The current state of continence in Canada: a population representative epidemiological survey.
Bibliographic record
Abstract
INTRODUCTION: Data on the prevalence of lower urinary tract symptoms (LUTS) and urinary incontinence (UI) in Canada are dated. This study aims to describe the current prevalence of LUTS and UI, to assess the state of knowledge of these conditions, the treatment for them and the treatment experience of symptomatic persons. MATERIALS AND METHODS: A nationally representative adult (= 18 years) sample was surveyed using a questionnaire based on the EPIC study. The margin of error associated with this probability-based sample was +/-3.1%, 19 times out of 20. RESULTS: Of the 1000 people contacted, (52% female, 48% male), 78.4% were either aware or vaguely aware of the term 'incontinence'. A total of 43.7% of respondents felt that UI was a serious problem that could easily ruin quality of life. When asked, 93.7% of respondents felt that people with UI should seek medical advice, but only 41.4% (27.4% men, 54.3% women) knew what help was available. Of 23.7% of the sample with UI, 145 (61.2%) experienced leakage a few times a month or more frequently and 23.7% had UI for > 11 years. A total of 48.8% of people with UI had initiated a discussion with their healthcare provider about their urinary symptoms, 52.4% within the last year. CONCLUSION: The current distribution of UI in Canada is similar to that found in 2004. There remains a lack of awareness of the available treatments despite an acknowledgement that UI is an important medical condition. Few people had actively engaged with treatments. Men remain less aware and less likely to seek help than women.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".