Digital health literacy and associated factors among internet users from China: a cross-sectional study.

BACKGROUND: As the internet develops and 5G technology becomes increasingly prominent, the internet has become a major source of health-related information. Increasingly, people use the internet to find health-related information, and digital health literacy is now a set of essential capabilities to improve their health in the digital era. However, little is known about the factors that influencing digital health literacy. This study aimed to assess digital health literacy scores and identify its influencing factors among internet users in China. Additionally, this study explored the participant's actual skills using an additional set of performance-based items from the Digital Health Literacy Instrument (DHLI). METHODS: An online cross-sectional study was conducted in August 2022. Participants aged ≥18 years were recruited to complete the survey. Data were collected using the Chinese revised version of the DHLI, the self-reported internet use questionnaire, and the sociodemographic questionnaire. We conducted multivariate linear regression analyses to explore the relationships among the sociodemographic variables, behavior of internet use, and the digital health literacy scores. RESULTS: In total, 702 participants completed the survey. The mean DHLI score was 2.69 ± 0.61. Multivariate linear regression analyses showed that the age groups 35-49 (ß = - 0.08, P = 0.033), 50-64 (ß = - 0.161, P < 0.001), and ≥ 65 (ß = - 0.138, P < 0.001) were negatively associated with DHL scores. However, education level, including bachelor's or associate degree (ß = 0.255, P = 0.002) and master's degree and above (ß = 0.256, P < 0.001), frequency of health-related Internet usage (ß = 0.192, P < 0.001), the number of digital devices used (ß = 0.129, P = 0.001), and OHISB (ß = 0.103, P = 0.006) showed a positive relationship with DHL scores. CONCLUSIONS: The study findings demonstrate that age, educational levels, number of technological devices used, and greater use of the web for health information were independently associated with DHL scores. Healthcare providers should consider providing training programs tailored to specific sociodemographic factors to improve the ability that find and use accurate information online to meet digital health services, which contributes to enhance their self-management and reduce health disparities.

Achieving Accuracy and Economy for Calculating Vertical Detachment Energies of Molecular Anions: A Model Chemistry Composite Methods.

The vertical detachment energy (VDE) is a vital factor for predicting the stability of anions that have important applications in the atom, molecule and cluster science. Due to the synthetic or characterization difficulty of anions, accurate and efficient predictions of VDE independent of laboratory data have always been an appealing task to remedy the experimental deficiencies. Unfortunately, the generally adopted CCSD(T) and electron propagator theory (EPT) methods have respectively been proven to be reliable but very cost-expensive, and cost-effective but sometimes problematic when Koopman's theorem is invalid. Here, we for the first time introduced and benchmarked a series of model chemistry composite methods (e. g., CBS-QB3, G4 and W1BD) on calculating VDE for 57 molecular anions. Notably, CBS-QB3 exceeds the accuracy of CCSD(T) while approaching the economy of EPT. Therefore, we highly recommend the composite method CBS-QB3 to compute VDEs for molecular anions in the attractive "killing two birds with one stone" manner.