Evidence map›Paper›PMID 34094883›Full record

ArticleInternet interventions2021

Liar! Liar! Identifying eligibility fraud by applicants in digital health research.

Jillian V Glazer, Kirsten MacDonnell, Christina Frederick, Karen Ingersoll, Lee M Ritterband

Open access · goldAbstract read
In one paragraph

Article in Internet interventions, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 51 papers.

0numbers the graph read from it
0cells of the map it votes in
51citing papers in PubMed
8.0field-weighted citation impact, top 2% of its field
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

51 citing papers in PubMed, 95 citations in OpenAlex.

  1. Trial
  2. Trial
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  5. Caregivers' Internet-Delivered Insomnia Intervention Engagement and Benefit: SHUTi-CARE Trial Primary Quantitative Analysis.Annals of behavioral medicine : a publication of the Society of Behavioral Medicine · 2024
    Trial
  6. Trial
  7. Trial
  8. Article
  9. Article
  10. Optimizing participation in digital health studies: understanding appointment attendance.Journal of the American Medical Informatics Association : JAMIA · 2026
    Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Observational
  16. Article
  17. Article
  18. Article
  19. Article
  20. I have been scammed in my qualitative research.Research integrity and peer review · 2025
    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

5 authors at 2 institutions in 1 country.

Jillian V GlazerUniversity of Virginia School of Medicine, Center for Behavioral Health & Technology, Department of Psychiatry & Neurobehavioral Sciences, 560 Ray C Hunt Dr, Charlottesville 22903, VA, USA.
Kirsten MacDonnellUniversity of Virginia School of Medicine, Center for Behavioral Health & Technology, Department of Psychiatry & Neurobehavioral Sciences, 560 Ray C Hunt Dr, Charlottesville 22903, VA, USA.
Christina FrederickUniversity of Virginia School of Medicine, Center for Behavioral Health & Technology, Department of Psychiatry & Neurobehavioral Sciences, 560 Ray C Hunt Dr, Charlottesville 22903, VA, USA.
Karen IngersollUniversity of Virginia School of Medicine, Center for Behavioral Health & Technology, Department of Psychiatry & Neurobehavioral Sciences, 560 Ray C Hunt Dr, Charlottesville 22903, VA, USA.
Lee M RitterbandUniversity of Virginia School of Medicine, Center for Behavioral Health & Technology, Department of Psychiatry & Neurobehavioral Sciences, 560 Ray C Hunt Dr, Charlottesville 22903, VA, USA.
University of Virginia · USIvy Foundation · US

Funding

An Insomnia Internet Intervention for Older AdultsR01AG047885 · NIA · UNIVERSITY OF VIRGINIA · PI RITTERBAND, LEE M · 2015 to 2019
$2.6M
NIA NIH HHS R01 AG047885
6 · The paper itself

Abstract

Online studies enable researchers to recruit large, diverse samples, but the nature of these studies provides an opportunity for applicants to misrepresent themselves to increase the likelihood of meeting eligibility criteria for a trial, particularly those that provide financial incentives. This study describes rates of fraudulent applications to an online intervention trial of an Internet intervention for insomnia among older adults (ages ≥55). Applicants were recruited using traditional (e.g., flyers, health providers), online (e.g., Craigslist, Internet searches), and social media (e.g., Facebook) recruitment methods. Applicants first submitted an interest form that included identifying information (name, date of birth, address). This data was then queried against a national database (TransUnion's TLOxp) to determine the application's verification status. Applications were determined to be verified (i.e., information from interest form matched TLOxp report), potentially fraudulent (i.e., potential discrepancy in provided information on interest form versus TLOxp report), or fraudulent (i.e., confirmed discrepancy). Of 1766 total interest forms received, 125 (7.08%) were determined to be fraudulent. Enrollment attempts that were fraudulent were detected among 12.22% of applicants who reported learning of the study through online, 7.04% through social media, 4.58% through traditional, and 4.27% through other methods. Researchers conducting online trials should take precautions, as applicants may provide fraudulent information to gain access to their studies. Reviewing all applications and verifying the identities and eligibility of participants is critical to the integrity of online research trials.

Indexed as

Digital researchFraudIdentity verificationInternet interventionRecruitment

Identifiers

PMID34094883
PMCPMC8164029
OpenAlexW3161471565

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

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.