With growing recognition of the importance of community engagement in addressing public health challenges, its role in promoting healthy behaviors and preventing infectious diseases has gained attention. However, vaccination coverage remains a significant concern in many developing countries. While previous studies have linked community engagement to positive health outcomes, there is a gap in understanding its influence on individual vaccination choices, particularly in the context of developing countries. Utilizing data from the 2021 Chinese General Social Survey (CGSS), this study examines the impact of community engagement on COVID-19 and flu vaccination uptake among 7281 individuals. Community engagement, measured by community vaccination notifications, serves as the key independent variable. The study employs Ordinary Least Squares (OLS) regression and Propensity Score Matching (PSM) methods to analyze the relationship between community engagement and vaccination behavior. The analysis reveals a positive association between community engagement and vaccination rates. Specifically, individuals receiving notifications were more likely to get the COVID-19 vaccine compared to non-recipients (vaccination rates: 100% vs. 53.3%), and flu vaccination rates were also significantly higher among those notified (2.7% vs. 1.9%). Mechanism analysis suggests that individuals receiving community notifications are more aware of the benefits of vaccination, leading to higher vaccination rates among this group. This study underscores the effectiveness of community engagement strategies in promoting positive vaccination behavior among individuals in China. By enhancing awareness and trust in immunization, community engagement initiatives play a crucial role in shaping health behaviors and improving vaccination uptake. These findings emphasize the importance of integrating community engagement approaches into public health interventions to address vaccination challenges.

Less than one-third of rural Chinese children with refractive error own or wear eyeglasses. To study the effect of teacher incentives on the acceptance of vision care offered to rural students with uncorrected refractive error, we conducted a cluster-randomized controlled trial in 18 townships in one county in Shaanxi Province. Primary and junior high schools within each township were assigned to either intervention (all teachers received an incentive) or control (no teacher incentives were offered) groups. A total of 42 schools were assigned to either the intervention group (13 schools) or the control group (29 schools). Teachers in the intervention group could elect to receive high-value (sunglasses worth USD 148), moderate-value (eyeglasses worth USD 89), or cash incentives (USD 35) if ≥70% of eligible students (uncorrected visual acuity (VA) ≤ 6/12 in both eyes and corrected VA ≤ 6/9.5 in both eyes) in the teacher’s class visited a program-affiliated vision center (VC) within 60 days after their vision screening. Among 8238 students, 3401 (41.2%, of which 53.0% were girls with a mean age of 12 (SD 1.75)) met the enrollment criteria and were randomly allocated to the intervention (n = 1645, 49.0%) and control groups (n = 1579, 51.0%). Among these, 3224 (94.8%) completed the study and underwent analysis. Nearly equal numbers of students had classroom teachers selecting the high-value (n = 524, 31.9%), moderate-value (n = 582, 35.4%), and cash incentives (n = 539, 32.8%). The rate of the acceptance of offered vision care was significantly higher in the intervention group (382/1645 = 23.2%) compared to the control group (172/1579 = 10.9%, 95% confidence interval for observed difference 12.3%, p < 0.001). Teacher incentives appeared effective in improving Chinese rural school-aged children’s uptake rate of vision services provided by county hospital-based VCs.

The lack of formal eye screening is the main reason for insufficient eye care utilization in rural China. Cataract, in particular, is increasingly prevalent with the aging population, but the treatment rate is relatively low. Village doctors are the most accessible health care resource for rural residents, receiving few empirical investigations into their role in eye care. This study aims to assess the role of village doctors in residents’ uptake of eye screening (vision and cataract screening), the first step of cataract treatment. Data come from a community-based, cross-sectional survey conducted in 35 villages of a county of the Gansu Province, Northwestern China, in 2020. Among 1010 residents aged ≥ 50 and 35 village doctors, the multivariate logistic regression shows that village doctors’ age, time spent on public health service, and service population were positively associated with residents’ uptake of vision and cataract screening. Village doctors were capable of playing an active role in primary eye health services due to their richer knowledge about cataracts than residents (accuracy rate 86.75% vs. 63.50%, p < 0.001), but less than half of them were willing to undertake eye screening. This study highlights the positive role of village doctors in aging residents’ eye screening and the potential role in improving the uptake of eye screening by offering health education.

This study focuses on the empowerment of intelligent finance classroom construction through generative artificial intelligence (exemplified by OpenAI), with Xi'an University of Finance and Economics as the empirical research subject. Utilizing a quasi-experimental design and multidimensional data analysis, the research explores the application potential and efficacy of this technology in financial education. Instructors from eight finance classes were divided into two groups: those using OpenAI and those not using it. Data were collected through semi-structured interviews, classroom observations, and performance metrics to comprehensively evaluate practical outcomes across dimensions such as lesson preparation time, instructional efficiency, and student learning achievements. Results demonstrate that instructors using OpenAI exhibited significantly lower mean preparation time (5.5 hours) compared to non-users (10.57 hours). Students in AI-assisted classrooms showed superior performance in academic scores (81.5 vs. 72.3), case analysis accuracy (78.9% vs. 65.2%), and resource access frequency (45.3 vs. 12.4 counts). The study analyzes the internal mechanisms through which OpenAI enhances intelligent classroom development in finance education, confirming its effectiveness in optimizing teaching workflows, reducing faculty workload, and improving educational quality. These findings provide robust support for educational digital transformation and offer critical insights into the future development of intelligent pedagogy.