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Working during a Pandemic between the Risk of Being Infected and/or the Risks Related to Social Distancing: First Validation of the SAPH@W Questionnaire

Author

Listed:
  • Daniela Converso

    (Department of Psychology, University of Turin, 10124 Turin, Italy)

  • Andreina Bruno

    (Department of Education Sciences, University of Genoa, 16128 Genova, Italy)

  • Vincenza Capone

    (Department of Humanities, University of Naples Federico II, 80133 Naples, Italy)

  • Lara Colombo

    (Department of Psychology, University of Turin, 10124 Turin, Italy)

  • Alessandra Falco

    (FISPPA Section of Applied Psychology, University of Padua, 35131 Padua, Italy)

  • Teresa Galanti

    (Department of Psychological, Health and Territory Sciences G. d’Annunzio, University of Chieti-Pescara, 66100 Chieti, Italy)

  • Damiano Girardi

    (FISPPA Section of Applied Psychology, University of Padua, 35131 Padua, Italy)

  • Gloria Guidetti

    (Department of Psychological, Health and Territory Sciences G. d’Annunzio, University of Chieti-Pescara, 66100 Chieti, Italy)

  • Sara Viotti

    (Department of Psychology, University of Turin, 10124 Turin, Italy)

  • Barbara Loera

    (Department of Psychology, University of Turin, 10124 Turin, Italy)

Abstract

Background: The COVID-19 pandemic led the worldwide healthcare system to a severe crisis in which personnel paid the major costs. Many studies were promptly dedicated to the physical and psychological consequences of the COVID-19 exposure among healthcare employees, whereas the research on the other working populations has been substantially ignored. To bridge the current lack of knowledge about safe behaviors related to the risk of COVID-19 contagion at work, the aim of the study was to validate a new tool, the SAPH@W (Safety at Work), to assess workers’ perceptions of safety. Methods: A total of 1085 participants, employed in several organizations sited across areas with different levels of risk of contagion, completed an online questionnaire. To test the SAPH@W validity and measurement invariance, the research sample was randomly divided in two. Results: In the first sub-sample, Confirmatory Factor Analysis demonstrated the adequacy of the SAPH@W factorial structure. In the second sub-sample, multi-group Confirmatory Factor Analysis revealed that the SAPH@W was invariant across gender, ecological risk level, and type of occupation (in-person vs. remote working). Conclusions: The study evidenced the psychometric properties of the SAPH@W, a brief tool to monitor workers’ experiences and safety perceptions regarding the COVID-19 risk in any organisational setting.

Suggested Citation

  • Daniela Converso & Andreina Bruno & Vincenza Capone & Lara Colombo & Alessandra Falco & Teresa Galanti & Damiano Girardi & Gloria Guidetti & Sara Viotti & Barbara Loera, 2021. "Working during a Pandemic between the Risk of Being Infected and/or the Risks Related to Social Distancing: First Validation of the SAPH@W Questionnaire," IJERPH, MDPI, vol. 18(11), pages 1-14, June.
    • Handle: RePEc:gam:jijerp:v:18:y:2021:i:11:p:5986-:d:567783
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    References listed on IDEAS

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    1. Teresa Galanti & Teresa Di Fiore & Stefania Fantinelli & Michela Cortini, 2021. "The Role of Organizational Support in Non-Technical Dimensions of Safety: A Case Study in the Automotive Sector," IJERPH, MDPI, vol. 18(5), pages 1-15, March.
    2. Paula Franklin & Anna Gkiouleka, 2021. "A Scoping Review of Psychosocial Risks to Health Workers during the Covid-19 Pandemic," IJERPH, MDPI, vol. 18(5), pages 1-20, March.
    3. Marco Giovanni Mariani & Michela Vignoli & Rita Chiesa & Francesco Saverio Violante & Dina Guglielmi, 2019. "Improving Safety through Non-Technical Skills in Chemical Plants: The Validity of a Questionnaire for the Self-Assessment of Workers," IJERPH, MDPI, vol. 16(6), pages 1-14, March.
    4. Georges Dionne & Denise Desjardins & Martin Lebeau & Stéphane Messier & André Dascal, 2018. "Health Care Workers’ Risk Perceptions and Willingness to Report for Work during an Influenza Pandemic," Risks, MDPI, vol. 6(1), pages 1-18, February.
    5. Rosseel, Yves, 2012. "lavaan: An R Package for Structural Equation Modeling," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 48(i02).
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