Investigating the Nursing Practitioners Perspectives about Undergraduate Nursing Internship and Apprenticeship Courses: Is Renewing Required?
Bibliographic record
Abstract
Nurses' professional capacity plays an important role in the health system to achieve their mission. This study aimed to investigate the perspectives of nursing practitioners about undergraduate nursing internship and apprenticeship courses and possible ways of renewing the courses. This cross sectional survey was performed over 258 bachelors and practitioners of nursing graduates of Alborz University of medical sciences in the second half of 2012. Based on a multi-stage sampling schedule, questionnaires were used to collect data about the perspectives of nursing practitioners about undergraduate nursing internship and apprenticeship courses. There were 81.4% of females and 80.6%, 17.1% and 2.3% of organizational post of participants were nurse, head nurse and supervisor respectively. The occupied posts for 60.1%, 25.6% and 14.1% of subjects, respectively were nurse, head nurse and the supervisor. The application of the internship and apprenticeship courses in bachelor of nursing were in moderate to high levels. The highest percentages of responses for internship and apprenticeship training courses were in internal surgery nursing and special nursing and the minimum percentage of responses were for community hygiene nursing and mental health nursing. Due to observing moderate to high levels of fulfillment and lack of compliance of training courses, renewing to improve the quality and effectiveness of training programs are highly recommended. This can be effective in the future of nursing career and provide a practical training environment to achieve the goals of theoretical training and can lead nurses to become specialized in their field.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".