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Impact of the COVID-19 Pandemic on Teacher Quality of Life: A Longitudinal Study from before and during the Health Crisis.

Pablo A LizanaGustavo Vega-FernadezAlejandro Gómez-BrutonBárbara LeytonLydia Lera
Published in: International journal of environmental research and public health (2021)
Prior to the COVID-19 pandemic, teachers were already reporting a low quality of life (QoL) perception, with a significant impact on mental and physical health due to various stress factors associated with work overload. The objective of this study was to evaluate the QoL impact on Chilean teachers before and during the COVID-19 pandemic. The analysis was performed following a longitudinal design on a sample of 63 Chilean teachers in pre-pandemic and COVID-19 pandemic timeframes. QoL perception, along with teachers' sociodemographic data, was evaluated via the Short-Form 36 Health Survey (SF-36) questionnaire. Sociodemographic variables presented no significant variations in pre-pandemic and pandemic comparisons. QoL, however, showed a significant decrease during the pandemic compared to the pre-pandemic measurement (p < 0.01). In each gender, there were significant differences between pre-pandemic and pandemic timeframes, with a greater impact among women in the mental and physical component summary variables and seven of the eight QoL scales (p < 0.01). Between age categories, people under 45 presented significant differences (p < 0.05) between pre-pandemic and pandemic timeframes in all summary dimensions and measurements. In conclusion, Chilean teachers' QoL perception has been affected by the COVID-19 pandemic. These findings could be related to work overload due to teleworking or feelings of uncertainty, loneliness, and fear that the pandemic and its associated confinements will worsen.
Keyphrases
  • sars cov
  • coronavirus disease
  • mental health
  • public health
  • healthcare
  • physical activity
  • type diabetes
  • metabolic syndrome
  • risk assessment
  • pregnant women
  • adipose tissue
  • machine learning
  • deep learning
  • stress induced