Beyond one-size-fits-all: mapping information-seeking and decision-making pathways in cancer care.

PURPOSE: To identify distinct archetypes among adult cancer patients based on information-seeking patterns from symptom onset to treatment initiation, including the use of digital and emerging technologies such as generative AI, and to characterize the decision-making dilemmas associated with these pathways. METHODS: We conducted a cross-sectional study in Israel, between February 2025 and December 2025, among 205 adult cancer patients to examine patterns of information seeking and decision-making during the period from symptom onset to treatment initiation. Participants completed a structured questionnaire assessing reliance on multiple information sources-including medical professionals, family members, digital resources, and generative AI-based tools-before and after diagnosis, along with sociodemographic and clinical characteristics. Patient archetypes were identified using cluster analysis, and decision-making dilemmas were explored using two methods (investigator-led constant comparative analysis and LLM) for open-ended responses. RESULTS: Four distinct information-seeking archetypes were identified: Digital Natives (27.6%), Family-Centered (38.8%), Balanced Traditional (25.0%), and Medical Professional-Focused (8.6%). Archetypes differed significantly by age, education, and the strongest differentiating factor (p = 0.005)-religiosity. Across archetypes, information seeking intensified after diagnosis, relying mostly on family members, internet sources, and additional medical professionals, whereas reliance on generative AI-based tools remained consistently low. Among respondents to the open-ended question, 86% reported significant decision-making dilemmas, most commonly related to treatment selection and choice of healthcare provider or facility. CONCLUSION: The marked heterogeneity observed in patients' information-seeking and decision-making pathways highlights the inadequacy of one-size-fits-all approaches in early cancer care. Implementing tailored, culturally responsive decision support may better align care with patients' needs during this critical phase.