JMIR Publications

ABSTRACT

Background:

Web-based surveys are a cost-effective technique to engage a large population of participants in research projects, including those who were previously difficult to reach due to geographic location, safety and vulnerability. Whilst web-based surveys have many advantages, they can be more susceptible to fraud, especially when a generic invitation link or a financial incentive is offered.

Objective:

This article shares lessons learned from experiences of fraud in four web-based surveys that can inform researchers and ethics committees/Institutional Research Boards (IRBs) about strategies to protect online survey data integrity.

Methods:

Our descriptive multiple case study presents four research projects from Australia and Canada that experienced survey fraud. These web-based surveys recruited patients of, and/or clinicians providing, family planning services. We describe each study’s approach to preventing fraud (primary prevention; e.g. CAPTCHA) and a screening protocol to detect fraudulent responses during data collection (secondary prevention). Once fraud was detected, each study team developed strategies to protect data integrity, in consultation with co-investigators, ethics committees/IRBs, +/- biostatisticians, to remove fraudulent respondents from the dataset (tertiary prevention).

Results:

All studies recruited via a generic survey link and provided remuneration, common risk factors for fraud. Several studies also relied on social media for recruitment. All four studies implemented tertiary fraud detection strategies to identify and remove fraudulent responses and maintain data integrity. Including personal identifiers during data collection provided three of the studies with a more robust option to identify and remove fraudulent respondents. Where personal identifiers could not be used (e.g. to protect the identity of a vulnerable study population) investigators relied on a complex fraud detection algorithm verified by manual team review.

Conclusions:

Commonly used web-based anonymized survey methods, particularly those offering incentives for participation, are at substantial risk for fraud. Across these four studies, robust fraud detection methods were essential to ensure data reliability, with varying strategies such as using personal identifiers, applied based on specific survey contexts. Fraud mitigation criteria explored in this multi case analysis can be adapted to other web-based surveys, survey topics and populations. Implementing the fraud prevention and detection methods within survey design will assist researchers and IRBs to protect data integrity. Clinical Trial: AusCAPPS: ACTRN12622000655741 SmartMom: ClinicalTrials.gov NCT05793944