First place in IAWC 2026

Confronting the challenge of building trust in AI-based medical tools, a team from the Teh Hong Piow Faculty of Business and Finance (THP FBF) rose to the occasion at the 4th International Article Writing Competition (IAWC 2026), and won the first place, along with a cash prize of RM800, and an e-certificate.

The team, comprising PhD student Ms Shanthi Isparan; FBF academic-cum-supervisor Assoc Prof Dr Seow Ai Na, THP FBF academic and research grant principal investigator Ts Dr Chang Jing Jing; and UCSI academic Dr Hew Jun Jie, investigated how trust mediates doctors’ acceptance of AI-based tools in clinical decision-making, a critical issue that holds significant implications for the future of healthcare.

Ms Shanthi said, “I was encouraged to join this competition, and it proved to be an opportunity for me to challenge myself beyond my doctoral research and to test how well I could translate my academic work into impactful, real-world contributions. I feel deeply grateful and honoured. This recognition marked a personal milestone and was also a reflection of the continuous guidance and support I have received throughout my PhD journey. I am also thankful for the transformative experience gained throughout my studies at UTAR. Its strong academic environment, vibrant research culture, and close mentorship have been instrumental in developing my research capabilities, critical thinking, and confidence as an independent scholar.”

Dr Seow enthused, “I recognised this competition as a good platform for my student to nurture her research talent and promote the visibility of impactful scholarly work beyond academia. It is rewarding to see research mentorship translated into meaningful recognition for both the student and the supervisory team. I have been fortunate to work in a supportive academic ecosystem at UTAR that encourages research excellence, collaboration, and student development.”

Dr Chang expressed, “This recognition enhances the visibility and credibility of our research output, and it provides further motivation to expand the scope and impact of our ongoing work. It reflects the strength of our collaborative research efforts and the quality of work produced under the UTARRF project titled ‘Reconceptualising Human-in-the-loop Design for Healthcare Automation,’ which was awarded to us.”

Dr Hew commented, “I’m glad that educational institutions are providing researchers with a strong foundation to strengthen research development, mentorship, and academic collaboration. This award strengthens the relevance of our research and encourages continued cross-institutional collaboration to enhance research impact.”

The award-winning article, titled Understanding Trust as a Mediating Mechanism in AI-Based Medical Tools and Clinical Decision Processes, investigated the factors influencing doctors’ use of AI-based medical tools in clinical decision-making, with trust as a mediating factor grounded in the Unified Theory of Acceptance and Use of Technology (UTAUT). Data were collected from 197 doctors in Selangor and Kuala Lumpur and analysed using PLS-SEM.

The findings showed that performance expectancy, effort expectancy, social influence, and facilitating conditions significantly influence trust in AI tools. Trust, in turn, significantly affects doctors’ engagement with AI-based clinical decision-making. The results also revealed that trust fully mediates the relationship between UTAUT factors and AI engagement. This highlights the importance of trust in encouraging AI adoption in healthcare. Healthcare organisations and AI developers should also focus on transparency, training, institutional support, and clear guidelines to strengthen trust and promote the effective use of AI in clinical practice.

The team also explained, “The study was inspired by the increasing integration of AI-based tools in healthcare and the growing importance of understanding how trust influences doctors’ acceptance and use of these technologies in clinical decision-making. Practically, the findings emphasised that healthcare organisations and AI developers should prioritise trust through transparent algorithms, structured training, institutional support, and clear policies to integrate AI effectively into clinical workflows. Societally, the research contributes to Sustainable Development Goal (SDG) 3: Good Health and Well-Being by supporting improved decision-making and patient care, and SDG 9: Industry, Innovation, and Infrastructure by promoting AI adoption and strengthening healthcare systems.”