Objectives To analyse differences in regional distribution and inequality in health-resource allocation at the hospital and primary health centre (PHC) levels in Shanghai over 7 years. Design A longitudinal survey using 2010–2016 data, which were collected for analysis. Setting The study was conducted at the hospital and PHC levels in Shanghai, China. Outcome measures Ten health-resource indicators were used to measure health-resource distribution at the hospital and PHC levels. In addition, the Theil Index was calculated to measure inequality in health-resource allocation. Results All quantities of healthcare resources per 1000 people in hospitals and PHCs increased across Shanghai districts from 2010 to 2016. Relative to suburban districts, the central districts had higher ratios, both in terms of doctors and equipment, and had faster growth in the doctor indicator and slower growth in the equipment indicator in hospitals and PHCs. The Theil Indices of all health-resource allocation in hospitals had higher values compared with those in PHCs every year from 2010 to 2016; furthermore, the Theil Indices of the indicators, except for technicians and doctors in hospitals, all exhibited downward time trends in hospitals and PHCs. Conclusions Increased healthcare resources and reduced inequality of health-resource allocation in Shanghai during the 7 years indicated that measures taken by the Shanghai government to deepen the new round of healthcare reform in China since 2009 had been successful. Meanwhile there still existed regional difference between urban and rural areas and inequality across different medical institutions. To solve these problems, we prescribe increased wages, improved working conditions, and more open access to career development for doctors and nurses; reduced investments in redundant equipment in hospitals; and other incentives for balancing the health workforce between hospitals and PHCs.

The unprecedented rapid growth of digital health has brought new opportunities to the health field. However, elderly patients with chronic diseases, as an important potential beneficiary group, are affected by the digital divide, leading to unsatisfactory usage of digital health technologies (DHTs). Our study focused on the factors influencing the adoption of DHTs among this vulnerable group. To extend the UTAUT theory, technology anxiety and several demographic predictors were included to address the age characteristics of the respondents. An on-site survey was conducted in general, district, and community hospitals in Shanghai (n = 309). Facilitating conditions negatively influenced technology anxiety. Technology anxiety hindered behavioural intention. Social influence had a significant but negative impact on behavioural intention. Education, whether older adults have had experience with DHTs and previous smartphone usage experiences were significantly associated with technology anxiety. The findings provide valuable information for multiple stakeholders, including family members of elderly users, product designers, and policymakers. Ameliorating facilitating conditions, improving devices’ usage experience, encouraging attempts and focusing on groups with lower educational levels can help to reduce technology anxiety and promote DHT acceptance and use in older age groups.

Objective: To investigate the effects of cell phone dependence (CPD) on mental health among undergraduates during the COVID-19 pandemic and further identify the determinants that may affect their mental health in China.Methods: The data were collected from 602 students at a medical school in Shanghai via an online survey conducted from December 2021 to February 2022. The Mobile Phone Addiction Index (MPAI) and Depression Anxiety Stress Scale (DASS) were applied to evaluate CPD and mental health, respectively. Independent sample t-test and one-way analysis of variance (ANOVA) were employed to compare the means of continuous variables among categorical groups. Correlations between continuous variables were detected using Pearson's correlation analysis. Univariable and multivariable logistic regressions were employed to identify the determinants of mental health.Results: Among the 402 eligible students, 73.88% were women with an average age of 20.19 ± 2.36 years. On average, the DASS score was 32.20 ± 11.07, the CPD score was 36.23 ± 11.89, and the cell phone use duration was 7.67 ± 3.61 h/day. CPD was found to have a negative effect on mental health among college students in Shanghai. Additionally, cell phone use duration, age, being senior students, faculty-student relationship, insomnia, tobacco use, obesity, and life satisfaction were clarified as contributing factors to mental health among college students.Conclusion: High degree of CPD could have a negative effect on college students' mental health, which might lead to some psychological problems. Appropriate actions and effective interventions are highly needed to prevent severe psychological injuries among college students in China.

Background: Physician trust is a critical determinant of the physician–patient relationship and is necessary for an effective health system. Few studies have investigated the association between acculturation and physician trust. Thus, this study analyzed the association between acculturation and physician trust among internal migrants in China by using a cross-sectional research design. Methods: Of the 2000 adult migrants selected using systematic sampling, 1330 participants were eligible. Among the eligible participants, 45.71% were female, and the mean age was 28.50 years old (standard deviation = 9.03). Multiple logistic regression was employed. Results: Our findings indicated that acculturation was significantly associated with physician trust among migrants. The length of stay (LOS), the ability of speaking Shanghainese, and the integration into daily life were identified as contributing factors for physician trust when controlling for all the covariates in the model. Conclusion: We suggest that specific LOS-based targeted policies and culturally sensitive interventions can promote acculturation among Shanghai’s migrants and improve their physician trust.

Background: Breast cancer imposes a considerable burden on both the health care system and society, and becomes increasingly severe among women in China. To reduce the economic burden of this disease is crucial for patients undergoing the breast cancer surgery, hospital managers, and medical insurance providers. However, few studies have evidenced the prediction of the total hospital expenses (THE) for breast cancer surgery. The aim of the study is to predict THE for breast cancer surgery and identify the main influencing factors.Methods: Data were retrieved from the first page of medical records of 3699 patients undergoing breast cancer surgery in one tertiary hospital from 2017 to 2018. Multiple liner regression (MLR), artificial neural networks (ANNs), and classification and regression tree (CART) were constructed and compared.Results: The dataset from 3699 patients were randomly divided into training and test sets at a 70:30 ratio (2599 and 1100 records, respectively). The average total hospital expenses were 12520.54 ± 7844.88 ¥ (US$ 1929.20 ± 1208.11). MLR results revealed six factors to be significantly associated with THE: age, LOS, type of disease, having medical insurance, minimally invasive surgery, and receiving general anesthesia. After comparing three models, ANNs was the best model to predict THEs in patients undergoing breast cancer surgery, and its strong predictive performance was also validated.Conclusions: To reduce the THEs, more attention should be paid to related factors of LOS, major and minimally invasive surgeries, and general anesthesia for these patient groups undergoing breast cancer surgery. This may reduce the information asymmetry between doctors and patients and provide more reliable cost, practical inpatient medical consumption standards and reimbursement standards reference for patients, hospital managers, and medical insurance providers ,respectively.

Introduction: This study investigated segmented assimilation patterns and factors influencing health education utilization (HEU) among internal migrant populations in China, driven by concerns over their declining health owing to urbanization-related changes.Methods: Data from the 2017 China Migrants Dynamic Survey were analyzed, focusing on 13,998 rural migrants. Negative binomial regression was used to explore assimilation patterns and determine the factors affecting HEU among internal migrants in China.Results: The results revealed diverse assimilation patterns among internal migrants in four clusters: first-generation classic assimilation, first-generation integration assimilation, second-generation segmented assimilation, and second-generation underclass assimilation. Adjusting for socioeconomic factors, first-generation integrated assimilation groups showed lower HEU (IRR = 0.922, p < 0.01), while second-generation underclass groups demonstrated higher HEU (IRR = 1.110, p < 0.001) than the second-generation segmented assimilation groups. Additionally, factors such as ethnicity, marital status, employment status, educational attainment, hukou type, health insurance type, time of access to healthcare, social integration, social participation, establishment of health records, and issues encountered in host and origin places significantly influenced HEU.Discussion: This study highlights diverse assimilation patterns among Chinese internal migrants regarding HEU, consistent with the theory of segmented assimilation. Specifically, second-generation immigrants exhibit higher HEU levels than their first-generation counterparts, with the second-generation underclass demonstrating the highest HEU. These findings underscore the need for targeted policy interventions addressing diverse migrant assimilation patterns. Specifically, first-generation migrants require accessible and culturally adapted health education programs to overcome systemic barriers, while second-generation underclass migrants need sustained support to leverage their engagement in health initiatives.