Impact of pandemic proximity and media use on risk perception during COVID-19 in China

Figures & data

Figure 1. Model for research hypotheses.

Figure 2. Results of the research model.

Table 1. Descriptive statistics and bivariate correlations between key variables.

Variable	1	2	3	4	5	6
1. Geographical proximity	1.000
2. Community proximity	–0.164*	1.000
3. Infection population proximity	–0.200*	0.257*	1.000
4. Traditional media use	–0.029	–0.088	–0.069	1.000
5. Social media use	–0.020	0.030	0.019	0.306*	1.000
6. Interpersonal communication	–0.050	0.017	–0.041	0.615*	0.421*	1.000
7. Pandemic risk perception	–0.146*	0.066	0.152*	0.199*	0.267*	0.248*

***p <. 001, **p <. 01, *p <. 05.

Table 2. Regression analysis of pandemic risk perception.

Variables	M1		M2		M3
	β	SE	β	SE	β	SE
Demographic
Gender (male = 1)	–0.014	0.358	–0.023	0.358	–0.042	0.344
Education	–0.136*	0.143	–0.122*	0.144	–0.057	0.143
Age	0.064	0.151	0.054	0.154	0.066	0.148
Region (city = 1)	0.005	0.388	0.009	0.409	–0.019	0.394
R^2（%）	2.41
Pandemic proximity
Geographical proximity（Hubei = 0） Guangdong Others
			–0.028	0.444	–0.051	0.426
			–0.080	0.495	–0.088	0.475
Community proximity			0.046	0.111	0.032	0.107
Infection population proximity			0.127*	0.276	0.132**	0.265
R^2（%）			5.44
Media use
Traditional media use					0.051	0.104
Social media use					0.200***	0.057
Interpersonal communication					0.120	0.109
Increment R^2（%）					8.55
R^2（%）					13.99
Adj R^2（%）					11.60

*p <. 05, **p <. 01, ***p <. 001; β as listed in the above table is the standardized regression coefficient.