Pelvic‐Floor‐Muscle Training Adherence: Tools, Measurements and Strategies—<i>2011 ICS State‐of‐the‐Science Seminar Research Paper II of IV</i>
Bibliographic record
Abstract
AIMS: This paper on pelvic-floor-muscle training (PFMT) adherence, the second of four from the International Continence Society's 2011 State-of-the-Science Conference, aims to (1) identify and collate current adherence outcome measures, (2) report the determinants of adherence, (3) report on PFMT adherence strategies, and (4) make actionable clinical and research recommendations. METHOD: Data were amassed from a literature review and an expert panel (2011 conference), following consensus statement methodology. Experts in pelvic floor dysfunction collated and synthesized the evidence and expert opinions on PFMT adherence for urinary incontinence (UI) and lower bowel dysfunction in men and women and pelvic organ prolapse in women. RESULTS: The literature was scarce for most of the studied populations except for limited research on women with UI. OUTCOME MEASURES: Exercise diaries were the most widely-used adherence outcome measure, PFMT adherence was inconsistently monitored and inadequately reported. Determinants: Research, mostly secondary analyses of RCTs, suggested that intention to adhere, self-efficacy expectations, attitudes towards the exercises, perceived benefits and a high social pressure to engage in PFMT impacted adherence. STRATEGIES: Few trials studied and compared adherence strategies. A structured PFMT programme, an enthusiastic physiotherapist, audio prompts, use of established theories of behavior change, and user-consultations seem to increase adherence. CONCLUSION: The literature on adherence outcome measures, determinants and strategies remains scarce for the studied populations with PFM dysfunction, except in women with UI. Although some current adherence findings can be applied to clinical practice, more effective and standardized research is urgently needed across all the sub-populations.
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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 | 0.028 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".