Defining and prioritizing modifiable risk factors towards the co-creation of a urinary incontinence self-management intervention for older men: A sequential multimethod study protocol
Bibliographic record
Abstract
Urinary incontinence (UI), characterized by involuntary urine leakage is a chronic, embarrassing and stigmatizing condition that is under-reported and under-treated). UI is under-prioritized and under-researched, particularly in older men (defined here as men 65+), and there have been calls for more targeted research focusing on this specific group. No existing self-management interventions focus on the needs of older men and none incorporate the perspectives of older men into their development. Furthermore, health inequalities and disparities in continence services for men, and a low level of health seeking behavior in men with UI make it crucial to incorporate their perspectives into intervention development to ensure optimal outcomes. The study will identify risk factors for UI that are potentially amenable to self-management in older men, assess their self-efficacy in managing UI, and determine what modifiable risk factors older men feel are pragmatic to include as part of a self-management program. We will conduct and report a sequential multi-method design consisting of a Delphi study among healthcare experts and a survey among older men with UI, according to the Guidance on Conducting and Reporting Delphi Studies (CREDES) Checklist and the Checklist for Reporting Of Survey Studies (CROSS). A geographically dispersed, multidisciplinary group of 30 health care professionals (urologists, geriatricians, family physicians, and nurses) involved in continence care and a representative sample of at least 128 ethnically diverse older men will participate in a Delphi survey and an older men's survey respectively. The healthcare experts will evaluate an evidence-synthesized list of UI risk factors to determine those potentially amenable to self-management. Delphi rounds will be repeated until consensus threshold of 75% is reached. Thereafter, older men recruited via stratified sampling of population subgroups will rate a list of expert-identified potentially modifiable risk factors to indicate which factors they deem practicable and can prioritize. Older men's survey questionnaires will capture information on patients' characteristics (socio-demographics and UI-related items). The Geriatric Self-Efficacy Index for UI (GSE-UI Index) as well as a Likert scale to assess perceived capability and willingness to modify the expert-identified UI modifiable risk factors will be included. Data will be analyzed quantitatively and qualitatively.
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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 | 0.045 | 0.035 |
| Meta-epidemiology (narrow) | 0.003 | 0.004 |
| Meta-epidemiology (broad) | 0.006 | 0.007 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.039 | 0.007 |
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".