From information tools to clinical agents: A scoping review of the application of chatbots across the hereditary cancer counseling pathway
Xu Liu, Han Yan, Wenjie Wang, Yuxing Xie, Li Jiaying, Dongchi Ma, Li Wang, Li NingObjective
This scoping review systematically synthesizes the technical characteristics, clinical application scenarios, and reported outcomes of chatbots within hereditary cancer counseling, providing an evidence-based reference for nursing practice and digital health implementation.
Methods
Following the Joanna Briggs Institute (JBI) methodology for scoping reviews, a comprehensive literature search was conducted across PubMed, Cochrane Library, Embase, Web of Science, CINAHL, ScienceDirect, CNKI, Wanfang, and China Biomedical Literature Database from database inception through December 10, 2025. Data from eligible articles were extracted and analyzed using a narrative synthesis approach.
Results
Eighteen articles were included. Identified chatbots encompassed proprietary platforms (e.g., Gia, BRIDGE, Rosa, GENIE) alongside custom conversational agents. These tools functioned as interactive agents driven by intent recognition with varying degrees of clinical system integration. Their application spanned the clinical genetic counseling continuum, encompassing pre-test screening and triage, intra-test decision support, and post-test management. Evaluative metrics were categorized into four core dimensions: clinical decision outcomes, psychosocial impact, technical performance, and operational efficiency.
Conclusion
Chatbots demonstrate considerable potential to enhance the accessibility of genetic counseling and testing, with favorable feasibility outcomes and emerging psychosocial support capabilities. However, substantial challenges persist regarding diagnostic accuracy in complex hereditary cancer scenarios, emotional rapport-building, therapeutic trust, and equitable access across diverse socioeconomic groups. Future development should prioritize improving domain-specific semantic recognition, enhancing human–computer empathic interaction, and implementing tailored interventions for varying digital literacy levels, alongside rigorous evaluation of long-term clinical outcomes.