Integrating the Caring Life Course Theory and Artificial Intelligence Applications to Enhance Cancer Care Across the Continuum

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OBJECTIVES: With the escalating global burden of cancer, there is an increasing imperative to adopt holistic, person-centered approaches that address the complex and evolving care needs of individuals across the cancer continuum. Integrating advanced technologies such as artificial intelligence (AI) into conventional cancer care models offers significant potential to enhance the responsiveness, inclusivity, and sustainability of cancer care delivery. This paper aimed to explore how the Caring Life Course Theory (CLCT), a comprehensive multidisciplinary framework of care, can inform and enhance the integration of AI into cancer care delivery. METHODS: A conceptual synthesis and narrative synthesis were employed to explore and understand how CLCT constructs can inform AI applications across different levels of cancer care (individual, relational/network and structural). RESULTS: AI technologies are being used to support personalized care planning, real-time symptom monitoring, survivorship management, and coordinated service delivery. Guided by the CLCT, these technologies offer a structured and contextually grounded approach to delivering longitudinal, life-course-informed care. Nonetheless, significant challenges remain, including ethical concerns, algorithmic bias, and implementation barriers. CONCLUSIONS: Aligning AI technologies with the CLCT framework can promote more personalized, equitable, and relationally responsive cancer care. Future research must prioritize ethical co-design, accountability, and sustained implementation. IMPLICATIONS FOR NURSING PRACTICE: The integration of CLCT and AI can support nurses in identifying care needs, facilitating remote monitoring, and coordinating personalized care. However, the integration of AI must be approached with critical attention to ethics, equity, and the preservation of fundamental nursing values.

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