Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14279/24038
DC FieldValueLanguage
dc.contributor.authorPlackett, Ruth-
dc.contributor.authorKassianos, Angelos P.-
dc.contributor.authorTimmis, Jessica-
dc.contributor.authorSheringham, Jessica-
dc.contributor.authorSchartau, Patricia-
dc.contributor.authorKambouri, Maria-
dc.date.accessioned2022-02-14T07:42:03Z-
dc.date.available2022-02-14T07:42:03Z-
dc.date.issued2021-06-01-
dc.identifier.citationJournal of Medical Internet Research, 2021, vol. 23, no. 6, articl. no. e24723en_US
dc.identifier.issn14388871-
dc.identifier.urihttps://hdl.handle.net/20.500.14279/24038-
dc.description.abstractBackground: Improving clinical reasoning skills—the thought processes used by clinicians to formulate appropriate questions and diagnoses—is essential for reducing missed diagnostic opportunities. The electronic Clinical Reasoning Educational Simulation Tool (eCREST) was developed to improve the clinical reasoning of future physicians. A feasibility trial demonstrated acceptability and potential impacts; however, the processes by which students gathered data were unknown. Objective: This study aims to identify the data gathering patterns of final year medical students while using eCREST and how eCREST influences the patterns. Methods: A mixed methods design was used. A trial of eCREST across 3 UK medical schools (N=148) measured the potential effects of eCREST on data gathering. A qualitative think-aloud and semistructured interview study with 16 medical students from one medical school identified 3 data gathering strategies: Thorough, Focused, and Succinct. Some had no strategy. Reanalysis of the trial data identified the prevalence of data gathering patterns and compared patterns between the intervention and control groups. Patterns were identified based on 2 variables that were measured in a patient case 1 month after the intervention: the proportion of Essential information students identified and the proportion of irrelevant information gathered (Relevant). Those who scored in the top 3 quartiles for Essential but in the lowest quartile for Relevant displayed a Thorough pattern. Those who scored in the top 3 quartiles for Relevant but in the lowest quartile for Essential displayed a Succinct pattern. Those who scored in the top 3 quartiles on both variables displayed a Focused pattern. Those whose scores were in the lowest quartile on both variables displayed a Nonspecific pattern. Results: The trial results indicated that students in the intervention group were more thorough than those in the control groups when gathering data. The qualitative data identified data gathering strategies and the mechanisms by which eCREST influenced data gathering. Students reported that eCREST promoted thoroughness by prompting them to continuously reflect and allowing them to practice managing uncertainty. However, some found eCREST to be less useful, and they randomly gathered information. Reanalysis of the trial data revealed that the intervention group was significantly more likely to display a Thorough data gathering pattern than controls (21/78, 27% vs 6/70, 9%) and less likely to display a Succinct pattern (13/78, 17% vs 20/70, 29%; χ23=9.9; P=.02). Other patterns were similar across groups. Conclusions: Qualitative data suggested that students applied a range of data gathering strategies while using eCREST and that eCREST encouraged thoroughness by continuously prompting the students to reflect and manage their uncertainty. Trial data suggested that eCREST led students to demonstrate more Thorough data gathering patterns. Virtual patients that encourage thoroughness could help future physicians avoid missed diagnostic opportunities and enhance the delivery of clinical reasoning teaching.en_US
dc.formatpdfen_US
dc.language.isoenen_US
dc.relation.ispartofJournal of Medical Internet Researchen_US
dc.rights© The Author(s).en_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectComputer simulationen_US
dc.subjectWeb-based patient simulationen_US
dc.subjectComputer-assisted instructionen_US
dc.subjectEducational technologyen_US
dc.subjectMedical educationen_US
dc.subjectClinical decision support systemsen_US
dc.subjectClinical decision makingen_US
dc.subjectClinical reasoningen_US
dc.subjectClinical skillsen_US
dc.subjectPrimary careen_US
dc.subjectDiagnosisen_US
dc.titleUsing virtual patients to explore the clinical reasoning skills of medical students: Mixed methods studyen_US
dc.typeArticleen_US
dc.collaborationUniversity College Londonen_US
dc.subject.categoryOther Medical Sciencesen_US
dc.journalsOpen Accessen_US
dc.countryUnited Kingdomen_US
dc.subject.fieldMedical and Health Sciencesen_US
dc.publicationPeer Revieweden_US
dc.identifier.doi10.2196/24723en_US
dc.identifier.pmid34085940-
dc.identifier.scopus2-s2.0-85107410977-
dc.identifier.urlhttps://api.elsevier.com/content/abstract/scopus_id/85107410977-
dc.relation.issue6en_US
dc.relation.volume23en_US
cut.common.academicyear2020-2021en_US
item.grantfulltextopen-
item.openairecristypehttp://purl.org/coar/resource_type/c_6501-
item.fulltextWith Fulltext-
item.languageiso639-1en-
item.cerifentitytypePublications-
item.openairetypearticle-
crisitem.journal.journalissn1438-8871-
crisitem.journal.publisherJournal of Medical Internet Research-
crisitem.author.deptDepartment of Nursing-
crisitem.author.facultyFaculty of Health Sciences-
crisitem.author.orcid0000-0001-6428-2623-
crisitem.author.parentorgFaculty of Health Sciences-
Appears in Collections:Άρθρα/Articles
Files in This Item:
File Description SizeFormat
PDF.pdf481.27 kBAdobe PDFView/Open
CORE Recommender
Show simple item record

SCOPUSTM   
Citations

4
checked on Feb 1, 2024

WEB OF SCIENCETM
Citations

4
Last Week
0
Last month
0
checked on Oct 29, 2023

Page view(s)

249
Last Week
1
Last month
5
checked on Dec 22, 2024

Download(s)

133
checked on Dec 22, 2024

Google ScholarTM

Check

Altmetric


This item is licensed under a Creative Commons License Creative Commons