Validation of the questionnaire for impulsive‐compulsive disorders in Parkinson's disease
Bibliographic record
Abstract
As no comprehensive assessment instrument for impulse control disorders (ICDs) in Parkinson's disease (PD) exists, the aim of this study was to design and assess the psychometric properties of a self-administered screening questionnaire for ICDs and other compulsive behaviors in PD. The Questionnaire for Impulsive-Compulsive Disorders in Parkinson's Disease (QUIP) has 3 sections: Section 1 assesses four ICDs (involving gambling, sexual, buying, and eating behaviors), Section 2 other compulsive behaviors (punding, hobbyism, and walkabout), and Section 3 compulsive medication use. For validation, a convenience sample of 157 PD patients at 4 movement disorders centers first completed the QUIP, and then was administered a diagnostic interview by a trained rater blinded to the QUIP results. A shortened instrument (QUIP-S) was then explored. The discriminant validity of the QUIP was high for each disorder or behavior (receiver operating characteristic area under the curve [ROC AUC]: gambling = 0.95, sexual behavior = 0.97, buying = 0.87, eating = 0.88, punding = 0.78, hobbyism = 0.93, walkabout = 0.79). On post hoc analysis, the QUIP-S ICD section had similar properties (ROC AUC: gambling = 0.95, sexual behavior = 0.96, buying = 0.87, eating = 0.88). When disorders/behaviors were combined, the sensitivity of the QUIP and QUIP-S to detect an individual with any disorder was 96 and 94%, respectively. Scores on the QUIP appear to be valid as a self-assessment screening instrument for a range of ICDs and other compulsive behaviors that occur in PD, and a shortened version may perform as well as the full version. A positive screen should be followed by a comprehensive, clinical interview to determine the range and severity of symptoms, as well as need for clinical management.
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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 | 0.013 | 0.022 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".