French version of the short form of neurogenic bladder symptom score: Cross-cultural adaptation and validation
Bibliographic record
Abstract
INTRODUCTION: This study aimed to empirically validate a French version of the Neurogenic Bladder Symptoms Score-Short From (NBSS-SF), a psychometric multidimensional tool to assess lower urinary tract symptoms (LUTS) for patients with a neurological condition. METHODS: One hundred and five participants with multiple sclerosis or spinal cord injury prospectively completed the questionnaire at baseline and 7-14 days later. The α coefficient of Cronbach (internal consistency) and the intraclass correlation coefficient (ICC) (test-retest reliability) were calculated. RESULTS: The internal consistency for the overall questionnaire was high (Cronbach's α coefficients from 0.79), while coefficients for each subscale were variable (urinary incontinence 0.91; storage and voiding 0.69; consequences 0.25). For test-retest reliability, 88/105 (84%) patients filled and sent back their questionnaire 10 days (±3.6 days) after baseline version. ICC was 0.90 for the total score and was 0.73 for the urinary incontinence subdomain, 0.79 for storage and voiding, and 0.75 for consequences. CONCLUSIONS: The psychometric qualities of the French version of the NBSS-SF are well-supported, thus providing a valid tool to measure bladder symptoms across three different domains in patients with neurogenic bladder.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".