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Migration of Health Workers and Its Impacts on the Nigerian Health Care Sector: Protocol for a Scoping Review.
JMIR Res Protoc
January 2025
Department of Medicine and Optometry, eHealth Institue, Linnaeus University, Kalmar, Sweden.
Background: Health worker migration from Nigeria poses significant challenges to the Nigerian health care sector and has far-reaching implications for health care systems globally. Understanding the factors driving migration, its effects on health care delivery, and potential policy interventions is critical for addressing this complex issue.
Objective: This study aims to comprehensively examine the factors encouraging the emigration of Nigerian health workers, map out the effects of health worker migration on the Nigerian health system, document the loss of investment in health training and education resulting from migration, identify relevant policy initiatives addressing migration, determine the effects of Nigerian health worker migration on destination countries, and identify the benefits and demerits to Nigeria of health worker migration.
Extracorporeal Life Support Organization 2024 Guideline for Early Rehabilitation or Mobilization of Adult Patients on Extracorporeal Membrane Oxygenation.
ASAIO J
January 2025
Departments of Surgery and Pediatrics, Congenital Heart Center, University of Florida, Gainesville, Florida.
This Extracorporeal Life Support Organization guideline describes early rehabilitation or mobilization of patients on extracorporeal membrane oxygenation (ECMO). The guideline describes useful and safe practices put together by an international interprofessional team with extensive experience in the field of ECMO and ECMO rehabilitation or mobilization. The guideline is not intended to define the delivery of care or substitute sound clinical judgment.
View Article and Find Full Text PDFDeveloping and validating a HEalthCare NAvigation Competency (HECNAC) Scale for refugees in the United States.
PLoS One
January 2025
Health Promotion Sciences Department, Mel and Enid Zuckerman College of Public Health, University of Arizona, Tucson, Arizona, United States of America.
The complex healthcare system in the United States (US) poses significant challenges for people, particularly minorities such as refugees. Refugees often encounter additional layers of challenges to healthcare navigation due to unfamiliarity with the system, limited health literacy, and language barriers. Despite their challenges, it is difficult to identify the gaps as few tools exist to measure navigation competency among this population and many conventional tools assume English proficiency, making them inadequate for refugees and other immigrants.
View Article and Find Full Text PDFConstruction on training course and training quality evaluation index system of chronic disease medication therapy management service (MTMs) in China: A Delphi study.
PLoS One
January 2025
Department of Pharmacy, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, Jiangsu, China.
Objective: This study aims to construct a training course and quality evaluation index system for chronic disease Medication Therapy Management service (MTMs) that is suitable for China's national conditions. It seeks to provide tools and a scientific foundation for assessing the quality of MTMs training.
Methods: Drawing from domestic and international literature and combining with the practice of chronic disease medication management by Chinese pharmacists, a preliminary framework for the evaluation index system was established.
Judges versus artificial intelligence in juror decision-making in criminal trials: Evidence from two pre-registered experiments.
PLoS One
January 2025
Center for International Education and Exchange, Osaka University, Suita, Osaka, Japan.
Background: Artificial intelligence (AI) is anticipated to play a significant role in criminal trials involving citizen jurors. Prior studies have suggested that AI is not widely preferred in ethical decision-making contexts, but little research has compared jurors' reliance on judgments by human judges versus AI in such settings.
Objectives: This study examined whether jurors are more likely to defer to judgments by human judges or AI, especially in cases involving mitigating circumstances in which human-like reasoning may be valued.
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