Next, we analyzed the data collected during the outbreak. We ran a series of regressions with emotional well-being as the dependent variable, perceived knowledge, actual knowledge, whether the individual resided in Hubei, age, sex, marital status, income, and the interaction terms between the demographic variables and perceived knowledge as predictors (see Table 2 ). Across all regression models, participants’ perceived knowledge about coronavirus infection was a consistent, significant predictor of their emotional well-being. However, their actual knowledge was not a consistent predictor. In other words, people's perceived level of knowledge about coronavirus infection served as a stronger protector of their emotional well-being during the outbreak than the actual amount of knowledge they possessed.
Table 2 Perceived knowledge helped protect emotional well-being during the coronavirus epidemic
Model 1 Model 2 Model 3 Model 4 Model 5 Model 6 Model 7 Model 8 Model 9 Model 10 Model 11 Model 12 Model 13 Model 14 Model 15 Model 16 Model 17
Perceived Knowledge .067⁎⁎⁎⁎ (.019) .068⁎⁎⁎⁎ (.019) .067⁎⁎⁎⁎ (.019) .067⁎⁎⁎⁎ (.019) .07⁎⁎⁎⁎ (.019) .069⁎⁎⁎⁎ (.02) .072⁎⁎⁎⁎ (.019) .073⁎⁎⁎⁎ (.02) .188⁎⁎ (.073) .193⁎⁎ (.073) .08⁎⁎⁎ (.026) .084⁎⁎⁎ (.027) .099⁎⁎⁎ (.033) .098⁎⁎⁎ (.033) .094⁎⁎⁎ (.033) .096⁎⁎⁎ (.033) .227⁎⁎⁎ (.08)
Actual Knowledge .019 (.011) .020 (.011) .022* (.011) .021* (.011) .022* (.011) .022* (.011) .020 (.011) .022* (.011) .021* (.011) .022* (.011) .019 (.011) .022* (.011) .02 (.011) .021* (.011) .019 (.011) .021* (.011) .021* (.011)
Hubei -.137* (.059) -.138* (.059) -.137* (.059) -.139* (.059) -.138* (.059) .295 (.4) .275 (.401) -.137* (.059) -.14* (.059) -.137* (.059) -.137* (.059) .271 (.402)
Age -.003* (.001) -.003* (.001) -.002 (.001) -.002 (.001) -.002 (.001) .011 (.008) .012 (.008) -.002 (.001) -.002 (.001) -.002 (.001) .012 (.01)
Sex .006 (.023) .007 (.023) .006 (.023) .005 (.023) .008 (.023) .123 (.154) .125 (.154) .007 (.023) .006 (.023) .138 (.155)
Married -.03 (.029) -.031 (.029) -.031 (.029) -.034 (.029) -.031 (.029) .123 (.161) .141 (.162) -.031 (.029) -.029 (.192)
Income .0003 (.001) .0003 (.001) .0003 (.001) .0003 (.001) .0003 (.001) .007 (.007) .007 (.007) .006 (.007)
PK × Hubei -.106 (.098) -.102 (.098) -.101 (.098)
PK × Age -.004 (.002) -.004 (.002) -.003 (.002)
PK × Sex -.028 (.038) -.03 (.038) -.033 (.038)
PK × Married -.043 (.04) -.044 (.04) -.001 (.048)
PK × Income -.002 (.002) -.002 (.002) -.001 (.002)
Constant -.211⁎⁎ (.083) -.212⁎⁎ (.083) -.127 (.092) -.131 (.093) -.149 (.094) -.148 (.094) -.228⁎⁎ (.084) -.164 (.096) -.608* (.293) -.639* (.295) -.269* (.111) -.206 (.12) -.31* (.132) -.258 (.139) -.319* (.134) -.253 (.14) -.776* (.322)
Notes:
⁎ p ≤ .05;
⁎⁎ p ≤ .01;
⁎⁎⁎ p ≤ .005;
⁎⁎⁎⁎ p ≤ .001
Standard errors are shown in parentheses below coefficient estimates.