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Record W4206432751 · doi:10.1080/03630242.2021.2023247

Profile of women choosing mixed-sex, women-only, and home-based cardiac rehabilitation models and impact on utilization

2022· article· en· W4206432751 on OpenAlexafffundabout
Fiorella A. Heald, Susan Marzolini, Tracey J. F. Colella, Paul Oh, Rajni Nijhawan, Sherry L. Grace

Bibliographic record

VenueWomen & Health · 2022
Typearticle
Languageen
FieldMedicine
TopicCardiac Health and Mental Health
Canadian institutionsToronto Rehabilitation InstituteYork UniversityUniversity of TorontoUniversity Health Network
FundersToronto General and Western Hospital FoundationUniversity Health Network
KeywordsMedicineRehabilitationCohortFamily medicinePhysical therapySession (web analytics)Retrospective cohort studyGerontology

Abstract

fetched live from OpenAlex

This study compared characteristics and program utilization in women electing to participate in mixed-sex, women-only, or home-based cardiac rehabilitation (CR). In this retrospective cohort study, electronic records of CR participants in Toronto who were offered the choice of program model between January 2017-February 2020 were analyzed. There were 727 women (74.7% mixed, 22.0% women-only, 3.3% home-based) who initiated CR. There were significantly more women who were not working in women-only than mixed-sex (80.4% vs 64.1%; P = .009). Session adherence was significantly greater with mixed-sex (58.8 ± 28.9% sessions attended/25) than women-only (54.3 ± 26.3% sessions attended/25; P = .046); program completion was significantly lower with home-based (33.3%) than either supervised model (59.7%; P = .035). Participation in women-only CR may be less accessible. Further research is needed to investigate offering remote women-focused sessions or peer support.

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)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.557
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
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 head0.022
GPT teacher head0.334
Teacher spread0.313 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations3
Published2022
Admission routes3
Has abstractyes

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