Prevalence and predictors of coronaphobia among frontline hospital and public health nurses

  1. Leodoro J. Labrague
  2. Janet Alexis A. De Los Santos

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Abstract

Objectives

To determine the prevalence as well as the predictors of coronaphobia in frontline hospital and public health nurses.

Design

This study used a cross‐sectional research study involving 736 nurses working in COVID‐19 designated hospitals and health units in Region 8, Philippines. Four structured self‐report scales were used, including the Coronavirus Anxiety Scale, the Brief Resilience Scale, the Perceived Social Support Questionnaire, and the single‐item measure for perceived health.

Results

The prevalence of coronaphobia was 54.76% ( n  = 402): 37.04% ( n  = 130) in hospital nurses and 70.91% ( n  = 273) in public health nurses. Additionally, nurses' gender ( β  = 0.148, p  < .001), marital status ( β  = 0.124, p  < .001), job status ( β  = 0.138, p  < .001), and personal resilience ( β  = −0.167, p  = .002) were identified as predictors of COVID‐19 anxiety. A small proportion of nurses were willing (19.94%, n  = 70) and fully prepared (9.40%, n  = 33) to manage and care for coronavirus patients.

Conclusion

Coronaphobia is prevalent among frontline Filipino nurses, particularly among public health nurses. Interventions to address coronaphobia among frontline nurses in the hospital and community should consider the predictors identified. By increasing personal resilience in nurses through theoretically driven intervention, coronaphobia may be alleviated.

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  1. ScreenIT

    SciScore for 10.1101/2020.10.18.20214692: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: Data Collection and Ethical Considerations: The research proposal was sent to the Institutional Research Ethics Committee of Samar State University (IRERC EA□0012□I).
    Consent: The front page of the Google form contained the basic information regarding the research as well as the letter of consent.
    RandomizationSamples and Settings: This study involved frontline hospital and public health nurses in Western Samar, Philippines, from 15 hospitals and 10 health units, which were chosen randomly from the list of all health centres and hospitals within the Region.
    Blindingnot detected.
    Power AnalysisTo achieve an 80% power with a small effect size (0.03) and an alpha set at 0.05, the required sample was 586 nurses as calculated by the G Power program (Soper, 2020).
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    To achieve an 80% power with a small effect size (0.03) and an alpha set at 0.05, the required sample was 586 nurses as calculated by the G Power program (Soper, 2020).
    G Power
    suggested: (G*Power, RRID:SCR_013726)
    Data Analysis: Descriptive and inferential statistics were used to analyse the data gathered using the SPSS version 25.
    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:
    Limitations of the Study: A few limitations of this study should be considered when analysing and interpreting the results. First, while sample calculation was conducted to determine the required sample size, increasing the sample size may be necessary to detect large effect size. Further, due to the nature of the research design, causality may be a challenge; hence, future studies using a more rigorous research design are recommended. While the coronavirus anxiety scale has been found valid and reliable to measure dysfunctional levels of anxiety, measures to clinically and accurately diagnose coronaphobia among nurses are imperative. Future studies should be undertaken considering other factors not included in the current study (e.g., self-efficacy, locus of control, personality) which could potentially affect the occurrence of dysfunctional anxiety levels.

    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 10.1111/phn.12841
  3. Version published to 10.1101/2020.10.18.20214692v1 on medRxiv