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Introduction: Diagnosis lies at the heart of general practice. Every day general practitioners (GPs) visit patients with a wide variety of complaints and concerns, with often minor but sometimes serious symptoms. General practice has many features which differentiate it from specialty care setting, but during the last four decades little attention was paid to clinical reasoning in general practice. Therefore, we aimed to critically review the clinical reasoning models with a focus on the clinical reasoning in general practice or clinical reasoning of general practitioners to find out to what extent the existing models explain the clinical reasoning specially in primary care and also identity the gaps of the model for use in primary care settings.
Methods: A systematic search to find models of clinical reasoning were performed. To have more precision, we excluded the studies that focused on neurobiological aspects of reasoning, reasoning in disciplines other than medicine decision making or decision analysis on treatment or management plan. All the articles and documents were first scanned to see whether they include important relevant contents or any models. The selected studies which described a model of clinical reasoning in general practitioners or with a focus on general practice were then reviewed and appraisal or critics of other authors on these models were included. The reviewed documents on the model were synthesized.
Results: Six models of clinical reasoning were identified including hypothetic-deductive model, pattern recognition, a dual process diagnostic reasoning model, pathway for clinical reasoning, an integrative model of clinical reasoning, and model of diagnostic reasoning strategies in primary care. Only one model had specifically focused on general practitioners reasoning.
Conclusion: A Model of clinical reasoning that included specific features of general practice to better help the general practitioners with the difficulties of clinical reasoning in this setting is needed.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5611427 | PMC |
Channels (Austin)
December 2025
Biorheology Research Laboratory, Faculty of Health, Griffith University, Gold Coast, Australia.
The hallmarks of mechanosensitive ion channels have been observed for half a century in various cell lines, although their mechanisms and molecular identities remained unknown until recently. Identification of the bona fide mammalian mechanosensory Piezo channels resulted in an explosion of research exploring the translation of mechanical cues into biochemical signals and dynamic cell morphology responses. One of the Piezo isoforms - Piezo1 - is integral in the erythrocyte (red blood cell; RBC) membrane.
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Skaggs School of Pharmacy & Pharmaceutical Sciences, UC San Diego Health Sciences, San Diego, California, USA.
Artificial intelligence (AI), particularly large language models (LLMs), offers the potential to augment clinical decision-making, including in palliative care pharmacy, where personalized treatment and assessments are important. Despite the growing interest in AI, its role in clinical reasoning within specialized fields such as palliative care remains uncertain. This study examines the performance of four commercial-grade LLMs on a Script Concordance Test (SCT) designed for pharmacy students in a pain and palliative care elective, comparing AI outputs with human learners' performance at baseline.
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The Third Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China.
J Physician Assist Educ
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Andrew P. Chastain, DMS, PA-C, is an assistant professor at Butler University, Indianapolis, Indiana.
Introduction: Artificial intelligence tools show promise in supplementing traditional physician assistant education, particularly in developing clinical reasoning skills. However, limited research exists on custom Generative Pretrained Transformer (GPT) applications in physician assistant (PA) education. This study evaluated student experiences and perceptions of a custom GPT-based clinical reasoning tool.
View Article and Find Full Text PDFMedEdPublish (2016)
May 2025
Newcastle University Faculty of Medical Sciences, Newcastle upon Tyne, England, UK.
Background: Whilst debriefing literature offers valuable tools for healthcare education, there remains a gap in resources specifically designed for debriefing communication skills. Effective communication is fundamental to patient care, particularly during sensitive interactions. This article provides a specialised toolkit for educators to enhance communication skills debriefing, developed through synthesis of existing literature and the authors' extensive experience teaching communication skills through simulation.
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