Language in a Time of COVID-19: Literacy Bias Ethnic Minorities Face During COVID-19 from Online Information in the UK

Sobia Khan,Ashar Asif, Ali Emad Jaffery

JOURNAL OF RACIAL AND ETHNIC HEALTH DISPARITIES(2020)

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摘要
Objectives To investigate the readability and presence of translated online information readily available to the British public during COVID-19. Design A cross-sectional study was performed. The terms “Coronavirus”, “COVID-19”, “Lockdown”, “Social Distancing”, “Handwashing”, “Furlough Scheme” and “Sick pay” were inputted into the popular search engine, Google. Websites were categorised by their source (i.e. Government, Non-Governmental Organisation, NHS and Commercial) and theme (i.e. general COVID-19 information, population practise and employment rulings). Reliable calculators for assessing readability (Simple Measure of Gobbledygook, Gunning Fog Index, Flesch-Kincaid Grade Level, Coleman-Liau Index and Automated Readability Index) were used. Main Outcome Measures The median scores with the interquartile range from each calculator of the pooled data were observed. The presence of accompanying translated material and graphic information was also counted and presented as counts and percentages. The number of readable websites (i.e. a score ≤ 8) for each source and theme category were also recorded. Setting UK Internet servers. Results The median scores of the pooled data ( n = 148) had shown that the majority of websites were unreadable to the average British reader according to each calculator used (SMOG 1.3%; GF 6.8%; FK 35.8%; CL 2.6%; ARI 40%). Only 3.4% and 6.8% of the pooled websites had readily available translated material and accompanying graphic material, respectively. Conclusion Readability of COVID-19 information is below national standards and that there is a lack of accompanying translated and graphics-based material online. This may lead to an amplified level of misunderstanding in BAME populations about the COVID-19 pandemic and the rulings put in place.
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关键词
Coronavirus, COVID-19, SARS-CoV2, Pandemic, BAME
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