Exploring the Link between Impulsivity, using the UPPS-P Impulsive Behavior Scale, and Decision-making Regarding Risky Choice
Bibliographic record
Abstract
Acting without forethought is a characteristic some individuals exhibit in their everyday lives, particularly those prone to impulsive behaviour. Many personality models incorporate impulsivity as a fundamental psychological construct. Consequently, understanding how impulsivity influences decision-making, especially in risky contexts, is essential for understanding the behavioural manifestation of personality traits. In this study, we aimed to determine the association between impulsivity, measured by the UPPS-P Impulsive Behavior Scale, and risky choice decision-making, measured by a risky choice paradigm. A total of one hundred and forty-two participants took part in our online study, where they completed the risky-choice paradigm as well as the UPPS-P questionnaire. The task involved presenting participants with a choice between risky and certain options. A regression analysis was conducted to examine the relationship between their probability of selecting the risky option, their reaction time when making that choice, and their UPPS-P Impulsive Behavior Scale scores. The results revealed that higher scores on the UPPS-P predicted a higher probability of picking the risky option. Moreover, higher scores on this scale predicted faster reaction times in the task, especially when participants rated high on both (Positive and Negative) Urgency subscales of the UPPS-P. Overall, this study provides a deeper understanding of how distinct facets of impulsivity contribute to risky decision-making behaviours, particularly by influencing both the likelihood and speed of risky choices.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.015 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.010 | 0.003 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads agree on what is shown here.
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".