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This study investigates the impact of the Stimulus-Organism-Response (SOR) strategy in AI-based chatbots on enhancing user trust in digital health applications. The SOR model analyzes how chatbot features such as information clarity, response speed, and personalization (stimuli) influence users’ perceptions of ease, comfort, and satisfaction (organism), which then affect trust (response). Using a quantitative survey of 90 active digital health app users in Indonesia, data were analyzed with Structural Equation Modeling (SEM) via SmartPLS. Results show that stimuli significantly affect organisms, and organisms significantly influence trust. Thus, SOR-based chatbot design effectively builds user trust in digital health services.

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SOR Strategy in Using Chat Robots with Artificial Intelligence to Increase User Trust in Digital Health Service Applications

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  • 发表日期：

    2026年

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  • Efa Wakhidatus Solikhah,
  • Fitroh Adhilla

摘要

This study investigates the impact of the Stimulus-Organism-Response (SOR) strategy in AI-based chatbots on enhancing user trust in digital health applications. The SOR model analyzes how chatbot features such as information clarity, response speed, and personalization (stimuli) influence users’ perceptions of ease, comfort, and satisfaction (organism), which then affect trust (response). Using a quantitative survey of 90 active digital health app users in Indonesia, data were analyzed with Structural Equation Modeling (SEM) via SmartPLS. Results show that stimuli significantly affect organisms, and organisms significantly influence trust. Thus, SOR-based chatbot design effectively builds user trust in digital health services.