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Record W2065150796 · doi:10.1016/s1474-5151(09)60148-1

SP37 Self-Management Support in a Women-Only Cardiac Rehabilitation Program: Are we Empowering our Patients?

2009· article· en· W2065150796 on OpenAlexaff
Jayne Price, Danielle Rolfe, Monique Landry, Erica J. Sutton, D. Childerhose, Ling Li, Faith Delos-Reyes, Libby Groff, L Sternberg

Bibliographic record

VenueEuropean Journal of Cardiovascular Nursing · 2009
Typearticle
Languageen
FieldMedicine
TopicCardiac Health and Mental Health
Canadian institutionsWomen's College HospitalUniversity of Toronto
Fundersnot available
KeywordsMedicineRehabilitationPhysical therapySelf-managementPhysical medicine and rehabilitationIntensive care medicine

Abstract

fetched live from OpenAlex

Background: Self-management approaches have been shown to have positive impacts on the wellbeing of individuals with chronic illness. Support is critical to the development of self-management and emphasizes the patients' central role in managing and being responsible for their health. Women with cardiovascular disease typically have more than one chronic illness and may be helped by a cardiac rehabilitation (CR) program that provides self-management support. It is unknown whether programs specifically developed on the principals of empowerment for women meet the self-management support needs of female cardiac patients. Objective: The objective of this qualitative study was to determine whether, from the perspective of participants in a women-only CR program, the program provided the education, problem-solving skills and support necessary to manage their health problems. Methods: Fourteen women previously enrolled in a women-only CR or primary prevention program participated in a one-time, in-person, semi-structured qualitative interview. Interviews were transcribed verbatim and analyzed using a constant comparative approach to develop a coding scheme and identify relevant themes.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.981
Threshold uncertainty score0.933

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
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 head0.010
GPT teacher head0.302
Teacher spread0.292 · 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 designOther design
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

Citations0
Published2009
Admission routes1
Has abstractyes

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