Intervención de Enfermería en una familia mexicana con factores de riesgo para enfermedades crónico-degenerativas
Bibliographic record
Abstract
Introduction: Family, as a society, has direct influences on the habits and customs of its members. Along the times, the familial structure and dynamics have been changing; for example, regarding to its practices and behaviors such as food preparation and consumption, recreation, and physical activities. Diabetes mellitus and blood hypertension are the main chronic and de - generative illnesses related to sedentary and unhealthy eating life styles. Objective: To provide health education to a specific family so that it can improve its self-care and health behaviors, as a result of its eating habits, physical activity, and chronic and degenerative illnesses prevention knowledge enhancement. Methods: The familial structure, development, and dynamics were assessed using the Calgary & Friedman model. After the detection of actual and potential problems, an education intervention focused on healthy eating habits, physical activity, and chronic and degenerative illnesses risk factors addressing, was developed. Results: This family acquired the corresponding knowledge, and engaged into an unhealthy ha- bits modification. Discussion: Assessing families is useful for nursing professionals in order to identify unhealthy behaviors as well as trans-generational illness patterns. Conclusions: In order to obtain results such as habits and life style modifications, it is necessary to continue following the education intervention up.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.003 | 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".