Incontinence Quality of Life Instrument in a survey of primary care physicians.
Bibliographic record
Abstract
OBJECTIVE: To assess the performance of the Incontinence Quality of Life (I-QOL) Instrument in measuring the impact of urinary incontinence on the quality of life of family medicine patients. STUDY DESIGN: Postal survey. Multiple imputations of missing answers. Linear regression analysis of I-QOL predictors. Comparison by receiver operating characteristic of the I-QOL and the Short Form 12 (SF-12). POPULATION: Women 45 years or older attending either of 2 family medicine clinics. Response rate was 605 (61%) of 992. OUTCOMES MEASURED: Prevalence of stress, urge, and mixed incontinence. Scores on the I-QOL and SF-12 instruments. RESULTS: Of the 605 respondents, 310 (51%) reported urinary incontinence in the month before the survey. One or more items were missing on 19% of the I-QOL scales and scores were imputed. The relation between I-QOL and the number of leakage episodes was nonlinear. I-QOL scores decreased with the number of episodes, the amount of leakage, and poorer general health. There was no association between the I-QOL and age, education, or type of incontinence. The I-QOL was more sensitive than the SF-12 to the statement, "urinary incontinence is a problem." CONCLUSIONS: The I-QOL is a useful instrument for the investigation of incontinence-related quality of life in the community setting.
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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 | 0.004 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".