MétaCan
Menu
Back to cohort
Record W1490437063 · doi:10.1080/10376178.2015.1089179

What can be learned from patient stories about living with the chronicity of heart illness? A narrative inquiry

2015· article· en· W1490437063 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueContemporary Nurse · 2015
Typearticle
Languageen
FieldMedicine
TopicCardiac Health and Mental Health
Canadian institutionsWestern UniversityToronto Metropolitan University
Fundersnot available
KeywordsNarrativeNarrative inquiryGlobeMedicineOutpatient clinicPsychologyNursing

Abstract

fetched live from OpenAlex

BACKGROUND: Patients' illness stories are valuable information that supports person-centred care across the illness trajectory. AIMS: To learn how older South Asian immigrant women experience living with heart illness long after discharge from hospital. METHOD: We used narrative inquiry, a personal experience method that explores and interprets lived and told stories through the three dimensions of experience. DESIGN: Four participants, over the age of sixty, living with heart illness for over ten years, were invited to engage in narrative interview and Narrative Reflective Process. OUTCOMES: Giving patients voice, allows caregivers insight into the human experience of illness beyond hospitalization. Considering the increased migration of people around the globe, this knowledge is significant in provision of person-centred care. IMPLICATIONS: Person-centred care does not end with the hospitalization and outpatient clinics. Inter-disciplinary teams need to reconsider the trajectory of chronic illnesses and the care required throughout, especially for marginalized populations.

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.766

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
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 head0.081
GPT teacher head0.349
Teacher spread0.268 · 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