Linking Cognitive Measures of Response Inhibition and Reward Sensitivity to Trait Impulsivity
Bibliographic record
Abstract
Impulsivity is regarded as a multifaceted construct that comprises two dimensions: rapid-response impulsivity and reward-delay impulsivity. It is unclear, however, which aspects of trait impulsivity, as assessed by self-report measures are related to rapid-response impulsivity and/or to reward-delay impulsivity, as different results have been reported in studies using both self-report and cognitive measures. This study aimed to directly relate self-report measures of impulsivity to cognitive measures of impulsivity in individuals at low- or high-levels on two impulsivity dimensions, specifically rapid-response impulsivity and reward-delay impulsivity. Participants were classified into high- or low-impulsivity groups based on (1) level of rapid-response impulsivity (determined by BIS-11 Motor subscale scores); (2) level of reward-delay impulsivity (determined by BIS/BAS subscale scores); and (3) a combination of rapid-response impulsivity and reward-delay impulsivity levels. Impulsivity was assessed using Go/No-Go, Stop-Signal and Delay-Discounting tasks and self-report measures. The high rapid-response impulsivity group showed significantly higher reward-delay impulsivity on both, the Delay-Discounting tasks and on self-report measures assessing reward-delay impulsivity, than the low-risk group. Based on the level of reward-delay impulsivity, the high reward-delay impulsivity group scored significantly higher on task-based (cognitive) and self-report measures assessing rapid-response inhibition than the low reward-delay impulsivity group. Combining both dimensions of impulsivity showed that the high-impulsivity group performed significantly worse in rapid-response paradigms and temporally discounted significantly more impulsively than the low-impulsivity group. Thus, combined impulsivity factors provide better assessment of impulsivity than each dimension alone. In conclusion, robust differences in impulsivity can be identified in non-clinical young adults.
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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 | 0.001 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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; a candidate call from one teacher head, 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".