大数据背景下医疗数据的隐私关注及其影响因素——基于保护动机理论的实证研究

Privacy Concern of Medical Data and its Influencing Factors in the Context of Big Data——An Empirical Study Based on Protection Motivation Theory

本文利用保护动机理论构建医疗隐私关注的结构方程模型,基于有效问卷,使用Amos24.0进行路径分析和多群组分析,考察了感知威胁和感知效能对医疗隐私关注的影响,验证不同医疗隐私泄露听闻经历群组的隐私关注形成路径的差异。研究结果表明,公众感知到的威胁严重性正向影响隐私关注,威胁脆弱性对隐私关注没有显著影响,自我效能负向影响隐私关注,反应效能正向影响隐私关注,不同隐私泄露听闻经历群组的威胁严重性、自我效能、反应效能对隐私关注的影响作用有显著差异。因此,医疗机构应当维护公众对于医疗隐私保护的知情权,让公众适当介入医疗数据管理进而提升自我效能感知,并谨防隐私泄露事件带来负面影响,尽力维持公众对医疗信息安全乃至医疗系统的长期信任。

Based on Protection Motivation Theory,this paper constructs a structural equation model of medical privacy concern.Based on valid questionnaires,using Amos24.0 to conduct path analysis and multi-group analysis,this paper investigates the impact of perceived threat and perceived effectiveness on medical privacy concern,and verifies the differences of privacy concern formation paths among different groups of medical privacy disclosure hearing experience groups.The results show that the threat severity perceived by the public has a positive impact on privacy concern,threat vulnerability has no significant impact on privacy concern,self-effectiveness negatively affects privacy concern,response effectiveness positively affects privacy concern,and the impact of threat severity,self-effectiveness and response effectiveness of different privacy disclosure listening experience groups on privacy concern are significantly different.Therefore,medical institutions should maintain the public’s right to know about the protection of medical privacy,let the public properly intervene in medical data management,so as to enhance self-effectiveness perception,and guard against the negative impact of privacy leakage,and try to maintain the public’s long-term trust in medical information security and even the medical system.