Effect of intervention management care program on improving quality of life outcome among mastectomy women with diabetic: A comparative study
Bibliographic record
Abstract
Objective: This study aimed to evaluate the effect of intervention management care program on improving quality of life outcome among mastectomy women with diabetic.Subjects and Methods: Design: A quasi-experimental deign was used. Setting: It was selected from two settings Port Said oncology outpatient clinic and Damietta oncology outpatient clinic. Sampling: A purposive sample of mastectomy diagnosed with diabetic. The total sample was 50 women. They were 20 women from Port Said and 30 mastectomy women from Damietta Tools: The study data were collected by using three tools: The first tool-A women Structure interviewing questionnaire Sheet-its consisted of three parts: part one, demographic characteristics; part two, past and present medical history, complications related to diabetes and cancer and obstetrics characteristics; part three, knowledge about diabetes and mastectomy. The second tool-self-reported practices. The third tool-quality of life scale.Results: The study sample age ranged between 35 to more than 60 years with a mean of (50.3 ±8.6 and 48.3 ± 9.4) respectively in Damietta and Port-Said. There was statistically significant positive but strong correlate on among the three variables the strongest being between total scores knowledge and practices (r = 0.466) and strongest between knowledge and quality of life (r = 0.367) especially psychological aspects.Conclusions: The present study concluded that there is a marked gap between knowledge, practice and quality of life among the mastectomy women with diabetic before implement the program. There was an improvement in mastectomy women of all groups' knowledge and practice after the program. Also there were positive changes in quality of life in psychological, spiritual, emotional and social aspects. Furthermore, there were improvement in knowledge practice and positive change in quality of life after the implementation of the program of Damietta group more than port Said group.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".