Status of clinical training of academic staff to medicalstudents in kurdistan region: a cross-sectional study
Bibliographic record
Abstract
Introduction: Clinical supervision plays a significant role in nursing and medical practice.We aimed to explore the experiences of medicine and nursing students from the clinical educational supervision.Material and methods: In this cross-sectional study, 144 students of colleges of nursing (n = 88) and medicine (n = 56) of the University of Duhok, who were receiving clinical training for clinical-based subjects at colleges of nursing and medicine at University of Duhok in Kurdistan Region were included in a convenient way.Results: The study found that 57.64% were satisfied with the clinical supervision and mostly had positive perceptions.The total clinical supervision score, trust/rapport, supervisor advice, support, improve care/skills, improvement/ value of clinical supervision, funding time, personal issues, and reflection were significantly higher among medicine students.The medicine students were more likely to be satisfied with clinical training characteristics and had longer clinical training compared to the nursing students: 19-24 months (44.64%) vs. 1-6 months (70.45%; p < 0.0001), respectively.The entire clinical training (100%) among medicine students was weekly compared to weekly (86.36%), 2-weekly (3.41%), monthly (6.82%), and over 3 months (3.41%) among nursing students (p = 0.0397).Conclusions: The medicine students were more likely to be satisfied with clinical supervision compared to the nursing students.This satisfaction was associated with longer and weekly duration of training.The weaknesses of clinical supervision can guide supervisors to improve clinical education.We suggest that the entire fourth year be devoted to clinical training at the nursing college.In addition, one-to-one clinical training techniques be applied to both nursing and medicine colleges.We suggest the issues of clinical supervision be examined in more detail through some qualitative studies.The quantitative studies may not uncover the real problems of clinical supervision of medical students.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".