Predictors of return to work with and without restrictions in public workers

PLoS One. 2019 Jan 17;14(1):e0210392. doi: 10.1371/journal.pone.0210392. eCollection 2019.

Abstract

Background: Sick leaves are important events for both the worker and the employer. Many factors are related with sick leaves and depending on the factors the worker could perform a successful return to work. In this sense, the objective of this study is to identify those factors associated with return to work after sick leaves in a group of public workers in Brazil.

Methods: A case-control study of return to work after sick leaves in a university campus from 2010 to 2015. Logistic regression models were adjusted for two different response variables: return to work with and without restrictions. A digital database was created and completed with data from manual sources.

Results: A computerised database has been created, based on manual records, which has allowed us to identify labour and non-labour factors associated with the return to work after a sick leave and the possible functional readaptation, with or without restrictions, in public workers. Age at the beginning of the process, number of sick leaves, those of more than 16 days, average duration (total time of sick leaves / number of medical records), and mid-level healthcare positions were associated with return to work without restrictions. In the model of return to work with restrictions, the age of hiring by the university, the number of sick leaves, those of more than 16 days, and mid-level healthcare positions, both rural work and operational positions, were associated to the response variable.

Conclusions: This study has allowed us to identify the factors associated with the return to work after a period of sick leave in a large group of public workers. However, more research is needed on the mental disorders that cause sick leaves, their evaluation and the handling of these situations.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Absenteeism
  • Adult
  • Brazil
  • Case-Control Studies
  • Databases, Factual
  • Decision Making
  • Employment / statistics & numerical data
  • Female
  • Humans
  • Logistic Models
  • Male
  • Middle Aged
  • Return to Work / statistics & numerical data*
  • Sick Leave / statistics & numerical data*
  • Time Factors
  • Universities
  • Work Capacity Evaluation
  • Young Adult

Grants and funding

Dr. Adriano Dias received a fund for research of the São Paulo Research Foundation (Fundação de Amparo à Pesquisa do Estado de São Paulo - FAPESP), process 2016-23096-1 (http://internet.aquila.fapesp.br/agilis/). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.