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Hawthorne effect

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The Hawthorne Effect, in experimental testing, is subject's behavioral change if the subject is aware of being observed. It sometimes leads to fallacious conclusions involving magical thinking if it is not carefully accounted for. It is strongly related to the confirmation bias. This effect highlights the importance of double-blinded trials. While the Hawthorne effect is demonstrably present in the short term, it tends to deteriorate over time as the subject becomes habituated to the presence of the observer. It is named after a series of experiments at a Western Electric factory at Hawthorne, Chicago in the late 1920s and early 30s, which showed the effect.[1] More recent studies have confirmed it.[2]

As an example, if a researcher were to visit a non-technological people living in a remote part of the world, obtain permission to live with them and learn about their style of life and immediately begins documenting, there is a strong possibility he or she may produce an inaccurate representation. A far better approach would be to first live with the group for some significant length of time in order to allow its members to get used to his or her presence, and only then begin.

One real-world example of the Hawthorne Effect is displayed, possibly, in response to high-stakes educational testing. School systems commonly respond to testing under No Child Left Behind by taking measures that improve schools' performance on standardized tests (e.g. selective retention of students in critical years, limited effort to deter low-performing students from dropping out, reclassification of students as special-needs) without necessarily improving their educational success. (In general terms, it is usually much easier to manipulate — "game," if you prefer — statistics that represent reality than it is to change the underlying reality itself.)


  1. The Hawthorne effect, The Economist, Nov 3, 2008
  2. Systematic review of the Hawthorne effect: New concepts are needed to study research participation effects, Jim McCambridge et al, J Clin Epidemiol. 2014 Mar; 67(3): 267–277.