Using Mechanical Turk to Study Clinical Populations
Abstract
Although participants with psychiatric symptoms, specific risk factors, or rare demographic characteristics can be difficult to identify and recruit for participation in research, participants with these characteristics are crucial for research in the social, behavioral, and clinical sciences. Online research in general and crowdsourcing software in particular may offer a solution. However, no research to date has examined the utility of crowdsourcing software for conducting research on psychopathology. In the current study, we examined the prevalence of several psychiatric disorders and related problems, as well as the reliability and validity of participant reports on these domains, among users of Amazon’s Mechanical Turk. Findings suggest that crowdsourcing software offers several advantages for clinical research while providing insight into potential problems, such as misrepresentation, that researchers should address when collecting data online.
