Table 6.
Summary of multiple regression analyses for COVID-19 perceived risk predicting different domains of telemedicine use while controlling demographic variables (n = 550).
| Criterion | Perceived Benefit | Accessibility | Privacy and Discomfort | ||||||
|---|---|---|---|---|---|---|---|---|---|
| Predictors | B (β) ### | t #### Value | UV (%) # | B (β) ### | t #### Value | UV (%) # | B (β) ### | t #### Value | UV (%) # |
| COVID-19 perceived risk | 0.6 (0.5) | 11.4 | 19.4 ** | 0.6 (0.5) | 14.0 | 26.6 ** | −0.5 (−0.4) | −10.4 | −16.8 ** |
| ≥41 years of age versus 18–25 years of age | 2.8 (0.2) | 3.6 | 2.4 ** | ||||||
| Married versus single | 1.6 (0.2) | 3.7 | −2.5 ** | ||||||
| Primary school versus no education | 2.7 (0.2) | 2.6 | 1.3 * | ||||||
| Secondary school versus no education | 3.1 (0.3) | 2.9 | 1.6 ** | ||||||
| University/college versus no education | 3.6 (0.2) | 3.4 | 2.1 ** | ||||||
| Part-time/casual versus full-time | 1.5 (0.1) | 2.6 | 1.3 * | ||||||
| (R2 = 25.7%, df = 13, f = 14.3 **) | (R2 = 30.1%, df = 13, f = 17.8 **) | (R2 = 24.4%, df = 13, f = 13.3 **) | |||||||
| Care Personnel Concerns | Usability | Satisfaction | |||||||
| COVID-19 perceived risk | −0.3 (−0.4) | −8.9 | −13.0 ** | 0.3 (0.4) | 9.9 | 15.5 *** | 0.4 (0.4) | 11.4 | 19.6 ** |
| 26–40 years of age versus 18–25 years of age | 0.8 (0.2) | 2.9 | 1.6 * | ||||||
| ≥41 years of age versus 18–25 years of age | 1.5 (0.2) | 2.9 | 1.5 * | ||||||
| Middle family income versus low income | 1.5 (0.2) | 3.4 | 2.2 ** | ||||||
| (R2 = 16.5%, df = 13, f = 8.1 **) | (R2 = 22.2%, df = 13, f = 11.2 **) | R2 = 25.5%, df = 13, f = 14.2 **) | |||||||
UV (%) # = unique variance because of variable (%), * p < 0.05, ** p < 0.01, *** p < 0.001. ### B is the unstandardized beta, representing the slope of the line between the predictor and the dependent variables. It shows for every one unit increase in the predictor, the dependent variable will increase by how much. β is the standardized beta ranging from 0 to 1 or 0 to −1, depending on the direction of the relationship. The closer the value is to 1 or −1, the stronger the relationship. #### t is the t-test statistic value, which is used to calculate the p-value for each variable.