Exploring Online Physician–Patient Interactions Through Information Sharing with Agent-Based Modeling

Donghua Chen ()
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Donghua Chen: University of International Business and Economics

A chapter in LISS 2022, 2023, pp 59-73 from Springer

Abstract: Abstract Online health communities enhance physician–patient interactions through various social connections. Health-related posts have a significant influence on patients who are suffering from various symptoms. However, misinformation from the posts may impact patients’ decision-making. This paper proposes an agent-based model to explore the physician–patient interactions through health information sharing in online health communities. First, we introduce two agent types, namely influential users and ordinary users for a general online health community. Network parameters like numbers of users, followers, and fans as well as posting probability are considered in our model. Physician and patient agents are used to measure users’ average posts and support degrees for specific topics. Physician–patient interaction with factors in posting actions, social support, and random behaviors are also simulated. Finally, we run the above model on NetLogo. Taking the haodf.com website, a famous Chinese online health community, as an example, we examined the changes of the physician–patient interaction in different model parameter settings. The results demonstrate the feasibility of the NetLogo-based model in understanding the relationships between physicians and patients, and improving their health decision-making abilities in simulation.

Keywords: Online health community; Physician–patient interaction; Agent-based modeling; Decision-making (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:spr:lnopch:978-981-99-2625-1_5

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DOI: 10.1007/978-981-99-2625-1_5

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