Cited by 129Simulation-Based Education in HealthcareInnovations in Medical EducationSurgical Simulation and Training

The DOI matches its Crossref record; 32 of the 32 references it cites were found in a registry or an index; none of the 33 sources its claims cite is checked for support yet.

The virtual patient as a learning tool: a mixed quantitative qualitative study

Open access
Isaza-Restrepo, Andrés, Gómez, María Teresa, Cifuentes, Gary, Argüello, Arturo·2018·BMC Medical Education

Abstract

BACKGROUND: The use of simulation in medical education has been widely accepted. There are different types of medical simulators that vary in both accuracy to emulate the real world (fidelity) and cost of development or acquisition. There is significant evidence that supports the use of high-fidelity simulators (i.e. mannequins or dummies) to prepare students for clinical environments, less attention has been given to low-fidelity simulators. This article aims to present evidence regarding the effectiveness of a low-fidelity simulator: Virtual Patient (VP), which develops several interactive computer-based clinical scenarios, seeking to promote an alternative learning environment and the development of necessary medical skills such as clinical reasoning in students of medicine. METHODS: A quasi-experimental study was designed to investigate the results on the development of history taking and clinical reasoning skills in a group of undergraduate medical students, in a course devised under the concepts of constructivism in education, which used the Virtual Patient as the fundamental teaching tool. Results were measured through a mixed, quantitative and qualitative study, triangulating the results of the students' skills evaluation when facing a clinical case represented by an actor patient before and after the course. Additionally, the description of the students' and tool's performance was measured by way of a qualitative study. RESULTS: The comparison of the students' skills on the evaluation matrix before-and-after the course evidenced a statistically significant advance (p < 0.01) in all aspects (interview, physical exam, clinical judgment, relevance of medical exams, and presentation of case). Students described the VP as an easy-to-use and motivating tool for learning without stress, especially at the beginning of their career. VP allowed them to create logical and structured processes, to be wrong without consequences, and to review and reassess information available. From the professor perspective, it allowed a better follow-up of the students' learning process and favored reflections on the teaching-learning process. CONCLUSIONS: VP proved to be a valuable and useful tool for the development of clinical reasoning and history taking skills in medical students, as part of a constructivist learning course.

Overview

AI snapshot

Written from the paper’s full text.

TL;DR

In a 16-week elective course using a web-based Virtual Patient as the core tool, 20 preclinical medical students at Universidad del Rosario showed statistically significant pre-post improvement in history taking and clinical reasoning skills when assessed with an actor patient. Qualitative data indicated the VP was easy to use, motivating, and allowed error without patient risk, though the authors caution that effects cannot be attributed to the VP alone.

Key findings

  • All five assessed skills—interview, physical exam, clinical judgment, relevance of medical exams, and presentation of case—improved significantly from pre- to post-course by Wilcoxon signed rank test across three evaluators (abstract reports p < 0.01 in all aspects; Table 3 reports p values from <0.01 to 0.02).
  • Students described the VP as easy-to-use and motivating, allowing them to make mistakes without consequences, review/reassess information, and build logical/structured processes; it was seen as especially useful early in the career.
  • Professors reported better follow-up of students’ learning and reflection on the teaching-learning process; qualitative categories included use of the tool, perceptions on learning, construction of knowledge/competencies, and contributions to teaching.
  • Cost per hour of VP was USD 12, compared with USD 160–800 per hour for high-fidelity simulators and USD 30–40 per hour for standardized patients; software and faculty time cost $49,000 USD.

Methods

  • Quasi-experimental before-and-after mixed-methods study. Participants: 20 voluntary undergraduate medical students from first to fifth academic periods at Universidad del Rosario, first half of 2012, without prior semiology course; elective “Introduction to clinical reasoning” lasted 16 weeks with two-hour weekly sessions using VP cases of abdominal pain.
  • Quantitative: each student handled a clinical case enacted by a professional actor in first and last sessions; performances videotaped and scored by three evaluators on a 1–3 matrix for five skills; non-parametric analysis (Wilcoxon signed rank test) in SPSS v22; matrix validated by three evaluators with Kappa coefficient.
  • Qualitative: student focus group, professor field journals, and ethnographic observation by an anthropologist; data transcribed, digitized, coded by predefined categories and analyzed/triangulated in Atlas.ti v7.0; mixed concurrent/triangulated design.

Limitations

  • Stated: the VP was embedded in a course designed with solid pedagogical principles, so observed changes cannot be completely attributed to the VP; no comparison was made with other learning strategies; cost-effectiveness analysis was outside the study scope.
  • Stated: current VP development is insufficient to simulate the complexity of physician–patient interaction; as sole methodology it can become monotonous, may have technical problems, and requires complementary methodologies.
  • Evident from the text: small sample (20 students), single institution, voluntary elective, and no control group; pre-post design leaves possible confounding by course structure, teacher guidance, peer collaboration, and self-selection.

Model-written summary. Check it against the paper before relying on it.

Integrity signals

Registry

Crossref · 10.1186/s12909-018-1395-8

Cites

32 of 32 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Figures

Fig. 1 Scores pre and post. Evaluator 1
Fig. 1 Scores pre and post. Evaluator 1CC BY · PubMed Central
Fig. 2 Scores pre and post. Evaluator 2
Fig. 2 Scores pre and post. Evaluator 2CC BY · PubMed Central
Fig. 3 Scores pre and post. Evaluator 3
Fig. 3 Scores pre and post. Evaluator 3CC BY · PubMed Central

Verification

Claims the paper makes

31 Own result · 21 Not checked yet · 9 Own interpretation · 7 Own method · 1 No basis given

Verify all 33 references — free account
  • It may state two separate claims as one. 32
  • The quote only partly states this claim. 1
  • Probably not a substantial claim. 27
48 of 48
  • The paper relies on this without support.

    The actor-patient clinical case exercise is the closest to authentic clinical performance of a physician.

    “This exercise was considered as the closest to authentic clinical performance of a physician.”
  • The paper relies on this without support.

    The 20 undergraduate medical students from Universidad del Rosario are representative of medical students in general, so the study's conclusions can generalize to medical students.

    “The course involved 20 voluntary undergraduate medical students from first to fifth academic periods from Universidad del Rosario in the first half of 2012, who had not had a prior semiology course.”
  • The paper relies on this without support.

    Less attention has been given to low-fidelity simulators than to high-fidelity simulators.

    “There is significant evidence that supports the use of high-fidelity simulators (i.e. mannequins or dummies) to prepare students for clinical environments, less attention has been given to low-fidelity simulators.”
  • The paper relies on this without support.

    The Virtual Patient is still under development and relatively unexplored from a pedagogic perspective.

    “VP is still under development and relatively unexplored from a pedagogic perspective.”
  • The paper relies on this without support.

    A greater number of worked cases results in better performance in real life.

    “Evidence shows that a greater number of worked cases results in a better performance in real life.”
5 of 5

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Metadata

Authors
Isaza-Restrepo, A., Gómez, M. T., Cifuentes, G., & Argüello, A.
Affiliations
  • Universidad del Rosario (CO)
  • Universidad de Los Andes (CO)
Corresponding author
Isaza-Restrepo, Andrés
Venue
BMC Medical Education
Published
2018-12
Volume
18
Issue
1
Pages
297-297
ISSN
1472-6920 (ISSN-L)
OpenAlex
W2902116953
Cited by
129
References
32
Citations by year
2026: 11 · 2025: 14 · 2024: 21 · 2023: 20 · 2022: 32 · 2021: 17 · 2020: 11 · 2019: 3
FWCI
5.31
Type
journal article
Language
en
Open access
Locations
  • BMC Medical Education (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, other-oa)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas) (submittedVersion, other-oa)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • Greater South Information System
Funders
  • Universidad de los Andes
  • Universidad del Rosario
  • Fundación Santa Fe de Bogotá
Topics
  • Social Sciences › Education › Simulation-Based Education in Healthcare
  • Social Sciences › Education › Innovations in Medical Education
  • Health Sciences › Medicine › Surgery › Surgical Simulation and Training
Keywords
virtual patients, low-fidelity simulation, simulation-based medical education, clinical reasoning, medical history, undergraduate medical students, constructivist learning
MeSH terms
Clinical Competence, Computer-Assisted Instruction, Education, Medical, Educational Measurement, Evaluation Studies as Topic, Humans, Health Knowledge, Attitudes, Practice, Learning, Manikins, Physical Examination, Students, Medical, User-Computer Interface, Patient Simulation, Problem-Based Learning, Qualitative Research

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