Towards an emotional ‘stress test’: a reliable, non-subjective cognitive measure of anxious responding
Bibliographic record
Abstract
Response to stress or external threats is a key factor in mood and anxiety disorder aetiology. Current measures of anxious responding to threats are limited because they largely rely on retrospective self-report. Objectively quantifying individual differences in threat response would be a valuable step towards improving our understanding of anxiety disorder vulnerability. Our goal is to therefore develop a reliable, objective, within-subject 'stress-test' of anxious responding. To this end, we examined threat-potentiated performance on an inhibitory control task from baseline to 2-4 weeks (n = 50) and again after 5-9 months (n = 22). We also describe single session data for a larger sample (n = 157) to provide better population-level estimates of task performance variance. Replicating previous findings, threat of shock improved distractor accuracy and slowed target reaction time on our task. Critically, both within-subject self-report measures of anxiety (ICC = 0.66) and threat-potentiated task performance (ICC = 0.58) showed clinically useful test-retest reliability. Threat-potentiated task performance may therefore hold promise as a non-subjective measure of individual anxious responding.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".