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Record W4294839516 · doi:10.3138/ptc-2021-0089

Accessibility of Pelvic Floor Physiotherapy for Treating Urinary Incontinence in Older Women in Quebec: An Online Survey

2022· article· en· W4294839516 on OpenAlexaffvenueabout
Mélanie Le Berre, Chantale Dumoulin

Bibliographic record

VenuePhysiotherapy Canada · 2022
Typearticle
Languageen
FieldMedicine
TopicPelvic floor disorders treatments
Canadian institutionsUniversité de MontréalInstitut Universitaire de Gériatrie de Montréal
Fundersnot available
KeywordsUrinary incontinencePelvic floorMedicinePhysical therapyPelvic floor dysfunctionGynecologyUrologySurgery

Abstract

fetched live from OpenAlex

Purpose: This cross-sectional descriptive study describes available pelvic floor physiotherapy (PT) services for older women with urinary incontinence (UI) in Quebec, Canada, and identifies possible affordability barriers. Methods: From September to December 2019, Quebec physiotherapists practising pelvic floor PT were invited to complete a survey on their clinical practice and perceptions of the affordability of UI treatment for older women. Results: Eighty-four of the 225 registered pelvic floor physiotherapists (37.3%) filled out the online survey. They worked a median of 32 hours/week in PT, with 15 of those hours (46.9%) in pelvic floor PT and three hours (9.8%) treating UI in older women. Only 13.0% of them offered group treatment, while 84.3% were interested in it. Most of the physiotherapists (92.2%) had met older women in their practice who had reported financial barriers to completing their pelvic floor PT treatment. Conclusions: The accessibility of UI care in Quebec appears hampered by the limited availability of pelvic floor PT treatments, mainly in public settings, and potential financial constraints. Providing pelvic floor PT to groups could constitute a promising avenue to tackle both issues. Future studies should look at ways of implementing this option.

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.

How this classification was reachedexpand

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.065
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.323
Teacher spread0.302 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations9
Published2022
Admission routes3
Has abstractyes

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