A Preliminary Exploration of Behaviours Associated with Negative Urgency in Individuals High and Low in Chronic Worry
Bibliographic record
Abstract
Abstract While chronic worry is typically associated with cautious and harm-avoidant behaviours, there is evidence that people high in chronic worry are characterised by negative urgency (NU), that is, the propensity to act rashly when experiencing negative affect. The present study was a preliminary examination of how rash action and impulsive decision-making manifest for chronic worriers compared to individuals low in worry. In total, 93 participants who endorsed high and low worry and NU responded to open-ended questions about their experience of NU on Amazon Mechanical Turk. Themes were identified using a data-driven approach. Participants high in chronic worry endorsed significantly greater NU compared to those low in worry. However, the types of NU behaviours were similar across participants, with a majority of responses involving initiating interpersonal conflict. Other themes included spending money, excessive eating, alcohol use, and aggressive behaviours. The manifestations of NU were largely consistent with those described in the model of NU. Although individuals higher in chronic worry engaged in NU behaviours to a greater extent, the types of behaviours were similar to those reported by people lower in worry. More research is needed to understand the characteristics of NU-motivated behaviour in individuals high in chronic worry.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".