Table 4 Relation between level of HLS-COVID-Q22 and demographic data (n = 3960)
From: COVID-19-related health literacy and preparedness to what may come: a cross-sectional study
Demographic data | COVID-19-related health literacy levels |  |  | χ2 (p) | COVID-19-related health literacy Scores |  |  |
|---|---|---|---|---|---|---|---|
|  | Inadequate (n = 683) | Problematic (n = 1585) | Sufficient (n = 1692) |  | Mean ± SD | Median | Test of Sig. (p) |
Gender | |||||||
 Male | 459 (19.6%) | 910 (38.9%) | 972 (41.5%) | 22.336* (< 0.001*) | 2.89 ± 0.48 | 2.91 | U = 1,789,159.0 *  (0.003*) |
Female | 224 (13.8%) | 675 (41.7%) | 720 (44.5%) |  | 2.93 ± 0.45 | 2.91 |  |
Age | |||||||
 16–29 | 243 (13.8%) | 689 (39.3%) | 823 (46.9%) | 53.720* (< 0.001*) | 2.95 ± 0.43 | 2.95 |  |
 30–44 | 237 (20.6%) | 475 (41.3%) | 438 (38.1%) |  | 2.86 ± 0.49 | 2.86 | H = 34.498* (< 0.001*) |
 45–59 | 115 (16.0%) | 302 (41.9%) | 304 (42.2%) |  | 2.91 ± 0.46 | 2.91 |  |
 60 + | 88 (26.3%) | 119 (35.6%) | 127 (38.0%) |  | 2.81 ± 0.55 | 2.86 |  |
Education | |||||||
 Illiterate | 88 (50.9%) | 56 (32.4%) | 29 (16.8%) | 413.203* (< 0.001*) | 2.49 ± 0.56 | 2.50 | H = 416.737* (< 0.001*) |
 Just read & write | 131 (34.4%) | 169 (44.4%) | 81 (21.3%) |  | 2.61 ± 0.50 | 2.68 |  |
 Primary, Intermediate, secondary | 201 (24.2%) | 360 (43.4%) | 269 (32.4%) |  | 2.80 ± 0.45 | 2.82 |  |
 Bachelors, Masters, Doctorate | 263 (10.2%) | 1000 (38.8%) | 1313 (51.0%) |  | 3.01 ± 0.42 | 3.0 |  |
Monthly household income | |||||||
 < 2000 LE | 337 (21.1%) | 674 (42.3%) | 583 (36.6%) | 66.262* (< 0.001*) | 2.83 ± 0.48 | 2.86 |  |
 2000-4999LE | 251 (15.3%) | 655 (40.0%) | 730 (44.6%) |  | 2.93 ± 0.44 | 2.91 | H = 90.402* (< 0.001*) |
 5000–9999 LE | 69 (13.9%) | 166 (33.5%) | 261 (52.6%) |  | 3.02 ± 0.47 | 3.0 |  |
 10,000–19999 LE | 20 (11.4%) | 69 (39.2%) | 87 (49.4%) |  | 3.00 ± 0.44 | 2.95 |  |
 20,000–49999 LE | 5 (12.8%) | 16 (41.0%) | 18 (46.2%) |  | 3.03 ± 0.52 | 2.95 |  |
 50,000LE | 1 (5.3%) | 5 (26.3%) | 13 (68.4%) |  | 3.33 ± 0.55 | 3.36 |  |
Job of participant | |||||||
 Medical | 62 (11.1%) | 141 (25.2%) | 356 (63.7%) | 66.262* (< 0.001*) | 3.08 ± 0.46 | 3.09 | U = 679,851.50* (< 0.001*) |
 Non-medical | 621 (18.3%) | 1444 (42.5%) | 1336 (39.3%) |  | 2.88 ± 0.46 | 2.86 |  |
How well are you informed about the coronavirus? | |||||||
 Not well at all | 137 (54.2%) | 83 (32.8%) | 33 (13.0%) | 1034.828* (< 0.001*) | 2.40 ± 0.59 | 2.45 |  |
 Not so well | 307 (36.4%) | 388 (46.0%) | 149 (17.7%) |  | 2.64 ± 0.42 | 2.68 | H = 1004.725* (< 0.001) |
 Well | 205 (10.1%) | 952 (46.7%) | 881 (43.2%) |  | 2.94 ± 0.36 | 2.91 |  |
 Very well | 34 (4.1%) | 162 (19.6%) | 629 (76.2%) |  | 3.25 ± 0.42 | 3.27 |  |
Do you feel confused about COVID-19 information? | |||||||
 Very confused | 253 (37.4%) | 300 (44.3%) | 124 (18.3%) | 659.478* (< 0.001*) | 2.60 ± 0.49 | 2.68 |  |
 Somewhat confused | 312 (18.8%) | 800 (48.1%) | 552 (33.2%) |  | 2.82 ± 0.40 | 2.86 | H = 739.967* (< 0.001) |
 Barely confused | 86 (7.8%) | 388 (35.3%) | 626 (56.9%) |  | 3.05 ± 0.38 | 3.0 |  |
 Not confused et al | 32 (6.2%) | 97 (18.7%) | 390 (75.1%) |  | 3.26 ± 0.46 | 3.27 |  |