Validation of electronic urinary incontinence questionnaires.
Bibliographic record
Abstract
OBJECTIVE: To investigate whether there is any significant difference between the electronic and the paper-based version of Urogenital Distress Inventory-6 questionnaire (UDI-6) and the Incontinence Impact Questionnaire-7 questionnaire (IIQ-7). MATERIALS AND METHODS: An electronic questionnaire and clinical tool was developed using a combination of open source questionnaire software and custom programming that closely replicated the paper version of the UDI-6 and IIQ-7 questionnaires. Ethics were reviewed and approved by the University Health Network of Toronto. The study randomized participants from the Urinary Incontinence Clinic to either complete the paper-and-pen version of the questionnaires or the electronic version at the beginning of their clinic visit. Sample size was determined to be 50 to sufficiently power the study but due to early closing of the clinic only 26 participants could be enrolled in the study. RESULTS AND CONCLUSION: The study found that there was no significant difference (p < .05) between the standardized pen-and-paper and electronic versions of the UDI-6 and IIQ-7. The electronic version can be used in place of the paper version facilitating physicians understanding and monitoring of the impact of incontinence on patients in order to formulate an appropriate treatment plan.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.055 | 0.125 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".