Reactive Risk-Taking: Anxiety Regulation Via Approach Motivation Increases Risk-Taking Behavior
Bibliographic record
Abstract
Experimental research and real-world events demonstrate a puzzling phenomenon—anxiety, which primarily inspires caution, sometimes precedes bouts of risk-taking. We conducted three studies to test whether this phenomenon is due to the regulation of anxiety via reactive approach motivation (RAM), which leaves people less sensitive to negative outcomes and thus more likely to take risks. In Study 1 ( N = 231), an achievement anxiety threat caused increased risk-taking on the Behavioral Analogue Risk Task (BART) among trait approach-motivated participants. Using electroencephalogram in Study 2 ( N = 97), an economic anxiety threat increased behavioral inhibition system-specific theta activity, a neural correlate of anxiety, which was associated with an increase in risk-taking on the BART among trait approach-motivated participants. In a preregistered Study 3 ( N = 432), we replicated the findings of Study 1. These results offer preliminary support for the reactive risk-taking hypothesis.
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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 | 0.002 |
| 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) | 0.002 | 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".