Exploring Patients’ Experiences with AI-Powered Telemedicine: Trust, Adaptation, and Care Dynamics
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Abstract
Objective: The rapid advancement of digital health systems has transformed healthcare delivery, yet little is known about how patients construct meaning from their interactions with AI-powered telemedicine. Existing research often emphasizes technical performance and clinical efficiency, while patients’ subjective experiences—particularly regarding trust, emotional adaptation, and relational dynamics—remain underexplored. Method: This study adopts an interpretative phenomenological approach (IPA), using semi-structured, in-depth interviews with 15 participants who had engaged in AI-assisted consultations. Thematic synthesis was employed to analyze transcripts and identify key patterns of meaning. Results: The analysis reveals three central themes: (1) trust and skepticism toward AI-based diagnoses, (2) emotional adaptation to digital healthcare, and (3) shifting patient–provider relationships. Patients described a constant negotiation between technological efficiency and human empathy, underscoring the importance of personalized care and transparent algorithmic decision-making. Conclusion: These findings deepen understanding of patient experiences in digital healthcare environments and emphasize the need for patient-centered design in AI-powered telemedicine. The study demonstrates that technological innovation must be aligned with human-centered values to foster trust, improve adoption, and enhance the quality of digital health services.
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