Cost and Data Quality Impact of Fraud Mitigation in Online Research: Framework Application and Evaluation Study - Summary - MDSpire
Coming Soon: Introducing MDSpire News. Learn more
Conexiant’s news site is now MDSpire News. Learn more

Evaluating the Costs and Data Quality Effects of Fraud Prevention in Online Research: Applying a Framework

  • By

  • Maya Stemmer

  • Benjamin Buck

  • Justin Tauscher

  • Angelina Pei-Tzu Tsai

  • Anna Larsen

  • Patrick Wedgeworth

  • Gillian Sparks

  • Ella DeVries

  • Mercedes Bishop

  • Alexa Beaulieu

  • Trevor Cohen

  • Dror Ben-Zeev

  • October 8, 2026

Share

Objective:

The paper applies the configure, assess, triage, corroborate, and hone (CATCH) framework to an ongoing, large study. The framework is intended to mitigate fraudulent participation while balancing data integrity objectives against operational feasibility.

Original Source(s)

Cost and Data Quality Impact of Fraud Mitigation in Online Research: Framework Application and Evaluation Study

  • by Maya Stemmer, Benjamin Buck, Justin Tauscher, Angelina Pei-Tzu Tsai, Anna Larsen, Patrick Wedgeworth, Gillian Sparks, Ella DeVries, Mercedes Bishop, Alexa Beaulieu, Trevor Cohen, Dror Ben-Zeev

  • October 8, 2026

Related Content

Development and validation of the Beliefs in Social Anxiety Scale (BIAS) for Chinese socially anxious adults and adolescents

AI-mediated health information seeking in a university-centered Chinese sample: Information overload, health anxiety, and conditional acceptance of AI-Assisted health communication support

Digital phenotyping reveals discordance between clinical guidelines and patient satisfaction in premenstrual dysphoric disorder