Understanding User Perceptions of Personalized Feedback in Digital Health Tools

Abstract

This study aimed to explore how users perceive and emotionally respond to personalized feedback in digital health tools. A qualitative research design was employed using semi-structured interviews with 20 adult participants from Mexico who had experience using digital health tools with personalized feedback features. Participants were selected through purposive sampling, and data collection continued until theoretical saturation was achieved. Interviews were audio-recorded, transcribed, and thematically analyzed using NVivo 14. The coding process followed three stages: open coding, axial coding, and selective coding, ensuring a comprehensive understanding of user experiences and interpretive patterns. Analysis revealed four core themes: perceived effectiveness of feedback, personal relevance and cultural fit, communication and design quality, and trust, privacy, and emotional resonance. Participants valued motivational and positively framed feedback that aligned with their health goals, but criticized messages that were overly generic, intrusive, or lacking emotional intelligence. Users expressed a preference for customizable settings, culturally and linguistically appropriate messages, and visual formats such as graphs or summaries. Trust in the system was strongly influenced by the tone, clarity, and perceived transparency of the feedback, while overly frequent or robotic messages sometimes triggered negative emotional reactions or disengagement. User perceptions of personalized feedback in digital health tools are multifaceted and shaped by emotional, cultural, cognitive, and technological factors. For feedback systems to be effective and engaging, they must be adaptive, empathetic, and contextually relevant. Incorporating user control, emotional intelligence, and cultural sensitivity into feedback design can enhance trust, increase adherence, and ultimately improve digital health outcomes.