# Pessimism or optimism? A tri-spatial analysis of public risk perception bias and its influencing mechanisms: evidence from 31 major cities in China

## TL;DR

This study examines public risk perception bias in 31 Chinese cities using a new tri-spatial model to understand its patterns and influencing factors.

## Contribution

The study introduces an Extended Tri-Spatial Prism Model to analyze public risk perception bias with multi-source data and mixed methods.

## Key findings

- PRPB is dominated by pessimism, with physical and cyber spaces showing pronounced pessimism and social space being neutral.
- PRPB follows a 'north-optimistic, south-pessimistic' spatial pattern and a V-shaped temporal trend disrupted by the pandemic.
- Factors like psychological stress, social capital, media rationality, and government trust mediate PRPB.

## Abstract

Public risk perception bias (PRPB) is a critical psychological and social determinant that substantially shapes public health outcomes and the effectiveness of safety governance—particularly during large-scale crises like the COVID-19 pandemic. Amid increasingly complex urban risk landscapes, traditional single/dual-spatial frameworks fail to capture PRPB’s multi-source and interactive nature.

This study develops an Extended Tri-Spatial Prism Model to measure PRPB across 31 major Chinese cities (2017–2023) 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).

(1) PRPB is dominated by pessimism with marked tri-spatial heterogeneity—physical and cyber spaces show pronounced pessimism, while social space remains cognitively neutral; (2) PRPB exhibits a “north-optimistic, south-pessimistic” spatial pattern and a COVID-19-disrupted V-shaped temporal trend (2017–2023); (3) Individual and urban factors shape PRPB through the mediation of psychological stress, social capital, media rationality, and government trust.

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.