ArticleJournal of medical Internet research2025
Lessons Learned Identifying and Controlling Fraudulent Participation in Online Randomized Trials.
Article in Journal of medical Internet research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- A US-Based National Virtual Cohort of People Living With HIV at Risk for Viral Nonsuppression: Protocol for the EPI-LoVE Prospective Cohort Study.JMIR research protocols · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
Abstract
Virtually conducted clinical trials have become an important tool for improving access to research. Online research gives rise to new avenues for potentially fraudulent actors to participate in studies to achieve monetary gain. We describe our experience of uncovering and removing fraudulent participants from a virtual research study and our methods to prevent fraudulent participants in the future. Fraudulent participation in the 2 linked online clinical trials was first uncovered in 2023, prompting our investigation and identification of additional fraudulent participants (falsified identity or information to meet eligibility criteria) who successfully enrolled in these trials. Our study team categorized indicators of suspicious activity at prescreening, screening, and baseline stages of study participation and implemented a manual checklist method to prevent fraudulent participation. We evaluate the effectiveness of our fraud prevention methods 6 months after the initial breach of the trials. Before initial detection, 10 fraudulent participants successfully enrolled in our trials. Following the implementation of new fraud prevention measures, 37 individuals were identified as fraudulent at the screening stage, and no new fraudulent participants were enrolled. We provide a comprehensive list of suspicious behaviors that may suggest the virtual research intrusion of persons using fake identities. For online clinical studies, manual methods of fraud prevention, used in conjunction with automated prevention methods, can equip researchers to detect evolving patterns of attempted fraudulent enrollment.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.