The influence of educational nursing intervention on the eating habits and anthropometric values of people who have undergone coronary surgery
Bibliographic record
Abstract
Objective: Educational nursing intervention is a strategy that can be useful for changing behaviours in a person’s health. Hospitalisation for coronary surgery is a valuable opportunity for the nurse to implement the knowledge which aims to promote healthy behaviours and secondarily, prevent coronary and cardiovascular disease, as these continue to be the main causes of death worldwide. The purpose of this study is to evaluate the influence of educational nursing intervention in the promotion of a healthy diet and in the anthropometric values (body mass index and waist perimeter) of people who have undergone coronary surgery.Methods: A quantitative and quasi-experimental study was conducted on a control group (20 participants in each group). The experimental group was submitted to a personalised structured educational intervention during hospitalisation, in the nursing follow-up visit (two to three weeks after surgery) and over the phone (two months after surgery). Each group went through two evaluations: the first before the surgery, and the second three months after the surgery. The instruments used to collect data included: the sociodemographic and clinical characterisation questionnaire and the Eating Habits Scale. Non-parametric tests were used.Results: The findings showed that 77.5% of the participants were male and 22.5% female. The participants’ average age was 67.35 ± 8.151. Results showed a significant improvement in the eating habits of both groups, with higher relevance in the experimental group and a reduction of the body mass index and waist perimeter exclusively in the experimental group.Conclusions: Regarding people who have undergone coronary surgery, personalised structured educational nursing intervention is a useful tool in obtaining health benefits and in secondary prevention of cardiovascular disease. More extensive and comprehensive studies are recommended to verify the results and enhance their success.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".