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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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.005
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.001
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 source (direct Gemma or distilled Codex), 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

Citations0
Published2009
Admission routes1
Has abstractyes

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Same venueEuropean Journal of Cardiovascular NursingSame topicCardiac Health and Mental HealthFrench-language works237,207