{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,4]],"date-time":"2026-06-04T18:31:54Z","timestamp":1780597914111,"version":"3.54.1"},"reference-count":78,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,2,16]],"date-time":"2026-02-16T00:00:00Z","timestamp":1771200000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Public Health"],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Public risk perception bias (PRPB) is a critical psychological and social determinant that substantially shapes public health outcomes and the effectiveness of safety governance\u2014particularly during large-scale crises like the COVID-19 pandemic. Amid increasingly complex urban risk landscapes, traditional single\/dual-spatial frameworks fail to capture PRPB\u2019s multi-source and interactive nature.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>This study develops an Extended Tri-Spatial Prism Model to measure PRPB across 31 major Chinese cities (2017\u20132023) using multi-source data and explores its spatiotemporal dynamics and multi-level influencing mechanisms via a mixed-methods approach (Delphi technique, entropy weighting, GIS spatial analysis, multiple regression, mediation analysis).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>(1) PRPB is dominated by pessimism with marked tri-spatial heterogeneity\u2014physical and cyber spaces show pronounced pessimism, while social space remains cognitively neutral; (2) PRPB exhibits a \u201cnorth-optimistic, south-pessimistic\u201d spatial pattern and a COVID-19-disrupted V-shaped temporal trend (2017\u20132023); (3) Individual and urban factors shape PRPB through the mediation of psychological stress, social capital, media rationality, and government trust.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>This study advances the theoretical understanding of PRPB by systematically delineating its tri-spatial characteristics and underlying mechanisms. These findings provide theoretical insights and practical guidance for optimizing public risk communication systems and urban safety governance frameworks.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fpubh.2026.1705187","type":"journal-article","created":{"date-parts":[[2026,2,16]],"date-time":"2026-02-16T06:36:38Z","timestamp":1771223798000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["Pessimism or optimism? A tri-spatial analysis of public risk perception bias and its influencing mechanisms: evidence from 31 major cities in China"],"prefix":"10.3389","volume":"14","author":[{"given":"Li","family":"Wang","sequence":"first","affiliation":[{"name":"School of Public Policy and Management, China University of Mining and Technology","place":["Xuzhou, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yiming","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Public Policy and Management, China University of Mining and Technology","place":["Xuzhou, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Minchun","family":"Wu","sequence":"additional","affiliation":[{"name":"School of Public Policy and Management, China University of Mining and Technology","place":["Xuzhou, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,2,16]]},"reference":[{"key":"ref1","doi-asserted-by":"publisher","first-page":"280","DOI":"10.1126\/science.3563507","article-title":"Perception of risk","volume":"236","author":"Slovic","year":"1987","journal-title":"Science"},{"key":"ref2","doi-asserted-by":"publisher","first-page":"R941","DOI":"10.1016\/j.cub.2011.10.030","article-title":"The optimism bias","volume":"21","author":"Sharot","year":"2011","journal-title":"Curr Biol"},{"key":"ref3","doi-asserted-by":"publisher","first-page":"177","DOI":"10.1111\/j.1539-6924.1988.tb01168.x","article-title":"The social amplification of risk: a conceptual framework","volume":"8","author":"Kasperson","year":"1988","journal-title":"Risk Anal"},{"key":"ref4","doi-asserted-by":"publisher","first-page":"1269","DOI":"10.1080\/13669877.2014.940599","article-title":"Complexity, uncertainty and future risks","volume":"17","author":"Pidgeon","year":"2014","journal-title":"J Risk Res"},{"key":"ref5","doi-asserted-by":"publisher","first-page":"872","DOI":"10.3390\/land13060872","article-title":"Spatial development and coupling coordination of society\u2013physics\u2013informational smart cities: a case study on thirty capitals in China","volume":"13","author":"Wang","year":"2024","journal-title":"Land"},{"key":"ref6","doi-asserted-by":"publisher","first-page":"1695","DOI":"10.3390\/buildings13071695","article-title":"Evaluation of urban resilience based on trio spaces: an empirical study in Northeast China","volume":"13","author":"Zhang","year":"2023","journal-title":"Buildings"},{"key":"ref7","doi-asserted-by":"publisher","first-page":"282","DOI":"10.3390\/fi17070282","article-title":"Responsible resilience in cyber\u2013physical\u2013social systems: a new paradigm for emergent cyber risk modeling","volume":"17","author":"Sobb","year":"2025","journal-title":"Future Internet"},{"key":"ref8","doi-asserted-by":"publisher","first-page":"351","DOI":"10.1080\/13669870701552235","article-title":"Are flood victims more concerned about climate change than other people? 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