The Impact of Beliefs on Health Information Social Sharing for Users: The Perspectives of Social Psychology and Information Technology

期望理论 心理学 社会心理的 社会影响力 结构方程建模 规范性 计划行为理论 技术接受与使用的统一理论 规范的社会影响 社会认同理论 社会心理学 实证研究 应用心理学 知识管理 社会团体 控制(管理) 计算机科学 认识论 精神科 机器学习 哲学 人工智能
作者
Ruiqi Yao,Dongfang Sheng
出处
期刊:Frontiers in Psychology [Frontiers Media SA]
卷期号:13 被引量:2
标识
DOI:10.3389/fpsyg.2022.891126
摘要

With the integration and penetration of digitization into healthcare services, the comprehensive health industrial market is developing flourishingly. Users are fast-changing the way of health communication. This study investigates psychosocial and technological factors on health information sharing adoption through social sharing services. Based on the unified theory of acceptance and use of technology, social influence theory, and innovation diffusion theory, we developed a hypothesized model for health information social sharing adoption (HISSA), and dimensions of attitude beliefs, control beliefs, and normative beliefs were created. We conducted an empirical study on the adoption intention using a survey for data collection. The results were obtained from 375 valid questionnaires, and their interactions were tested and analyzed using PLS-structural equation modeling. Results implied that (1) social identity of normative beliefs was the most critical variable affecting behavioral intention, which revealed the importance of psychosocial factors; (2) behavioral intention was also determined by user's performance expectancy, facilitating conditions, subjective norm; (3) personal innovativeness had a negative effect on behavioral intention and positive effect on effort expectancy; and (4) effort expectancy and social identity had a positive effect on performance expectancy. This study advances the understanding of social sharing for health and provides references for the development of both virtual health communities and social sharing services to upgrade their products from user's behavior and psychology. This empirical research model may also be useful for researchers who are interested in user's health information behavior.
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