An in-home rehabilitation program for the treatment of urinary incontinence symptoms in endometrial cancer survivors: a single-case experimental design study
Bibliographic record
Abstract
INTRODUCTION AND HYPOTHESIS: There is a high prevalence of urinary incontinence among endometrial cancer survivors. They are also known to present with pelvic floor muscle alterations. Evidence on the effects of conservative interventions for the management of UI is scarce. This study aims at verifying the effects of an in-home rehabilitation program, including the use of a mobile technology, to reduce UI severity in endometrial cancer survivors. METHODS: This study used a single-case experimental design with replications. Primary outcome for UI severity was the pad test, and secondary outcomes were the ICIQ-UI SF questionnaire and 3-day bladder diary. Pelvic floor muscle function was assessed using 2D-transperineal ultrasound and intravaginal dynamometry. Adherence was documented using mobile technology and an exercise log. Visual and non-parametric analyses of longitudinal data were conducted. RESULTS: Results show a reduction in UI severity for 87.5% of participants, with a significant relative treatment effect of moderate size (RTE: 0.30). Significant small relative treatment effects were found for the quick contraction and endurance dynamometric tests. CONCLUSION: This study provides new evidence that endometrial cancer survivors can improve the severity of their UI following an in-home rehabilitation program, including the use of a mobile technology. This mode of delivery has the potential to address a gap in access to pelvic floor physiotherapy services for survivors of EC living in rural and remote communities.
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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 | 0.007 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".