在线医疗用户隐私关注影响因素及行为规律研究

发布时间：2018-06-22 02:25

本文选题：在线医疗服务 + 隐私关注　；参考：《北京邮电大学》2017年硕士论文

【摘要】：随着互联网技术的高速发展,互联网在各个领域的渗透不断改变着人们的生活,改善人们现有的生活方式。同样地,医疗领域也在不断演化更新,变得更加智能化和数字化。人们的看病方式从最开始的线下去医院就医转变为以互联网为依托的线上寻医问诊方式,有效缓解了传统的挂号难、看病难的情况。在线医疗网站的用户可以与医生沟通获得对病情的初步诊断,得到有效建议及个性化的服务。除此之外,网站一般会设有讨论社区,用户可以通过与社区成员交流或浏览帖子获取对自己有用的信息及情感上的慰藉与依恋,同样也有很多用户通过分享或公开自己的诊治就医信息帮助他人。尽管用户可以通过在线医疗网站获取有效、个性化的服务,但由于担心自己的健康隐私信息遭到泄露,从而选择拒绝公开分享自己的健康信息。因此,对用户而言,是否选择分享自己的个人健康信息成为了大多数用户难以抉择的事情;对网站而言,用户不愿意公开个人健康信息的这种行为也会阻碍基于互联网的医疗保健服务的健康发展。目前,学者们对在线医疗领域隐私问题的研究较少,主要集中在信息技术本身的感知、信任、用户态度等因素,忽略了用户自身因素的影响,并且研究方法相对单一。因此,根据上文提出的问题,本文聚焦于对用户隐私关注产生影响的自身因素以及由此引发的用户行为规律等相关问题,分别通过构建隐私关注—健康信息分享意愿理论模型及演化博弈矩阵的方法对上述问题进行了分析阐述,最后提出相关建议:(1)用户隐私关注-分享健康信息意愿理论模型构建研究用户自身因素(个人性格特征、个人健康状况、医疗信息敏感性)对隐私关注的影响,并探讨了情感承诺(affective commitment)对隐私关注-分享健康信息意愿之间的调节作用,构建理论模型提出研究假设。研究结果表明隐私关注的影响因素取决于个人性格特征、医疗信息的敏感性,同时用户隐私关注对分享意愿的关系也受到情感承诺调节因素的影响。(2)隐私问题演化博弈研究基于前部分用户群体感知收益对分享健康信息行为的影响以及对成本-收益的理解,构建了用户与网站间的演化博弈模型,用户的策略是分享、不分享,网站的策略是滥用、不滥用,最后得出收益矩阵及复制者动态方程。通过对模型的求解分析,给出了在三种不同条件下的ESS演化稳定策略,随后对模型进行MATLAB数据仿真,模拟用户与网站之间的动态演化过程,最终得出不同参数条件对系统稳定状态的影响。研究结果表明,完善的市场监管机制及良好的公众的隐私保护意识能够在一定程度上消除用户与网站间的不信任与信息不对称性,改善用户与在线医疗网站博弈过程中的劣势。用户可以通过分享自己的个人健康信息获得更加专业化、个性化的服务以及情感支持,网站可以利用用户多维度数据进行挖掘提供更好的服务,而不是滥用(例如贩卖)用户信息获得不法收益,共同促进在线医疗环境的健康持续发展。最后从营销管理角度指出研究的策略建议,分析了本研究的局限性和未来的研究方向。
[Abstract]:With the rapid development of Internet technology, the infiltration of Internet in various fields is changing people's life and improving people's existing way of life. Similarly, the medical field is constantly evolving and updated, becoming more intelligent and digitized. The online medical inquiry method has effectively relieved the traditional registration and difficult conditions. The online medical website users can communicate with the doctors to get a preliminary diagnosis of the disease, get effective advice and personalized service. In addition, the website usually has a discussion community, users can communicate with the community members or A list of information and emotional consolation and attachment to themselves, as well as many users help others by sharing or disclosing their own medical information. Although users can get effective and personalized services through online medical websites, they choose to refuse to fear that their own health privacy information is leaked. Therefore, for users, it is difficult for most users to choose to share their own personal health information. For the web site, the behavior that users do not want to disclose personal health information will also impede the healthy development of health care services based on the Internet. There are few studies on privacy issues in the field of online medical treatment, mainly focusing on the perception, trust, and user attitude of the information technology itself, ignoring the influence of the user's own factors and the relatively single research method. The problems related to users' behavior rules are discussed, and the above problems are analyzed by constructing the theoretical model of health information sharing will and evolutionary game matrix, and some suggestions are put forward at last: (1) the user privacy concern - the theory model of sharing health trust intention is built to study the user's own factors. The impact of human personality, personal health, medical information sensitivity on privacy concerns, and the regulatory role of emotional commitment (affective commitment) on privacy concerns - the willingness to share health information, and the construction of a theoretical model to put forward research hypotheses. The results show that the influence factors of privacy concern depend on personal character characteristics. The sensitivity of medical information, while the relationship of user privacy concern to the willingness to share is also influenced by affective commitment adjustment factors. (2) the evolutionary game of privacy issues is based on the influence of the perceived benefit of the former part of the user group on the sharing of health information behavior and the understanding of the cost benefit. The evolutionary game between the user and the web site is constructed. The strategy of the user is sharing and non sharing. The strategy of the website is abused and not abused. Finally, the return matrix and the dynamic equation of the replicator are obtained. Through the analysis of the model, the ESS evolution stabilization strategy under three different conditions is given, and then the model is simulated with MATLAB data to simulate the dynamic evolution between the user and the web site. The results show that the perfect market supervision mechanism and the good public awareness of privacy protection can eliminate the distrust and information asymmetry between users and websites to a certain extent, and improve the disadvantages of users and online medical websites in the game. More specialized, personalized services and emotional support can be obtained by sharing personal health information, and web sites can provide better services by using users' multidimensional data to provide better services instead of misusing (such as trafficking) user information to gain unlawful benefits and jointly promote the healthy and sustained development of the online medical environment. Finally, From the point of view of marketing management, the strategic recommendations of the study are pointed out, and the limitations and future research directions of the study are analyzed.
【学位授予单位】：北京邮电大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：R-05;F724.6;F224.32

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