How information processing and risk/benefit perception affect COVID-19 vaccination intention of users in online health communities.

Objective: To investigate the relationship among information processing, risk/benefit perception and the COVID-19 vaccination intention of OHCs users with the heuristic-systematic model (HSM). Methods: This study conducted a cross-sectional questionnaire via an online survey among Chinese adults. A structural equation model (SEM) was used to examine the research hypotheses. Results: Systematic information processing positively influenced benefit perception, and heuristic information processing positively influenced risk perception. Benefit perception had a significant positive effect on users' vaccination intention. Risk perception had a negative impact on vaccination intention. Findings revealed that differences in information processing methods affect users' perceptions of risk and benefit, which decide their vaccination intention. Conclusion: Online health communities can provide more systematic cues and users should process information systematically to increase their perceived benefits, consequently increase their willingness to receive COVID-19 vaccine.

Research on the influencing factors of users’ information processing in online health communities based on heuristic-systematic model

With the rapid development of the Internet and the normalization of COVID-19 epidemic prevention and control, Online health communities (OHCs) have gradually become one of the important ways for people to obtain health information, and users have to go through a series of information processing when facing the massive amount of data. Understanding the factors influencing user information processing is necessary to promote users’ health literacy, health knowledge popularization and health behavior shaping. Based on the Heuristic-Systematic Model (HSM), Information Ecology Theory, Privacy Trade-Off and Self-Efficacy Theory, we constructed a model of factors influencing user information processing in online health communities. We found that information quality and emotional support had indirect effects on heuristic and systematic information processing, and these effects were mediated by privacy concerns and self-efficacy. In our research model, systematic information processing was most positively influenced directly by self-efficacy. Privacy concerns had a direct negative correlation with both dual information processing pathways. Therefore, OHCs managers should develop relevant regulations to ensure the information quality in OHCs and improve privacy protection services to promote user information processing by improving users’ self-efficacy and reducing their privacy concerns. Providing a user-friendly and interactive environment for users is also recommended to create more emotional support, thus facilitating more systematic information processing.

The Development and Preliminary Application of the Chinese Version of the COVID-19 Vaccine Literacy Scale.

(1) Background: Vaccine literacy (VL) of the public is crucial to deal with anti-vaccination rhetoric. This study aims to (1) develop a Chinese COVID-19 Vaccine Literacy Scale and examine the factor structure and psychometric characteristics, and (2) explore the association between COVID-19 VL and sociodemographic characteristics and other variables; (2) Methods: An online cross-sectional survey was conducted among 362 Chinese residents from 23 May 2022 to 31 May 2022 using snowball sampling; (3) Results: Exploratory and confirmatory factor analysis indicated that the scale of 15 items, consisting of three factors, functional, interactive and critical vaccine literacy, explained 63.3% of the total variance. Cronbach's α coefficient was 0.885 for the overall scale: 0.838, 0.891, and 0.857 for three subscales, respectively. The results showed a medium level of vaccine literacy (M = 3.71, SD = 0.72) and significant differences among functional, interactive, and critical vaccine literacy (p < 0.001). The level of vaccine literacy grew with the level of education (p < 0.001) and age (p = 0.049). Men, participants who were single, or those living in rural areas had a lower level of vaccine literacy; (4) Conclusions: The Chinese COVID-19 VL Scale has adequate validity and reliability for assessing vaccine literacy among Chinese residents. A deep understanding of the factors that affect vaccine literacy is needed.

Exploring the Willingness of the COVID-19 Vaccine Booster Shots in China Using the Health Belief Model: Web-Based Online Cross-Sectional Study.

(1) Objective: To explore Chinese residents' willingness to receive COVID-19 vaccine booster shots and identify predictors of the level of willingness based on the health belief model (HBM). (2) Methods: The snowball sampling method was used to distribute online questionnaires. A chi-square test was used to analyze the relationship between different variables. The causal relationship between HBM-related factors and booster vaccination intentions was explored by Structural equation modeling (SEM). (3) Results: A total of 898 complete responses were included; 64.3% had already received the booster injection. Most respondents intended to vaccinate themselves, while 16.1% were hesitant. Nearly half of the respondents chose to take the booster injection to support China's vaccination policy. Using the SEM, perceived susceptibility and perceived barriers were found to have a negative effect on booster vaccination intentions, whereas perceived benefit and cues to action positively affected booster vaccination intentions in the HBM. (4) Conclusions: Factors included in this study have different effects on the willingness to take the COVID-19 booster injections. Sociodemographic characteristics and characteristics of participants' COVID-19 vaccination have a significant effect on the willingness to receive vaccine booster shots. The HBM constructs can serve as good predictors of the acceptance of vaccine booster shots with the exception of perceived severity, which may benefit health officials in terms of conducting targeted strategies in vaccine programs.

Effect of Information Framing on Wearing Masks During the COVID-19 Pandemic: Interaction With Social Norms and Information Credibility

Objective The main objectives of this study were to use the effect of information framing (different expressions of the same issue, e.g., positive messages and negative messages) to explore key factors that influence the attitude of and intention of the public toward wearing masks and to understand the internal and external factors of intervention on information framing perception. Methods This study performed an online questionnaire survey to explore the influence of demographic characteristics, information framing, social norms, and information credibility on the attitude of the public toward masks and their intention to wear them. Results (1) Information framing had a significant impact on the attitudes of people toward masks and their intention to wear them, and the persuasion effect of gain-framed messages was higher than that of loss-framed messages. (2) Gender, income, occupation, educational background, and residence have no significant difference in attitude and intention to wear masks. There was a significant correlation between age and wearing of masks (p = 0.041 < 0.05). (3) Social norms affected people's perception of information framing and their attitude toward wearing masks, but only the impact of loss-framed messages on intention was significant. (4) Information framing affected people's perception of information credibility, which had a positive impact on their intention to wear masks;however, information credibility only had a significant impact on attitude toward wearing masks under the gain-framed messages and played an intermediary role. Conclusion The impact of information framing on the attitude of people toward masks and their intention to wear them varies. Individuals involved in the publicity of health information related to this issue should pay attention to the influence of information framing and content on the public wearing masks as a means of enhancing public health awareness.

The Uptake and Vaccination Willingness of COVID-19 Vaccine among Chinese Residents: Web-Based Online Cross-Sectional Study.

OBJECTIVE: To investigate the uptake and vaccination willingness of the COVID-19 vaccine among Chinese residents and analyze the difference and factors that impact vaccination. METHODS: The snowball sampling method was used to distribute online questionnaires. Relevant sociodemographic data along with the circumstances of COVID-19 vaccination were collected from the respondents. The χ2 test, independent samples t test and binary logistic regression analysis were used to analyze the data. RESULTS: Among 786 respondents, 84.22% had been vaccinated. Over 80% of the vaccinated population have completed all the injections because of supporting the national vaccination policies of China, while the unvaccinated population (23.91%) is mainly due to personal health status. Meanwhile, statistical analysis revealed that the main predictors of not being vaccinated were younger age (3 to 18 years old), personal health status, and lower vaccinated proportion of family members and close friends (p < 0.05). CONCLUSIONS: There was a high level of uptake of the COVID-19 vaccine in China, and people who have not been vaccinated generally had a low willingness to vaccinate in the future. Based on our results, it suggested the next work to expand the coverage of the COVID-19 vaccination should be concentrated on targeted publicity and education for people who have not been vaccinated.

Information Framing Effect on Public's Intention to Receive the COVID-19 Vaccination in China.

The aims of the study were (1) to explore information framing effect on the public's intention to receive the COVID-19 vaccination and (2) to understand the key factors influencing the intention of COVID-19 vaccinations in China. An online questionnaire survey was conducted to explore the influence of demographic characteristics, individual awareness, social relationship, risk disclosure, perceived vaccine efficacy, and protection duration under the assumptions of information framing. The results showed that (1) the persuasion effect under loss frame was higher than that under gain frame (B = 0.616 vs. 0.552); (2) there was no significant difference between sex, age, income, occupation, educational background and residence for the participants' intention to be vaccinated; whether family members/friends were vaccinated had a strong correlation with their vaccination intention under the gain frame; (3) the higher the understanding of COVID-19 and the compliance with government COVID-19 prevention and control measures were, the higher the vaccination intention was; (4) risk disclosure had the greatest impact on people's COVID-19 vaccination intention; (5) perceived vaccine effectiveness and duration of protection had little effect on people's intention to receive vaccination. The influence of information framing on the intention of COVID-19 vaccination is different. The publicity of relevant health information should pay attention to the influence of information framing and contents on the behavior of public vaccination, so as to enhance public health awareness and promote the vaccination of the whole population.

Forecast of the COVID-19 Epidemic Based on RF-BOA-LightGBM.

In this paper, we utilize the Internet big data tool, namely Baidu Index, to predict the development trend of the new coronavirus pneumonia epidemic to obtain further data. By selecting appropriate keywords, we can collect the data of COVID-19 cases in China between 1 January 2020 and 1 April 2020. After preprocessing the data set, the optimal sub-data set can be obtained by using random forest feature selection method. The optimization results of the seven hyperparameters of the LightGBM model by grid search, random search and Bayesian optimization algorithms are compared. The experimental results show that applying the data set obtained from the Baidu Index to the Bayesian-optimized LightGBM model can better predict the growth of the number of patients with new coronary pneumonias, and also help people to make accurate judgments to the development trend of the new coronary pneumonia.