The DOI matches its Crossref record; 44 of the 44 references it cites were found in a registry or an index.
The impact of fake news on social media and its influence on health during the COVID-19 pandemic: a systematic review
Open accessAbstract
Purpose As the new coronavirus disease propagated around the world, the rapid spread of news caused uncertainty in the population. False news has taken over social media, becoming part of life for many people. Thus, this study aimed to evaluate, through a systematic review, the impact of social media on the dissemination of infodemic knowing and its impacts on health. Methods A systematic search was performed in the MedLine, Virtual Health Library (VHL), and Scielo databases from January 1, 2020, to May 11, 2021. Studies that addressed the impact of fake news on patients and healthcare professionals around the world were included. It was possible to methodologically assess the quality of the selected studies using the Loney and Newcastle–Ottawa Scales. Results Fourteen studies were eligible for inclusion, consisting of six cross-sectional and eight descriptive observational studies. Through questionnaires, five studies included measures of anxiety or psychological distress caused by misinformation; another seven assessed feeling fear, uncertainty, and panic, in addition to attacks on health professionals and people of Asian origin. Conclusion By analyzing the phenomenon of fake news in health, it was possible to observe that infodemic knowledge can cause psychological disorders and panic, fear, depression, and fatigue.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Wang, C., Pan, R., Wan, X., Tan, Y., Xu, L., Ho, C. S., & Ho, R. C. (2020) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph17051729 · Cited by 9,923
Huang, Y., & Zhao, N. (2020) · Psychiatry Research · doi:10.1016/j.psychres.2020.112954 · Cited by 3,736 · cited 2×
“This is contradicted in two previous studies by Huang and Zhao (2020) and Wang et al. (2020); when evaluating the psychological impact of the uncontrolled spread of COVID-19, they realized that the manifestations of anxiety and psychological outbreaks were more common especially in the younger…”
BackgroundResultMethley, A. M., Campbell, S., Chew-Graham, C., McNally, R., & Cheraghi-Sohi, S. (2014) · BMC Health Services Research · doi:10.1186/s12913-014-0579-0 · Cited by 2,706
Galea, S., Merchant, R. M., & Lurie, N. (2020) · JAMA Internal Medicine · doi:10.1001/jamainternmed.2020.1562 · Cited by 2,089
Less than you think: Prevalence and predictors of fake news dissemination on Facebook
Guess, A., Nagler, J., & Tucker, J. (2019) · Science Advances · doi:10.1126/sciadv.aau4586 · Cited by 1,652
Susceptibility to misinformation about COVID-19 around the world
Roozenbeek, J., Schneider, C. R., Dryhurst, S., Kerr, J., Freeman, A. L. J., Recchia, G., van der Bles, A. M., & van der Linden, S. (2020) · Royal Society Open Science · doi:10.1098/rsos.201199 · Cited by 1,447
A Novel Coronavirus Emerging in China — Key Questions for Impact Assessment
Munster, V. J., Koopmans, M., van Doremalen, N., van Riel, D., & de Wit, E. (2020) · New England Journal of Medicine · doi:10.1056/nejmp2000929 · Cited by 1,415
The pandemic of social media panic travels faster than the COVID-19 outbreak
Depoux, A., Martin, S., Karafillakis, E., Preet, R., Wilder-Smith, A., & Larson, H. (2020) · Journal of Travel Medicine · doi:10.1093/jtm/taaa031 · Cited by 1,068
Depression and Anxiety in Hong Kong during COVID-19
Choi, E. P. H., Hui, B. P. H., & Wan, E. Y. F. (2020) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph17103740 · Cited by 893
(2020) · doi:10.2196/19556 · Cited by 753
Cited by
Deng, J., Zhou, F., Hou, W., Heybati, K., Lohit, S., Abbas, U., Silver, Z., Wong, C. Y., Chang, O., Huang, E., et al. (2023) · Annals of the New York Academy of Sciences · doi:10.1111/nyas.14947 · Cited by 283
Typology of Risks of Generative Text-to-Image Models
Bird, C., Ungless, E., & Kasirzadeh, A. (2023) · Proceedings of the 2023 AAAI/ACM Conference on AI, Ethics, and Society · doi:10.1145/3600211.3604722 · Cited by 121
Kops, M., Schittenhelm, C., & Wachs, S. (2025) · Computers in Human Behavior · doi:10.1016/j.chb.2025.108650 · Cited by 39
The impact of confirmation bias awareness on mitigating susceptibility to misinformation
Piksa, M., Noworyta, K., Gundersen, A., Kunst, J., Morzy, M., Piasecki, J., & Rygula, R. (2024) · Frontiers in Public Health · doi:10.3389/fpubh.2024.1414864 · Cited by 20
Motta, M., Hwang, J., & Stecula, D. (2024) · Health Communication · doi:10.1080/10410236.2023.2254583 · Cited by 11
Metadata
- Authors
- Rocha, Y. M., de Moura, G. A., Desidério, G. A., de Oliveira, C. H., Lourenço, F. D., & de Figueiredo Nicolete, L. D.
- Venue
- Journal of Public Health
- Published
- 2021-10-09
- Volume
- 31
- Issue
- 7
- Pages
- 1007-1016
- ISSN
- 0943-1853 (ISSN-L)
- 2198-1833
- 1613-2238
- OpenAlex
- W3205958211
- Cited by
- 482
- References
- 44
- FWCI
- 18.99
- Type
- journal article
- Language
- en
- Open access
- bronze
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: The impact of fake news on social media and its influence on health during the COVID-19 pandemic: a systematic review. https://app.cochat.ai/papers/10.1007/s10389-021-01658-z
- The paper
- Rocha, Y. M., de Moura, G. A., Desidério, G. A., de Oliveira, C. H., Lourenço, F. D., & de Figueiredo Nicolete, L. D. (2023). The impact of fake news on social media and its influence on health during the COVID-19 pandemic: a systematic review. Journal of Public Health. https://doi.org/10.1007/s10389-021-01658-z
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.