{"title":"人工智能驱动的治理:利用以风险预防为中心的公共卫生危机管理综合模式应对新出现的风险。","authors":"Ching-Hung Lee, Zhichao Wang, Dianni Wang, Shupeng Lyu, Chun-Hsien Chen","doi":"10.1186/s12961-025-01390-0","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>In response to the coronavirus disease 2019 (COVID-19) pandemic, an emerging public health crisis with global impact, various artificial intelligence (AI)-enabled devices for pandemic-prevention emerged, highlighting the urgent need to understand public leverage of AI-enabled digital technologies.</p><p><strong>Methods: </strong>This study constructs a comprehensive model, the Risk Prevention-centred and AI-enabled Anti-pandemic Technology Acceptance Model (RPAA-TAM), to elucidate public adoption of anti-pandemic digital tools, contributing to innovative governance. Integrating TAM, social influence theory and risk perception theory, RPAA-TAM analyses technology development and explores factors influencing public acceptance of AI in pandemic prevention.</p><p><strong>Results: </strong>The study identifies seven key factors impacting public acceptance, including external variables, public trust, perceived benefit, perceived risk, attitude toward use, behavioural intention to use and system usage, offering insights into the integration of AI in managing emerging public health crises. The study offers seven novel propositions derived from a literature review on the basis of the RPAA-TAM.</p><p><strong>Conclusions: </strong>The Risk Prevention-centred and AI-enabled Anti-pandemic Technology Acceptance Model (RPAA-TAM) offers a comprehensive framework for understanding public acceptance of AI in pandemic prevention. Identifying seven key factors impacting acceptance, our study provides novel propositions on the basis of literature review. RPAA-TAM contributes to innovative governance strategies, guiding the ethical and socially acceptable integration of AI in managing public health crises.</p>","PeriodicalId":12870,"journal":{"name":"Health Research Policy and Systems","volume":"23 1","pages":"115"},"PeriodicalIF":3.2000,"publicationDate":"2025-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12465421/pdf/","citationCount":"0","resultStr":"{\"title\":\"Artificial-intelligence-driven governance: addressing emerging risks with a comprehensive risk-prevention-centred model for public health crisis management.\",\"authors\":\"Ching-Hung Lee, Zhichao Wang, Dianni Wang, Shupeng Lyu, Chun-Hsien Chen\",\"doi\":\"10.1186/s12961-025-01390-0\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>In response to the coronavirus disease 2019 (COVID-19) pandemic, an emerging public health crisis with global impact, various artificial intelligence (AI)-enabled devices for pandemic-prevention emerged, highlighting the urgent need to understand public leverage of AI-enabled digital technologies.</p><p><strong>Methods: </strong>This study constructs a comprehensive model, the Risk Prevention-centred and AI-enabled Anti-pandemic Technology Acceptance Model (RPAA-TAM), to elucidate public adoption of anti-pandemic digital tools, contributing to innovative governance. Integrating TAM, social influence theory and risk perception theory, RPAA-TAM analyses technology development and explores factors influencing public acceptance of AI in pandemic prevention.</p><p><strong>Results: </strong>The study identifies seven key factors impacting public acceptance, including external variables, public trust, perceived benefit, perceived risk, attitude toward use, behavioural intention to use and system usage, offering insights into the integration of AI in managing emerging public health crises. The study offers seven novel propositions derived from a literature review on the basis of the RPAA-TAM.</p><p><strong>Conclusions: </strong>The Risk Prevention-centred and AI-enabled Anti-pandemic Technology Acceptance Model (RPAA-TAM) offers a comprehensive framework for understanding public acceptance of AI in pandemic prevention. Identifying seven key factors impacting acceptance, our study provides novel propositions on the basis of literature review. RPAA-TAM contributes to innovative governance strategies, guiding the ethical and socially acceptable integration of AI in managing public health crises.</p>\",\"PeriodicalId\":12870,\"journal\":{\"name\":\"Health Research Policy and Systems\",\"volume\":\"23 1\",\"pages\":\"115\"},\"PeriodicalIF\":3.2000,\"publicationDate\":\"2025-09-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12465421/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Health Research Policy and Systems\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1186/s12961-025-01390-0\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"HEALTH POLICY & SERVICES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Health Research Policy and Systems","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1186/s12961-025-01390-0","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"HEALTH POLICY & SERVICES","Score":null,"Total":0}
Artificial-intelligence-driven governance: addressing emerging risks with a comprehensive risk-prevention-centred model for public health crisis management.
Background: In response to the coronavirus disease 2019 (COVID-19) pandemic, an emerging public health crisis with global impact, various artificial intelligence (AI)-enabled devices for pandemic-prevention emerged, highlighting the urgent need to understand public leverage of AI-enabled digital technologies.
Methods: This study constructs a comprehensive model, the Risk Prevention-centred and AI-enabled Anti-pandemic Technology Acceptance Model (RPAA-TAM), to elucidate public adoption of anti-pandemic digital tools, contributing to innovative governance. Integrating TAM, social influence theory and risk perception theory, RPAA-TAM analyses technology development and explores factors influencing public acceptance of AI in pandemic prevention.
Results: The study identifies seven key factors impacting public acceptance, including external variables, public trust, perceived benefit, perceived risk, attitude toward use, behavioural intention to use and system usage, offering insights into the integration of AI in managing emerging public health crises. The study offers seven novel propositions derived from a literature review on the basis of the RPAA-TAM.
Conclusions: The Risk Prevention-centred and AI-enabled Anti-pandemic Technology Acceptance Model (RPAA-TAM) offers a comprehensive framework for understanding public acceptance of AI in pandemic prevention. Identifying seven key factors impacting acceptance, our study provides novel propositions on the basis of literature review. RPAA-TAM contributes to innovative governance strategies, guiding the ethical and socially acceptable integration of AI in managing public health crises.
期刊介绍:
Health Research Policy and Systems is an Open Access, peer-reviewed, online journal that aims to provide a platform for the global research community to share their views, findings, insights and successes. Health Research Policy and Systems considers manuscripts that investigate the role of evidence-based health policy and health research systems in ensuring the efficient utilization and application of knowledge to improve health and health equity, especially in developing countries. Research is the foundation for improvements in public health. The problem is that people involved in different areas of research, together with managers and administrators in charge of research entities, do not communicate sufficiently with each other.