Current status and influencing factors of online health information seeking behavior in elderly stroke patients : a cross-sectional potential profile analysis

Background Owing to its abundant information resources, convenient accessibility,and low cost of use,the Internet has become an important channel for patients to obtain health-related information.Access to sufficient online health information enables patients to manage their diseases more effectively,thereby reducing disease risk and improving health outcomes.However,studies on online health information-seeking behavior among elderly stroke patients remain limited.This study aimed to examine the current status and latent profile characteristics of online health information-seeking behavior among older stroke patients and to explore its influencing factors,thereby providing a reference for the development of individualized intervention strategies. Methods A cross-sectional study was applied between January and July 2025.A total of 327 elderly stroke participants hospitalized in the Department of Neurology of The Second Affiliated Hospital of Dalian Medical University were recruited as study participants.A general information questionnaire,Internet Health Information Seeking Behaviour,eHealth Literacy Scale,Patient Activation Measure scale,Perceived Social Support Scale,and General Self-Efficacy Scale were used to investigate. Latent profile analysis was performed to explore potential subtypes of online health information-seeking behavior,and multinomial logistic regression analysis was used to examine the influencing factors associated with different latent profiles. Results Online health information-seeking behavior among elderly stroke patients was at a relatively low level.Three latent profile subtypes were identified:the “information apathy type”(48.0%), the“moderate attention type”(35.2%),and the“proactive inquistive type”(16.8%).Patient age,education level,monthly family income,eHealth literacy,patient activation,perceived social support,and self-efficacy were predictors of potential online health information-seeking behavior typology in elderly stroke patients( P < 0.05). Conclusion Heterogeneity exists in online health information-seeking behavior of elderly stroke patients, and this behavior is influenced by multiple factors. Healthcare professionals should take targeted intervention strategies based on different potential profile typology to improve online health information-seeking behavior in this population.