The Psychometric Properties of a Short UPPS-P Impulsive Behavior Scale Among Psychiatric Patients Evaluated in an Emergency Setting
Bibliographic record
Abstract
Objective: Impulsivity is a multidimensional construct that has an important role for the understanding of diverse psychopathologies and problematic behaviors. The UPPS-P impulsive behavior scale, measuring five distinct facets of impulsivity, has been subject to several studies. No study has investigated the clinical utility of this questionnaire amongst an unstable psychiatric population. The aim of the current study is to examine the psychometric properties of the short version of this scale in a psychiatric emergency unit. Method: The S-UPPS-P was administered to 1097 psychiatric patients in an emergency setting, where a subgroup of 148 participants completed a follow-up. The internal consistency, the construct validity, the test-retest reliability and the convergent validity of the scale were examined. Results: Confirmatory factor analyses supported a five-factor solution. Results indicated good psychometric properties across psychiatric diagnoses and gender. The S-UPPS-P was partially invariant across sexes. The authors have found differences on the loading of one item and on the thresholds of two items from lack of premeditation and positive urgency subscales. Conclusion: This validation study showed that the UPPS-P conserved good psychometric properties in an unstable psychiatric sample, indicating that the instrument can be utilized in such settings.
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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 | 0.003 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".