Protective Elements of Mental Health Status during the COVID-19 Outbreak in the Portuguese Population

  1. Pedro Silva Moreira
  2. Sónia Ferreira
  3. Beatriz Couto
  4. Mafalda Machado-Sousa
  5. Marcos Fernández
  6. Catarina Raposo-Lima
  7. Nuno Sousa
  8. Maria Picó-Pérez
  9. Pedro Morgado

Reviewed by

Read the full article

Listed in

Log in to save this article

Abstract

The outbreak of COVID-19 might produce dramatic psychological effects on individuals’ lives. In this study, we aimed to explore the elements that may reduce the negative effects on mental health of the quarantine period imposed by most governments during this worldwide crisis. We conducted an online survey to evaluate demographic, lifestyle and mental health variables in a sample of 1280 Portuguese individuals (79.8% females) with an average age of 37 years. We observed that factors related to living conditions, maintaining work either online or in the workplace, frequency of exercise and absence of previous psychological or physic disorders are protective features of psychological well-being (anxiety, depression, stress and obsessive-compulsive symptoms). Finally, the individuals previously receiving psychotherapeutic support exhibited better psychological indicators if they did not interrupt the process as a consequence of the outbreak. Our results indicate that the practice of physical exercise, reduced consumption of COVID-19 information and the implementation of remote mental healthcare measures might prevent larger impacts on mental health during the COVID-19 outbreak.

Article activity feed

  1. Version published to 10.3390/ijerph18041910
  2. ScreenIT

    SciScore for 10.1101/2020.04.28.20080671: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIACUC: Ethical approval was obtained from the Ethical Committee for Life Sciences of University of Minho (Braga, Portugal).
    Consent: Electronic informed consent was obtained from all the participants in which study goals were comprehensively explained.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    The visualization of the regression models was produced with the sjPlot package.
    sjPlot
    suggested: None

    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: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    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.

  3. Version published to 10.1101/2020.04.28.20080671v1 on medRxiv