Background: Since the coronavirus disease (COVID-19) epidemic in China in December 2019, information and discussions about COVID-19 have spread rapidly on the internet and have quickly become the focus of worldwide attention, especially on social media. Objective: This study aims to investigate and analyze the public’s attention to events related to COVID-19 in China at the beginning of the COVID-19 epidemic (December 31, 2019, to February 20, 2020) through the Sina Microblog hot search list. Methods: We collected topics related to the COVID-19 epidemic on the Sina Microblog hot search list from December 31, 2019, to February 20, 2020, and described the trend of public attention on COVID-19 epidemic-related topics. ROST Content Mining System version 6.0 was used to analyze the collected text for word segmentation, word frequency, and sentiment analysis. We further described the hot topic keywords and sentiment trends of public attention. We used VOSviewer to implement a visual cluster analysis of hot keywords and build a social network of public opinion content. Results: The study has four main findings. First, we analyzed the changing trend of the public’s attention to the COVID-19 epidemic, which can be divided into three stages. Second, the hot topic keywords of public attention at each stage were slightly different. Third, the emotional tendency of the public toward the COVID-19 epidemic-related hot topics changed from negative to neutral, with negative emotions weakening and positive emotions increasing as a whole. Fourth, we divided the COVID-19 topics with the most public concern into five categories: the situation of the new cases of COVID-19 and its impact, frontline reporting of the epidemic and the measures of prevention and control, expert interpretation and discussion on the source of infection, medical services on the frontline of the epidemic, and focus on the worldwide epidemic and the search for suspected cases. Conclusions: Our study found that social media (eg, Sina Microblog) can be used to measure public attention toward public health emergencies. During the epidemic of the novel coronavirus, a large amount of information about the COVID-19 epidemic was disseminated on Sina Microblog and received widespread public attention. We have learned about the hotspots of public concern regarding the COVID-19 epidemic. These findings can help the government and health departments better communicate with the public on health and translate public health needs into practice to create targeted measures to prevent and control the spread of COVID-19.

Background: During the COVID-19 pandemic, the internet has significantly spread information, providing people with knowledge and advice about health protection regarding COVID-19. While a previous study demonstrated that health and eHealth literacy are related to COVID-19 prevention behaviors, few studies have focused on the relationship between health literacy, eHealth literacy, and COVID-19–related health behaviors. The latter includes not only preventative behaviors but also conventional health behaviors. Objective: The objective of this study was to develop and verify a COVID-19–related health behavior questionnaire, explore its status and structure, and examine the associations between these behaviors and participants’ health literacy and eHealth literacy. Methods: A snowball sampling method was adopted to recruit participants to complete anonymous cross-sectional questionnaire surveys online that assessed sociodemographic information, self-reported coronavirus knowledge, health literacy, eHealth literacy, and COVID-19–related health behaviors. Results: Of 1873 college students who were recruited, 781 (41.7%) had adequate health literacy; the mean eHealth literacy score was 30.16 (SD 6.31). The COVID-19–related health behavior questionnaire presented a two-factor structure—COVID-19–specific precautionary behaviors and conventional health behaviors—with satisfactory fit indices and internal consistency (Cronbach α=.79). The mean score of COVID-19–related health behaviors was 53.77 (SD 8.03), and scores differed significantly (P<.05) with respect to residence, college year, academic major, family economic level, self-reported health status, having a family member or friend infected with coronavirus, and health literacy level. Linear regression analysis showed that health literacy and eHealth literacy were positively associated with COVID-19–specific precautionary behaviors (βhealth literacy=.149, βeHealth literacy=.368; P<.001) and conventional health behaviors (βhealth literacy=.219, βeHealth literacy=.277; P<.001). Conclusions: The COVID-19–related health behavior questionnaire was a valid and reliable measure for assessing health behaviors during the pandemic. College students with higher health literacy and eHealth literacy can more actively adopt COVID-19–related health behaviors. Additionally, compared to health literacy, eHealth literacy is more closely related to COVID-19–related health behaviors. Public intervention measures based on health and eHealth literacy are required to promote COVID-19–related health behaviors during the pandemic, which may be helpful to reduce the risk of COVID-19 infection among college students.

Objective: Digital divide in health-related technology use is a prominent issue for older adults. Improving eHealth literacy may be an important solution to this problem. This study aimed to explore the associations between health literacy, digital skills, and eHealth literacy among older Chinese adults. Methods: A total of 2,144 older adults (mean age, 72.01 ± 6.96 years) from Jinan City, China participated in this study. The eHealth Literacy Scale was used to measure eHealth literacy in older adults. A linear regression model was used to analyze the associations among health literacy, digital skills, and eHealth literacy in older Chinese adults. Results: The mean eHealth literacy score of the older adults was 17.56 ± 9.61. After adjusting for sociodemographic characteristics and experience of Internet usage, the results of the linear regression showed that health literacy ( B = 0.258, 95% confidence interval (CI) = 0.215–0.302, P< 0.001) and digital skills ( B = 0.654, 95% CI = 0.587–0.720, P < 0.001) were positively associated with eHealth literacy. Sensitivity analyses revealed that this association remained robust. Conclusions: The level of eHealth literacy in older Chinese adults is low. Health literacy and digital skills are associated with eHealth literacy in older adults. In the future, eHealth literacy intervention research should be considered from the perspective of health literacy and digital skills.

Purpose: The current research on frontline medical staff in China fighting against COVID-19 has not yet addressed job satisfaction. The purpose of this study is to investigate the job satisfaction of those who were sent to support Hubei province, China, or worked in local designated hospitals, and then analyze the associated influencing factors. Materials and Methods: A total of 455 medical staff who worked at the frontline of the prevention and control of COVID-19 in Hubei province was selected using simple random sampling. They were asked to fill out a self-developed general information questionnaire as well as the Minnesota Satisfaction Questionnaire (MSQ), from 10 January to 10 March 2020. Results: The average job satisfaction score of the participants was 82.58 ± 11.11. The influencing factors include education (P = 0.002), years of work experience (P = 0.006), anti-epidemic work duration (P = 0.048), daily sleep duration (P < 0.001), and the form of participation (P < 0.001). Conclusions: This study, for the first time, measures the job satisfaction of frontline medical staff in fighting against COVID-19 in China. The job satisfaction of frontline medical staff was at a “relatively decent” level, higher than the previous similar measures among medical staff. Related management departments should further improve the job satisfaction of frontline medical staff by meeting their reasonable demands, strengthening the emergency response and practical operation training of junior staff, and ensuring their ample time for sleep and rest. This study is of great reference value for improving the job satisfaction level of frontline medical staff during public health emergencies, developing medical staff security policies, and promoting the establishment of emergency response teams.

Background: Healthy lifestyles and health literacy are strongly associated with cognitive health in older adults, however, it is unclear whether this relationship can be generalized to health-promoting lifestyles and eHealth literacy. To date, no research has examined the interactive effect of health-promoting lifestyles and eHealth literacy on cognitive health. Objective: To examine the associations among health-promoting lifestyles, eHealth literacy, and cognitive health in older adults. Methods: Using a stratified cluster sampling method, we conducted a survey with older adults in four districts and two counties in Jinan (China). Older adults (n = 1201; age ≥ 60 years) completed our survey. We assessed health-promoting lifestyles, eHealth literacy, and cognitive health, and collected participants’ sociodemographic information. Results: Health-promoting lifestyles and eHealth literacy were significantly and positively associated with cognitive health (both p < 0.01). In addition, eHealth literacy was positively associated with health-promoting lifestyles. Moreover, the interaction of health-promoting lifestyle and eHealth literacy negatively predicted cognitive health (β = −0.465, p < 0.01). Conclusions: Health-promoting lifestyles and eHealth literacy were associated with the cognitive health of Chinese older adults, both independently and interactively. Further, eHealth literacy was associated with health-promoting lifestyles in older adults. Therefore, interventions regarding healthy lifestyles and eHealth literacy would benefit older adults.