A Scoping Review of the Experiences of Internationally Educated Nurses Working With Older Adults in High‐Income Countries
Bibliographic record
Abstract
AIM: To comprehensively review the experiences and support needs of internationally educated nurses in healthcare settings for older people, identify current supportive interventions for internationally educated nurses in gerontological nursing practice and determine research gaps in the existing literature on their experiences and support needs. The review includes all types of nurses, except those focusing solely on undergraduate nurses who have yet to practise and nursing assistants. METHODS: A scoping review by a Canadian review group followed the methodological framework outlined by Arksey and O'Malley (2005) and later refined by Levac, Colquhoun, and O'Brien (2010). Articles of any publication date were included. A two-stage screening process was conducted independently to determine eligibility. Data extraction was performed using a piloted charting form. We also conducted a consultative exercise with Canadian nurses. Thematic and descriptive analyses were employed to analyse the extracted data. DATA SOURCES: Seven databases (PubMed, PsycINFO, PsychArticles, CINAHL, Scopus, Web of Science and EThOS) were systematically searched on April 27, 2024. Grey literature was searched using Google search engines, OpenGrey, ProQuest Sociological Abstracts and ProQuest ERIC, Healthcare Management Information Consortium, Open Grey repository, Proceedings First, Canada Health and Council for Allied Health Professions Research, and through expert consultation. RESULTS: The scoping review identified 11 articles from Canada, Germany, Ireland, the Netherlands, New Zealand, Norway and the United Kingdom, highlighting positive experiences and challenges internationally educated nurses face in healthcare settings for older people. Nurses were primarily registered nurses. Challenges included workplace interpersonal issues, language barriers and organisational constraints, while positive experiences included being valued by older adults and colleagues. CONCLUSION: The findings highlight the need for supportive interventions like mentorship, cultural competency training and organisation-led initiatives to improve internationally educated nurses' integration and retention in geriatric care, enhancing care quality for older persons. IMPLICATIONS FOR PRACTICE: Enhancing mentorship programs, cultural competency training, and organization-led support initiatives can improve the integration, retention, and overall well-being of internationally educated nurses in geriatric care, ultimately enhancing the quality of care for older adults. TRIAL REGISTRATION: osf.io/cwjem.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".