An Examination of the difference in Performance of Self-Care Behaviours between White and Non-White Patients Following CABG Surgery: A Secondary Analysis
Bibliographic record
Abstract
BACKGROUND: The demographic profile of the patient receiving coronary artery bypass graft (CABG) surgery in Canada has changed significantly over the past 20 years from mainly white (i.e., English, Irish, Scottish) to non-white (i.e., Indian or Chinese). To support individuals who have recently undergone a CABG procedure, patient education is provided to guide performance of self-care behaviours in the home environment. The relevance of this education, when applied to the current CABG surgery population, is questionable, as it was designed and tested using a white, homogenous sample. Thus, the number and type of self-care behaviours performed by persons of Indian and Chinese origin has not been investigated. These individuals may have varying self-care needs that are not reflected in the current self-care patient education materials. PURPOSE: The intent of this study was to examine the difference in the type and number of self-care behaviours performed between white and non-white patients following CABG surgery. METHODS: This study is a sub-study of a descriptive, exploratory design that included a convenience sample. Ninety-nine patients were recruited, representing three cultural groups (White, Indian, and Chinese). Descriptive data were used to describe the sample and identify specific self-care behaviours performed in the home environment. FINDINGS: Results indicate statistically significant differences between white and non-white individuals related to use of incentive spirometer (p = 0.04), deep breathing and coughing exercises (p = 0.04), and activity modification (p < 0.05) at 1 week following hospital discharge. IMPLICATIONS: Future research and theoretical exploration are required to assist in the understanding of the underlying mechanisms that contribute to the differences that are noted between white and non-white groups.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".