Analysis of Factors Influencing Online Health Information-Seeking Behavior based on Structural Equation Modeling

Wenhao Li; Tianyi Zhang

doi:10.54691/tcgagx84

Authors

Wenhao Li
Tianyi Zhang

DOI:

https://doi.org/10.54691/tcgagx84

Keywords:

Health information, social support, SOR, ChatGPT.

Abstract

Objective To explore the influencing factors of online health information-seeking behavior, elucidate the intrinsic relationship between online health information-seeking behavior and social support, and promote the integration of "ChatGPT + online health" as a significant opportunity to modernize the public health management system. Methods Guided by social support theory and utilizing the Stimulus-Organism-Response (SOR) model, this study constructed an online health information-seeking model incorporating five variables: informational support, emotional support, social companionship support, perceived risk, and perceived value. A questionnaire survey was conducted to collect data on the online health information-seeking behaviors of 240 residents, aiming to investigate the influencing factors and their interrelationships. Results Perceived value and perceived risk had significant impacts on online health information-seeking behavior, with coefficients of 0.252 (P < 0.001) and -0.426 (P < 0.001), respectively. Emotional support and social companionship support positively influenced users' perceived value, while informational support, emotional support, and social companionship support negatively influenced users' perceived risk. Conclusion Governments and online health community administrators should actively leverage the role of online health communities to encourage user participation in health information-seeking activities.

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