To Deceive or Self-Deceive?

Framing Language to Discourage Deception in Diabetes Lifestyle Management Systems

Bachelor Thesis (2025)
Author(s)

M. Mădăraș (TU Delft - Electrical Engineering, Mathematics and Computer Science)

Contributor(s)

Catholijn Jonker – Mentor (TU Delft - Interactive Intelligence)

J.D. Top – Mentor (Rijksuniversiteit Groningen)

Avishek Anand – Graduation committee member (TU Delft - Web Information Systems)

Faculty
Electrical Engineering, Mathematics and Computer Science
More Info
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Publication Year
2025
Language
English
Graduation Date
25-06-2025
Awarding Institution
Delft University of Technology
Project
['CSE3000 Research Project']
Programme
['Computer Science and Engineering']
Faculty
Electrical Engineering, Mathematics and Computer Science
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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.

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