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Allostatic load and physiological responses to work stress: an integrative review.

John Camillo GarciaAníbal Arteaga-Noriega
Published in: Revista brasileira de medicina do trabalho : publicacao oficial da Associacao Nacional de Medicina do Trabalho-ANAMT (2024)
Assessing the allostatic load of workers in the context of COVID -19 is of vital importance to elucidate the physiological responses to social and work stress. This is an integrative review of the literature including seven established steps: 1) identification of the topic and the guiding question; 2) definition of MeSH terms and search equations; 3) search in databases following defined criteria; 4) data collection according to inclusion criteria; 5) evaluation of the studies included in the integrative review; 6) discussion of results; and 7) presentation of the review/synthesis of knowledge. Seventeen studies were included, of which 15 were cross-sectional observational studies and two were longitudinal studies. Heterogeneity in the measurement of allostatic load was the common denominator of the studies. Allostatic load is mentioned in all of them as a parameter of measurement, but they measured it diferently; therefore, the relationship between burnout, work environment, and allostatic load, although positive in most studies, was highly variable. In conclusion, it is necessary to conduct studies that combine both biological markers and clinimetric tests, trying to standardize the batery of tests of allostatic load, so that the correlation with work stress is significant and reliable. Similarly, allostatic load requires a systemic and interdisciplinary approach, since this condition puts chronic stress on all organs and physiological compensation mechanisms. Therefore, the allostatic load invites to a comprehensive care of people, considering the work, social, psychological, and biological domains.
Keyphrases
  • case control
  • healthcare
  • cross sectional
  • mental health
  • sars cov
  • coronavirus disease
  • single cell
  • electronic health record
  • depressive symptoms
  • network analysis
  • patient reported
  • bioinformatics analysis