Sickness presenteeism: Are we sure about what we are studying? A research based on a literature review and an empirical illustration

Am J Ind Med. 2019 Jul;62(7):580-589. doi: 10.1002/ajim.22982. Epub 2019 May 10.

Abstract

Background: There has been an increasing interest in studying sickness presenteeism (SP). An ever-increasing amount of scientific literature is published using this term, yet there appears to be considerable heterogeneity in how it is assessed, which could result in substantial differences in the definition and interpretation of the phenomenon really being studied. We aim to discuss what really is being studied, depending on how the phenomenon is operationalized, measured, and analyzed.

Methods: A study based on a literature review and an empirical illustration using data of the third Spanish Psychosocial Risks Survey (2016).

Results: Differences are observed based on the population in which SP is measured, the cut-off points used to define a worker as presenteeist, the reasons for an SP episode and even an analysis of the phenomenon treated as a count or as a dichotomous.

Conclusions: Without being completely exclusive, it seems that restricting the population of analysis to only those workers who consider that they should not have gone to work due to their health, and/or establishing low cut-off points to define someone as presenteeist, would more clearly delimit the study of SP to the exercise of a right to sick leave. In contrast, working with the entire population or using high cut-off points appears to relate the study of SP more with health status and less with the exercise of rights. On the other hand, taking the reasons for SP into account would probably help to improve interpretation of the phenomenon.

Keywords: construct; operationalization; sickness presenteeism.

Publication types

  • Research Support, Non-U.S. Gov't
  • Review

MeSH terms

  • Adult
  • Female
  • Health Status
  • Humans
  • Male
  • Middle Aged
  • Occupational Health / statistics & numerical data*
  • Presenteeism / statistics & numerical data*
  • Research Design
  • Sick Leave / statistics & numerical data*
  • Terminology as Topic