Predictive variables for feelings of sadness and depression while working remotely in Brazil during the COVID-19 pandemic

Work. 2022;72(2):421-429. doi: 10.3233/WOR-210846.

Abstract

Background: Remote work was evidenced in the pandemic and studies in this area increased. Most studies focus on professionals of companies or professors/students in the academic environment. At the same time, non-academic staff, that provide all the support required for the core activities of the institutions (research/teaching/extension activities) have been neglected.

Objective: This article aims to exploratory analyse which variables (interruptions when working remotely (1), health concerns (2) and fear of contracting coronavirus (3), anxiety and concern about professional career (4), frustration to have cancelled plans and missed opportunities (5) and gender (6)) can impact feelings of sadness and depression experienced by non-academic staff of a university working remotely.

Methods: Using a database on behaviour and feelings of non-academic staff from a Brazilian university working remotely during the COVID-19 pandemic, a binary logistic regression model was structured. In an exploratory manner, six independent variables (presented in the previous item) were analysed in terms of their ability to predict the dependent variable (feelings of sadness and depression).

Results: The results presented the prediction power of the independent variables for the dependent variable. The variables regarding concern with their health, increased anxiety and concern about their career presented Odds Ratios of 3.6 (1.4-8.5 -95% C.I.) and 3.3 (2.2-5.0 -95% C.I.), respectively, standing out from the other variables.

Conclusions: These results focus on staff at one institution, but they can contribute to better understand feelings and behaviours experienced by professionals working remotely and provide information for debates on the field of COVID-19-related changes of work.

Keywords: COVID-19; Remote work; feelings and behaviours; pandemic.

MeSH terms

  • Brazil / epidemiology
  • COVID-19* / epidemiology
  • Depression / epidemiology
  • Humans
  • Pandemics
  • Sadness