Qualitative research approach could be as important as quantitative one, particularly in medical education, as long as it meets the common goal of both-improving the quality of education. In contrary to the end-i.e. achieving the common goals, the means of both approaches of inquiry is different. Their dissimilarity in the means or process is not confined to data collection techniques, study designs or analysis methods; but, they also differ in assumptions about the world, reality, science and knowledge. Implicitly or explicitly, these assumptions are revealed in a researcher's discussion about philosophical assumptions and research paradigms. The researcher's inclination towards any of paradigms and assumption in light of the most common philosophical concepts such as ontology, epistemology and methodology results in choice of either of the dominant research paradigms to follow such as objectivism/positivism and interpretivisim/constructivism. This is common practice in the quantitative-qualitative dichotomy of research world disregarding the emerging mixed approach with predominantly pragmatism paradigm. Besides framing the methodology of the study, researcher's explicit description of philosophical assumptions and paradigms helps readers easily understand study findings. Many authors from both dominant traditions fail to describe this important aspect of the research in their published works. In our study, the ontological and epistemological assumptions led us choose interpretivist/constructivist paradigm and phenomenological qualitative approach with Collaizi's descriptive phenomenological analysis adapted to our context. The experience and lesson learned from the study found to be worse sharing in a modified and extended construct of methodology part. Therefore, this article deals with philosophical positions, research paradigms and traditions that led to the specific qualitative approach from the perspective of methodology part in our study about objective structure clinical examination (OSCE) experience in a medical department.
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http://dx.doi.org/10.1016/j.amsu.2019.11.013 | DOI Listing |
JMIR Form Res
January 2025
Faculty of Medicine, The University of Queensland, Brisbane, Australia.
Background: Opioid medications are important for pain management, but many patients progress to unsafe medication use. With few personalized and accessible behavioral treatment options to reduce potential opioid-related harm, new and innovative patient-centered approaches are urgently needed to fill this gap.
Objective: This study involved the first phase of co-designing a digital brief intervention to reduce the risk of opioid-related harm by investigating the lived experience of chronic noncancer pain (CNCP) in treatment-seeking patients, with a particular focus on opioid therapy experiences.
JMIR Res Protoc
January 2025
Institute for Health Care Management and Research, University of Duisburg-Essen, Essen, Germany.
Background: Artificial intelligence (AI)-based clinical decision support systems (CDSS) have been developed for several diseases. However, despite the potential to improve the quality of care and thereby positively impact patient-relevant outcomes, the majority of AI-based CDSS have not been adopted in standard care. Possible reasons for this include barriers in the implementation and a nonuser-oriented development approach, resulting in reduced user acceptance.
View Article and Find Full Text PDFJ Health Serv Res Policy
January 2025
Associate Professor, Exeter Collaboration for Academic Primary Care, University of Exeter Medical School, Exeter, UK.
Objective: Digital services in primary care are becoming more common, yet access to and use of services can create inequities. Our aim was to explore the drivers, priorities, and evolving policy context influencing digital facilitation in primary care as reported by national, regional and local level stakeholders in England.
Methods: We conducted online semi-structured qualitative interviews with stakeholders, including those in NHS England organisations, local commissioners for health care, statutory and third sector organisations, those working within the research community, and digital platform providers.
PLoS One
January 2025
College of Education for the Future, Beijing Normal University, Zhuhai, Guangdong, China.
Personalized sports training plans are essential for addressing individual athlete needs, but traditional methods often need to integrate diverse data types, limiting adaptability and effectiveness. Existing machine learning (ML) and rule-based approaches cannot dynamically generate context-specific training programs, reducing their applicability in real-world scenarios. This study aims to develop a Generative Adversarial Network (GAN)- based framework to create context-specific training plans by integrating numeric attributes (e.
View Article and Find Full Text PDFPLoS One
January 2025
Faculty of Health, Liverpool John Moores University, Liverpool, England, United Kingdom.
Background: Although the benefits of engaging in cardiac rehabilitation are well established, patient perceptions of the changes in their health-related quality of life are poorly documented. This systematic review synthesized qualitative studies on patients' perspectives of change in their health-related quality of life after attending cardiac rehabilitation.
Objective: To identify and synthesize the best available evidence on the perspective of patients living with heart disease about the changes in their health-related quality of life after attending cardiac rehabilitation.
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