Literature DB >> 24738550

Virtual patient simulations and optimal social learning context: a replication of an aptitude-treatment interaction effect.

Teresa R Johnson1, Rebecca Lyons, Regis Kopper, Kyle J Johnsen, Benjamin C Lok, Juan C Cendan.   

Abstract

BACKGROUND: Virtual patients (VPs) offer valuable alternative encounters when live patients with rare conditions, such as cranial nerve (CN) palsies, are unavailable; however, little is known regarding simulation and optimal social learning context. AIM: Compare learning outcomes and perspectives between students interacting with VPs in individual and team contexts.
METHODS: Seventy-eight medical students were randomly assigned to interview and examine four VPs with possible CN damage either as individuals or in three-person teams, using Neurological Examination Rehearsal Virtual Environment (NERVE). Learning was measured through diagnosis accuracy and pre-/post-simulation knowledge scores. Perspectives of learning context were collected post-simulation.
RESULTS: Students in teams submitted correct diagnoses significantly more often than students as individuals for CN-IV (p = 0.04; team = 86.1%; individual = 65.9%) and CN-VI (p = 0.03; team = 97.2%; individual = 80.5%). Knowledge scores increased significantly in both contexts (p < 0.001); however, a significant aptitude-treatment interaction effect was observed (p = 0.04). At pre-test scores ≤25.8%, students in teams scored significantly higher (66.7%) than students as individuals (43.1%) at post-test (p = 0.03). Students recommended implementing future NERVE exercises in teams over five other modality-timing combinations.
CONCLUSION: Results allow us to define best practices for integrating VP simulators into medical education. Implementing NERVE experiences in team environments with medical students in the future may be preferable.

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Year:  2014        PMID: 24738550      PMCID: PMC4097175          DOI: 10.3109/0142159X.2014.890702

Source DB:  PubMed          Journal:  Med Teach        ISSN: 0142-159X            Impact factor:   3.650


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  2 in total

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