The Validity and Reliability of the Neurogenic Bladder Symptom Score
Bibliographic record
Abstract
PURPOSE: The neurogenic bladder symptom score is a tool to measure urinary symptoms and consequences in patients with acquired or congenital neurogenic bladder. We describe score validity and reliability. MATERIALS AND METHODS: Exploratory factor analysis was used to assess item variability and subscale structure. Reliability was assessed by the Cronbach α and correlation with retest data. Validity was assessed with a priori hypotheses specifying relationships with the AUASS (American Urological Association symptom score), ICIQ-UI (International Consultation on Incontinence-Urinary Incontinence) and urinary specific quality of life SF-Qualiveen questionnaires, and a self-assessed global bladder problem score. Known groups analysis was used to further assess construct validity. RESULTS: A cohort of 230 patients with spinal cord injury (35%), multiple sclerosis (59%) and congenital neurogenic bladder (6%) were included in study. Factor analysis suggested 3 neurogenic bladder symptom score domains, including incontinence, storage and voiding symptoms, and consequences. Overall internal consistency was high (Cronbach α=0.89). Test-rest reliability was also excellent with an ICC2,1 of 0.91. Validity was demonstrated by the confirmation of hypothesized correlations with the AUASS, ICIQ-UI and SF-Qualiveen, and significant differences in neurogenic bladder symptom score scores among known groups. Patients with a history of seeing a urologist had a significantly higher mean score, as did those with a higher global bladder problem score (22.1 vs 17.1 and 22.1 vs 12.6, respectively, each p<0.001). CONCLUSIONS: The neurogenic bladder symptom score, developed specifically to assess symptoms and consequences associated with neurogenic bladder dysfunction, has appropriate psychometric properties. Depending on the measurement need individual domains may be selected or it can be used as a comprehensive score.
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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 | 0.006 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".