DefinePK

Abstract

Background: As artificial intelligence (AI) becomes increasingly integrated into healthcare, patient perspectives on trust and acceptance are critical to its successful implementation. Despite technological advancements, there remains limited qualitative insight into how patients evaluate and respond to AI-driven medical decision-making systems, particularly in non-Western settings.
Objective: To explore patient trust and acceptance of AI-driven healthcare services within the sociocultural and clinical context of Islamabad, Pakistan.
Methods: A qualitative study design was employed, utilizing semi-structured in-depth interviews with 32 adult patients exposed to AI-supported healthcare tools. Participants were purposively sampled from both public and private hospitals over an eight-month period. Interviews were transcribed, translated, and analyzed using Braun and Clarke’s thematic analysis framework. Ethical approval was obtained, and informed consent was secured from all participants.
Results: Six major themes emerged: perceived trust in AI systems, comparative reliance on human versus AI decisions, emotional reactions and privacy concerns, transparency and understanding, cultural and religious influences, and willingness for future use. Patients viewed AI as potentially efficient but stressed the need for human oversight, emotional empathy, and system transparency. Trust was conditional and deeply influenced by previous healthcare experiences, data security concerns, and personal belief systems.
Conclusion: Patient trust in AI healthcare systems is multifaceted, shaped by technical, emotional, and cultural factors. Enhancing transparency, ensuring ethical safeguards, and maintaining human oversight are essential to increasing patient acceptance. These insights are crucial for designing AI systems that are both clinically effective and socially acceptable.