Threats and Opportunities of the Health Reform Plan from the Nurses’ Perspective in Ilam
Bibliographic record
Abstract
BACKGROUND: The Health Reform Plan is one of the greatest state services in Iran. However, this plan has its own weaknesses and strengths. This study was conducted with the purpose of determining strengths and weaknesses of the Health Reform Plan from nurses' perspective. METHODS: This is a cross-sectional study in which 100 nurses who work in clinical education centers on Ilam participated. The data collection tool was a questionnaire which consisted of 12 items regarding the strengths of the Health Reform Plan and 18 items about the plan's weaknesses on a six-option Lickert scale. Data analysis was carried out using SPSS V. 19 and applying descriptive and inferential statistics. RESULTS: The mean score for weaknesses was 79.94 and the mean score for strengths was 52.49. There was a significant statistical relationship between the variable of age and the strengths (P=0.015). CONCLUSION: If we manage to increase strengths and reduce weakness of the Health Reform Movement, we can be hopeful that this great plan will be administered more efficiently at a national level. It is suggested that future studies be conducted about individuals' perspectives in other occupations in the field of medical sciences working in different medical communities and hospitals in Iran and the results be compared.
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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 | 0.011 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| 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".