Accepted for/Published in: Journal of Medical Internet Research
Date Submitted: Aug 13, 2020
Date Accepted: Feb 17, 2021
Date Submitted to PubMed: Mar 12, 2021
Factors Affecting Public Adoption of Prevention and Treatment Information Under the Infodemic: An Integrated Conceptual Adoption Framework
ABSTRACT
Background:
With the spread of the COVID-19 pandemic, the infodemic is emerging. In public health emergencies, the use of information to achieve disease prevention and treatment is incredibly important. Although both the Model of Information Acceptance (IAM) and Health Belief Model (HBM) have their own merits, they only focus on information or public influence factors to explain the public's online prevention and treatment information adoption intention.
Objective:
This study aimed to use IAM and 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 information sending and receiving.
Methods:
We carried out an online survey to collect the respondents (n=501) in China. Structural equation modeling was used to evaluate items and construct reliability and validity via confirmatory factor analysis, and the model goodness of fit and mediation effects were analyzed.
Results:
The overall fitness indices for the model developed in this study indicated an acceptable fit. Adoption intention is predicted by information characteristic (beta=0.266, t=4.454) and perceived usefulness (beta=0.565, t=8.003), which jointly explanation nearly 67% of the adoption intention variance. Information characteristic (beta=0.244, t=4.730), perceived drawbacks (beta=-0.097, t=-3.102), perceived benefits (beta=0.512, t=7.641), and self-efficiency (beta=0.141, t=3.659) jointly determine Perceived usefulness and explanation about 81% variance of perceived usefulness. However, social influence is not statistically significant on perceived usefulness, and self-efficiency did not significantly influence adoption intention directly.
Conclusions:
By integrating IAM and HBM, this study provided the insight and an understanding that perceived usefulness and adoption intentions of the online health information could be influenced by the information characteristic, people's perception of information drawbacks and benefits, and self-efficiency. Moreover, people also have proactive behavior rather than reactive behavior to adopt information. Thus, we should consider these factors to help the “informed public” obtain useful information from two aspects, and one is to improve the quality of government and other official information. The other is to improve public information-obtaining capacity, to promote truths and fight rumors. Thereby contributing to saving lives as the pandemic continues to unfold and run its course.
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