| Literature DB >> 33072524 |
Hsing-Ying Ho1, Yi-Lung Chen1,2, Cheng-Fang Yen3,4.
Abstract
BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic spread rapidly, as did COVID-19-related information on diverse media platforms. Excessive COVID-19-related information caused substantial mental distress among the public. Although most studies focused on the impact of information on individuals during the pandemic, they usually focused on information from internet sources, and few studies compared the impacts between different information sources. We examine the sociodemographic profiles of participants receiving different information sources and the impact of various COVID-19-related information sources on public worry.Entities:
Keywords: COVID-19; Information source; Knowledge; Public worry
Year: 2020 PMID: 33072524 PMCID: PMC7550055 DOI: 10.1016/j.invent.2020.100350
Source DB: PubMed Journal: Internet Interv ISSN: 2214-7829
Sociodemographics and worry about COVID-19 in the online survey.
| Variable | N = 2007 | |
|---|---|---|
| Mean ± SD, n (%) | Min–max | |
| Age | 37.72 ± 10.83 | 20–74 |
| Gender | ||
| Female | 1325 (66.18) | – |
| Male | 660 (32.97) | – |
| Transgender | 17 (0.85) | – |
| Education levels | ||
| High school or below | 220 (10.97) | – |
| Bachelor's degree | 1159 (57.81) | – |
| Master's degree and above | 626 (31.22) | – |
| Healthcare workers | ||
| No | 1358 (67.73) | – |
| Yes | 647 (32.27) | – |
| Physician | 265 (40.96) | – |
| Nurse | 123 (19.01) | – |
| Therapists | 72 (11.13) | – |
| Others or unknown | 187 (28.90) | – |
| Time period of participation (days) | 76.70 (9.52) | 59.79–105.14 |
| COVID-19 information sources (high-frequency) | ||
| Internet media | 1616 (80.52) | – |
| Traditional media | 1056 (52.62) | – |
| Family members | 489 (24.36) | – |
| Coworkers | 473 (23.57) | – |
| Friends | 423 (21.08) | – |
| Academic courses | 405 (20.18) | – |
| Medical staffs | 382 (19.03) | – |
| Worry of infection | ||
| Past worry | 1.59 ± 1.00 | 0–4 |
| Current worry | 6.13 ± 2.25 | 1–10 |
| Anticipated worry | 2.93 ± 0.92 | 0–4 |
Abbreviations: SD, standard deviation; N, sample size.
Healthcare workers contained two missing values.
Sociodemographic profiles among groups receiving COVID-19 information from different sources.
| Variable | Information sources | |||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Internet media | Traditional media | Family members | Coworkers | Friends | Academic course | Medical staffs | ||||||||
| Low | High | Low | High | Low | High | Low | High | Low | High | Low | High | Low | High | |
| Mean (SD) | ||||||||||||||
| Age | 40.58 (11.85) | 37.02 (10.46) | 36.84 (11.11) | 38.51 (10.51) | 37.86 (10.68) | 37.28 (11.28) | 37.86 (11.14) | 37.27 (9.75) | 38.02 (10.98) | 36.58 (10.20) | 37.37 (10.84) | 39.09 (10.68) | 37.49 (11.00) | 38.69 (10.05) |
| N (%) | ||||||||||||||
| Gender | ||||||||||||||
| Female | 236 (60.51) | 1089 (67.56) | 588 (62.09) | 737 (69.86) | 968 (63.94) | 357 (73.16) | 982 (64.18) | 343 (72.67) | 1039 (65.72) | 286 (67.93) | 1055 (66.02) | 270 (66.83) | 1061 (65.45) | 264 (69.29) |
| Male | 151 (38.72) | 509 (31.58) | 348 (36.75) | 312 (29.57) | 530 (35.01) | 130 (26.64) | 533 (34.84) | 127 (26.91) | 527 (33.33) | 133 (31.59) | 530 (33.17) | 130 (32.18) | 548 (33.81) | 112 (29.4) |
| Transgender | 3 (0.77) | 14 (0.87) | 11 (1.16) | 6 (0.57) | 16 (1.06) | 1 (0.2) | 15 (0.98) | 2 (0.42) | 15 (0.95) | 2 (0.48) | 13 (0.81) | 4 (0.99) | 12 (0.74) | 5 (1.31) |
| Education levels | ||||||||||||||
| High school or below | 60 (15.35) | 160 (9.91) | 90 (9.46) | 130 (12.33) | 153 (10.09) | 67 (13.73) | 167 (10.9) | 53 (11.21) | 178 (11.24) | 42 (9.95) | 186 (11.63) | 34 (8.4) | 184 (11.34) | 36 (9.42) |
| Bachelor's degree | 206 (52.69) | 953 (59.05) | 561 (58.99) | 598 (56.74) | 881 (58.08) | 278 (56.97) | 877 (57.25) | 282 (59.62) | 914 (57.74) | 245 (58.06) | 931 (58.19) | 228 (56.3) | 931 (57.36) | 228 (59.69) |
| Master's degree and above | 125 (31.97) | 501 (31.04) | 300 (31.55) | 326 (30.93) | 483 (31.84) | 143 (29.3) | 488 (31.85) | 138 (29.18) | 491 (31.02) | 135 (31.99) | 483 (30.19) | 143 (35.31) | 508 (31.3) | 118 (30.89) |
| Healthcare workers | ||||||||||||||
| No | 250 (63.94) | 1103 (68.34) | 647 (68.03) | 706 (66.98) | 1006 (66.32) | 347 (71.11) | 1127 (73.56) | 226 (47.78) | 1083 (68.41) | 270 (63.98) | 1213 (75.81) | 140 (34.57) | 1252 (77.14) | 101 (26.44) |
| Yes | 141 (36.06) | 511 (31.66) | 304 (31.97) | 348 (33.02) | 511 (33.68) | 141 (28.89) | 405 (26.44) | 247 (52.22) | 500 (31.59) | 152 (36.02) | 387 (24.19) | 265 (65.43) | 371 (22.86) | 281 (73.56) |
Abbreviations: SD, standard deviation; N, sample size.
P-value threshold (0.007) was adjusted based on Bonferroni method for different information sources.
P < 0.007.
Due to the scarceness of transgender participants (n = 17), the analysis between gender and COVID-19 information sources did not include them.
Impacts of information sources on worry about COVID-19.
| Information sources | Past worry | Current worry | Anticipated worry |
|---|---|---|---|
| Regression coefficient (standard error) | |||
| Internet media | 0.06 (0.06) | 0.27 (0.13) | 0.11 (0.05) |
| Traditional media | 0.09 (0.05) | 0.30 (0.11) | 0.05 (0.05) |
| Family members | 0.01 (0.06) | 0.18 (0.13) | 0.04 (0.05) |
| Coworkers | 0.05 (0.07) | 0.16 (0.15) | 0.04 (0.06) |
| Friends | 0.18 (0.06) | 0.30 (0.14) | 0.04 (0.06) |
| Academic courses | −0.15 (0.07) | −0.30 (0.16) | −0.17 (0.07) |
| Medical staffs | 0.04 (0.08) | 0.05 (0.18) | −0.001 (0.07) |
The general linear model is adjusted by age, gender, education levels, healthcare workers, and time period of participation (days).
P value of academic courses to current worry was 0.07.
P < 0.05.
P < 0.01.