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Record W2414469324 · doi:10.32920/ryerson.14638503.v1

An examination of current patient education interventions delivered to culturally diverse patients following CABG surgery.

2021· article· en· W2414469324 on OpenAlexaff
Suzanne Fredericks, Souraya Sidani, Mandana Vahabi, Vaska Micevski

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldHealth Professions
TopicFamily and Patient Care in Intensive Care Units
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsRelevance (law)Cultural diversityPsychological interventionMedicineWork (physics)Culturally sensitivePsychologyMedical educationNursingPolitical scienceSocial psychology

Abstract

fetched live from OpenAlex

The design of current educational initiatives for heart surgery patients is based on feedback from individuals of Western European origin. The relevance of these initiatives is unknown when provided to individuals from non-Western European cultures. This study examined the cultural relevance of heart surgery patient educational initiatives delivered to individuals of diverse backgrounds. It used a non-experimental descriptive design involving 252 participants. Cultural relevance was assessed through self-care behaviours performed as recommended in the educational initiative. The participants of non-Western European origin were found to engage in more work-related activities and fewer self-care behaviours than their Western European counterparts in the first week following hospital discharge, indicating lack of adherence to educational recommendations. The study provides preliminary evidence suggesting that current self-care educational initiatives may not be culturally relevant. Continued evaluation to determine reasons why specific cultural groups engage in specific types of behaviour is needed.

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)0.011
metaresearch head score (Gemma)0.039
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 score0.011
Threshold uncertainty score0.058

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.039
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.130
GPT teacher head0.427
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 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

Citations4
Published2021
Admission routes1
Has abstractyes

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