This paper is in the following e-collection/theme issue:

Review Articles (34) Electronic/Mobile Data Capture, Internet-based Survey & Research Methodology (1008) Quality/Credibility of eHealth Information and Trust Issues (664) Recruitment of Research Participants (382)

Published on in Vol 17 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/70926, first published .
Imposters, Bots, and Other Threats to Data Integrity in Online Research: Scoping Review of the Literature and Recommendations for Best Practices

Imposters, Bots, and Other Threats to Data Integrity in Online Research: Scoping Review of the Literature and Recommendations for Best Practices

Imposters, Bots, and Other Threats to Data Integrity in Online Research: Scoping Review of the Literature and Recommendations for Best Practices

Authors of this article:

Isabella B Strickland1 Author Orcid Image ;   Amy K Ferketich1, 2 Author Orcid Image ;   Alayna P Tackett2, 3 Author Orcid Image ;   Joanne G Patterson1 Author Orcid Image ;   Nicholas J K Breitborde4 Author Orcid Image ;   Jade Davis1 Author Orcid Image ;   Megan Roberts1, 2 Author Orcid Image
Article Authors Cited by (1) Tweetations Metrics

Journals

  1. Stemmer M, Tauscher J, Buck B, Wedgeworth P, Bear Don’t Walk O, Cohen T, Ben-Zeev D. Practical guidance for mitigating fraud in online research: The Configure, Assess, Triage, Corroborate, and Hone (CATCH) framework. DIGITAL HEALTH 2026;12 View