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Main Author: Mohammed Alajlan
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Published: Zenodo 2026
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Online Access:https://doi.org/10.5281/zenodo.20200075
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author Mohammed Alajlan
author_facet Mohammed Alajlan
contents <p class="MsoNormal"><strong><em><span>Recent advances in artificial intelligence (AI) and tele-audiology have transformed hearing healthcare by enabling adaptive sound processing, remote device management, and improved service accessibility. This study evaluates the effectiveness of AI-driven hearing aids and remote audiology services within the Saudi Arabian healthcare context using a mixed-methods approach that integrates technological performance assessment, policy analysis, and user experience evaluation. Primary data were collected through structured questionnaires administered to 45 hearing aid users, supported by expert input from audiologists (N = 7) and healthcare policymakers (N = 5). Descriptive statistical analysis was applied to assess performance improvements and user satisfaction outcomes. The findings indicate that AI-enabled hearing aids achieved an average 38% improvement in speech recognition performance and an 85% user satisfaction rate, compared with 65% satisfaction reported for conventional hearing aids. Policy analysis revealed substantial national progress in tele-audiology adoption; however, implementation gaps of approximately 30% in AI integration and 45% in remote adjustment services were identified. These results demonstrate the practical potential of AI-based hearing technologies to enhance accessibility, usability, and overall hearing healthcare delivery. The study concludes that strengthening policy frameworks, expanding digital infrastructure, and providing targeted professional training are essential for supporting the large-scale adoption of AI-enabled audiological services. These findings contribute to the growing body of evidence supporting the role of intelligent hearing technologies in advancing digital healthcare transformation in Saudi Arabia and comparable healthcare environments.</span></em></strong></p>
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spellingShingle AI-DRIVEN HEARING AIDS AND TELE-AUDIOLOGY IN SAUDI ARABIA: A MIXED-METHODS EVALUATION OF PERFORMANCE, POLICY INTEGRATION, AND USER SATISFACTION
Mohammed Alajlan
AI-Driven Hearing Aids, Remote Audiology, Methodology, Speech Recognition Improvement, Hearing Healthcare Policy, User Satisfaction.
<p class="MsoNormal"><strong><em><span>Recent advances in artificial intelligence (AI) and tele-audiology have transformed hearing healthcare by enabling adaptive sound processing, remote device management, and improved service accessibility. This study evaluates the effectiveness of AI-driven hearing aids and remote audiology services within the Saudi Arabian healthcare context using a mixed-methods approach that integrates technological performance assessment, policy analysis, and user experience evaluation. Primary data were collected through structured questionnaires administered to 45 hearing aid users, supported by expert input from audiologists (N = 7) and healthcare policymakers (N = 5). Descriptive statistical analysis was applied to assess performance improvements and user satisfaction outcomes. The findings indicate that AI-enabled hearing aids achieved an average 38% improvement in speech recognition performance and an 85% user satisfaction rate, compared with 65% satisfaction reported for conventional hearing aids. Policy analysis revealed substantial national progress in tele-audiology adoption; however, implementation gaps of approximately 30% in AI integration and 45% in remote adjustment services were identified. These results demonstrate the practical potential of AI-based hearing technologies to enhance accessibility, usability, and overall hearing healthcare delivery. The study concludes that strengthening policy frameworks, expanding digital infrastructure, and providing targeted professional training are essential for supporting the large-scale adoption of AI-enabled audiological services. These findings contribute to the growing body of evidence supporting the role of intelligent hearing technologies in advancing digital healthcare transformation in Saudi Arabia and comparable healthcare environments.</span></em></strong></p>
title AI-DRIVEN HEARING AIDS AND TELE-AUDIOLOGY IN SAUDI ARABIA: A MIXED-METHODS EVALUATION OF PERFORMANCE, POLICY INTEGRATION, AND USER SATISFACTION
topic AI-Driven Hearing Aids, Remote Audiology, Methodology, Speech Recognition Improvement, Hearing Healthcare Policy, User Satisfaction.
url https://doi.org/10.5281/zenodo.20200075