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Exploring young adult cancer survivors' perspectives on generative AI chatbots for symptom support
Yupawadee Kantabanlang1, Grace Kanzawa-Lee1, Rachel A Pozzar2,3
1Department of Human Behavior and Clinical Sciences, University of Michigan School of Nursing, Ann Arbor, MI, 48109, USA.
Background:
Young adult cancer survivors (ages 18-39) often experience persistent treatment-related symptoms that negatively affect daily functioning, psychosocial well-being, and quality of life, yet report unmet educational needs for symptom management. Generative artificial intelligence (AI) technologies, such as large language model-powered chatbots, offer scalable, personalized, and empathetic symptom support but remain largely untested in young adults' survivorship care.
Objective:
This qualitative descriptive study explored young adult cancer survivors' perspectives, preferences, and experiences related to the use of generative AI chatbots for oncology symptom management.
Methods:
Eighteen post-treatment young adult cancer survivors who had completed cancer treatment within the past two years were recruited from the University of Michigan Rogel Cancer Center. Participants completed the PROMIS-29, PROMIS Self-Efficacy for Managing Symptoms, and the Digital Health Literacy Scale to quantify symptom burden, self-efficacy, and digital readiness. Semi-structured interviews explored experiences with cancer treatment-related symptoms and AI use, including preferences for personalization, tone, functionality, and data governance.
Results:
Qualitative analyses revealed three themes: (1) the need for personalized, emotionally supportive, and credible AI symptom guidance; (2) accessible and user-centered design drives engagement with AI symptom support; and (3) trust, privacy, and human oversight as preconditions for AI symptom support. Survivors viewed AI as a supplemental resource to enhance symptom monitoring, decision support, and emotional reassurance without replacing clinical care.
Conclusion:
Generative AI chatbots were perceived as acceptable and potentially valuable for AYA symptom management. Findings can guide the development of tailored digital self-management interventions responsive to the complex and evolving needs of this population.