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An Exploration of the Relationship Between Coronary Artery Bypass Graft Patients' Self-Sought Educational Resources and Outcomes

2008· article· en· W2329475237 on OpenAlexaff
Suzanne Fredericks, Souraya Sidani

Bibliographic record

VenueThe Journal of Cardiovascular Nursing · 2008
Typearticle
Languageen
FieldHealth Professions
TopicHealth and Wellbeing Research
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsMedicineArteryInternal medicineCardiologyBypass graftingIntensive care medicine

Abstract

fetched live from OpenAlex

Postoperative coronary artery bypass graft (CABG) patients seek educational resources around discharge. There is limited research on the type and perceived effectiveness of self-sought educational resources. The purpose of this study was to describe the use of self-sought educational resources by patients around time of discharge and to explore relationships between use of self-sought educational resources and self-care knowledge, performance of self-care behavior, and symptom frequency. This study is a substudy of a randomized clinical trial that included a convenience sample of first-time CABG patients. Significant correlations were found between use of self-sought educational resources and greater frequency of patient's behavior (P ≤ .05), and a decrease in symptom frequency (P ≤ .05). This study represents a first step toward identifying the association between the use of self-sought educational resources after CABG and outcomes expected of education.

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)0.002
metaresearch head score (Gemma)0.012
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.095
GPT teacher head0.403
Teacher spread0.309 · 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

Citations6
Published2008
Admission routes1
Has abstractyes

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