确定影响用户披露隐私意向的因素在在线健康社区:双计算模型
Zhuo Sun1,2, Guoquan Zang1, Zongshui Wang3
1School of Information Management, Zhengzhou University, Zhengzhou, China.
Frontiers in public health
|August 4, 2023
概括
在线健康社区 (OHC) 的患者根据对医生和应用程序的信任披露健康信息. 感知到的好处会增加信任,而风险会降低信任,从而影响披露决策.
科学领域:
- 医疗信息学 医疗信息学
- 医学社会学 医学社会学
- 信息安全 信息安全
背景情况:
- 在线健康社区 (OHCs) 改善了医疗资源的获取,但也引发了患者隐私方面的担忧.
- 患者在OHC中面临着平衡信息共享与健康隐私风险的挑战.
研究的目的:
- 探索用户的动机和决策,以便在OHC中披露隐私.
- 开发一个双计算模型,整合风险和隐私计算理论.
主要方法:
- 开发了一种双计算模型,将风险和隐私计算理论结合起来.
- 不同的信任,对医生的信任和对应用程序的信任.
- 分析了感知到的好处和风险对信任和披露意向的影响.
主要成果:
- 对医生和应用程序的信任对于OHC中的健康信息披露至关重要.
- 感知到的好处会对信任产生积极的影响;感知到的风险会对信任产生负面影响.
- 对医生的信任显著影响隐私披露决策,比对应用程序的信任更重要.
结论:
- 双计算模型解释了OHC中的用户隐私披露机制.
- 调查结果强调了信任在感知因素和披露意图之间的关系中扮演的调解角色.
- 为OHC平台制定强有力的隐私政策和保护机制提供了见解.
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