Managing and Minimizing Online Survey Questionnaire Fraud: Lessons from the Triple C Project

Abstract

With the increasing sophistication of online survey tools and the necessity of distanced research during the COVID-19 pandemic, the use of online questionnaires for research purposes has proliferated. Still, many researchers undertake online survey research without knowledge of the prevalence and likelihood of experiencing survey questionnaire fraud nor familiarity with measures used to identify fraud once it has occurred. This research note is based on the experience of researchers across four sites who implemented an online survey of families’ experiences with COVID-19 in the U.S. that was subject to substantial fraud. By the end of data collection, over 70% of responses were flagged as fraudulent with duplicate IP addresses and concurrent start/end times representing the most common indicators of fraud observed. We offer lessons learned to illustrate the sophisticated nature of fraud in online research and the importance of multi-pronged strategies to detect and limit online survey questionnaire fraud.

Aasli Abdi Nur

Postdoctoral Research Fellow in Computational Demography

Aasli Abdi Nur, PhD, MPH, is a Postdoctoral Research Fellow in the Department of Sociology at the University of Oxford.