MétaCan
Menu
Back to cohort
Record W2080830133 · doi:10.1016/s1474-5151(09)60146-8

SP35 A Qualitative Examination of Factors that Influence Women'S Qol as they Live with Heart Disease

2009· article· en· W2080830133 on OpenAlexaff
Colleen M. Norris, Kathryn King

Bibliographic record

VenueEuropean Journal of Cardiovascular Nursing · 2009
Typearticle
Languageen
FieldMedicine
TopicCardiac Health and Mental Health
Canadian institutionsUniversity of CalgaryUniversity of Alberta
Fundersnot available
KeywordsMedicineDiseaseQualitative researchGerontologyHeart diseasePhysical therapyInternal medicine

Abstract

fetched live from OpenAlex

Purpose: The purpose of this study was aimed at understanding women's experiences and perceptions regarding women health related quality of life in the context of living with heart disease. Method: Sampling was purposive and continued until data saturation. The women participated in semi-structured interviews, conducted in-person, which were audio-recorded and usually completed in less than one hour. The interviews were transcribed for analysis. Conventional content analysis was used to analyze the data. Results: Results indicated that heart disease influenced the participants QOL. This occurred through elements the investigators labeled “dealing with one more thing”; “surrendering roles and pleasures”; “managing the health system”; “understanding heart disease”; and “resolving to be strong”. Branching out from immediate family, social networks, including those developed through cardiac rehabilitation programs, played a significant role in women's descriptions of what contributed to having good QOL. These social networks also proved useful in helping the women manage the health system and understand their heart disease. Bringing friends/daughters along with them for their medical appointments assisted the women in ensuring that they understood what was being discussed at appointments and processes involved in managing their symptoms. Conversely, the women who lacked social networks reflected that the inability to manage their health contributed to their quality of life or lack thereof.

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)0.003
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 score0.918
Threshold uncertainty score0.557

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
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 head0.026
GPT teacher head0.323
Teacher spread0.297 · 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

Citations0
Published2009
Admission routes1
Has abstractyes

Explore more

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