Career Development of Nursing Preceptors in Iran: A Descriptive Study
Bibliographic record
Abstract
Background: The career development of nursing preceptors is key to improving the quality of clinical education. However, there is a lack of sufficient and specific information about the career development of nursing preceptors in Iran. Objectives: This study aimed to investigate the nursing preceptors’ career development status. Methods: A descriptive cross-sectional study was carried out with the participation of 92 nursing preceptors. Participants were selected by census sampling method from 5 hospitals in Tabriz, Iran. Demographic and 6-dimension career development questionnaires were used to collect data. The collected data were analyzed using SPSS version 22, and the significance level for all statistical tests was determined to be less than 0.05. Results: Participants received the highest career development on ethical, cultural, and individual dimensions with mean scores of 3.55 ± 0.471, 3.41 ± 0.525, and 3.38 ± 0.540, respectively. However, they obtained the lowest career development on the organizational, research, and educational dimensions with mean scores of 2.68 ± 0.580, 2.28 ± 0.672, and 2.20 ± 0.690, respectively. Moreover, a comparison of career development based on demographic information showed that female preceptors, preceptors with more than 20 years of work experience, preceptors with master’s degrees, and contract employees had the highest mean scores for career development. Conclusions: Given the preceptors’ cooperation with nursing faculty as clinical nursing educators and their role in nursing education, officials of nursing faculties should develop specific career development programs (especially in organizational, research, and educational dimensions) and establish an effective relationship between preceptors and professors to enhance nursing students education.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".