Background: Decentralized clinical trials (DCT), digital survey methodologies, and health monitoring technologies create the potential to reduce study participant burden as well as enhance sample diversity and enrollment pace. However, fraudulent participant activity poses a significant threat to study validity and data integrity.
Purpose: This study quantifies fraudulent attempts at participation in a DCT of a mobile mental health intervention for problematic substance use and discusses methods to prevent and detect fraudulent activity.
Methods: Adults residing in the US reporting problematic substance use were recruited for a fully remote DCT via 2 primary channels: social media advertisements and survey panels. The DCT offered incentives totaling up to $100 for completing assessments over the 12-week study. To prevent and detect fraudulent activity, the research team utilized VPN and proxy detection, checked for duplicate identifiers (e.g., emails, phone numbers, IP Addresses), and compared age and date of birth (DOB) responses across timepoints. Descriptive statistics and group comparisons across the 2 sources of recruitment methodology were utilized to quantify and characterize fraudulent activity.
Results: Of the 2,781 eligible screeners completed, 1,725 (62%) were determined to be fraudulent prior to randomization, detected most commonly by duplicate identifiers (65%) and/or VPN and proxy detection (47%). Of the 258 randomized participants, 51 (20%) were later determined to be fraudulent based upon age and/or DOB mismatch. Notable patterns in fraudulent activity (e.g., 42% of fraudulent screening respondents reported the exact age of 30 years; stylistic formatting of email address accounts) were identified. The fraudulent recruitment rate was higher for social media advertising (85%) than survey panels (26%).
Conclusions: Both social media and survey panel recruitment resulted in high levels of fraudulent activity in a DCT of a mobile mental health intervention. Researchers conducting DCTs and/or online surveys are urged to take several precautions and preventative measures to insulate against fraudulent activity including embedding identity verification procedures in consent processes. Researchers should consider making personal contact with a participant to verify identity as well as remain vigilant for fraudulent activity and its real-time dynamic potential.
Trial registration: NCT04925570.
Keywords: data integrity; decentralized clinical trials; fraudulent data; fraudulent participant detection; mobile health intervention.
Research that is done virtually (i.e., without face-to-face contact) can open up opportunities to participate. However, fully remote research runs the risk of attracting people who misrepresent themselves to gain research payments. The current study was conducted fully remotely and aimed to evaluate an 8-week mobile app for reducing substance use. People were recruited via social media and from online survey panels. The study offered up to $100 for participation. Notably, the research team determined that over 60% of people seeking to join the study were not legitimate. To detect fraud, the research team used tools to identify masked or encrypted internet activity, checked for duplicated emails and phone numbers, and looked for discrepancy in reported age and birthdate. Even after participants were enrolled, another 1 in 5 were later identified as fraudulent. Fraud was especially problematic via social media recruitment channels. The findings highlight the need for stronger safeguards in online research, such as verifying identities during consent and maintaining real-time monitoring throughout the study.
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