Implicit associations between anxiety-related symptoms and catastrophic consequences in high anxiety sensitive individuals
Bibliographic record
Abstract
Anxiety sensitivity refers to the fear of anxiety-related physical sensations arising from beliefs that these sensations have harmful consequences (Reiss & McNally, 1985). The present study examined whether individuals with high (vs. low) anxiety sensitivity show stronger implicit associations in memory between anxiety-related symptoms, as opposed to neutral body parts, and harmful, as compared to harmless, consequences. A total of 22 undergraduate students (14 F, 8 M) completed the Extrinsic Affective Simon Task (EAST; De Houwer, 2003). Results indicated that high anxiety sensitive individuals (n = 10) tended to implicitly associate harmful consequences with anxiety-related symptoms. Their performance was significantly faster on trials where target words related to anxiety symptoms were mapped on to the same response key as harmful consequences. No significant difference in performance was found for low anxiety sensitive individuals (n = 12) or when target words were body parts unlikely related to diseases. Between-group differences persisted after controlling for trait anxiety and history of panic attacks, but not when illness-related beliefs were introduced as a covariate. Identifying this implicit association bias provides additional empirical support for the concept of anxiety sensitivity.
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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 | 0.001 | 0.004 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".