The influence of trait anxiety on autonomic response and cognitive performance during an anticipatory anxiety task
Bibliographic record
Abstract
The interaction between emotion and cognition is thought to be intimately involved in the development and maintenance of anxiety disorders. In a set of studies, we investigated whether trait anxiety modulates cognitive performance and autonomic activity during an anticipatory anxiety task. Participants completed a letter-size decision-making task with two alternating 28-32 s background screen color-blocks. One of the colors was associated with the presentation of an aversive noise [unconditioned stimulus (UCS)]. Participants were aware of the background color that would (CTX+) and would not (CTX-) be paired with the UCS but did not know when or how often the UCS would be presented. Two experiments were conducted. In Experiment 1, the UCS was presented during the decision-making task in the CTX+ color-blocks using a partial reinforcement schedule. Different noises were presented each time to increase unpredictability and prevent habituation. In Experiment 2, the UCS was never presented during the decision-making task. Results suggested that only the paradigm used in Experiment 1 was successful in eliciting anticipatory anxiety. In Experiment 1, continuously measured skin conductance response (SCR) data suggested that anxiety was significantly greater during CTX+ compared to CTX- trials; no SCR differences were found between high and low trait-anxious participants. Results further indicated that high trait-anxious participants responded significantly faster on the decision-making task during CTX+ compared to CTX- trials, whereas low trait-anxious participants displayed the opposite pattern. Our results reveal an interesting dissociation between the effects of individual differences in trait anxiety on autonomic activity and cognitive performance during an anticipatory anxiety task.
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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 | 0.001 |
| 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".