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Record W4410881567 · doi:10.1016/j.cont.2025.101906

Group-based pelvic floor muscle training for urinary incontinence in Postmenopausal Women: Tips and tricks for successful practice: ICS 2023 workshop

2025· article· en· W4410881567 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueContinence · 2025
Typearticle
Languageen
FieldMedicine
TopicPelvic floor disorders treatments
Canadian institutionsUniversité de MontréalInstitut Universitaire de Gériatrie de Montréal
FundersCanadian Institutes of Health ResearchRéseau québécois de recherche sur le vieillissement
KeywordsPelvic Floor MuscleUrinary incontinenceMedicinePostmenopausal womenPhysical therapyUrologyPelvic floorPhysical medicine and rehabilitationInternal medicineAnatomy

Abstract

fetched live from OpenAlex

Pelvic floor muscle training (PFMT) is the recommended first-line treatment for urinary incontinence and lower urinary tract symptoms. However, global availability of human and financial resources limits its accessibility. Group-based PFMT, which has been studied in postmenopausal women, offers a potential solution. This paper is based on the Group-based intervention for pelvic floor muscle dysfunctions in postmenopausal women workshop held during the 2023 International Continence Society Annual Scientific Meeting, in Toronto. It reviews the current evidence on group-based PFMT, discusses participant inclusion criteria, details the structure of the 12-week PFMT programme, presents remote group-based PFMT as an alternative to in-person group-based PFMT and proposes tips and tricks to empower clinicians in conducting Group-Based interventions for urinary incontinence and lower urinary tract symptoms.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.791
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.021
GPT teacher head0.320
Teacher spread0.298 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it