Transnational Healthcare Practices Among Migrants: A Concept Analysis
Bibliographic record
Abstract
AIMS: To present a conceptual definition of transnational healthcare in the context of migrant older adults. DESIGN: This article follows the Walker and Avant concept analysis framework to conduct an in-depth analysis of transnational healthcare. METHODS: Databases were searched for scholarly articles using keywords associated with transnational healthcare. The DistillerSR software was employed to screen articles for inclusion in the concept analysis. Titles and abstracts of 390 articles were screened with 50 identified for full-text screening. Thirty-seven articles were included to inform the concept analysis. DATA SOURCES: Social Science Citation Index (Clarivate), PsycInfo and CINAHL databases. Search dates: March-May 2024. RESULTS: Defining attributes of the concept include cultural comfort and alignment, perceived quality and trust, integration barriers and experiences of discrimination, use of digital platforms and informal networks, challenges navigating host country health systems. Cases, antecedents, consequences, empirical referents and cultural considerations were used to shape a conceptual definition of transnational healthcare. CONCLUSION: Transnational healthcare is defined as a practice involving those living outside of their country of origin seeking healthcare from that country of origin through physical or other means. IMPLICATIONS FOR PROFESSIONAL PRACTICE: This conceptual definition highlights the importance of understanding healthcare access, quality and continuity of care across national borders. IMPACT: This study addresses gaps in available literature regarding transnational healthcare and its impacts on treatment outcomes, healthcare satisfaction and continuity of care in migrant communities. REPORTING METHOD: This article adheres to the PRISMA (2020) reporting guidelines for systematic reviews. PATIENT OR PUBLIC CONTRIBUTION: No patient or public contribution.
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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 | 0.027 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.011 | 0.009 |
| Science and technology studies | 0.003 | 0.007 |
| Scholarly communication | 0.006 | 0.011 |
| Open science | 0.002 | 0.007 |
| 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".