Virtual Delivery of Simulation Education to Undergraduate Medical Students During the COVID-19 Pandemic

  1. Kay Wu
  2. Alex Chan
  3. Avinash Pandey
  4. Puru Panchal
  5. Maroof Khalid
  6. Sudarshan Bala
  7. Samveg Shah
  8. Matthew C. Miller

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Abstract

Background

The COVID-19 pandemic has restricted in-person clinical training for medical students. Simulation-based teaching is a promising tool to introduce learners to the clinical environment. MacSim is a student-led simulation workshop for learners to develop clinical competencies. The objective of this study was to assess the impacts of MacSim and participants’ perspectives regarding simulation-based teaching.

Methods

A comprehensive simulation, representative of a virtual care scenario, was delivered to 42 pre-clerkship medical students via video conferencing. In pairs, participants obtained histories and carried out management plans for simulated patients. Participants were surveyed and interviewed. Survey data were analyzed using the Wilcoxon signed-ranks test. Interview transcript data were thematically analyzed.

Results

Post-simulation, participants (n=24) felt more prepared to make clinical decisions, collaborate, and communicate in a virtual setting. 92% of respondents agreed MacSim was a valuable learning experience and 96% agreed more simulation-based learning should be integrated into curricula. Emergent themes from interviews (n=12) included: 1) value of simulation fidelity, 2) value of physician feedback, and 3) effectiveness of MacSim in improving virtual clinical skills.

Conclusion

Simulation-based teaching is of importance and educational value to medical students. It may play an increasingly prevalent role in education as virtual care is likely to become more prevalent.

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  1. ScreenIT

    SciScore for 10.1101/2021.08.20.21262347: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    EthicsIRB: The study design included comparison of pre- and post-event survey data, as well as post-event interview to assess perspectives regarding simulation teaching and COVID-19.14 The study was PIPEDA-compliant and exempted from ethics approval by the Hamilton Integrated Research Ethics Board due to it being a quality improvement project
    Sex as a biological variablenot detected.
    RandomizationAfter the event, one-on-one interviews were conducted and transcribed verbatim with 12 randomly selected participants by one of the authors.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    14 Statistical Analysis: Analysis was done using Statistical Package for the Social Sciences (SPSS) 26.
    Statistical Package for the Social Sciences
    suggested: (SPSS, RRID:SCR_002865)
    SPSS
    suggested: (SPSS, RRID:SCR_002865)

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    Several limitations are recognized for the present study. Sampling bias and nonresponse bias may have factored into the survey data of the present study as participants involved in the study were solely composed of participants in the simulation event. A lack of a validated survey for data collection, and a small sample size may additionally impact the validity of findings.

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    Results from scite Reference Check: We found no unreliable references.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  2. Version published to 10.1101/2021.08.20.21262347v1 on medRxiv