Study On Factors Of Sharing Willingness And Behavior Evolution Of Information Sharing Among Online Chronic Patient Communities

With the change of lifestyle,chronic diseases gradually become the main threats to human health.The effective treatment and prevention of chronic diseases need patients’ self-health management,among which the key is to obtain effective health information.With the development of information technology,more and more chronic disease patients seek health-related information support through online chronic patient communities.However,most online communities are not active and sustainable enough in information sharing.In order to promote the sustainable development of online chronic disease patient community,this thesis analyzed the willingness,process and stable equilibrium level of information sharing among chronic disease patients.The main research contents and conclusions are as follows.Firstly,from the perspective of patients’ information sharing willingness,this thesis constructed an information sharing willingness model of online chronic disease patient community.Based on the questionnaire data,through the structural equation hypothesis test,this thesis studied the direct impact of the positive and negative utility of online community patients’ information sharing on their information sharing willingness,and the regulatory role of information sensitivity and disease severity.The results demonstrated that although patients’ privacy concerns have a strong inhibition on information sharing intention,when the severity of the disease is high,the impact of privacy concerns on the willingness to share information will decrease.At the same time,although information support can promote the willingness to share,information sensitivity can negatively regulate the relationship between information support and sharing intention.Secondly,from the perspective of information sharing process,based on the different content generated by the community patients,the multi-agent evolution model of information sharing among online chronic disease patients is constructed.Through the Netlogo experimental platform,this thesis analyzes the influence mechanism of trust relationship between patients on the process of community information sharing in eight different sharing scenarios.Results found: when patients share pessimistic emotions or wrong health information,the high trust relationship will promote the transmission and absorption of negative information,which may lead to the deterioration of patients’ status in the community,and it is not conducive to the sustainability of information sharing behavior in the community.When the patients in the community share optimistic emotions and real health information,even if the trust between the patients is low,with the passage of information interaction time,information sharing behavior will gradually evolve to a high level.Thirdly,from the perspective of the final stability state of the community,the hypothesis of even mixing of community members in the existing literature is broadened,and the network structure model and evolutionary game model of information sharing of online chronic disease patients’ community are constructed.With the help of MATLAB simulation experiment,this thesis analyzes the influence of patient network structure and game parameters on the level of information sharing equilibrium.The experimental results show that: when the benefits and costs of information sharing are within a certain range,under the same game scenario,we can improve the equilibrium level of information sharing by optimizing the network structure of community patients.Finally,based on the information sharing willingness and behavior evolution law of online chronic disease patients community,this thesis puts forward measures and suggestions from three aspects: improving the willingness to participate in information sharing,optimizing the evolution process of sharing behavior and improving the stable level of information sharing,so as to promote the enthusiasm,effectiveness and participation stickiness of community patients’ information sharing.