Internationally educated nursing students’ experiences of integration in the hospital setting
Bibliographic record
Abstract
In North America, internationally educated nurses (IEN) have played an essential role in addressing the nursing shortage as a result of immigration and increasing international recruitment. Given the importance of the IEN role in the delivery of patient care, it is vital that IENs who are involved in educational programs to prepare them for practice in North America are integrated as health care team members. The purpose of this paper is to explore internationally educated nursing students’ experiences of integration in the acute care hospital setting. A qualitative design was used to explore nine IEN students’ experiences of integration in the acute care practice setting. IEN students involved in a bridging educational program in nursing participated in individual interviews lasting 60-90 minutes. Interviews were transcribed verbatim. Researchers engaged in meaning making where initial categories were shaped into themes. Participants expressed having a dual identity as nurse and student, feeling like outsiders and experiencing discrimination in the practice setting, and IENs experienced challenges around discontinuity of relationships, language, and use of technology. IENs also discovered opportunities to learn and grow. To support the meaningful integration of IENs into clinical practice, it is crucial that the academic environment and practice partners ensure IEN students have positive and effective learning experiences where they feel part of the interprofessional team, and can ultimately deliver safe client care.
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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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.007 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.014 |
| Research integrity | 0.002 | 0.005 |
| 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".