Perceptions, Barriers, and Facilitators of Artificial Intelligence-Based Hearing Rehabilitation among Individuals with Hearing Impairment in Punjab, Pakistan: A Qualitative Study

Abstract

Background: Hearing impairment is a significant global health challenge affecting communication, social participation, and quality of life. Artificial Intelligence (AI)-based hearing rehabilitation technologies provide opportunities for personalized auditory support; however, their implementation depends on user acceptance, accessibility, and contextual experiences. Evidence regarding perceptions of AI-based hearing rehabilitation remains limited, particularly in low- and middle-income settings such as Pakistan. Objective: This study explored perceptions and technology-related experiences of individuals with hearing impairment regarding AI-based hearing rehabilitation technologies, identified barriers and facilitators to adoption, and examined perceived benefits, challenges, and future potential. Methods: A qualitative exploratory study was conducted among 18 individuals with hearing impairment in Punjab, Pakistan, recruited through purposive sampling. Data were collected through semi-structured individual interviews conducted in sign language, with interpreters where required. Interviews were audio-recorded, transcribed verbatim, and analyzed using Braun and Clarke’s reflexive thematic analysis. The Technology Acceptance Model (TAM) guided exploration of perceived usefulness, perceived ease of use, and contextual influences on adoption. Results: Five themes emerged: (1) AI as a promising but unfamiliar pathway toward improved communication; (2) acceptance shaped by usability, learning, and personal readiness; (3) trust, uncertainty, and the importance of human involvement; (4) accessibility realities influencing adoption; and (5) the role of support systems in sustainable rehabilitation. Participants viewed AI as potentially improving communication, independence, and personalized rehabilitation, but identified concerns regarding usability, awareness, affordability, digital readiness, privacy, and professional guidance. Conclusion: AI-based hearing rehabilitation technologies have substantial potential to enhance communication and independence. Equitable implementation requires human-centered, context-specific strategies addressing affordability, training, accessibility, privacy, and continued involvement of audiologists and rehabilitation professionals.