Eating disorder prevalence among Amazon MTurk workers assessed using a rigorous online, self-report anthropometric assessment.

ABSTRACT

Online, anonymous data collection is common and increasingly available to researchers studying eating disorders (ED), particularly since the development of online crowdsourcing platforms. Crowdsourcing for participant recruitment may also be one effective strategy to address ED research disruptions caused by the COVID-19 pandemic. We aimed to (a) develop a rigorous method for assessing self-reported athropometrics; (b) determine if individuals with EDs self-select into MTurk studies assessing eating behaviors; and (c) characterize ED-related psychopathology in an MTurk sample. We recruited 400 US adults to complete an MTurk study assessing ED features. Results did not indicate the presence of a self-selection bias among individuals with EDs; however, 40% of the sample met criteria for a current ED diagnosis, with all diagnoses represented except ARFID, and 18.1% reported currently being in ED treatment. The sample was characterized by higher scores on measures of ED psychopathology compared to extant non-clinical norms. Approximately 66% of the overall sample and 73% of participants with EDs indicated that they have participated in more MTurk studies since the COVID-19 pandemic began. Finally, we identified an alternative approach to assessing self-reported height and weight that appears to reduce error, which we strongly recommend researchers conducting online surveys use. Our findings suggest that individuals with EDs appear to be overrepresented on MTurk and highlight the utility of crowdsourcing using MTurk as an ED data collection alternative during and after the COVID-19 pandemic.