Healthy user bias

Summary

The healthy user bias or healthy worker bias is a bias that can damage the validity of epidemiologic studies testing the efficacy of particular therapies or interventions.

Specifically, it is a sampling bias or selection bias: the kind of subjects that voluntarily enroll in a clinical trial and actually follow the experimental regimen are not representative of the general population. People who volunteer for a study can be expected, on average, to be healthier than people who don't volunteer, as they are concerned for their health and are predisposed to follow medical advice,[1] both factors that would aid one's health. In a sense, being healthy or active about one's health is a precondition for becoming a subject of the study, an effect that can appear under other conditions such as studying particular groups of workers. For example, someone in ill health is unlikely to have a job as manual laborer. As a result, studies of manual laborers are studies of people who are currently healthy enough to engage in manual labor, rather than studies of people who would do manual labor if they were healthy enough.

References

  1. ^ Shrank, William H.; Patrick, Amanda R.; Alan Brookhart, M. (May 2011). "Healthy User and Related Biases in Observational Studies of Preventive Interventions: A Primer for Physicians". Journal of General Internal Medicine. 26 (5): 546–550. doi:10.1007/s11606-010-1609-1. ISSN 0884-8734. PMC 3077477. PMID 21203857.

Further reading

  • Li, C. -Y.; Sung, F. -C. (1999). "A review of the healthy worker effect in occupational epidemiology". Occupational Medicine. 49 (4): 225–9. doi:10.1093/occmed/49.4.225. PMID 10474913.
  • Fornalski, K. W.; Dobrzyński, L. (2010). "The Healthy Worker Effect and Nuclear Industry Workers". Dose-Response. 8 (2): 125–147. doi:10.2203/dose-response.09-019.Fornalski. PMC 2889508. PMID 20585442.
  • Tabuchi T., Nakayama T., Fukushima W., Matsunaga I., Ohfuji S., Kondo K., Oshima A. (2015). "Determinants of participation in prostate cancer screening: A simple analytical framework to account for healthy‐user bias". Cancer Science. 106 (1): 108–114. doi:10.1111/cas.12561. PMC 4317786. PMID 25456306.CS1 maint: multiple names: authors list (link)

External links

  • "Do We Really Know What Makes Us Healthy?"