Fear of COVID-19 among nurses in mobile COVID-19 testing units in Greece

  1. Petros Galanis
  2. Emmanouela Petrogianni
  3. Irene Vraka
  4. Olympia Konstantakopoulou
  5. Olga Siskou
  6. Angeliki Bilali
  7. Daphne Kaitelidou

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Abstract

Background

Mobile COVID-19 testing units are used worldwide to test quickly and easily individuals for COVID-19.

Aim

To assess the level of fear of COVID-19 among nurses in mobile COVID-19 testing units and compare it with demographic characteristics.

Methods

A cross-sectional study was conducted during November and December 2020. Study population included 57 nurses working in mobile COVID-19 testing units in Attica, Greece. We collected demographic data from the nurses, i.e. gender, age, marital status, children, living status (alone or with others), clinical experience, and chronic disease. We used the fear of COVID-19 scale to measure fear of the COVID-19 pandemic.

Results

The mean score on the fear of COVID-19 scale was 14.3. Among nurses, 31.6% experienced elevated fear indicative of presence of anxiety symptoms, while the respective percentages for health anxiety and post-traumatic stress symptomatology were 22.8% and 17.5%. Fear of COVID-19 was not affected by demographic variables. However, fear was higher in females, nurses who had children and nurses who lived with others. Increased clinical experience was related with decreased fear.

Conclusions

Creating a secure work environment for nurses in these units could decrease fear of COVID-19 and increase work performance.

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  1. ScreenIT

    SciScore for 10.1101/2021.07.05.21260037: (What is this?)

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

    Table 1: Rigor

    EthicsConsent: Moreover, all nurses provided informed consent to participate in the study.
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Cell Line AuthenticationAuthentication: In particular, the validated Greek language version of the FCV-19S was used [11].

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Statistical analysis was performed with IBM SPSS Version 21.0.
    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:
    The nature of our study was exploratory and thus had several limitations. First, the sample size was relatively small and our study was performed within one district of Greece. However, all the nurses working in mobile COVID-19 testing units in this district were invited to participate and the response rate was very high. Next, we investigated only a few demographic variables as possible determinants of fear of COVID-19 and further studies should explore other personal and psychological variables. Additionally, we used a standardized and valid instrument to measure fear of COVID-19 but an information bias is still probable. Another limitation is that our study was conducted during November and December 2020 and further research should be carried out since fear of COVID-19 is an evolving issue. Despite these limitations, the results of our study could provide useful information since mobile COVID-19 testing units are used worldwide as another weapon against the COVID-pandemic. Creating a secure work environment for nurses in these units could decrease fear of COVID-19 and increase work performance.

    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 10.1101/2021.07.05.21260037v1 on medRxiv