COVID-19 Information on Youtube: Analysis of Quality and Reliability of Videos in Eleven Widely Spoken Languages Across Africa

• DOI: 10.2139/ssrn.4034493
• Publication Date: 2022-02-17T12:35:32Z
• Authors: Kapil Narain; Kingsley Appiah B...; O’Neil Kosasia Wa...; Oloruntoba Ogunfo...; Nelson Udeme-Abasi U; Anirban Dutta; Ayodeji Ogunleye; Eileen van der We...; Emmanuel Eni; Almthani Hamza; Samuel Mesfin; Aimée Bernice Mun...; Nazo Nxumalo; Okuhle Xozwa
• Keywords: Artificial intelligence; Sociology and Political Science; Social Sciences; Epistemology; 02 engineering and technology; Quantum mechanics; Amharic; 03 medical and health sciences; 0302 clinical medicine; Computer security; FOS: Mathematics; 0202 electrical engineering, electronic engineering, information engineering; Humans; Language; Modeling the Dynamics of COVID-19 Pandemic; Physics; COVID-19; Reproducibility of Results; The Spread of Misinformation Online; Immunization Coverage; Power (physics); Computer science; FOS: Philosophy, ethics and religion; 3. Good health; Philosophy; Reliability (semiconductor); Health; Modeling and Simulation; Africa; Physical Sciences; Misinformation; Quality (philosophy); Factors Affecting Vaccine Hesitancy and Acceptance; Medicine; Public aspects of medicine; RA1-1270; Social Media; Mathematics; Research Article

Introduction. Whilst the coronavirus disease 2019 (COVID-19) vaccination rollout is well underway, there is a concern in Africa where less than 2% of global vaccinations have occurred. In the absence of herd immunity, health promotion remains essential. YouTube has been widely utilised as a source of medical information in previous outbreaks and pandemics. There are limited data on COVID-19 information on YouTube videos, especially in languages widely spoken in Africa. This study investigated the quality and reliability of such videos. Methods. Medical information related to COVID-19 was analysed in 11 languages (English, isiZulu, isiXhosa, Afrikaans, Nigerian Pidgin, Hausa, Twi, Arabic, Amharic, French, and Swahili). Cohen’s Kappa was used to measure inter-rater reliability. A total of 562 videos were analysed. Viewer interaction metrics and video characteristics, source, and content type were collected. Quality was evaluated using the Medical Information Content Index (MICI) scale and reliability was evaluated by the modified DISCERN tool. Results. Kappa coefficient of agreement for all languages was p < 0.01 . Informative videos (471/562, 83.8%) accounted for the majority, whilst misleading videos (12/562, 2.13%) were minimal. Independent users (246/562, 43.8%) were the predominant source type. Transmission of information (477/562 videos, 84.9%) was most prevalent, whilst content covering screening or testing was reported in less than a third of all videos. The mean total MICI score was 5.75/5 (SD 4.25) and the mean total DISCERN score was 3.01/5 (SD 1.11). Conclusion. YouTube is an invaluable, easily accessible resource for information dissemination during health emergencies. Misleading videos are often a concern; however, our study found a negligible proportion. Whilst most videos were fairly reliable, the quality of videos was poor, especially noting a dearth of information covering screening or testing. Governments, academic institutions, and healthcare workers must harness the capability of digital platforms, such as YouTube to contain the spread of misinformation.