School of Public Health, Capital Medical University, Beijing, China.
J Med Internet Res. 2021 Mar 11;23(3):e23097. doi: 10.2196/23097.
With the spread of COVID-19, an infodemic is also emerging. In public health emergencies, the use of information to enable disease prevention and treatment is incredibly important. Although both the information adoption model (IAM) and health belief model (HBM) have their own merits, they only focus on information or public influence factors, respectively, to explain the public's intention to adopt online prevention and treatment information.
The aim of this study was to fill this gap by using a combination of the IAM and the HBM as the framework for exploring the influencing factors and paths in public health events that affect the public's adoption of online health information and health behaviors, focusing on both objective and subjective factors.
We carried out an online survey to collect responses from participants in China (N=501). Structural equation modeling was used to evaluate items, and confirmatory factor analysis was used to calculate construct reliability and validity. The goodness of fit of the model and mediation effects were analyzed.
The overall fitness indices for the model developed in this study indicated an acceptable fit. Adoption intention was predicted by information characteristics (β=.266, P<.001) and perceived usefulness (β=.565, P<.001), which jointly explained nearly 67% of the adoption intention variance. Information characteristics (β=.244, P<.001), perceived drawbacks (β=-.097, P=.002), perceived benefits (β=.512, P<.001), and self-efficacy (β=.141, P<.001) jointly determined perceived usefulness and explained about 81% of the variance of perceived usefulness. However, social influence did not have a statistically significant impact on perceived usefulness, and self-efficacy did not significantly influence adoption intention directly.
By integrating IAM and HBM, this study provided the insight and understanding that perceived usefulness and adoption intention of online health information could be influenced by information characteristics, people's perceptions of information drawbacks and benefits, and self-efficacy. Moreover, people also exhibited proactive behavior rather than reactive behavior to adopt information. Thus, we should consider these factors when helping the informed public obtain useful information via two approaches: one is to improve the quality of government-based and other official information, and the other is to improve the public's capacity to obtain information, in order to promote truth and fight rumors. This will, in turn, contribute to saving lives as the pandemic continues to unfold and run its course.
随着 COVID-19 的传播,信息疫情也在出现。在公共卫生突发事件中,利用信息进行疾病预防和治疗至关重要。虽然信息采纳模型(IAM)和健康信念模型(HBM)都有其自身的优点,但它们分别只关注信息或公众影响因素,以解释公众对在线预防和治疗信息的采纳意愿。
本研究旨在通过将 IAM 和 HBM 结合作为框架,探讨影响公共卫生事件中公众对在线健康信息和健康行为采纳的影响因素和途径,从而填补这一空白,重点关注客观和主观因素。
我们进行了一项在线调查,以收集来自中国参与者的回复(N=501)。结构方程模型用于评估项目,验证性因子分析用于计算结构的可靠性和有效性。分析了模型的拟合优度和中介效应。
该研究开发的模型的整体拟合指数表明具有可接受的拟合度。采用意愿由信息特征(β=.266,P<.001)和感知有用性(β=.565,P<.001)预测,两者共同解释了约 67%的采用意愿方差。信息特征(β=.244,P<.001)、感知缺陷(β=-.097,P=.002)、感知益处(β=.512,P<.001)和自我效能(β=.141,P<.001)共同决定了感知有用性,并解释了感知有用性方差的约 81%。然而,社会影响对感知有用性没有统计学上的显著影响,自我效能也没有显著直接影响采用意愿。
通过整合 IAM 和 HBM,本研究提供了见解和理解,即在线健康信息的感知有用性和采用意愿可以受到信息特征、人们对信息优缺点的感知以及自我效能的影响。此外,人们在采取信息时表现出主动行为而不是被动行为。因此,在帮助知情公众通过两种方法获得有用信息时,我们应该考虑这些因素:一种是提高政府和其他官方信息的质量,另一种是提高公众获取信息的能力,以促进真相和打击谣言。这反过来将有助于在大流行继续发展和持续的过程中拯救生命。