Self-reported Health Status Differs for Amazon's Mechanical Turk Respondents Compared with Nationally Representative Surveys

Karoline Mortensen, Manuel G. Alcalá, Michael French, Tianyan Hu

Research output: Contribution to journalArticlepeer-review

19 Scopus citations


Background: Amazon's Mechanical Turk (MTurk) platform has become a data source for peer-reviewed academic research publications, with over 24,000 Google Scholar search results. Although well-developed and supportive in other disciplines, the literature in health and medicine comparing results from samples generated on MTurk to gold standard, nationally representative health and medical surveys is beginning to emerge. Objective: To compare the demographic, socioeconomic, and self-reported health status variables in an MTurk sample to those from 2 prominent national probability surveys, including the Medical Expenditure Panel Survey (MEPS) and the Behavioral Risk Factor Surveillance System (BRFSS). Research Design: We analyze weighted and unweighted tabulations of the MTurk, MEPS, and BRFSS. Wald tests identify statistical significance. Measures: Demographic, socioeconomic, and health status variables in an adult MTurk sample collected in 2016 (n=1916), the 2015 MEPS household survey component (n=21,210), and the 2015 BRFSS (n=283,502). Results: Our findings indicate statistically significant differences in the demographic, socioeconomic, and self-perceived health status tabulations in the MTurk sample relative to the unweighted and weighted MEPS and BRFSS. The MTurk sample is more likely to be female (65.8% in MTurk, 50.9% in MEPS, 50.2% in BRFSS), white (80.1% in MTurk, 76.9% in MEPS, and 73.9% in BRFSS), non-Hispanic (91.1%, 82.4%, and 81.4%, respectively), younger, and less likely to report excellent health status (6.8% in MTurk, 28.3% in MEPS, and 20.2% in BRFSS). Conclusions: We find significant differences across variables that warrant hesitation in using MTurk data as a replacement for the gold standard datasets in health services research.

Original languageEnglish (US)
Pages (from-to)211-215
Number of pages5
JournalMedical Care
Issue number3
StatePublished - Jan 1 2018


  • crowdsourcing
  • gold standard dataset
  • MTurk
  • nonprobability samples
  • probability surveys
  • self-perceived health status

ASJC Scopus subject areas

  • Public Health, Environmental and Occupational Health


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