Validation of the French version of the Wisconsin Quality of Life (WISQOL) questionnaire for patients with urolithiasis
Bibliographic record
Abstract
INTRODUCTION: The Wisconsin Stone Quality of Life (WISQOL) questionnaire has been recently developed to objectively assess quality of life (QOL) in patients with nephrolithiasis. However, a French version of the questionnaire was lacking. Therefore, the aim of the present study was to develop and validate the French version of this tool. METHODS: The French version of the WISQOL (F-WISQOL) was developed in a multistep process involving primary translation, back-translation, and pilot testing among a group of patients (n=12). Nephrolithiasis patients from two tertiary care institutions were recruited into this study and completed the following questionnaires: the medical history form and either the WISQOL or F-WISQOL. Internal consistency was assessed using Cronbach's α, and inter-domain associations were evaluated using Spearman's rank correlation (r). One-way ANOVA was used to compare scores from the two groups (WISQOL and F-WISQOL). RESULTS: A total of 210 patients were enrolled in this study: 68 in the WISQOL group and 148 in the F-WISQOL group. Internal consistency was high for all domains in both groups (F-WISQOL: 0.924-0.970; WISQOL: 0.888-0.965). No statistically significant difference was found between the two groups' scores. Inter-domain association, measured by Spearman correlation, was moderate to very strong between all the domains in the F-WISQOL. Values ranged from r=0.676-0.915, with acceptable correlation between D1, D2, and D3, but weaker correlation between D4 (vitality) and the three other domains (r=0.676-0.729). CONCLUSIONS: In the present study, the French version of the WISQOL questionnaire was validated at two academic institutions.
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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 | 0.010 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".