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Uncertainty and Well-Being amongst Homeworkers in the COVID-19 Pandemic: A Longitudinal Study of University Staff

Author

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  • Stephen Wood

    (School of Business, University of Leicester, Brookfield, London Road, Leicester LE2 1RQ, UK)

  • George Michaelides

    (Norwich Business School, University of East Anglia, Norwich NR4 7TJ, UK)

  • Kevin Daniels

    (Norwich Business School, University of East Anglia, Norwich NR4 7TJ, UK)

  • Karen Niven

    (Sheffield University Management School, University of Sheffield, Sheffield S10 1FL, UK)

Abstract

The COVID-19 pandemic heightened uncertainties in people’s lives—and was itself a source of fresh uncertainty. We report a study of homeworkers on whether such uncertainties, and particularly those related to their work environment, are associated with lower levels of well-being and whether this association is exacerbated by prior poor well-being. We focus on five uncertainties surrounding the pandemic and employment—the virus, the job quality, workload, logistics of work lives, and support from the employer. Our empirical tests show that uncertainties around the virus, employer support, and their job quality have the strongest negative associations with well-being. These are based on data collected over three time periods in the first year of the pandemic from a sample of university staff (academics and non-academics) and well-being is measured on two continua, anxiety–contentment and depression–enthusiasm. The effects of uncertainties around workload and logistics are less pronounced, but more apparent among employees with better (not poorer) past well-being, at various times of the recession. The study adds to our understanding of the pandemic and highlights the need to link uncertainty to mental health more than it has in the past.

Suggested Citation

  • Stephen Wood & George Michaelides & Kevin Daniels & Karen Niven, 2022. "Uncertainty and Well-Being amongst Homeworkers in the COVID-19 Pandemic: A Longitudinal Study of University Staff," IJERPH, MDPI, vol. 19(16), pages 1-17, August.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:16:p:10435-:d:894296
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    References listed on IDEAS

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    3. 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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