A theoretical model for brisk walking‐ and running‐induced lower urinary tract symptoms (BRUTS) and the development of the BRUTS‐questionnaire (BRUTS‐Q): A focus group and Delphi study
Bibliographic record
Abstract
AIMS: Existing questionnaires provide limited information on the nature, severity and context surrounding lower urinary tract symptoms (LUTS) experienced during running, jogging and brisk walking. The aims of this study were to develop a theoretical model of the experience of LUTS by females participating in gait-based exercise activities and to use this model to generate a questionnaire to evaluate the presence, symptoms and bother associated with LUTS experienced by females during gait-based activities. METHODS: A theoretical model was developed through a review of the literature and refined through a focus group consultation including pelvic health physiotherapists, females who experienced leakage during exercise and academic researchers who studied female LUTS. A draft questionnaire was developed using key constructs identified in the model by the focus group. A new expert panel was recruited, which included physiotherapists, women with self-reported gait-induced LUTS and urogynecologists. This panel followed a DELPHI process to evaluate the relevance and completeness of the constructs within the questionnaire. RESULTS: Two rounds of consultation were required to reach consensus on the completeness of included constructs as well as the inclusion and wording of questions. The resulting questionnaire contains questions related to five key constructs: physical activity characteristics, symptoms of urgency, urgency urinary incontinence, stress urinary incontinence experienced during exercise and management/mitigation strategies adopted by respondents. CONCLUSIONS: The content validity of the brisk walking- and running-induced lower urinary tracts symptoms questionnaire has been established. The next steps are to ensure that the questionnaire has adequate comprehensibility, followed by adequate measurement properties.
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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 | 0.095 | 0.054 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.005 | 0.018 |
| Scholarly communication | 0.006 | 0.009 |
| Open science | 0.004 | 0.007 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".