Paper Number
ECIS2025-1051
Paper Type
CRP
Abstract
Chatbots are being introduced to fill the gap between consultations, with the motivation of supporting adherence to treatment, especially in the case of chronic diseases. Such a task requires chatbots to have a persuasive ability to influence patient attitudes or behaviour, which is achievable through the advancement of Large Language Models (LLMs). By means of prompting engineering, we aim to accomplish the design goal of persuasive chatbots powered by LLMs that can systematically apply persuasion strategies and dynamically adapt such strategies to the user. We have converted well-founded persuasion strategies into guidelines for prompt crafting to enhance the persuasiveness of LLM-based chatbots. This paper contributes to the design of persuasive chatbots by providing a list of guidance on prompt crafting, meta-prompts, and a proof-of-concept of the developed guidance from a digital health application. This paper also initiates the discourse on prompt guidance as a new type of design artefact within Design Science Research (DSR).
Recommended Citation
Wu, Wenyuan; Dolata, Mateusz; de Spindler, Alexandre; and Schwabe, Gerhard, "Persuasive Prompting: The Case of Digital Health" (2025). ECIS 2025 Proceedings. 10.
https://aisel.aisnet.org/ecis2025/health_it/health_it/10
Persuasive Prompting: The Case of Digital Health
Chatbots are being introduced to fill the gap between consultations, with the motivation of supporting adherence to treatment, especially in the case of chronic diseases. Such a task requires chatbots to have a persuasive ability to influence patient attitudes or behaviour, which is achievable through the advancement of Large Language Models (LLMs). By means of prompting engineering, we aim to accomplish the design goal of persuasive chatbots powered by LLMs that can systematically apply persuasion strategies and dynamically adapt such strategies to the user. We have converted well-founded persuasion strategies into guidelines for prompt crafting to enhance the persuasiveness of LLM-based chatbots. This paper contributes to the design of persuasive chatbots by providing a list of guidance on prompt crafting, meta-prompts, and a proof-of-concept of the developed guidance from a digital health application. This paper also initiates the discourse on prompt guidance as a new type of design artefact within Design Science Research (DSR).
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