallocation of attention to salient, but irrelevant, visual search distractors. Like their low-anxiety counterparts ( n = 19), highly anxious individuals ( n = 19) were able to suppress the distractor, as evidenced by the presence of a P D . Critically, however, the distractor was found to trigger an earlier N2pc in the high-anxiety group but not in the low-anxiety group. These findings indicate that, whereas individuals with low anxiety can prevent distraction in a proactive fashion, anxious individuals deal with distractors only after they have diverted attention.
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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".