Citation

Bari, Md Akramul and Ahmad, Zauwiyah and Ab. Aziz, Kamarulzaman (2026) Strengthening Treatment Adherence in Clubfoot Management Through AI-Supported Co-Production: A Conceptual Perspective. In: 2nd IEEE International Conference on Quantum Photonics, Artificial Intelligence and Networking, QPAIN 2026, 16 April 2026 - 18 April 2026, Chittagong.

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Abstract

Congenital talipes equinovarus (clubfoot) stays as one of the main reasons of preventable childhood infirmity in many low- and middle-income countries, it is because of delayed diagnosis, poor care pathways, and poor long-term treatment adherence. The Ponseti method is widely known as the gold standard for non-surgical treatment; its success significantly relays on the sustained caregiver engagement and continuous brace rules compliance, which stay challenging in resource-constrained and rural settings. In response to these research gaps, this study proposes an integrated framework that combines artificial intelligenceenabled digital health technologies with co-production principles to strengthen treatment adherence in clubfoot management. Drawing on the concept of co-production, patient engagement, and human– AI collaboration in healthcare, the current study develops a multistakeholder conceptual model where caregivers, clinicians, and practitioners collaboratively design and implement AI-supported treatment pathways. The framework conceptualizes the role of intelligent mobile health systems in facilitating early detection, personalized educational guidance, real-time adherence monitoring, and constant feedback between families and healthcare contributors. By embedding AI tools within a co-produced care ecosystem, the model aims to improve trust, accountability, and shared responsibility through the treatment duration. This paper contributes to the literature by advancing a theoretically grounded and practiceoriented model that integrates digital innovation with participatory healthcare delivery. The proposed framework offers a scalable approach for improving adherence-driven outcomes in clubfoot treatment and provides conceptual guidance for the design of AIenabled co-production tactics in pediatric orthopedics and other chronic childhood circumstances. The paper will suggest suitable research designs for future work.

Item Type:	Conference or Workshop Item (Paper)
Uncontrolled Keywords:	Artificial intelligence in healthcare
Subjects:	R Medicine > R Medicine (General) > R858-859.7 Computer applications to medicine. Medical informatics
Divisions:	Faculty of Business (FOB)
Depositing User:	Ms Rosnani Abd Wahab
Date Deposited:	31 Jul 2026 06:53
Last Modified:	31 Jul 2026 06:53
URII:	http://shdl.mmu.edu.my/id/eprint/16422

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