Facilitators and barriers to adjustment of international nurses: an integrative review
Bibliographic record
Abstract
BACKGROUND: There is a scarcity of research focusing on issues encountered by international nurses (INs) in their adjustment to foreign health-care environments. Increasingly, INs are relied upon to address staffing shortages in many Western countries. As such, it is vital to identify what facilitates and what the barriers are to the successful adjustment in order to assist their integration into new workplace environments. AIM: This integrative review identifies facilitators and barriers encountered by INs as they adjust to foreign health-care environments. METHOD: Based on Cooper's Five Stages of Integrative Research Review, a systematic search of eight electronic databases was conducted, combined with hand and ancestral searches. Two authors independently reviewed each qualified study for relevance and significance. Subsequently, facilitators and barriers were identified and categorized into themes and subthemes. FINDINGS: Twenty-nine studies conducted in Australia, Canada, Iceland, UK and the USA were included in this review. Findings indicated that positive work ethic, persistence, psychosocial and logistical support, learning to be assertive and continuous learning facilitated the adjustment of INs to their new workplace environments. In contrast, language and communication difficulties, differences in culture-based lifeways, lack of support, inadequate orientation, differences in nursing practice and inequality were barriers. CONCLUSION: The review findings provide the basis for the development and testing of an evidence-informed programme to facilitate the successful adjustment of INs to their new work environments.
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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 | 0.007 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| 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".