Analysis of Differences in User Groups and Post Sentiment of COVID-19 Vaccine Hesitators in Chinese Social-Media Platforms.

(1) Background: The COVID-19 epidemic is still global and no specific drug has been developed for COVID-19. Vaccination can both prevent infection and limit the spread of the epidemic. Eliminating hesitation to the COVID-19 vaccine and achieving early herd immunity is a common goal for all countries. However, efforts in this area have not been significant and there is still a long way to go to eliminate vaccine hesitancy. (2) Objective: This study aimed to uncover differences in the characteristics and sentiments of COVID-19 vaccine hesitators on Chinese social-media platforms and to achieve a classification of vaccine-hesitant groups. (3) Methods: COVID-19-vaccine-hesitation posts and user characteristics were collected on the Sina Microblog platform for posting times spanning one year, and posts were identified for hesitation types. Logistic regression was used to conduct user-group analysis. The differences in user characteristics between the various types of COVID-19 vaccine posts were analysed according to four user characteristics: gender, address type, degree of personal-information disclosure, and whether they followed health topics. Sentiment analysis was conducted using sentiment analysis tools to calculate the sentiment scores and sentiment polarity of various COVID-19 vaccine posts, and the K-W test was used to uncover the sentiment differences between various types of COVID-19-vaccine-hesitation posts. (4) Results: There are differences in the types of COVID-19-vaccine-hesitation posts posted by users with different characteristics, and different types of COVID-19-vaccine-hesitation posts differ in terms of sentiment. Differences in user attributes and user behaviors are found across the different COVID-19-vaccine-hesitation types. Ultimately, two COVID-19-vaccine-hesitant user groups were identified: Body-related and Non-bodily-related. Users who posted body-related vaccine-hesitation posts are more often female, disclose more personal information and follow health topics on social-media platforms. Users who posted non-bodily-related posts are more often male, disclose less personal information, and do not follow health topics. The average sentiment score for all COVID-19-vaccine-hesitant-type posts is less than 0.45, with negative-sentiment posts outweighing positive- and neutral-sentiment posts in each type, among which the "Individual rights" type is the most negative. (5) Conclusions: This paper complements the application of user groups in the field of vaccine hesitation, and the results of the analysis of group characteristics and post sentiment can help to provide an in-depth and comprehensive analysis of the concerns and needs of COVID-19 vaccine hesitators. This will help public-health agencies to implement more targeted strategies to eliminate vaccine hesitancy and improve their work related to the COVID-19 vaccine, with far-reaching implications for COVID-19-vaccine promotion and vaccination.

Research on Knowledge Learning of COVID-19 Video Viewers: Based on Cognitive Mediation Model.

During the COVID-19 epidemic, social media has become the main channel for people to learn information related to the epidemic, among which information in the form of videos has played a significant role in the prevention and control of COVID-19. However, few studies have analyzed the process of knowledge learning of individuals through watching COVID-19 videos. Therefore, to explore the process of COVID-19 video viewers' knowledge acquisition, this paper constructs a knowledge learning path model based on the cognitive mediation model and dual coding theory. A sample of 255 valid questionnaires was collected to validate this model. The results of this study show that an individual's perceived risk of COVID-19 affects their surveillance motivation positively, while surveillance motivation further stimulates the attention and elaboration about the information in COVID-19 videos. Among them, attention positively influences the elaboration about the information. Ultimately, both an individual's attention and elaboration positively influence the knowledge he or she acquires from the COVID-19 videos. This paper not only verifies the hypothesized relationships in the original cognitive mediation model, but also extends the model to the context of video knowledge learning. Analyzing the knowledge learning process of COVID-19 video viewers, this paper can provide suggestions for government propaganda departments and relevant media to improve public knowledge of COVID-19.

Increase the Number of Views and Shares of COVID-19 Videos: Content Relevance and Emotional Consistency with Virus Variant Topics.

(1) Background: The coronavirus variants have posed serious challenges for the prevention and control of the COVID-19 pandemic. Individuals selectively watch and forward videos that help them reduce the damage caused by the virus. Therefore, the factors influencing video viewing and sharing in the context of the COVID-19 pandemic caused by virus variation must be explored. (2) Method: Based on a combination of uncertainty reduction theory and functional emotion theory, this paper designed hypotheses regarding how content relevance and emotional consistency affect video views and shares. We used the support vector machine (SVM) classification algorithm to measure the content relevance between videos and virus variant topics. We performed sentiment analysis of video text to evaluate the emotional consistency between videos and virus variant topics. Then, we used empirical analysis to build the model. (3) Results: The trained SVM classifier was effective in judging whether the video text was related to virus variant topics (F = 88.95%). The content relevance between COVID-19 videos and virus variant topics was generally low. The results showed that the higher the content relevance, the more views (IRR = 1.005, p = 0.017) and shares (IRR = 1.008, p = 0.009) the video received. Individuals were more willing to view (IRR = 1.625, p < 0.001) and share (IRR = 1.761, p < 0.001) COVID-19 videos with high emotional consistency with virus variant topics. (4) Conclusions: The results of empirical analysis showed that content relevance and emotional consistency between videos and virus variant topics significantly positively impacted video views and shares. The trained SVM classifier can support public health departments in monitoring and assessing the COVID-19 pandemic. Our study provides management advice while helping individuals reduce harm and inform next-step decisions.

What Motivates People to Receive Continuous COVID-19 Vaccine Booster Shots? An Expectation Confirmation Theory Perspective.

(1) Background: Abundant evidence has shown that the COVID-19 vaccine booster is highly effective against the Omicron variant. It is of great practical significance to explore the factors influencing the intention to receive COVID-19 booster shots. (2) Methods: We introduced expectation confirmation theory as the basis to construct a model of the factors of the vaccination intention for COVID-19 vaccine boosters. We obtained two batches of questionnaires through Chinese social platforms, with a valid sample size of 572. To test the model, we used SmartPLS3.0 software for empirical analysis. (3) Results: In terms of the characteristics of the vaccine itself, perceived vaccine efficacy and perceived vaccine safety had significant positive effects on expectation confirmation. Regarding vaccination services, perceived vaccination convenience also had a significant positive effect on expectation confirmation. Expectation confirmation positively affected the vaccination intention for the COVID-19 vaccine boosters. Furthermore, the results showed two moderating effects: first, health consciousness negatively moderated the positive effect of perceived vaccine safety on expectation confirmation; second, the time interval since the last dose negatively moderated the positive effect of perceived vaccine efficacy on expectation confirmation. (4) Conclusions: Our research demonstrated that there is an expectation confirmation process for previous COVID-19 vaccines before people consider whether to obtain a booster shot. Perceived vaccine efficacy and perceived vaccine safety remained important factors in receiving COVID-19 booster shots, and our conclusions were consistent with previous literature. In this study, multiple dimensions such as distance and cost were used to measure perceived vaccination convenience. This new variable improve the explanatory power of the convenience of the vaccination service and enrich the variables of the factor model of vaccination intention. In addition, the moderating effects of health consciousness and time interval were found. The findings can provide a theoretical reference for public health institutions to help them understand the formation process of people's intention to receive the COVID-19 vaccine booster.

Influencing factors of adult thyroid volume in Lanzhou City

Objective: To investigate the thyroid volume of adults in Lanzhou City, and analyze its influencing factors.

Detecting Suicidal Ideation in Social Media: An Ensemble Method Based on Feature Fusion.

Suicide has become a serious problem, and how to prevent suicide has become a very important research topic. Social media provides an ideal platform for monitoring suicidal ideation. This paper presents an integrated model for multidimensional information fusion. By integrating the best classification models determined by single and multiple features, different feature information is combined to better identify suicidal posts in online social media. This approach was assessed with a dataset formed from 40,222 posts annotated by Weibo. By integrating the best classification model of single features and multidimensional features, the proposed model ((BSC + RFS)-fs, WEC-fs) achieved 80.61% accuracy and a 79.20% F1-score. Other representative text information representation methods and demographic factors related to suicide may also be important predictors of suicide, which were not considered in this study. To the best of our knowledge, this is the good try that feature combination and ensemble algorithms have been fused to detect user-generated content with suicidal ideation. The findings suggest that feature combinations do not always work well, and that an appropriate combination strategy can make classification models work better. There are differences in the information contained in different functional carriers, and a targeted choice classification model may improve the detection rate of suicidal ideation.

Change of Disease Spectrum Characteristics of Psychiatric Inpatients Before and After Lockdown Lifted During the COVID-19 Pandemic - Wuhan City, Hubei Province, China, 2021.

What is already known about this topic?: The coronavirus disease 2019 (COVID-19) pandemic poses a significant threat to mental health globally and may change the proportion of hospitalized patients. What is added by this report?: This report analyzed and compared the disease characteristics of psychiatric inpatients one year before and after Wuhan lifted lockdown during COVID-19. About 50% of the inpatients were diagnosed with bipolar disorder; females and adolescents had a higher prevalence of mental disorders. What are the implications for public health practice?: More attention should be paid to the mental health of children, adolescents, and females.

Obesity or increased body mass index and the risk of severe outcomes in patients with COVID-19: A protocol for systematic review and meta-analysis.

BACKGROUND: To assess the effect of obesity or a high body mass index (BMI) on the risk of severe outcomes in patients with coronavirus disease 2019 (COVID-19). METHODS: Studies on the relationship between BMI or obesity and COVID-19 since December 2019. The odds ratio (OR) and weighted mean difference (WMD) with their 95% confidence intervals (CIs) were used to assess the effect size. RESULTS: BMI was significantly increased in COVID-19 patients with severe illness (WMD: 1.18; 95% CI: 0.42-1.93), who were admitted to an intensive care unit (ICU) (WMD: 1.46; 95% CI: 0.96-1.97), who required invasive mechanical ventilation (IMV) (WMD: 2.70, 95% CI: 1.05-4.35) and who died (WMD: 0.91, 95% CI: 0.02-1.80). In Western countries, obesity (BMI of ≥30 kg/m2) increased the risk of hospitalization (OR: 2.08; 95% CI: 1.22-3.54), admission to an ICU (OR: 1.54; 95% CI: 1.29-1.84), need for IMV (OR: 1.73, 95% CI: 1.38-2.17), and mortality (OR: 1.43; 95% CI: 1.17-1.74) of patients with COVID-19. In the Asian population, obesity (BMI of ≥28 kg/m2) increased the risk of severe illness (OR: 3.14; 95% CI: 1.83-5.38). Compared with patients with COVID-19 and a BMI of <25 kg/m2, those with a BMI of 25-30 kg/m2 and ≥30 kg/m2 had a higher risk of need for IMV (OR: 2.19, 95% CI: 1.30-3.69 and OR: 3.04; 95% CI: 1.76-5.28, respectively). The risk of ICU admission in patients with COVID-19 and a BMI of ≥30 kg/m2 was significantly higher than in those with a BMI of 25-30 kg/m2 (OR: 1.49; 95% CI: 1.00-2.21). CONCLUSION: As BMI increased, the risks of hospitalization, ICU admission, and need for IMV increased, especially in COVID-19 patients with obesity. ETHICS AND DISSEMINATION: This systematic review and meta-analysis does not require an ethics approval as it does not collect any primary data from patients.

Exploring and Monitoring the Reasons for Hesitation with COVID-19 Vaccine Based on Social-Platform Text and Classification Algorithms.

(1) Background: The COVID-19 pandemic is globally rampant, and it is the common goal of all countries to eliminate hesitation in taking the COVID-19 vaccine and achieve herd immunity as soon as possible. However, people are generally more hesitant about the COVID-19 vaccine than about other conventional vaccines, and exploring the specific reasons for hesitation with the COVID-19 vaccine is crucial. (2) Methods: this paper selected text data from a social platform to conduct qualitative analysis of the text to structure COVID-19 vaccine hesitancy reasons, and then conducted semiautomatic quantitative content analysis of the text through a supervised machine-learning method to classify them. (3) Results: on the basis of a large number of studies and news reports on vaccine hesitancy, we structured 12 types of the COVID-19 vaccine hesitancy reasons. Then, in the experiment, we conducted comparative analysis of three classifiers: support vector machine (SVM), logistic regression (LR), and naive Bayes classifier (NBC). Results show that the SVM classification model with TF-IDF and SMOTE had the best performance. (4) Conclusions: our study structured 12 types of COVID-19 vaccine hesitancy reasons through qualitative analysis, filling in the gaps of previous studies. At the same time, this work provides public health institutions with a monitoring tool to support efforts to mitigate and eliminate COVID-19 vaccine hesitancy.

Research on the Influencing Factors of Audience Popularity Level of COVID-19 Videos during the COVID-19 Pandemic.

(1) Background: During the COVID-19 pandemic, users share and obtain COVID-19 information through video platforms, but only a few COVID-19 videos become popular among most audiences. Therefore, it is a very interesting and important research question to explore the influencing factors of the popularity of COVID-19 videos during the COVID-19 pandemic; (2) Our research collects video data related to the keyword "COVID-19" on video platform, the data are analyzed by content analysis and empirical analysis. We then constructed a theoretical model based on the information adoption model; (3) A total of 251 videos were divided into three categories. The least common category was the data and analysis category (11.2%), followed by the prevention and control status category (13.5%); the knowledge and general science category was the most common (75.3%). From the perspective of video quality, the information sources of most videos are relatively reliable, and the content of medical information is low. The research results showed that short video lengths, longer descriptions, more reliable video sources and lower medical information content were more popular with audiences. Audiences are more likely to be attracted to videos in the prevention and control status category and knowledge and general science category. Videos uploaded by uploaders who have a higher influence are more popular with audiences; (4) Conclusions: During the COVID-19 pandemic, information quality (video length, description length, video content type, and medical information and content index) and source credibility (information source reliability, influence and certification type) all significantly influence the popularity level of COVID-19 videos. Our research conclusions can provide management suggestions for the platform, make videos released by uploaders more popular with audiences, and help audiences better understand COVID-19 information and make prevention and control efforts.

Nurses endured high risks of psychological problems under the epidemic of COVID-19 in a longitudinal study in Wuhan China.

BACKGROUND: Health care workers, especially frontline nurses, faced great challenges during the coronavirus disease 2019 (COVID-19) outbreak. AIMS: To assess the magnitude of the psychological status and associated risk factors among nurses in the pandemic center in Wuhan, China. METHODS: In this study, we enrolled nurses from Renmin Hospital of Wuhan University. The questionnaire was designed to obtain basic information of the participants, and included four psychological assessment scales. We issued the questionnaires at two different points of time. We conducted the first survey on January 29 to February 2 (outbreak period) with 709 eligible responses, and the second survey on February 26 to February 28 (stable period) with 621 eligible responses. The nurses from Wuchang Fangcang shelter hospital were also enrolled in the second survey. RESULTS: During the pandemic, over one-third of nurses suffered from depression, anxiety, and insomnia. In the outbreak period, the nurses showed significantly higher risks for depression, anxiety, and posttraumatic stress disorder (PTSD) symptoms than those in the stable period (P < 0.01). Notably, the nurses from the Fangcang shelter hospitals were more likely to present psychological problems than those from other frontline or non-frontline (all P < 0.001) units, especially for insomnia (38.3% with severe insomnia). The nurses from the frontline, with worse physical condition and uncertain concerns about this pandemic as compared to the others, were more likely to bear psychological problems. Thus, online psychological information and sufficient protection conditions were effective interventions to help mitigate psychological distress. The nurses from Fangcang shelter hospitals suffered a significantly higher risk of psychological problems than those from other units. CONCLUSION: The psychological status of nurses needs more attention during the COVID-19 pandemic, especially for those who fought in the frontline during the peak of the outbreak.