Calgary Family Intervention Model Approach to Improve Quality of Life for Diabetes Mellitus Patients
Bibliographic record
Abstract
Calgary Family Intervention Model (CFIM) is a nursing care model that is dominated by the family and integrated with the nursing paradigm that focuses on families. A case study was conducted to determine the intervention to improve the quality of life for the patient with diabetes mellitus. Nursing care was carried out using the Calgary Family Intervention Model approach with the author for three days and continued by the family for two weeks. With data collection techniques include interviews, observation, physical examination, and documentation. The tools used in this case study are a set of physical examination tools, blood sugar check tools, a nursing kit, and the WHOQOL-BREF questionnaire. The results showed that Mr. J’s family had problems in the dimensions of physical and psychological health, with the established nursing diagnosis being a poor quality of life. In family members who experience diabetes mellitus with quality of life problems there are positive changes to the family and in handling, nutrition, exercise, foot care, and stress management for the patient. It can be seen from the results questionnaire which showed an improvement in scores than before, especially in the dimensions of physical and psychological health. Keywords: Calgary, diabetes mellitus, family, nursing, quality of life
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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 | 0.001 |
| 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 | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".