Objectives: To identify the learning needs and preferred learning methods of First5 general practitioners (GPs) in National Health Service (NHS) Scotland.
Design: Qualitative research study using grounded theory methods. First5 GPs were interviewed in small focus groups or individual interviews in-person, or over the telephone depending on their preference.
Setting: General practice in NHS Scotland.
Participants: GPs, within the first 5 years of completion of GP training, who were working in NHS Scotland.
Results: Thirty-eight First5s were recruited to the study. Participants recognised that gaps in their GP training became apparent in independent practice. Some of this related to NHS appraisal and revalidation, and with the business of general practice. They were interested in learning from an older generation of GPs but perceived that preferred learning methods differed. First5 GPs were less reliant on reading journals to change their practice, preferring to find learning resources that allowed them to gain new knowledge quickly and easily. There were considerations about resilience and of the challenges of learning in remote and rural areas of NHS Scotland. This related to travel costs and time, and to accessibility of learning courses. Participants appreciated collective learning and commented about the logistics and costs of learning.
Conclusions: Preferred learning methods and learning resources differ with First5 GPs compared with those who have been in practice for some years. Learning providers need to recognise this and take these differences into account when planning and preparing learning in the future.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8126297 | PMC |
http://dx.doi.org/10.1136/bmjopen-2020-044859 | DOI Listing |
JMIR Form Res
December 2024
Department of Dermatology and Allergy, Technical University of Munich, Munich, Germany.
Background: The rapid development of large language models (LLMs) such as OpenAI's ChatGPT has significantly impacted medical research and education. These models have shown potential in fields ranging from radiological imaging interpretation to medical licensing examination assistance. Recently, LLMs have been enhanced with image recognition capabilities.
View Article and Find Full Text PDFJMIR Aging
December 2024
Clinical Research, Telemedicine and Telepharmacy Centre, School of Medicinal and Health Products Sciences, University Camerino, Camerino, Italy.
Background: To diagnose Alzheimer disease (AD), individuals are classified according to the severity of their cognitive impairment. There are currently no specific causes or conditions for this disease.
Objective: The purpose of this systematic review and meta-analysis was to assess AD prevalence across different stages using machine learning (ML) approaches comprehensively.
Human aging affects the ability to remember new experiences, in part, because of altered neural function during memory formation. One potential contributor to age-related memory decline is diminished neural selectivity -- i.e.
View Article and Find Full Text PDFCureus
November 2024
Division of Institutional Technology, Nova Southeastern University Dr. Kiran C. Patel College of Osteopathic Medicine, Fort Lauderdale, USA.
Background Virtual reality (VR) is typically used for entertainment or gaming, but many studies have shown that the applications of VR can also extend to medical and clinical education. This is because VR can help health professionals learn complex subjects, improve memory, and increase interest in abstract concepts. In the context of medical education, the immersive nature of a VR setting allows students and clinicians in training to interact with virtual patients and anatomical structures in a three-dimensional environment or from a clinician's point of view.
View Article and Find Full Text PDFCureus
November 2024
Faculty of Nursing, Japanese Red Cross Toyota College of Nursing, Toyota, JPN.
This study explored the use of virtual reality (VR) in disaster preparedness education, focusing on VR scenarios, disaster types, and user interactivity to identify gaps in existing research. A scoping review methodology, based on the Arksey and O'Malley framework and Preferred Reporting Items for Systematic Reviews and Meta-Analyses-Scoping Reviews (PRISMA-ScR) guidelines, was used, and the protocols were registered in the UMIN Clinical Trials Registry (UMIN000052800). The review included PubMed, CINAHL, the Cochrane Central Register of Controlled Trials in the Cochrane Library, and Ichushi-Web of the Japan Medical Abstract Society, with data up to January 31, 2024.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!