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P262 Overcommitment at work is associated with long term sickness absence due to anxiety disorders
  1. Frida Fischer1,
  2. João Silvestre da Silva Junior,
  3. Rosane Härter Griep1,2,3
  1. 1School of Public Health, University of São Paulo, São Paulo, Brazil
  2. 2Brazilian National Social Security Institute, São Paulo, Brazil
  3. 3Oswaldo Cruz Foundation, Rio De Janeiro, Brazil


Objective To evaluate the association between psychosocial factors at work and workers on long term sickness absence due to depression or anxiety disorders.

Methods A cross-sectional study was conducted in São Paulo, Brazil in 2014. Participants were 160 workers claiming for a social security benefit due to mental sickness and out of work for more than 15 days. Diagnoses were defined according to the report of medical experts who evaluate the claim for benefit. The participants answered a comprehensive questionnaire on sociodemographics and occupational features. Multiple logistic regressions were built to evaluate the association between anxiety/depression and ERI dimensions.

Results Most participants were women (74.4%), mean age of 36.1 years (SD + 9.3), 11 or more years of education (83.1%), diagnosed as depression (66.2%), perception of ERI at work (58.8%) and low overcommitment (62.5%). The final model showed the association between disabling anxiety and high perception on overcommitment at work (OR 2.14; 95% CI: 1.03–4.43) when adjusted by sex, age and education.

Conclusion We observed that overcommitment is a significant variable associated to disabling anxiety when compared to workers with long absence due to depression. However, effort-reward imbalance didn´t provide a statistical influence on both studied mental disorders. A mental health program focused in prevent sickness absence due to anxiety disorders should include improvements on psychosocial factors at work related to individual intrinsic efforts, as overcommitment. Funding sources: The Brazilian National Council of Scientific and Technological Development (CNPq) (grant #442051/2014-0), and Brazilian National Social Security Institute (INSS).

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