Topics, concerns, and feelings commented on Facebook after the first death by COVID-19 in Mozambique

Temas, preocupaciones y sentimientos comentados en Facebook tras la primera muerte por COVID-19 en Mozambique

Published 2023-03-24

Open | Download
HTML Icon XML Icon
Issue
Vol. 5 No. 1 (2023)
Section
Research Article
How to Cite
1.
Topics, concerns, and feelings commented on Facebook after the first death by COVID-19 in Mozambique. Rev. Investig. Innov. Cienc. Salud [Internet]. 2023 Mar. 24 [cited 2024 Dec. 21];5(1):in press. Available from: https://riics.info/index.php/RCMC/article/view/165
DOI

https://doi.org/10.46634/riics.165
Dimensions
PlumX
license
Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Gérson Muitana
Department of Psychology; Faculty of Education; Eduardo Mondlane University; Maputo; Mozambique
    https://orcid.org/0000-0002-0724-6607
    Cibelle Amato
    Center for Biological and Health Sciences; Mackenzie Presbyterian University; Sao Paulo-SP; Brazil
      https://orcid.org/0000-0003-2422-6998
      Show authors biography

      In Mozambique, as in other parts of the world, COVID-19 has had consequences in many areas, especially in the health sector. This study aims to analyze the comments made and discussed on Facebook after the first death from the disease, verifying the main topics, concerns, and feelings that users most expressed on that social network. Using the content analysis method, IRaMuTeQ® generated a dendrogram focused on death, diagnostic circumstances, disease prevention, and restrictive government measures. Users also raised concerns about health care professionals, family and community, and feelings of sadness. Although the feelings presented reflect the language used in comments on a social network, and it is impossible to diagnose from them, this study creates paths for further research in the area. Therefore, for the first time, it demonstrates results from a mental health study with data analyzed from a social network in Mozambique. These results can guide and alert local health entities about health communications, strategies, and attention that should be given to the mental health of individuals during this pandemic and in the long term.

      Article visits 617 | PDF visits 98

      1. World Health Organization [WHO]. WHO Coronavirus (COVID-19) Dashboard. WHO; 2022. Available from: https://covid19.who.int/info (accessed March 21, 2023).
      2. Dyer O. Covid-19: Africa records over 10 000 cases as lockdowns take hold. BMJ 2020;369:1–1. doi: https://doi.org/10.1136/bmj.m1439
      3. Obi-Ani NA, Anikwenze C, Isiani MC. Social media and the Covid-19 pandemic: Observations from Nigeria. Cogent Arts Humanit. 2020;7. doi: https://doi.org/10.1080/23311983.2020.1799483
      4. MOÇAMBIQUE. Conselho de Ministros. Boletim da República. Maputo: Imprensa Nacional de Moçambique; 2020.
      5. MOÇAMBIQUE. Ministério da Saúde. Comunicado diário de actualização de casos de coronavirus. Maputo: MISAU. Maputo; 2020.
      6. Cox CR, Swets JA, Gully B, Xiao J, Yraguen M. Death Concerns, Benefit-Finding, and Well-Being During the COVID-19 Pandemic. Front Psychol. 2021;12:1–11. doi: https://doi.org/10.3389/fpsyg.2021.648609
      7. Nicola M, Alsafi Z, Sohrabi C, Kerwan A, Al-Jabir A, Iosifidis C, et al. The socio-economic implications of the coronavirus pandemic (COVID-19): A review. Int J Surg. 2020;78:185–93. doi: https://doi.org/10.1016/j.ijsu.2020.04.018
      8. Masciantonio A, Bourguignon D, Bouchat P, Balty M, Rimé B. Don’t put all social network sites in one basket: Facebook, Instagram, Twitter, TikTok, and their relations with well-being during the COVID-19 pandemic. PLoS One. 2021;16:1–14. doi: https://doi.org/10.1371/journal.pone.0248384
      9. Sarkadi A, Sahlin Torp L, Pérez-Aronsson A, Warner G. Children’s Expressions of Worry during the COVID-19 Pandemic in Sweden. J Pediatr Psychol. 2021;46:939–49. doi: https://doi.org/10.1093/jpepsy/jsab060
      10. Carvalho PM de M, Moreira MM, Oliveira MNA de, Landim JMM, Neto MLR. The psychiatric impact of the novel coronavirus outbreak. Psychiatry Res. 2020;286:1–2. doi: https://doi.org/10.1016/j.psychres.2020.112902
      11. Wang C, Pan R, Wan X, Tan Y, Xu L, Ho C, et al. Immediate Psychological Responses and Associated Factors during the Initial Stage of the 2019 Coronavirus Disease (COVID-19) Epidemic among the General Population in China. Int J Environ Res Public Health. 2020;17:1–25. doi: https://doi.org/10.3390/ijerph17051729
      12. Wu T, Jia X, Shi H, Niu J, Yin X, Xie J, et al. Prevalence of mental health problems during the COVID-19 pandemic: A systematic review and meta-analysis. J Affect Disord. 2021;281:91–8. doi: https://doi.org/10.1016/j.jad.2020.11.117
      13. Sinnenberg L, Buttenheim AM, Padrez K, Mancheno C, Ungar L, Merchant RM. Twitter as a tool for health research: A systematic review. Am J Public Health. 2017;107(1):e1–8. doi: https://doi.org/10.2105/AJPH.2016.303512
      14. Clement J. Facebook - statistics & facts. Statista 2022. https://www.statista.com/topics/751/facebook (accessed January 1, 2023).
      15. Oh HJ, Ozkaya E, Larose R. How does online social networking enhance life satisfaction? the relationships among online supportive interaction, affect, perceived social support, sense of community, and life satisfaction. Comput Human Behav. 2014;30:69–78. doi: https://doi.org/10.1016/j.chb.2013.07.053
      16. Paula FR de, Mello MG da S. Análise de Redes Sociais: a formação de grupos do Facebook frente à epidemia da COVID-19 no Brasil. VITTALLE - Rev Ciências Da Saúde. 2020;32(1):32–42. doi: https://doi.org/10.14295/vittalle.v32i1.11406
      17. Crisóstomo S, Matos AR, Borges M, Santos M. O Facebook faz bem à saúde? O caso “MAIS PARTICIPAÇÃO melhor saúde” em Portugal. Rev Bras Pesqui Em Saúde. 2019;21:123–33. doi: https://doi.org/10.21722/rbps.v21i2.29085
      18. Raamkumar AS, Tan SG, Wee HL. Measuring the Outreach Efforts of Public Health Authorities and the Public Response on Facebook during the COVID-19 Pandemic in Early 2020: Cross-Country Comparison. J Med Internet Res. 2020;22(5):e19334. doi: https://doi.org/10.2196/19334
      19. Revez J. Redes sociais e sociais e desinformação na saúde: o caso do facebook. Rev EDICIC. 2022;2(3):1–21.
      20. Pang PCI, Cai Q, Jiang W, Chan KS. Engagement of government social media on facebook during the COVID-19 pandemic in Macao. Int J Environ Res Public Health. 2021;18(7):14–7. doi: https://doi.org/10.3390/ijerph18073508
      21. Ribeiro PEO. COVID-19 and DGS on Facebook: analyzing Health in images and written text. J Semiot Cult. 2020;2021(10):7–20. doi: https://doi.org/10.25768/21.04.04.10.06
      22. Li X, Zhou M, Wu J, Yuan A, Wu F, Li J. Analyzing COVID-19 on Online Social Media: Trends, Sentiments and Emotions. ArXiv. 2020;3:1–9. doi: https://doi.org/10.48550/arXiv.2005.14464
      23. Chang A, Xian X, Liu MT, Zhao X. Health Communication through Positive and Solidarity Messages Amid the COVID-19 Pandemic: Automated Content Analysis of Facebook Uses. Int J Environ Res Public Health. 2022;19(10). doi: https://doi.org/10.3390/ijerph19106159
      24. Hung M, Lauren E, Hon ES, Birmingham WC, Xu J, Su S, et al. Social network analysis of COVID-19 sentiments: Application of artificial intelligence. J Med Internet Res. 2020;22(8):1–19. doi: https://doi.org/10.2196/22590
      25. Islam MS, Sarkar T, Khan SH, Kamal AHM, Murshid Hasan SM, Kabir A, et al. COVID-19-Related infodemic and its impact on public health: A global social media analysis. Am J Trop Med Hyg. 2020;103(4):1621–9. doi: https://doi.org/10.4269/ajtmh.20-0812
      26. Tan SG, Sesagiri Raamkumar A, Wee HL. Users’ Beliefs Toward Physical Distancing in Facebook Pages of Public Health Authorities During COVID-19 Pandemic in Early 2020. Heal Educ Behav. 2021;48(4):404–11. doi: https://doi.org/10.1177/10901981211014428
      27. Valdez D, ten Thij M, Bathina K, Rutter LA, Bollen J. Social media insights into US mental health during the COVID-19 pandemic: Longitudinal analysis of twitter data. J Med Internet Res. 2020;22(12):1–18. doi: https://doi.org/10.2196/21418
      28. Hsieh HF, Shannon SE. Three approaches to qualitative content analysis. Qual Health Res. 2005;15(9):1277–88. doi: https://doi.org/10.1177/1049732305276687
      29. Pandarachalil R, Sendhilkumar S, Mahalakshmi GS. Twitter Sentiment Analysis for Large-Scale Data: An Unsupervised Approach. Cognit Comput. 2015;7:254–62. doi: https://doi.org/10.1007/s12559-014-9310-z
      30. Júnior JG, Sales JP, Silva FCT, Filho JDQ, Cavalcanti RCPB, Landim JMM, et al. Análise da saúde mental da população carcerária na pandemia de Sars-Cov-2: análise qualitativa. Psychiatry Res. 2021;296:113669. doi: https://doi.org/10.1016/j.psychres.2020.113669
      31. Reinert M. Alceste une méthodologie d’analyse des données textuelles et une application: Aurelia De Gerard De Nerval. Bull Méthodologie Sociol. 1990;26(1):24–54. doi: https://doi.org/10.1177/075910639002600103
      32. Camargo BV, Justo AM. Tutorial para uso do software IRaMuteQ. Florianópolis: Laboratório de Psicologia Social da Comunicação e Cognição - UFSC – Brasil; 2018.
      33. Loubère L, Ratinaud P. Documentation IRaMuTeQ 0.6 alpha 3 version 0.1. Toulouse, France: Plone & Python; 2014.
      34. Lahlou S. Text mining methods: an answer to Chartier and Meunier. Pap Soc Represent. 2012;20(2):1–7.
      35. Ahmed MS, Aurpa TT, Anwar MM. Detecting sentiment dynamics and clusters of Twitter users for trending topics in COVID-19 pandemic. PLoS One. 2021;16(8):1–20. doi: https://doi.org/10.1371/journal.pone.0253300
      36. Cai R, Zhang J, Li Z, Zeng C, Qiao S. Using Twitter Data to Estimate the Prevalence of Symptoms of Mental Disorders in the United States During the COVID-19 Pandemic: Ecological Cohort Study. JMIR Publications. 2022;6(12):1–11. doi: https://doi.org/10.2196/37582
      37. Keller SN, Honea JC, Ollivant R. How social media comments inform the promotion of mask-wearing and other covid-19 prevention strategies. Int J Environ Res Public Health. 2021;18(11):Article5624. doi: https://doi.org/10.3390/ijerph18115624
      38. Correia RB, Wood IB, Bollen J, Rocha LM. Mining Social Media Data for Biomedical Signals and Health-Related Behavior. Annual Review of Biomedical Data Science [Internet]. 2020 Jul 20;3(1):433–58. doi: http://dx.doi.org/10.1146/annurev-biodatasci-030320-040844
      39. Kaila RP, Prasad AVK. Informational Flow on Twitter - Corona Virus Outbreak – Topic. Int J Adv Res Eng Technol. 2020;11:128–34.
      40. Berry N, Emsley R, Lobban F, Bucci S. Social media and its relationship with mood, self-esteem and paranoia in psychosis. Acta Psychiatr Scand. 2018;138(6):558–70. doi: https://doi.org/10.1111/acps.12953
      41. Obiała J, Obiała K, Mańczak M, Owoc J, Olszewski R. COVID-19 misinformation: Accuracy of articles about coronavirus prevention mostly shared on social media. Heal Policy Technol. 2021;10(1):182–6. doi: https://doi.org/10.1016/j.hlpt.2020.10.007
      42. Bekele D, Tolossa T, Tsegaye R, Teshome W. The knowledge and practice towards COVID-19 pandemic prevention among residents of Ethiopia. An online cross-sectional study. PLoS One. 2021;16:1–13. doi: https://doi.org/10.1371/journal.pone.0234585
      43. Rao LN, Shetty A, Latha Senthilkumar P, Shetty KS, Shetty B, Natarajan S, et al. Knowledge, attitude and practice of dental students and practitioners during the early days of COVID-19 pandemic in India: A cross-sectional study. Int J Clin Pract. 2021;75(11):1–10. doi: https://doi.org/10.1111/ijcp.14858
      44. Liu Q, Luo D, Haase JE, Guo Q, Wang XQ, Liu S, et al. The experiences of health-care providers during the COVID-19 crisis in China: a qualitative study. Lancet Glob Heal. 2020;8(6):e790–8. doi: https://doi.org/10.1016/S2214-109X(20)30204-7
      45. Silva SM, Rosa AR. The impact of Covid-19 on the students’ mental health and the role of teaching institutions to protect and promote their emotional well-being. Praksis. 2021;2:189–206. doi: https://doi.org/10.25112/RPR.V2I0.2446
      46. Li Q, Guan X, Wu P, Wang X, Zhou L, Tong Y, et al. Early Transmission Dynamics in Wuhan, China, of Novel Coronavirus–Infected Pneumonia. N Engl J Med. 2020;382:1199–207. doi: https://doi.org/10.1056/nejmoa2001316
      47. Lwin MO, Lu J, Sheldenkar A, Schulz PJ, Shin W, Gupta R, et al. Global sentiments surrounding the COVID-19 pandemic on Twitter: Analysis of Twitter trends. JMIR Public Heal Surveill. 2020;6(2):1–4. doi: https://doi.org/10.2196/19447
      48. Curcio CSS, Moreira-Almeida A. Investigação dos conceitos de religiosidade e espiritualidade em amostra clínica e não clínica em contexto brasileiro: Uma análise qualitativa. Interação Em Psicol. 2019;23(2):281–92. doi: https://doi.org/10.5380/psi.v23i02.65434
      49. Moore CA, Ruisch BC, Granados Samayoa JA, Boggs ST, Ladanyi JT, Fazio RH. Contracting COVID-19: a longitudinal investigation of the impact of beliefs and knowledge. Sci Rep. 2021;11:1–12. doi: https://doi.org/10.1038/s41598-021-99981-8
      50. Carvalho KM, Silva CRDT, Felipe SGB, Gouveia MT de O. A crença em saúde na adoção de medidas de prevenção e controle da COVID-19. Rev Bras Enferm. 2010;74(1):1–4. doi: https://doi.org/10.1590/0034-7167-2020-0576
      51. Vasco SADJ. Aplicabilidade do marketing digital como meio de promoção do marketing social em meio à pandemia da covid-19 no contexto moçambicano. Rev Cient UEM. 2020:1–10.
      Publish with RIICS

      Scimago

      Most read in the last 30 days

      Sistema OJS 3.4.0.7 - Metabiblioteca |