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A qualitative analysis of virtual patient descriptions in healthcare education based on a systematic literature review

Overview of attention for article published in BMC Medical Education, May 2016
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1 tweeter

Citations

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Title
A qualitative analysis of virtual patient descriptions in healthcare education based on a systematic literature review
Published in
BMC Medical Education, May 2016
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.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 102 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Ireland 1 <1%
Unknown 101 99%

Demographic breakdown

Readers by professional status Count As %
Student > Master 20 20%
Student > Ph. D. Student 14 14%
Researcher 13 13%
Student > Bachelor 12 12%
Professor > Associate Professor 10 10%
Other 18 18%
Unknown 15 15%
Readers by discipline Count As %
Medicine and Dentistry 21 21%
Computer Science 16 16%
Social Sciences 15 15%
Nursing and Health Professions 13 13%
Psychology 5 5%
Other 12 12%
Unknown 20 20%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 29 May 2016.
All research outputs
#6,778,841
of 7,826,281 outputs
Outputs from BMC Medical Education
#1,088
of 1,196 outputs
Outputs of similar age
#224,234
of 269,257 outputs
Outputs of similar age from BMC Medical Education
#60
of 66 outputs
Altmetric has tracked 7,826,281 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,196 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.3. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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We're also able to compare this research output to 66 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.