Análise de série temporal de informações do governo sobre COVID-19 nas redes sociais e o número de novos casos durante os primeiros 6 meses da pandemia: o caso do Brasil

Autores

DOI:

https://doi.org/10.33448/rsd-v10i16.23797

Palavras-chave:

COVID-19; Comunicação em saúde; Educação em saúde; Acesso à informação de Saúde; Rede social.

Resumo

Este estudo retrospectivo buscou avaliar a associação entre a evolução da pandemia de COVID-19 no Brasil e a qualidade dos materiais educativos publicados nos perfis oficiais dos órgãos governamentais de saúde brasileiros no Instagram. As postagens sobre COVID-19, publicadas entre 31 de janeiro e 15 de agosto de 2021, foram selecionadas, datadas, quantificadas e classificadas de acordo com seu conteúdo por três pesquisadoras. O engajamento do público foi calculado pelo número de curtidas, comentários e visualizações. A qualidade das postagens educativas foi avaliada por duas pesquisadoras treinados e calibradas (Kappa intra e inter-examinadores, k=0.96 e k=0.92, respectivamente), utilizando a versão brasileira do Índice de Comunicação Clara (BR-CDC-CCI), o número de casos novos do COVID-19 foi coletado através da calculadora epidêmica Covid-19 fornecida pela OPAS, no site https:// covid-calc.org/. A relação entre a evolução do indicador da COVID-19 e a qualidade das postagens educativas foi calculada através do modelo estatístico de uma série temporal quinzenal. Em média, as postagens educativas alcançaram 6,4 no escore BR-CDC-CCI (mediana = 6,5). No modelo múltiplo ajustado pela quantidade de publicações disponibilizadas e engajamento do público, observou-se que a cada aumento de um ponto no escore BR-CDC-CCI, houve uma redução de 327.864 novos casos de Covid-19 (p <0,001). Concluiu-se que houve relação entre a baixa qualidade das postagens e o maior número de novos casos da doença, assinalando a necessidade de maior atenção por parte de órgãos governamentais brasileiros com a qualidade das informações disponibilizadas nas redes sociais para auxiliar no controle da pandemia de COVID-19.

Referências

Brazil. (1988). Constituição da República Federativa do Brazil (Senado Federal).

Centers for Disease Control and Prevention. (2009, April). Simply put; a guide for creating easy-to-understand materials (3rd ed.). https://stacks.cdc.gov/view/cdc/11938

Centers for Disease Control and Prevention. (2010). National Action Plan to Improve Health Literacy | Health Literacy. https://www.cdc.gov/healthliteracy/planact/national.html

Centers for Disease Control and Prevention. (2019). CDC clear communication index : a tool for developing and assessing CDC public communication products : user guide. https://stacks.cdc.gov/view/cdc/107490

COVID-19 in Brazil: “So what?” [Editorial]. (2020, May 9). The Lancet, 395(10235), 1461. https://doi.org/10.1016/S0140-6736(20)31095-3

Daraz, L., Morrow, A., Ponce, O., Farah, W., Katabi, A., Majzoub, A., Seisa, M., Benkhadra, R., Alsawas, M., Larry, P., & Murad, M. (2018). Readability of Online Health Information: A Meta-Narrative Systematic Review. American Journal of Medical Quality : The Official Journal of the American College of Medical Quality, 33(5), 487–492. https://doi.org/10.1177/1062860617751639

de Melo Cunha, M. A. G., Lino, P. A., Dos Santos, T. R., Vasconcelos, M., Lucas, S. D., & de Abreu, M. H. N. G. (2015). A 15-year time-series study of tooth extraction in Brazil. Medicine, 94(47).

Fleary, S., Joseph, P., & Pappagianopoulos, J. (2018). Adolescent health literacy and health behaviors: A systematic review. Journal of Adolescence, 62, 116–127. https://doi.org/10.1016/J.ADOLESCENCE.2017.11.010

Garcia, P., Fera, J., Mohlman, J., & Basch, C. H. (2021). Assessing the Readability of COVID-19 Testing Messages on the Internet. Journal of Community Health, 46, 913-917. https://doi.org/10.1007/S10900-021-00973-6

Geboers, B., Reijneveld, S., Jansen, C., & de Winter, A. (2016). Health Literacy Is Associated With Health Behaviors and Social Factors Among Older Adults: Results from the LifeLines Cohort Study. Journal of Health Communication, 21(sup2), 45–53. https://doi.org/10.1080/10810730.2016.1201174

Johns Hopkins University & Medicine. Coronavirus Resource Center.(2021). COVID-19 Dashboard by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University (JHU). https://coronavirus.jhu.edu/map.html

Korda, H., & Itani, Z. (2013). Harnessing social media for health promotion and behavior change. Health Promotion Practice, 14(1), 15–23. https://doi.org/10.1177/1524839911405850

Levin-Zamir D, Bertschi I. (2018) Media Health Literacy, eHealth Literacy, and the Role of the Social Environment in Context. Int J Environ Res Public Health, 15(8), 1643. https://doi.org/10.3390/ijerph15081643.

Limaye, R., Sauer, M., Ali, J., Bernstein, J., Wahl, B., Barnhill, A., & Labrique, A. (2020). Building trust while influencing online COVID-19 content in the social media world. The Lancet. Digital Health, 2(6), e277–e278. https://doi.org/10.1016/S2589-7500(20)30084-4

Liu, Y., Liu, L., Li, Y., & Chen, Y. (2015). Relationship between Health Literacy, Health-Related Behaviors and Health Status: A Survey of Elderly Chinese. International Journal of Environmental Research and Public Health, 12(8), 9714–9725. https://doi.org/10.3390/IJERPH120809714

Loeb, S., Taylor, J., Borin, J., Mihalcea, R., Perez-Rosas, V., Byrne, N., Chiang, A. L., & Langford, A. (2020). Fake News: Spread of Misinformation about Urological Conditions on Social Media. European Urology Focus, 6(3), 437–439. https://doi.org/10.1016/J.EUF.2019.11.011

Marinho, A., Faur, C., Ferreira, F., Borges-Oliveira, A., & Abreu, M. (2020). Cross-cultural adaptation of the Clear Communication Index to Brazilian Portuguese. Revista de Saude Publica, 54(26). https://doi.org/10.11606/S1518-8787.2020054001561

McClure, E., NG, J., Vitzthum, K., & Rudd, R. (2016). A Mismatch Between Patient Education Materials About Sickle Cell Disease and the Literacy Level of Their Intended Audience. Preventing Chronic Disease, 13(5). https://doi.org/10.5888/PCD13.150478

Pang, P., Cai, Q., Jiang, W., & Chan, K. (2021). Engagement of Government Social Media on Facebook during the COVID-19 Pandemic in Macao. International Journal of Environmental Research and Public Health, 18(7), 3508. https://doi.org/10.3390/IJERPH18073508

Park, C.L., Russell, B.S., Fendrich, M., Finkelstein-Fox, L., Hutchison, M., Becker, J. (2020) Americans' COVID-19 Stress, Coping, and Adherence to CDC Guidelines. J Gen Intern Med , 35(8), 2296-2303. https://doi.org/0.1007/s11606-020-05898-9.

R Core Team. (2020). R: The R Project for Statistical Computing. (Version 4.0.3) [Computer Software]. https://www.r-project.org/

Roberts, M., Callahan, L., & O’Leary, C. (2017). Social Media: A Path to Health Literacy . Stud Health Technol Inform, 240, 464–475. https://pubmed.ncbi.nlm.nih.gov/28972534/

Schillinger, D., Chittamuru, D., & Ramírez, A. S. (2020). From “Infodemics” to Health Promotion: A Novel Framework for the Role of Social Media in Public Health. American Journal of Public Health, 110(9), 1393. https://doi.org/10.2105/AJPH.2020.305746

Sørensen, K., Pelikan, J., Röthlin, F., Ganahl, K., Slonska, Z., Doyle, G., Fullam, J., Kondilis, B., Agrafiotis, D., Uiters, E., Falcon, M., Mensing, M., Tchamov, K., van den Broucke, S., Brand, H., HLS-EU Cosortium. (2015). Health literacy in Europe: comparative results of the European health literacy survey (HLS-EU).

European Journal of Public Health, 25(6), 1053–1058. https://doi.org/10.1093/EURPUB/CKV043

Shumway, R. H. & Stoffer, D. S. (2010). Time series analysis and its applications (Vol. 3). New York: springer.

Takla M, Jeevaratnam K. (2020) Chloroquine, hydroxychloroquine, and COVID-19: Systematic review and narrative synthesis of efficacy and safety. Saudi Pharm J, 28(12), 1760-1776. https://doi.org/10.1016/j.jsps.2020.11.003.

United States Government. (2010). An act to enhance citizen access to Government information and services by establishing that Government documents issued to the public must be written clearly, and for other purposes. https://www.govinfo.gov/content/pkg/PLAW-111publ274/html/PLAW-111publ274.htm

Wardle, C., & Derakhshan, H. (2017). Information disorder: Toward an interdisciplinary framework for research and policy making. Council of Europe. https://edoc.coe.int/en/media/7495-information-disorder-toward-an-interdisciplinary-framework-for-research-and-policy-making.html

Wojtowicz, A. (2020). Addressing Health Misinformation with Health Literacy Strategies: Proceedings of a Workshop—in Brief. National Academies of Sciences, Engineering, and Medicine. Washington, DC: The National Academies Press. https://doi.org/10.17226/26021

World Health Organization. (2020). 1st WHO Infodemiology Conference. How infodemics affect the world & how it can be managed. https://www.who.int/news-room/events/detail/2020/06/30/default-calendar/1st-who-infodemiology-conference

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Publicado

17/12/2021

Como Citar

SILVA, L. da .; MARINHO, A. M. C. L.; BRAGA, N. S. .; SANTOS , T. R. dos; ABREU, M. H. N. G. de .; ASSUNÇÃO, C. M.; FERREIRA , F. M. Análise de série temporal de informações do governo sobre COVID-19 nas redes sociais e o número de novos casos durante os primeiros 6 meses da pandemia: o caso do Brasil. Research, Society and Development, [S. l.], v. 10, n. 16, p. e501101623797, 2021. DOI: 10.33448/rsd-v10i16.23797. Disponível em: https://rsdjournal.org/index.php/rsd/article/view/23797. Acesso em: 17 jul. 2024.

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Seção

Ciências da Saúde