Evidence map›Paper›PMID 41160082›Full record

ArticleJournal of medical Internet research2025

Lessons Learned Identifying and Controlling Fraudulent Participation in Online Randomized Trials.

Robert Siebers, Kara M Magane, Hattie Slayton, Skylar Karzhevsky, Tibor P Palfai, Ana M Abrantes, Lisa M Quintiliani, Michael D Stein

Abstract read
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Robert SiebersSchool of Public Health, Boston University, Boston, MA, United States.ORCID https://orcid.org/0009-0001-2920-6905
Kara M MaganeSchool of Public Health, Boston University, Boston, MA, United States.ORCID https://orcid.org/0000-0001-8930-8949
Hattie SlaytonSchool of Public Health, Boston University, Boston, MA, United States.ORCID https://orcid.org/0009-0007-6767-6215
Skylar KarzhevskySchool of Public Health, Boston University, Boston, MA, United States.ORCID https://orcid.org/0009-0007-5240-1913
Tibor P PalfaiDepartment of Psychological and Brain Sciences, Boston University, Boston, MA, United States.ORCID https://orcid.org/0000-0002-3334-5203
Ana M AbrantesDepartment of Psychiatry and Human Behavior, Alpert Medical School, Brown University, Providence, RI, United States.ORCID https://orcid.org/0000-0001-6854-140X
Lisa M QuintilianiDepartment of Medicine, Tufts University, Tufts Medical Center, Boston, MA, United States.ORCID https://orcid.org/0000-0002-3328-6768
Michael D SteinSchool of Public Health, Boston University, Boston, MA, United States.ORCID https://orcid.org/0000-0002-2466-5192

Funding

Integrated telehealth intervention to reduce chronic pain and unhealthy drinking among people living with HIVP01AA029546 · NIAAA · BOSTON UNIVERSITY MEDICAL CAMPUS · PI SAITZ, RICHARD · 2021 to 2025
$7.4M
NIAAA NIH HHS P01 AA029546
6 · The paper itself

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

FraudInternetRandomized Controlled Trials as TopicHumansPatient Selectionclinical trials as topicfraudfraud detection in clinical researchfraudulent research participationHIVvirtual clinical trials

Identifiers

PMID41160082
PMCPMC12612639

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

None linked

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.