The ‘Turing Test’ to Reduce Bots and Fraud When Using Online Data Collection Approaches in Nutrition
Virtual, Event
February 4, 2026
1:00 pm – 2:00 pm
Online data collection became a more prominent research approach following restrictions introduced by the COVID-19 pandemic. These methods can be more cost-effective and potentially more efficient compared to in-person data collection, especially within nutrition research where traditional assessments for dietary intake require considerable time and resources.
At the same time, there are new risks with online data collection, such as bots and fraudulent actors. Better understanding and managing novel risks is critical to ensuring data quality. When sound methods are used, online data collection can add significant value by supporting larger sample sizes without compromising data quality control.
In this webinar, speakers will discuss novel approaches to online data collection and risk mitigation, with the specific example of application to an evaluation of a state-wide Supplemental Nutrition Assistance Program (SNAP) fruit and vegetable incentive program.
Speakers:
Marie Latulippe, MS MBA RDN, IAFNS – Moderator
Maya Vadiveloo, PhD, University of Rhode Island
Emily Elenio, MPH, Brown University
Learning Outcomes:
(1) Describe the risks and benefits of online data collection approaches.
(2) Articulate mitigation techniques, considerations, and expertise required for implementation.
(3) Identify patterns of data that are suggestive of bot or fraudulent actor activity.
IAFNS is a Continuing Professional Education (CPE) provider with the Commission on Dietetic Registration (CDR). The Webinar: ‘The ‘Turing Test’ to Reduce Bots and Fraud When Using Online Data Collection Approaches in Nutrition,’ is pending approval to award 1 Continuing Professional Education Unit (CPEU) in accordance with the Commission on Dietetic Registration’s CPEU Prior Approval Program.
This webinar is supported by IAFNS. Contact science@iafns.org with any questions.