To Deceive or Self-Deceive?
Framing Language to Discourage Deception in Diabetes Lifestyle Management Systems
M. Mădăraș (TU Delft - Electrical Engineering, Mathematics and Computer Science)
Catholijn Jonker – Mentor (TU Delft - Interactive Intelligence)
J.D. Top – Mentor (Rijksuniversiteit Groningen)
Avishek Anand – Graduation committee member (TU Delft - Web Information Systems)
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Abstract
Deceptive self-reporting in diabetes lifestyle management (DLM) systems limits their ability to offer meaningful and accurate support. Deception can function as a self-protective mechanism, driven by factors such as low self-esteem or the desire to protect self-image. This research builds on CHIP, a chatbot-based DLM prototype, to explore whether the language framing of its responses can influence the psychological determinants of deception. Two framing strategies, empathic and affirming, were implemented and evaluated through a pilot user study, which offers insights for refining the intervention and experimental design in future research.