Table 2.
Difference in the adjusted rates of telemedicine use between April 2020 and August-September 2020 by age.
| Age group (years) | Number of participants | Adjusted rate, % | Differencea, % (95% CI) | P valueb | Difference in differencesa (95% CI) | P valueb | |
|
|
|
April 2020 | August-September 2020 |
|
|
|
|
| 18-29 | 3388 | 4.3 | 10.2 | 5.8 (3.0 to 8.7) | <.001 | Reference | N/Ac |
| 30-39 | 3784 | 3.0 | 6.3 | 3.3 (1.7 to 4.9) | <.001 | −2.5 (−5.8 to 0.7) | .19 |
| 40-49 | 4883 | 1.8 | 4.1 | 2.3 (1.2 to 3.3) | <.001 | −3.5 (−6.6 to −0.5) | .04 |
| 50-59 | 4278 | 1.2 | 3.2 | 2.0 (0.9 to 3.1) | <.001 | −3.9 (−6.9 to −0.8) | .01 |
| 60-69 | 4286 | 0.8 | 2.2 | 1.4 (0.4 to 2.4) | .004 | −4.5 (−7.5 to −1.4) | .003 |
| 70-79 | 3907 | 0.2 | 3.8 | 3.5 (2.2 to 4.8) | <.001 | −2.3 (−5.5 to 0.8) | .19 |
aWe calculated the differences in the adjusted rates of telemedicine use between April 2020 and August-September 2020 for each age group. Then, we examined how the difference in the rates of telemedicine use between the two time points varied by age (difference in differences). The analyses were weighted to account for selection in an internet survey. For each analysis, standard errors were clustered at the prefecture level.
bThe P values were adjusted post hoc to account for multiple comparisons with the use of the Benjamini-Hochberg method.
cN/A: not applicable.