| Literature DB >> 35732387 |
Ashley Lindsay Quigley1, Mallory Trent2, Holly Seale3, Abrar Ahmad Chughtai3, C Raina MacIntyre2.
Abstract
OBJECTIVES: Since mask uptake and the timing of mask use has the potential to influence the control of the COVID-19 pandemic, this study aimed to assess the changes in knowledge toward mask use in Sydney and Melbourne, Australia, during the 2020 COVID-19 pandemic.Entities:
Keywords: COVID-19; epidemiology; public health
Mesh:
Year: 2022 PMID: 35732387 PMCID: PMC9226465 DOI: 10.1136/bmjopen-2021-057860
Source DB: PubMed Journal: BMJ Open ISSN: 2044-6055 Impact factor: 3.006
Figure 1Frequency percentage of COVID-19 risk-control measures from March 2020 to April 2020.
Figure 2Percentage changes of the COVID-19 risk-control measures from March 2020 to July 2020.
Figure 3Percentage changes of the COVID-19 risk-control measures from March 2020 to September 2020.
Predictors of mask uptake during the pandemic in Sydney and Melbourne in 2020
| N (%) | OR (95% CI) | P value | |
| Age (<45.711 years)* | 384 (54.86) | 0.67 (0.50 to 0.91) | 0.011 |
| Gender (male) | 348 (49.71) | 1.00 (0.74 to 1.35) | 1.000 |
| City of residence (Sydney, reference) | 402 (57.43) | – | – |
| Melbourne | 298 (42.57) | 1.24 (0.99 to 1.22) | 0.072 |
| Barriers to wearing a mask | |||
| Felt embarrassed to wear it | 59 (8.43) | 0.24 (0.10 to 0.54) | 0.001 |
| People stared at me | 41 (5.86) | 0.48 (0.15 to 1.52) | 0.212 |
| I received negative comments | 26 (3.71) | 0.87 (0.29 to 2.64) | 0.804 |
| I received racist comments | 25 (3.57) | 0.43 (0.05 to 3.98) | 0.458 |
| People thought I was infected | 25 (3.57) | 0.46 (0.18 to 1.20) | 0.114 |
| People laughed at me | 13 (1.86) | 0.39 (0.11 to 1.40) | 0.148 |
| Factors which influenced mask wearing | |||
| A recommendation from government or health department | 315 (45.0) | 1.83 (1.32 to 2.53) | <0.000 |
| How much infection is around at the time | 203 (29.0) | 1.45 (1.00 to 2.09) | 0.049 |
| Media information (TV, radio, internet and print) | 144 (20.57) | 0.83 (0.54 to 1.29) | 0.405 |
| A recommendation from friends or family members | 124 (17.71) | 1.22 (0.76 to 1.95) | 0.405 |
| A recommendation from my doctor | 118 (16.86) | 1.45 (0.92 to 2.29) | 0.106 |
| Experience with using these products | 86 (12.29) | 2.32 (1.35 to 4.00) | 0.002 |
| Social media (Facebook, Twitter, Instagram, etc) | 65 (9.29) | 0.86 (0.44 to 1.65) | 0.644 |
| Perceived COVID-19 severity >average* | 348 (49.71) | 1.96 (1.44 to 2.66) | <0.000 |
| Perceived risk of getting COVID-19 >average* | 442 (63.14) | 1.98 (1.43 to 2.74) | <0.000 |
| High trust in state government‡ | 446 (63.71) | 1.62 (1.19 to 2.22) | 0.003 |
| High trust in national government‡ | 470 (67.14) | 1.77 (1.29 to 2.44) | <0.000 |
*Average refers to the population mean of each variable. Variables were coded as ‘1’ if their values were larger than the population mean and coded as ‘0’ if smaller than the population mean.
†Indicates statistical significance at p≤0.05 (logistic regression used for analysis).
‡On a scale of 0–5, where ‘5’ represents highest level of trust/confidence. Variables were coded as ‘1’(high) if their values were larger than 3 and coded as ‘0’ if smaller than or equal to 3.