*3.5. Predictive Factors of Having Suffered from COVID-19*

The correlational analysis indicated a significant association between the variable of having suffered from COVID-19 and all the SOC subscales (total r = −0.23, *p* < 0.001; comprehensibility r = −0.58, *p* < 0.001; manageability r = −0.21, *p* < 0.001; significance r = −0.22, *p* < 0.001), the risk perception scale (r = −0.47, *p* < 0.001), the risk factor subscales (FR1 r = −0.84, *p* < 0.001; FR2 r = −0.41, *p* < 0.001), the coping style subscales (EA1 r = −0.57, *p* < 0.001; EA2 r = −0.61, *p* < 0.001; EA3 r = −0.84, *p* < 0.001) and knowledge (r = −0.25, *p* < 0.001).

A forward stepwise multiple regression analysis was performed using having suffered from COVID-19 as the dependent variable and the different SOC scales, risk perception, risk factors, coping style and knowledge as predictor variables. The model was significant (F = 3.68; *p* < 0.001) and managed to explain 15% of the variance in the criterion variable (suffering from COVID-19) by means of the predictor variables EA3, FR1 and FR2. The subscale EA3 (support-seeking) is the most relevant predictor (beta = −0.12; *p* < 0.001), explaining 8% of the variance of the criterion variable, followed by FR1 (extrinsic factors) (beta = 0.07; *p* = 0.008) and FR2 (intrinsic factors) (beta = 0.06; *p* < 0.001) (Table 5).

**Table 5.** Multiple regression analysis.


Dependent variable: having suffered from COVID-19. EA3 = support-seeking; FR1= extrinsic risk factors; FR2 = intrinsic risk factors. R2 total for the model = 0.15; R<sup>2</sup> total model adjustment = 0.15 (F = 3.68; *p* < 0.001).

#### **4. Discussion**
