Accessibility settings

Published on in Vol 27 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/78554, first published .
White mask on a laptop keyboard displaying code, symbolizing cyber security and anonymity.

Flagged for Fraud: Lessons From 3 Case Studies on Detecting Inauthentic Participants in Online Research

Flagged for Fraud: Lessons From 3 Case Studies on Detecting Inauthentic Participants in Online Research

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
  2. Hoy L, Dashper K. Fraudulent participation in online qualitative leisure research: a cautionary tale from a dog walking study. Leisure Studies 2026:1 View
  3. Stemmer M, Buck B, Tauscher J, Tsai A, Larsen A, Wedgeworth P, Sparks G, DeVries E, Bishop M, Beaulieu A, Cohen T, Ben-Zeev D. Cost and Data Quality Impact of Fraud Mitigation in Online Research: Framework Application and Evaluation Study. Journal of Medical Internet Research 2026;28:e93951 View
  4. Farash S, Sienkiewicz H, Solomon M, Lynch K. Equitable spam detection and prevention in a community-engaged public health survey. Frontiers in Public Health 2026;14 View
  5. Niles L, Graham L, Prevost S. Fraud in nursing research: lessons learned from two case studies. Nurse Researcher 2026 View