Title |
A qualitative analysis of virtual patient descriptions in healthcare education based on a systematic literature review
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Published in |
BMC Medical Education, May 2016
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DOI | 10.1186/s12909-016-0655-8 |
Pubmed ID | |
Authors |
Inga Hege, Andrzej A. Kononowicz, Daniel Tolks, Samuel Edelbring, Katja Kuehlmeyer |
Abstract |
Virtual Patients (VPs) have been in the focus of research in healthcare education for many years. The aim of our study was to analyze how virtual patients are described in the healthcare education literature, and how the identified concepts relate to each other. We performed a literature review and extracted 185 descriptions of virtual patients from the articles. In a qualitative content analysis approach we inductively-deductively developed categories and deducted subcategories. We constructed a concept map to illustrate these concepts and their interrelations. We developed the following five main categories: Patient, Teacher, Virtual Patient, Curriculum, and Learner. The concept map includes these categories and highlights aspects such as the under-valued role of patients in shaping their virtual representation and opposing concepts, such as standardization of learner activity versus learner-centeredness. The presented concept map synthesizes VP descriptions and serves as a basis for both, VP use and discussions of research topics related to virtual patients. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United Kingdom | 1 | 100% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Practitioners (doctors, other healthcare professionals) | 1 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Ireland | 1 | <1% |
Unknown | 148 | 99% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Master | 23 | 15% |
Researcher | 20 | 13% |
Student > Ph. D. Student | 19 | 13% |
Student > Bachelor | 14 | 9% |
Professor > Associate Professor | 11 | 7% |
Other | 30 | 20% |
Unknown | 32 | 21% |
Readers by discipline | Count | As % |
---|---|---|
Medicine and Dentistry | 34 | 23% |
Nursing and Health Professions | 20 | 13% |
Computer Science | 18 | 12% |
Social Sciences | 14 | 9% |
Engineering | 6 | 4% |
Other | 18 | 12% |
Unknown | 39 | 26% |