(Press-News.org) FOR IMMEDIATE RELEASE
Wednesday, November 5, 2025
Contact:
Jillian McKoy, jpmckoy@bu.edu
Michael Saunders, msaunder@bu.edu
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The rise in virtual research since the COVID-19 pandemic has created opportunities for researchers to expand and diversify clinical trials, but it has also opened up avenues for fraudulent participation in these studies. A new study led by Boston University School of Public Health (BUSPH) researchers directed by Michael Stein, chair and professor of the Department of Health Law, Policy & Management (HLPM) at BUSPH, provides a comprehensive checklist of indicators that researchers can utilize to quickly identify suspicious behavior and prevent fraudulent actors from enrolling in online studies and compromising valuable data.
The most effective way to prevent this fraudulent activity is to implement a combination of automated and manual actions during the prescreening, screening, and enrollment process, according to the report published in the Journal of Medical Internet Research.
In addition to automated fraud detection methods, the study suggests that researchers should utilize a checklist of precautions to spot, along with videoconferencing and photo identification requests from participants during the screening process. These actions can reveal fraudulent actors—who are largely driven by financial gain from research compensation—before the actual enrollment process begins.
“Modest financial remuneration is a cornerstone of most studies, important for recognizing participants’ time and effort, while also helping to boost engagement and retention,” says study corresponding author Kara Magane, senior director of research operations in HLPM at BUSPH. “However, as compensated research opportunities expand in the online setting, so too do opportunities for fraudulent participation, from participants misrepresenting their eligibility or enrolling multiple times, to automated bots attempting to complete online surveys. As online research becomes more prevalent, it is essential for investigators to be vigilant and design their digital studies with fraud prevention in mind.”
Digital recruitment is especially valuable because it allows researchers to collect data among populations that are underrepresented or difficult to reach through traditional in-person methods.
“Online research has lowered barriers to participating in research, particularly for people with stigmatized diagnoses, such as HIV,” says study lead author Robert Siebers, an HLPM research coordinator at BUSPH at the time of the study. “Allowing participants to remain in their own home ensures higher levels of privacy and comfort that in-person research cannot. Without proper guardrails, fraudulent participation can arise due to the ability to more easily misrepresent one’s identity online.”
In the study, the researchers and colleagues from BU’s College of Arts and Sciences, Tufts Medical Center, and the Warren Alpert Medical School of Brown University describe the team’s own experience with fraudulent participants when screening and enrolling people with HIV into two linked online trials: “Integrated Telehealth Intervention to Reduce Chronic Pain” and “Unhealthy Drinking Among People Living With HIV.” The randomized trials were conducted through the Boston ARCH Comorbidity Center in 2023 and 2024. After a research assistant noticed during a videoconference screening that a participant appeared to be wearing a wig and resembled another person who had been interviewed days prior, the team discovered that 10 fraudulent participants had enrolled in the trials, and they quickly disenrolled them at an early stage. The team created a checklist of precautions to refer to during each stage of the selection process moving forward, and was able to detect 37 additional fraudulent participants during the screening process. They evaluated their enrollment protection methods six months later and found no new fraudulent actors participating in their trials.
Some of the suspicious behavior that researchers should look for during the prescreening process include similar patterns in email addresses (such as those that use multiple numbers), zip codes that do not correspond to the participant’s home state, or other details that seem unusually similar, such as the same level of physical activity among multiple participants. During the screening portion, the team says researchers should also investigate participants who enroll multiple times, provide predictable responses or swift answers to questions that typically require thought, or have similar accents or patterns of speech to participants previously identified as fraudulent. In their trials, the team modified the study protocol to allow phone screenings to take place on camera so that they could monitor participants’ appearance and other suspicious behavior, such as muting their microphone frequently after each question.
During baseline interviews on video, the team recommends that researchers ask—but not mandate—that participants show photo identification on the screen.
“Ensuring participant comfort and privacy is of utmost importance for all researchers, but particularly in research that involves stigmatized populations or diagnoses,” Siebers says. “Requesting, but not requiring, a photo ID in our study was a key flexibility that allowed us to be respectful of participant privacy concerns while ensuring we had the opportunity to verify someone’s true identity when needed.” They also did not request electronic copies of IDs, he adds.
Automated methods, such as IP address identification systems and bot detection tools, can also be effective at identifying fraudulent activity in the earliest stages of the selection process, but these methods often require financial or technological resources that may not be available to all researchers.
The team also recommends that researchers coordinate with their institution’s Institutional Review Board (IRB), committees that ensure that human research is ethical and compliant with regulations.
“IRBs and funding agencies can play an important role by recognizing fraud prevention as an integral part of research workflows, particularly for online studies,” Magane says. “They can encourage researchers to include fraud detection and prevention plans in their study protocols, and allocate appropriate resources for these efforts within study budgets. They can also provide clear guidance and support around recognizing and responding to research participation fraud.”
Ultimately, there is no one-size-fits-all approach, and all precautions should be tailored to each study design, the researchers say.
“As a community of researchers, I’m not sure we have a grip on how much virtual research involves fraudulent participants and therefore how much published data might be tainted,” says Stein, senior author author of the study. “What we unexpectedly and unfortunately learned as researchers was that from the moment of planning an online study through the participant recruitment phase, researchers need to be alert to the possibility that bad actors—and I mean that literally—can ruin the reliability of their findings. Fraud protection may need to be described in all published fully virtual studies going forward.”
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About Boston University School of Public Health
Founded in 1976, Boston University School of Public Health is one of the top ten ranked schools of public health in the world. It offers master's- and doctoral-level education in public health. The faculty in six departments conduct policy-changing public health research around the world, with the mission of improving the health of populations—especially the disadvantaged, underserved, and vulnerable—locally and globally.
END
How to identify and prevent fraudulent participants in health research
A new study presents a comprehensive checklist of manual methods that researchers can implement to detect suspicious behavior during the prescreening, screening, and enrollment process for clinical trials
2025-11-05
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[Press-News.org] How to identify and prevent fraudulent participants in health researchA new study presents a comprehensive checklist of manual methods that researchers can implement to detect suspicious behavior during the prescreening, screening, and enrollment process for clinical trials