Background: As the coronavirus disease 2019 (COVID‐19) pandemic is sweeping across the globe, there is an urgent need to develop effective vaccines as the most powerful strategy to end the pandemic. This study aimed to examine how factors related to vaccine characteristics, their social normative influence and convenience of vaccination can affect the public's preference for the uptake of the COVID‐19 vaccine in China.Methods: An online discrete choice experiment (DCE) survey was administered to a sample of China's general population. Participants were asked to make a series of hypothetical choices and estimate their preference for different attributes of the vaccine. A mixed logit regression model was used to analyse the DCE data. Willingness to pay for each attribute was also calculated.Results: Data of 1236 participants who provided valid responses were included in the analysis. There was strong public preference for high effectiveness of the vaccine, followed by long protective duration, very few adverse events and being manufactured overseas. Price was the least important attribute affecting the public preference in selecting the COVID‐19 vaccine.Conclusions: The strong public preferences detected in this study should be considered when developing COVID‐19 vaccination programme in China. The results provide useful information for policymakers to identify the individual and social values for a good vaccination strategy.Patient or Public Contribution: The design of the experimental choices was fully based on interviews and focus group discussions participated by 26 Chinese people with diverse socio‐economic backgrounds. Without their participation, the study would not be possible.

Background: Although previous studies have shown that a high level of health literacy can improve patients’ ability to engage in health-related shared decision-making (SDM) and improve their quality of life, few studies have investigated the role of eHealth literacy in improving patient satisfaction with SDM (SSDM) and well-being. Objective: This study aims to assess the relationship between patients’ eHealth literacy and their socioeconomic determinants and to investigate the association between patients’ eHealth literacy and their SSDM and well-being. Methods: The data used in this study were obtained from a multicenter cross-sectional survey in China. The eHealth Literacy Scale (eHEALS) and Investigating Choice Experiments Capability Measure for Adults were used to measure patients’ eHealth literacy and capability well-being, respectively. The SSDM was assessed by using a self-administered questionnaire. The Kruskal-Wallis one-way analysis of variance and Wilcoxon signed-rank test were used to compare the differences in the eHEALS, SSDM, and Investigating Choice Experiments Capability Measure for Adults scores of patients with varying background characteristics. Ordinary least square regression models were used to assess the relationship among eHealth literacy, SSDM, and well-being adjusted by patients’ background characteristics. Results: A total of 569 patients completed the questionnaire. Patients who were male, were highly educated, were childless, were fully employed, were without chronic conditions, and indicated no depressive disorder reported a higher mean score on the eHEALS. Younger patients (SSDM≥61 years=88.6 vs SSDM16-30 years=84.2) tended to show higher SSDM. Patients who were rural residents and were well paid were more likely to report good capability well-being. Patients who had a higher SSDM and better capability well-being reported a significantly higher level of eHealth literacy than those who had lower SSDM and poorer capability well-being. The regression models showed a positive relationship between eHealth literacy and both SSDM (β=.22; P<.001) and well-being (β=.26; P<.001) after adjusting for patients’ demographic, socioeconomic status, lifestyle, and health status variables. Conclusions: This study showed that patients with a high level of eHealth literacy are more likely to experience optimal SDM and improved capability well-being. However, patients’ depressive status may alter the relationship between eHealth literacy and SSDM.

Background: The rapid proliferation of web-based information on health and health care has profoundly changed individuals’ health-seeking behaviors, with individuals choosing the internet as their first source of information on their health conditions before seeking professional advice. However, barriers to the evaluation of people’s eHealth literacy present some difficulties for decision makers with respect to encouraging and empowering patients to use web-based resources. Objective: This study aims to examine the psychometric properties of a simplified Chinese version of the eHealth Literacy Scale (SC-eHEALS). Methods: Data used for analysis were obtained from a cross-sectional multicenter survey. Confirmatory factor analysis (CFA) was used to examine the structure of the SC-eHEALS. Correlations between the SC-eHEALS and ICEpop capability measure for adults (ICECAP-A) items and overall health status were estimated to assess the convergent validity. Internal consistency reliability was confirmed using Cronbach alpha (α), McDonald omega (ω), and split-half reliability (λ). A general partial credit model was used to perform the item response theory (IRT) analysis. Item difficulty, discrimination, and fit were reported. Item-category characteristic curves (ICCs) and item and test information curves were used to graphically assess the validity and reliability based on the IRT analysis. Differential item functioning (DIF) was used to check for possible item bias on gender and age. Results: A total of 574 respondents from 5 cities in China completed the SC-eHEALS. CFA confirmed that the one-factor model was acceptable. The internal consistency reliability was good, with α=0.96, ω=0.92, and λ=0.96. The item-total correlation coefficients ranged between 0.86 and 0.91. Items 8 and 4 showed the lowest and highest mean scores, respectively. The correlation coefficients between the SC-eHEALS and ICECAP-A items and overall health status were significant, but the strength was mild. The discrimination of SC-eHEALS items ranged between 2.63 and 5.42. ICCs indicated that the order of categories’ thresholds for all items was as expected. In total, 70% of the information provided by SC-eHEALS was below the average level of the latent trait. DIF was found for item 6 on age. Conclusions: The SC-eHEALS has been demonstrated to have good psychometric properties and can therefore be used to evaluate people’s eHealth literacy in China.

Background: For patients with rare diseases (RD), misdiagnosis (or erroneous diagnosis) is one of the key issues that hinder RD patients’ accessibility to timely treatment. Yet, little is known about the main factors that are associated with RD patients’ misdiagnosis. The objective of this study is to analyze data from a national survey among 2040 RD patients from China to explore the association between misdiagnosis and various factors, including patients’ demographics, socio-economic status, medical history, and their accessibility to RD information. Results: Three binary logistic regression analyses were performed to assess the relationships between misdiagnosis and level of rarity of the RDs (mild, moderate, and severe), demographics, health insurance levels, and accessibility to disease-related information by using the total sample, and the adult and non-adult sub-samples. We found that accessibility to RD information is the most critical factor influencing the patients’ chances of being misdiagnosed (odds ratio [OR] = 4.459, p < 0.001). In other words, the greater the difficulty in accessing the information on RD management, the higher the possibility of experiencing misdiagnosis. Such influences of information accessibility on misdiagnosis were repeatedly discovered when examining the adult (OR = 3.732, p < 0.001) and the non-adult (OR = 5.174, p < 0.001) sub-samples. The association between perceived economic status and misdiagnosis was only significant in the total sample. The only other factor significantly associated with misdiagnosis was disease multimorbidity: participants who reported no multimorbidity are less likely to experience misdiagnosis (OR = 0.42, p < 0.001). Conclusions: Our study indicated that patients with RDs who have difficulty in accessing disease-related information are two to five times more likely to have experienced misdiagnosis. Even after adjusting for the patients’ age, gender, economic levels, and education levels, the impact of information accessibility was still significant. Our finding highlights the importance of access to information in reducing misdiagnosis among RD patients.

Objectives To evaluate the effect of hypertension and related comorbidities on the health-related quality of life (HRQoL) using EuroQol 5-dimensions instrument with five-level scale (EQ-5D-5L) Hong Kong (HK) version. Design Data were analysed by a secondary data analysis based on a cross-sectional study assessing experience on public specialist outpatient service. Setting A representative sample was recruited from 26 specialist outpatient clinics in HK. Participants A total of 4528 patients with hypertension aged 18 or above who responded to the survey. Intervention EQ-5D-5L HK was applied to assess the HRQoL. The five-dimension descriptive system and the utility index of EQ-5D-5L were treated as the dependent variable in the current study. Regression modelling was applied to estimate the effect of hypertension and related comorbidities on health-related quality of life. Results More respondents were women (53.9%), aged ≥65 years old (60.1%), and with primary educational attainment or below (52.3%). A total of 1466 respondents (32.4%) also reported suffering from diabetes, heart disease (20.8%), vision problem (1.7%) and cancer (1.5%). In the ordinal least squares model, utility decreased most when patients reported having physical disability associated with hypertension (beta=−0.395, SE=0.047), and 0.128, 0.064, 0.05 and 0.048 for mental problem, cancer, vision problem and heart problem. In the Tobit model, the utility reduced most for comorbidity of physical disability, and then mental problem, cancer, vision problem, heart problem and diabetes. For first part of two-part model, respondents coliving with mental problem were 10% less likely to report a full health. For the second part of two-part model, the respondents with physical disability had 0.294 lower in utility. Conclusions Respondents with hypertension reported a low EQ-5D utility score. Respondents were women, with a high education, fully employed and living with families reported better HRQoL. There is a significant effect of comorbidity influence on the decreased HRQoL, particularly those with physical disability and mental problem.

Purpose: This study aimed to estimate the health preference scores of the Chinese population with Diabetes Mellitus (DM) using the EQ-5D-5L Hong Kong (HK) population tariff according to different sociodemographic characteristics in HK. Methods: Data were obtained from a cross-sectional, territory-wide study of patient experience on specialist outpatient services in a public setting in HK. The EQ-5D-5L HK was used to collect the patients’ health status. A total of 2326 respondents were reported to suffer from DM, and their information was elicited and used for the analysis in this study. A robust ANOVA method was used to compare the differences in EQ-5D-5L index scores among subgroups. Binary logistic regressions were used to predict the probability of respondents reporting full health, and ordinal least square (OLS) model was used to assess the relationship between DM and health-related quality of life (HRQoL). Results: The mean EQ-5D-5L index score for DM patients was 0.84. A total of 229 EQ-5D health states were reported. Altogether, 47.5% of the respondents reported having some problems with pain/discomfort, followed by mobility (26.4%), usual activities (26.0%), and anxiety/depression (23.5%). Logistic regression and OLS models indicated that male and fully employed respondents were less likely to report having problems with any of the five dimensions and index score of EQ-5D than female and non-fully employed respondents. The findings of OLS model also showed that DM patients that experience comorbidity with three and more chronic conditions were more likely to show a lower index score than respondents who reported living with DM alone. Conclusion: The EQ-5D index scores varied among DM patient characteristics and were more highly impaired with multimorbidity status. Interventions targeting at-risk subgroups, such as modifying single-diseased guidelines, might be helpful to improve their HRQoL.