Research Appraisals
Evidence-based critical appraisals of the latest medical research, systematically evaluated using Oxford CEBM methodology.
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International journal of qualitative studies on health and well-being
Between duty and constraint: a qualitative systematic review of healthcare providers' ethical challenges and moral stressors in caring for undocumented migrants
PURPOSE: Healthcare providers play a critical role in delivering care to undocumented migrants, who face systemic barriers to healthcare access. While research has documented undocumented migrants' legal and policy barriers, less is known about the ethical challenges and moral stressors experienced by providers. This systematic review synthesizes qualitative studies on providers' experiences when delivering care to undocumented migrants. METHODS: The review followed PRISMA guidelines. PubMed, Embase, CINAHL, and the Cochrane Library were searched for relevant qualitative studies. Studies were screened by title, abstract, and full text using predefined inclusion and exclusion criteria. Quality assessment was conducted using the CASP checklist. Data were synthesized using the Qualitative Analysis Guide of Leuven (QUAGOL), integrating Graneheim and Lundman's approach to qualitative content analysis. RESULTS: The systematic search identified 37 qualitative studies. Analysis revealed 58 themes and subthemes, organized under five key concepts: experiences, perceptions, attitudes, practices and coping mechanisms, and ethical challenges. Providers reported moral distress, emotional exhaustion, and professional dilemmas arising from legal constraints, resource limitations, and conflicting obligations. Ethical tensions centered on beneficence vs. non-maleficence, professional duty vs. legal compliance, and the moral dilemma of deservingness. Across these findings, the synthesis identifies ethical burden-shifting as a central analytical contribution: restrictive systems transfer the moral and practical consequences of exclusionary arrangements onto providers and undocumented migrants at the point of care. CONCLUSION: This review shows that providers' ethical challenges are not only individual clinical dilemmas but structurally generated moral stressors. Addressing these challenges requires structural interventions, including policy reforms that reconcile professional ethics with legal constraints and institutional support to mitigate moral distress.
10 July 2026
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Deep learning four decades of human migration
Human migration is a fundamental driver of global demographic change, shaping population structure, labour markets and social policy across countries1-3. Although long-term migration patterns are often linked to economic development4, they can shift rapidly in response to shocks such as conflict, environmental crises and political change5. Despite its importance, migration remains difficult to measure consistently: existing data are sparse, concentrated in high-income settings and are fragmented across incompatible definitions, temporal resolutions and data types6-8. Past efforts have relied on partial datasets, including flow records, stock estimates and model-based reconstructions with limited coverage9-14. A central challenge is therefore to construct a globally consistent, high-resolution account of migration flows over time. Here we present a new dataset of annual origin-destination migration across 230 countries and regions from 1990 to the present, integrating diverse data sources into a unified modelling framework. By combining official statistics, census-based stocks, net migration estimates and past flow reconstructions, our approach produces temporally detailed and spatially comprehensive estimates that substantially extend existing resources. Using an ensemble of deep recurrent neural networks informed by geographic, economic, cultural and political covariates, we capture both persistent trends and short-term responses to changing conditions-all while propagating uncertainty to generate confidence bounds. Our results outperform existing five-year flow estimates on held-out data and provide finer temporal resolution, revealing previously obscured dynamics in global migration patterns. This framework highlights regions in which uncertainty remains high and data collection is most urgently needed. By releasing all data, code and trained models, we provide a transparent and reproducible foundation for future work. These advances enable a more timely and detailed understanding of human mobility, with implications for research and policy in an increasingly dynamic global system.
3 July 2026
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