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.