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Stakeholder perspectives on AI-assisted pain assessment in pediatrics: A qualitative study of shared needs and
Ziyang Wang1, Jinjiu Hu1, Xianlan Zheng1
1Department of Nursing, Children's Hospital of Chongqing Medical University, National Clinical Research Center for Children and Adolescents' Health and Diseases, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Child Neurodevelopment and Cognitive Disorders, Chongqing 400010, China.
Insights
Artificial intelligence (AI) can improve pediatric pain assessment by providing objective monitoring. However, successful implementation requires integrating AI into workflows and building trust, addressing varied stakeholder needs for clinical support, empowerment, and communication.
Area of Science:
- Pediatric healthcare technology
- Artificial intelligence in medicine
- Pain management innovations
Background:
- Pediatric pain is often under-assessed and undertreated, posing a significant clinical challenge.
- Artificial intelligence (AI) integration in healthcare is growing, but its application in pediatric pain management is limited.
- Understanding stakeholder perceptions is vital for developing effective and ethical AI solutions for pediatric pain assessment.
Purpose of the Study:
- To explore the needs, implementation priorities, and barriers related to AI-based pain assessment in pediatric care.
- To gather insights from children, family caregivers, and medical staff on AI adoption in pain management.
Main Methods:
- A qualitative study involving 35 participants (11 children, 12 family caregivers, 12 medical staff) from September to October 2025.
- Individual interviews were conducted, guided by the Technology Acceptance Model.
- Thematic analysis was used to analyze interview data.
Main Results:
- All stakeholder groups recognized AI's value for objective, continuous pain monitoring.
- Divergent priorities emerged: medical staff sought clinical decision support, caregivers desired empowerment, and children focused on communication and emotional support.
- Key barriers included workload and integration challenges; willingness to use AI depended on proven accuracy, workflow compatibility, and safety.
Conclusions:
- Significant disparities exist in stakeholder priorities for AI in pediatric pain care.
- AI should augment, not replace, clinical judgment, with successful implementation dependent on seamless workflow integration and trust.
- Findings provide guidance for translating AI tools into practice to improve pain assessment accuracy and enhance pediatric pain care quality and equity.
Abstract:
Pain management remains a significant challenge in pediatric care, where pain is frequently under-assessed and undertreated. Artificial intelligence is increasingly integrated into healthcare, yet its practical implementation in pediatric pain management remains limited. A systematic understanding of stakeholder perceptions is crucial for designing ethically sound, effective, and sustainable AI‑driven solutions in this sensitive domain. This study aimed to explore stakeholder needs, implementation priorities, and barriers regarding AI‑based pain assessment in pediatric care. Individual interviews guided by the Technology Acceptance Model were conducted from September to October 2025 with 35 participants: 11 children, 12 family caregivers, and 12 medical staff. Data were analyzed using a thematic analysis approach. All groups identified the core value of AI as providing objective, continuous monitoring to counter episodic human assessment. Priorities diverged: medical staff emphasized clinical decision support; family caregivers valued empowerment via real‑time information; children sought communication facilitation and emotional support. A consensus held that AI should aid, not replace, clinical judgment. Key adoption barriers included workload and integration challenges, with willingness to use hinging on proven accuracy, workflow compatibility, and safety. This study reveals significant disparities in stakeholder priorities for AI in pediatric pain care. Although all groups endorse AI as a clinical aid, its successful implementation hinges on seamless workflow integration and establishing trust. These findings provide stakeholder‑informed guidance to translate AI tools into clinical practice, with the goal of improving pain assessment accuracy, reducing under‑assessment, and enhancing the quality and equity of pediatric pain management. PERSPECTIVE: These findings offer critical clinical guidance for implementing AI tools that align with stakeholder needs, ultimately enhancing pain recognition, supporting timely interventions, and advancing person-centered pediatric pain care.
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