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Experiences and perceptions of respectful maternity care among mothers during childbirth in health facilities of Eastern province of Rwanda: An appreciative inquiry.
PLoS One
January 2025
School of Nursing and Midwifery, University of Rwanda, Kigali, Rwanda.
Introduction: The World Health Organization (WHO) has emphasized the importance of ensuring respectful and dignified childbirth experiences. However, many countries, including Rwanda, have documented negative experiences during childbirth. Identifying best practices can help uncover sustainable solutions for resource-limited settings rather than focusing solely on the challenges and negative aspects.
View Article and Find Full Text PDFA Digital Tool for Clinical Evidence-Driven Guideline Development by Studying Properties of Trial Eligible and Ineligible Populations: Development and Usability Study.
J Med Internet Res
January 2025
Advanced Care Research Centre, Usher Institute, The University of Edinburgh, Edinburgh, United Kingdom.
Background: Clinical guideline development preferentially relies on evidence from randomized controlled trials (RCTs). RCTs are gold-standard methods to evaluate the efficacy of treatments with the highest internal validity but limited external validity, in the sense that their findings may not always be applicable to or generalizable to clinical populations or population characteristics. The external validity of RCTs for the clinical population is constrained by the lack of tailored epidemiological data analysis designed for this purpose due to data governance, consistency of disease or condition definitions, and reduplicated effort in analysis code.
View Article and Find Full Text PDFEmpowering nurse leaders: readiness for AI integration and the perceived benefits of predictive analytics.
BMC Nurs
January 2025
Nursing Administration, Faculty of Nursing, Helwan University, Cairo, Egypt.
Introduction: Artificial Intelligence (AI) is increasingly being integrated into healthcare, particularly through predictive analytics that can enhance patient care and operational efficiency. Nursing leaders play a crucial role in the successful adoption of these technologies.
Aim: This study aims to assess the readiness of nursing leaders for AI integration and evaluate their perceptions of the benefits of AI-driven predictive analytics in healthcare.
Cultural competence, professional values, and spiritual well-being in nursing interns: a descriptive cross-sectional study.
BMC Nurs
January 2025
Student Research Committee, School of Nursing and Midwifery, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Background: Cultural competence, professional values, and spiritual well-being are among the topics that are widely considered today in response to turbulent and complex environments in organizations. The purpose of this study was to investigate the relationship between cultural competence, professional values, and spiritual well-being of nursing interns.
Methods: In this study, a total of 200 nursing interns affiliated with universities of medical sciences in Tehran city (Tehran, Shahid Beheshti, and Iran) were included as participants.
High-reward, high-risk technologies? An ethical and legal account of AI development in healthcare.
BMC Med Ethics
January 2025
Faculty of Law, University of Montreal, Ch de la Tour, Montreal, QC, H3T 1J7, Canada.
Background: Considering the disruptive potential of AI technology, its current and future impact in healthcare, as well as healthcare professionals' lack of training in how to use it, the paper summarizes how to approach the challenges of AI from an ethical and legal perspective. It concludes with suggestions for improvements to help healthcare professionals better navigate the AI wave.
Methods: We analyzed the literature that specifically discusses ethics and law related to the development and implementation of AI in healthcare as well as relevant normative documents that pertain to both ethical and legal issues.
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