Introduction: College students’ mental health education is crucial for holistic individual development and societal quality. It shapes well-rounded personalities, fosters innovation, and cultivates responsible citizens, contributing to social stability and national development. Our research aims to establish an evaluation system for college student mental health education policies based on the Policy Modeling Consistency Index (PMC-Index) model and text mining techniques, quantitatively assessing 15 representative policies.Method: This paper first retrieves policy documents through specialized policy databases and government websites, excluding policies that have already expired or become invalid. The sample selections of this research range from 2001 to 2024, including national guidelines and specific actions. Referring to the above steps of policy effectiveness evaluation, our research comprehensively analyses the implementation effectiveness of the foregoing policies regarding mental health curricula, service systems, crisis intervention, and family cooperation. In the following, based on 10 major variables, 38 sub-variables are constructed with a binary coding system to quantify the content of policy for objectivity. Then, the ROSTCM 6.0 software is used for text segmentation and word frequency statistics, meanwhile, keywords and semantic networks of core policies will be considered for analysis. Subsequently, the PMC-Index is computed based on the multi-input–output matrix and a diagram of the PMC-Surface is drawn with the help of MATLAB to express policy consistency and deficiencies in different dimensions intuitively.Results: Among the 15 policies, 11 exhibit Great Consistency (GC), and 4 fall under Acceptable Consistency (AC). Higher scores are found in Policy Function (X₆), Policy Evaluation (X₈), and Policy Goals (X₉), indicating practical implementation and clear guidance. However, lower scores in Policy Nature (X₁), Policy Timeliness (X₂), Policy Issuing Agency (X₃), and Policy Object (X₄) reveal deficiencies in policy innovation, long-term planning, and target group coverage. Particularly, short-term policies lack sustainability, limiting their long-term effectiveness in supporting students’ mental health. Through PMC-Surface analysis, it is found that lower scores in timeliness and adaptability to target groups are primary factors contributing to surface depressions in the diagram, suggesting that these policies struggle to meet the diverse needs of different types of higher education institutions. The research also highlights significant areas for improvement in resource allocation, support system construction, and personalized mental health services. Some policies fail to address regional disparities, with weaker implementation in underdeveloped areas and insufficient safeguard mechanisms.Discussion: In the future, long-term planning for policy optimization is expected, in which priority would be given to localized resource allocation and close collaboration among schools, families, and society to ensure the comprehensiveness and sustainability of mental health education services. The research has identified certain strengths and weaknesses in the policies concerning mental health education for college students in China, thus providing theoretical references and specific recommendations that can be effectively implemented in higher education institutions.

Background: With the rapid advancement of artificial intelligence technologies, AI-generated content (AIGC) was increasingly applied in the health information sector, becoming a vital tool to enhance the efficiency and quality of health information exchange.Purpose: This research investigated the motivations behind users’ adoption with AIGC during health information searches, aiming to advance public health management and technological innovation in health information.Methods: The study employed a model constructed from the UTAUT and the Health Belief Model. Comprehensive analysis of survey data was conducted using Structural Equation Modeling (SEM) and Fuzzy-Set Qualitative Comparative Analysis (fsQCA). Data handling and model verification were performed using SPSS 27, SmartPLS 4, and fsQCA 4.1 software tools.Results: The SEM results reveal that performance expectancy, effort expectancy, perceived susceptibility, perceived severity, perceived benefits, perceived barriers, and self-efficacy significantly positively influence adoption intentions, while facilitating conditions showed no significant effect. Fuzzy-Set Qualitative Comparative Analysis identifies two pathways that trigger adoption intention: Comprehensive Support and Health-Dominated.Conclusion: The study integrates the UTAUT and HBM in the context of health information technology adoption intention and employs a hybrid approach to deepen understanding of user behavior in the health information environment. Further exploration of emerging theories suitable for the rapidly evolving field of health information technology is still needed.

Background: Health short videos, as an emerging mode of information dissemination, play a crucial role in enhancing health awareness and promoting healthy behavior among college students. It is crucial to optimize both the content and dissemination strategies of these videos to amplify their impact on health communication and to enhance the health literacy of this demographic.Objective: This study aims to construct a comprehensive model to explore the key factors influencing the use of health short videos among Chinese college students, including perceived usefulness, perceived ease of use, and performance expectations, among other factors. The goal is to supply theoretical foundations and practical guidance for optimizing health short video content and dissemination strategies, thereby enhancing college students’ health literacy and quality of life.Methods: An online survey was conducted among Chinese college students to investigate their inclination to acquire health information from health short videos. Based on TAM and UTAUT frameworks, a model was constructed to examine the factors influencing college students’ adoption of health information from health short videos. Through structural equation modeling, the study analyzed the impact of health short videos on the information adoption behavior of college students.Results: This study included a total of 296 Chinese college students. Results from the structural equation model indicated that perceived usefulness (β = 0.443, p < 0.001), perceived ease of use (β = 0.398, p < 0.001), performance expectancy (β = 0.434, p < 0.001), effort expectancy (β = 0.456, p < 0.001), social influence (β = 0.443, p < 0.001), information quality (β = 0.427, p < 0.001), and perceived trust (β = 0.482, p < 0.001) significantly positively influenced intention to adopt health short videos. Conversely, perceived risk (β = −0.415, p < 0.001) and perceived disease threat (β = −0.480, p < 0.001) had significant negative effects on adoption intention. Additionally, facilitating conditions (β = 0.421, p < 0.001) positively influenced adoption behavior, and adoption intention significantly affected adoption behavior (β = 0.406, p < 0.001).Conclusion: The adoption of health short videos by Chinese college students is primarily positively influenced by factors such as perceived usefulness, ease of use, performance expectancy, effort expectancy, social influence, information quality, and trust. Conversely, perceived risk and disease threat negatively affect their usage. Therefore, to promote college students’ continuous attention to and adoption of health short videos, the quality and credibility of health short videos should be improved, the user interface design should be optimized, usability should be enhanced, and social influence strategies should be used to enhance the attractiveness and persuasiveness of health information.

This study aims to conduct a systematic and comprehensive analysis of the combination of medical and elderly care policy (CMECP) texts and to identify the composition, characteristics, and shortcomings of existing policies. On this basis, optimization suggestions are proposed to improve the policy system for the CMECP, thereby more effectively addressing the health and care needs of elderly individuals. To understand and analyse in depth the current situation and problems of the CMECP, this study first conducts text mining. By using the ROST CM6 tool to analyse the policy focus of CMECP text, this research comprehensively reveals the core issues and main concerns of the policy text. Simultaneously, this study conducts a dynamic topic evolution of policies related to the CMECP based on the LDA topic model and visualizes it using a Sankey diagram. Second, our research employs the PMC index model to quantitatively assess the comprehensiveness and implementation effect of policies. Finally, this study systematically evaluates and analyses the CMECP by integrating text mining and the PMC index model to more accurately understand and assess the developmental direction, implementation effects, and existing problems of China’s CMECP. The results reveal that the average PMC index of the 12 policy samples stands at 6.67, representing an impressively high standard of policy text quality. The study also finds that while China’s CMECP has achieved results in terms of fostering service integration and technological innovation, long-term planning and voluntary policy tools are not being used effectively. In addition, through policy analysis, it can be inferred that many of the policies mentioned emphasize the expansion of telemedicine and the integration of traditional Chinese and Western medicine, but the specific incentive measures and methods need to be strengthened. At the same time, the combination of medical and elderly care services is moving towards home-based and community-based elderly care, but resource allocation and policy coherence need to be improved. This study not only provides valuable insights for improving China’s CMECP but also further promotes the implementation of the Healthy China 2030 strategy.