Table 4.
Type of information related to COVID-19 that impacts on creating panic on social media.
| Variables | Total (n = 942) n(%) | Gender |
P value1 | Age group (years) |
P value1 | |||
|---|---|---|---|---|---|---|---|---|
| Female (n = 640) n(%) | Male (n = 322) n(%) | 6-9 (n = 205) n(%) | 10-14 (n = 556) n(%) | 15-18 (n = 181) n(%) | ||||
| Dissemination of the number of COVID-19 infections (A) | 38 (4.0) | 23 (3.7) | 15 (4.7) | 0.008 | 2 (1.0) | 31 (5.6) | 5 (2.8) | <0.001 |
| Dissemination of the death toll (B) | 9 (1.0) | 4 (0.6) | 5 (1.6) | 0 (0.0) | 6 9 (1.1) | 3 (1.7) | ||
| Dissemination of panic-inducing information about COVID-19 (C) | 50 (5.3) | 23 (3.7) | 27 (8.4) | 1 (0.5) | 31 (5.6) | 18 (9.9) | ||
| Posting of videos, photos, and news of the countries with a high number of cases (D) | 9 (1.0) | 7 (1.1) | 2 (0.6) | 0 (0.0) | 7 (1.3) | 2 (1.1) | ||
| Fake news about the COVID-19 outbreak (E) | 68 (7.2) | 46 (7.4) | 22 (6.8) | 2 (1.0) | 51 (9.2) | 15 (8.3) | ||
| Dissemination of the number of infections (A) and dissemination of the death toll (B) | 6 (0.6) | 5 (0.8) | 1 (0.3) | 1 (0.5) | 4 (0.7) | 1 (0.6) | ||
| Dissemination of the number of COVID-19 infections (A) and dissemination of panic-inducing information about COVID-19 (C) | 132 (14.0) | 81 (13.1) | 51 (15.8) | 32 (15.5) | 82 (14.8) | 18 (9.9) | ||
| Dissemination of the number of infections (A) and posting of videos and photos of the countries with a high number of cases (D) | 40 (4.2) | 19 (3.1) | 21 (6.5) | 5 (2.4) | 27 (4.9) | 8 (4.4) | ||
| Dissemination of the number of infections (A) and fake news about the COVID-19 outbreak (E) | 553 (58.7) | 386 (62.3) | 167 (51.9) | 150 (72.5) | 302 (54.5) | 101 (55.8) | ||
| Dissemination of the death toll (B) and dissemination of panic-inducing information about COVID-19 (C) | 19 (2.0) | 13 (2.1) | 6 (1.9) | 8 (3.9) | 3 (0.5) | 8 (4.4) | ||
| Others | 18 (1.9) | 13 (2.1) | 5 (1.6) | 6 (92.9) | 10 (1.8) | 2 (1.1) | ||
1
Calculated by Chi-squared (χ2) test, P-value significant at ≤ 0.05.