ABSTRACT
Background: Reports on using virtual patients to assess counselling skills is scarce. Aim(s): This paper describes the feasibility and acceptability of assessing patient counselling skills of pharmacy students using a virtual patient simulator. Description: In this innovative method, a high quality simulator 'Virtual Patient Learning' (VPL) was developed at Gulf Medical University (GMU) and was used to assess the counselling skills of 15 pharmacy graduate students. Counselling skills were measured using a four-domain scoring rubric of 1 to 5 marks followed by instant feedback for improvements. Student and faculty satisfaction scores were collected based on the feasibility and acceptability of the assessment method. Evaluation: The average counselling skills score for all students was 68.4 (85.5%) out of 80 (range 54-76), with a standard deviation of 5.8. The overall student agreement on the feasibility and acceptability of the assessment method was 92.8%;it was 100% agreement for faculty. Conclusion(s): The use of a high quality VPL simulator in assessing counselling skills was deemed feasible and acceptable for students and faculty. The assessment was repeated among 30 Doctor of Pharmacy (Pharm.D.) graduates with similar outcomes. The virtual counselling method will be used in the programme exit exams, as well as in students entering their experiential year. Further studies are required to assess its validity and reliability with more students. Copyright © 2020, International Pharmaceutical Federation. All rights reserved.
ABSTRACT
BACKGROUND: The COVID-19 pandemic has precipitated rapid changes in medical education to protect students and patients from the risk of infection. Virtual Patient Simulators (VPS) provide a simulated clinical environment in which students can interview and examine a patient, order tests and exams, prioritize interventions, and observe response to therapy, all with minimal risk to themselves and their patients. Like high-fidelity simulators (HFS), VPS are a tool to improve curricular integration. Unlike HFS, VPS require limited infrastructure investment and can be used in low-resource settings. Few studies have examined the impact of VPS training on clinical education. This international, multicenter cohort study was designed to assess the impact of small-group VPS training on individual learning process and curricular integration from the perspective of nursing and medical students. METHODS: We conducted a multi-centre, international cohort study of nursing and medical students. Baseline perceptions of individual learning process and curricular integration were assessed using a 27-item pre-session questionnaire. Students subsequently participated in small-group VPS training sessions lead by a clinical tutor and then completed a 32-item post-session questionnaire, including 25 paired items. Pre- and post-session responses were compared to determine the impact of the small-group VPS experience. RESULTS: Participants included 617 nursing and medical students from 11 institutions in 8 countries. At baseline, nursing students reported greater curricular integration and more clinical and simulation experience than did medical students. After exposure to small-group VPS training, participants reported significant improvements in 5/6 items relating to individual learning process and 7/7 items relating to curricular integration. The impact of the VPS experience was similar amongst nursing and medical students. CONCLUSIONS: In this multi-centre study, perceptions of individual learning process and curricular integration improved after exposure to small-group VPS training. Nursing and medical students showed similar impact. Small-group VPS training is an accessible, low-risk educational strategy that can improve student perceptions of individual learning process and curricular integration.
Subject(s)
COVID-19 , Education, Medical/methods , Education, Nursing/methods , Patient Simulation , Students, Medical , Students, Nursing , Virtual Reality , Clinical Competence , Cohort Studies , Humans , PandemicsABSTRACT
BACKGROUND: Shortage of human resources, increasing educational costs, and the need to keep social distances in response to the COVID-19 worldwide outbreak have prompted the necessity of clinical training methods designed for distance learning. Virtual patient simulators (VPSs) may partially meet these needs. Natural language processing (NLP) and intelligent tutoring systems (ITSs) may further enhance the educational impact of these simulators. OBJECTIVE: The goal of this study was to develop a VPS for clinical diagnostic reasoning that integrates interaction in natural language and an ITS. We also aimed to provide preliminary results of a short-term learning test administered on undergraduate students after use of the simulator. METHODS: We trained a Siamese long short-term memory network for anamnesis and NLP algorithms combined with Systematized Nomenclature of Medicine (SNOMED) ontology for diagnostic hypothesis generation. The ITS was structured on the concepts of knowledge, assessment, and learner models. To assess short-term learning changes, 15 undergraduate medical students underwent two identical tests, composed of multiple-choice questions, before and after performing a simulation by the virtual simulator. The test was made up of 22 questions; 11 of these were core questions that were specifically designed to evaluate clinical knowledge related to the simulated case. RESULTS: We developed a VPS called Hepius that allows students to gather clinical information from the patient's medical history, physical exam, and investigations and allows them to formulate a differential diagnosis by using natural language. Hepius is also an ITS that provides real-time step-by-step feedback to the student and suggests specific topics the student has to review to fill in potential knowledge gaps. Results from the short-term learning test showed an increase in both mean test score (P<.001) and mean score for core questions (P<.001) when comparing presimulation and postsimulation performance. CONCLUSIONS: By combining ITS and NLP technologies, Hepius may provide medical undergraduate students with a learning tool for training them in diagnostic reasoning. This may be particularly useful in a setting where students have restricted access to clinical wards, as is happening during the COVID-19 pandemic in many countries worldwide.