Predictors of Anxiety Regarding The COVID-19 Pandemic Among Health-care Workers in a Hospital Not Assigned to Manage COVID-19 Patients in Nepal

  1. Lekhjung Thapa
  2. Aparna Ghimire
  3. Sulochana Ghimire
  4. Nooma Sharma
  5. Shakti Shrestha
  6. Medha Devkota
  7. Suman Bhattarai
  8. Anzil Man Singh Maharjan
  9. Subash Lohani
  10. Subash Phuyal
  11. Pratibha Maharjan

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Abstract

Introduction

We studied the levels and severity of anxiety caused by COVID-19 amongst frontline health-care workers (HCWs) in a tertiary care neurological hospital in Nepal, not assigned to manage COVID-19 cases.

Methods

A cross-sectional study was conducted on 100 frontline Health Care Workers (HCWs) using a 10-point subjective assessment tool, the Anxiety Level Index (ALI), and the Zung Self Rating Anxiety Score (SAS), to assess the level of anxiety regarding COVID-19.

Results

On ALI 55% of HCW were found to have marked severe anxiety (6-9), however, on SAS 44% of HCW’s reported anxiety. The majority HCW’s were female (n=78) with nurses forming 62% of the sample size. The mean age (±SD) was 26.8 years (± 8.17). Factors associated with significantly higher levels of anxiety regarding COVID-19 on ALI were age (p=0.002), sex (p=0.001), receiving regular COVID-19 updates via social media (p=0.011) and a high frequency of checking for COVID-19 information authenticity (p=0.039). Work experience (p=0.026) and frequency of checking for information authenticity (p=0.029) were factors found to increase SAS measured anxiety and were found to be associated with significantly higher levels of anxiety. Multivariate logistic regression analysis showed that respondents with work experience of ≤2 years were 0.380 (95% CI 0.158 to 0.910) times less likely to have anxiety than those with work experience of ≥2 years. Similarly, the odds of having anxiety among those who checked information authenticity less frequently was 0.377 (95% CI 0.153 to 0.931) times less than those who often did.

Conclusion

The COVID-19 outbreak has caused a substantial impact on the mental health of frontline HCWs in a hospital not assigned to manage COVID-19 patients. Length of time of worked in healthcare and the frequency of checking for COVID-19-related information were significant predictors of anxiety.

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  1. ScreenIT

    SciScore for 10.1101/2020.07.08.20148866: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: Measurements: Procedure: The Institutional Review Board approved the study.
    Consent: Before data collection, all participants gave informed, written consent.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    No key resources detected.

    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:
    Limitations and future directions: Although our study gives information about the anxiety regarding COVID-19 among HCWs not engaged in managing COVID-19 cases in Nepal, it has a few limitations. We intended to enroll all the HCWs in UDM-NINAS; however, because of the lockdown we only could collect data from 100 HCWs, which represents over 50% of the total HCWs of the hospital. Anxiety is a complex phenomenon45 and incorporation of essential variables like marital status, partner support, relationship with employer and colleagues, cultural background etc., which can heavily influence anxiety, is suggested. Future longitudinal studies are needed to understand chronic courses and prognosis of anxiety following COVID-19 in these individuals.

    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 10.1101/2020.07.08.20148866v1 on medRxiv