Perceived stress level of the postoperative coronary artery bypass graft patients in the intensive care unit
Bibliographic record
Abstract
Objective: The purpose of this study was to measure the level of stress perceived by postoperative coronary artery bypass graft (CABG) patients. Coronary artery bypass graft is the most used surgical intervention to treat patients with coronary artery disease (CAD). Many patients consider CABG surgery as life threatening and stressful. There is a need for nurses to be aware of the patient’s perception of stress to create a more therapeutic environment within the intensive care unit (ICU).Methods: The research method was a quantitative descriptive survey design and descriptive statistics were used for data analysis. A convenience sampling method was used resulting in a sample size of 60 participants who had recently undergone a CABG surgical procedure. The participants completed the Intensive Care Unit Environmental Stressor Scale (ICUESS) survey.Results: The results of the ICUESS survey were analyzed according to rank order and mean with standard deviation scores for each of the 40 items. Findings showed the following stressors were ranked as the highest level of stress: “Being in pain”, “missing your husband or wife”, “having tubes in your nose or mouth”, and “only seeing family and friends for a few minutes each day”.Conclusions: The participants in this study were not highly stressed. Pain was the highest ranked stressor. Nurses need to be aware of the perceived level of stress by the postoperative CABG patients to reduce stressors and enhance recovery. The Neuman Systems Model was appropriate for this study.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".