Novice Nurses' Experiences of Unpreparedness at the Beginning of the Work
Bibliographic record
Abstract
INTRODUCTION: Unpreparedness of novice nurses during the process of transition to their professional role can has broad consequences for the nurse and health care system and leads to reduction of the quality of patient care. This study has been carried out with the aim of investigating the experiences of the unpreparedness of novice nurses. METHOD: This study was conducted qualitatively by using conventional content analysis. Participants were 21 persons including 17 novice nurses, 2 supervisors, and 2 experienced nurses who were selected through purposeful sampling from four hospitals dependent on Tehran University of Medical Sciences. FINDINGS: Participants' experiences were reflected in three main themes of "functional disability", "communicative problems", and "managerial challenges". Each of these dimensions consisted of several sub-categories. These areas had represented the inability to apply the learned knowledge in practice. DISCUSSION: The sensitivity of health system, especially, educational mentors and nursing managers to create preparation in novice nurses by providing appropriate orientation programs at the beginning of work and the revision and amendment of nursing curriculum can solve this problem to some extent.
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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 | 0.002 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".