COVID-19 Pandemic in University Hospital: Is There an Effect on The Medical Interns?

  1. WeiHonn Lim
  2. Li Ying Teoh
  3. Kanesh Kumaran A/L Seevalingam
  4. Shanggar Kuppusamy

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Abstract

Introduction

Coronavirus Disease 2019 (COVID-19) pandemic has disrupted the current healthcare system and carries a major impact to the healthcare workers (HCW). University Malaya Medical Centre (UMMC) has been selected as one of the centres in managing COVID-19 cases in Malaysia. Many HCW including the medical interns, are directly or indirectly involved in the management.

Methods

This is a cross-sectional, pilot study to determine the impact of the pandemic on UMMC medical interns. A survey which comprises 37-items was used. Data are analysed by Ordinal Logistic Regression Analysis.

Results

Our study shows that medical interns are tired (p = 0.014), starving (p = 0.004), have inadequate exercises (p = 0.004) and burdened with heavy workload (p=0.023) during pandemic period. Many are depressed (p = 0.043), scared to work (p = 0.03), and worried of getting infected (p < 0.05). Some quarrel with their colleagues (p < 0.05), losing contact with friends (p = 0.022) and feel that it will be beneficial to have a peer support group (p = 0.027).

Conclusion

In summary, the impact of COVID-19 amongst medical interns is significant and their overall well-being should be protected without jeopardising their training.

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    SciScore for 10.1101/2020.10.01.20205112: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Subsequently, all data are downloaded into Excel form and transcript into SPSS Version 16.0.
    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:
    Limitation:

    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.

    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 10.1101/2020.10.01.20205112 on medRxiv