| Literature DB >> 36062247 |
Israel Júnior Borges do Nascimento1, Ana Beatriz Pizarro2, Jussara M Almeida3, Natasha Azzopardi-Muscat4, Marcos André Gonçalves3, Maria Björklund5, David Novillo-Ortiz4.
Abstract
Objective: To compare and summarize the literature regarding infodemics and health misinformation, and to identify challenges and opportunities for addressing the issues of infodemics.Entities:
Mesh:
Year: 2022 PMID: 36062247 PMCID: PMC9421549 DOI: 10.2471/BLT.21.287654
Source DB: PubMed Journal: Bull World Health Organ ISSN: 0042-9686 Impact factor: 13.831
Fig. 1Selection of systematic reviews on infodemics and health misinformation
Summary of included reviews on infodemics and health misinformation
| Review, year | No. of databases (names) | No. of studies (study types) | Study objective |
|---|---|---|---|
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| Abbott et al., 2022 | 8 (PubMed®, Epistemonikos, Cochrane Library of Systematic Reviews, Cochrane COVID-19 Study Register, Embase®, CINAHL, Web of Science and WHO databases) | 280 (systematic reviews, overviews and meta-analysis) | To map the nature, scope and quality of evidence syntheses on COVID-19 and to explore the relationship between review quality and the extent of researcher, policy and media interest |
| Alvarez-Galvez et al., 2021 | 7 (Scopus, MEDLINE®, Embase®, CINAHL, Sociological Abstracts, Cochrane Library of Systematic Reviews and grey literaturea) | 42 (quantitative and qualitative studies and mixed-methods studies) | To identify the factors that make possible the spread of medical and health misinformation during outbreaks and to reveal the needs and future directions for the development of new protocols that might contribute to the assessment and control of information quality in future infodemics |
| Aruhomukama & Bulafu, 2021 | 2 (PubMed® and CINAHL) | 10 (quantitative and qualitative studies) | To interrogate and integrate knowledge levels and media sources of information findings of the studies on knowledge, attitudes, perceptions and practices towards COVID-19 done in low- and middle-income countries in Africa |
| Bhatt et al., 2021 | 4 (MEDLINE®, Embase®, Cochrane Databases and Google) | 5 (quantitative and qualitative studies) | To assess the current use of social media in clinical practice guidelines dissemination across different medical specialties |
| Eckert et al., 2018 | 8 (PubMed®, Web of Science, CINAHL, CINAHL Complete, Communication and Mass Media Complete, PsychInfo®, WHO databases and Google Scholar) along with social media companies' reports | 79 (quantitative and qualitative studies and case studies) | To conduct a systematic review on the extant literature on social media use during all phases of a disaster cycle |
| Gabarron et al., 2021 | 5 (PubMed®, Scopus, Embase®, PsychInfo® and Google Scholar) | 22 (mixed-methods studies) | To review misinformation related to COVID-19 on social media during the first phase of the pandemic and to discuss ways to counter misinformation |
| Gunasekeran et al., 2022 | 3 (PubMed®, including MEDLINE® and Institute of Electrical and Electronics Engineers Xplore) | 35 (quantitative and qualitative studies) | To highlight a brief history of social media in health care and report its potential negative and positive public health impacts |
| Lieneck et al., 2022 | 2 (EBSCO host and PubMed®) | 25 (quantitative and qualitative studies) | To identify common facilitators and barriers in the literature which influence the promotion of vaccination against COVID-19 |
| Muhammed & Mathew, 2022 | 7 (Web of Science, ACM digital library, AIS electronic library, EBSCO host, ScienceDirect, Scopus and Springer link) | 28 (quantitative and qualitative studies) | To identify relevant literature on the spread of misinformation |
| Patel et al., 2020 | 6 (all databases of Web of Science, PubMed®, ProQuest, Google News, Google and Google Scholar) | 35 | To canvas the ways disinformation about COVID-19 is being spread in Ukraine, so as to form a foundation for assessing how to mitigate the problem |
| Pian et al., 2021 | 12 (PubMed®, CINAHL Complete, PsychInfo®, Psych Articles, ScienceDirect, Wiley Online Library, Web of Science, EBSCO, Communication & Mass Media Complete Library, Information Science & Technology Abstracts and Psychology & Behavioral Sciences Collection) | 251 (quantitative and qualitative studies) | To synthesize the existing literature on the causes and impacts of the COVID-19 infodemic |
| Rocha et al., 2021 | 3 (MEDLINE®, Virtual Health Library and Scielo) | 14 (quantitative and qualitative studies) | To evaluate the impact of social media on the dissemination of infodemic knowing and its impacts on health |
| Suarez-Lledo & Alvarez-Galvez, 2021 | 2 (MEDLINE® and PREMEDLINE) | 69 (policy briefs and technical reports) | To identify the main health misinformation topics and their prevalence on different social media platforms, focusing on methodological quality and the diverse solutions that are being implemented to address this public health concern |
| Tang et al., 2018 | 5 (PubMed®, PsychInfo®, CINAHL Plus, ProQuest® and Communication Source) | 30 (quantitative and qualitative studies) | To better understand the status of existing research on emerging infectious diseases communication on social media |
| Truong et al., 2022 | 4 (PsychInfo®, MEDLINE®, Global Health and Embase®) | 28 (quantitative and qualitative studies) | To examine the factors that promote vaccine hesitancy or acceptance during pandemics, major epidemics and global outbreaks |
| Walter et al., 2021 | 7 (Communication Source, Education Resources Information Center, Journal Storage, MEDLINE®, ProQuest, PubMed® and Web of Science) | 24 (quantitative and qualitative studies) | To evaluate the relative impact of social media interventions designed to correct health-related misinformation |
| Wang et al., 2019 | 5 (PubMed®, Cochrane Library of Systematic Reviews, Web of Science, Scopus and Google Scholar) | 57 (mixed-methods studies) | To uncover the current evidence and better understand the 47 mechanisms of misinformation spread |
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| Adu et al., 2021 | NA | NA | To estimate COVID-19 vaccine uptake and hesitancy rates for before-and-after the first COVID-19 vaccine was approved by FDA |
| Dong et al., 2022 | NA | NA | To review and synthesize the findings from qualitative studies conducted in different countries on the emergence, spread and consequences of false and misleading information about the pandemic |
| Fazeli et al., 2021 | NA | NA | Awaiting classification (limited access to the full-text file) |
| Gentile et al., 2021 | NA | NA | Awaiting classification (limited access to the full-text file) |
| Goldsmith et al., 2022 | NA | NA | To determine the extent and nature of social media use in migrant and ethnic minority communities for COVID-19 information and implications for preventative health measures including vaccination intent and uptake |
| Hilberts et al., 2021 | NA | NA | To establish the risk of health misinformation in social media to public health |
| Karimi-Shahanjarin et al., 2021 | NA | NA | To identify what initiatives and policies have been suggested and implemented to respond to and alleviate the harm caused by misinformation and disinformation concerning COVID-19 |
| McGowan & Ekeigwe, 2021 | NA | NA | To assess if exposure to misinformation or disinformation influence health information-seeking behaviours |
| Pauletto et al., 2021 | NA | NA | To evaluate what are pros and cons of using social media during the COVID-19 pandemic |
| Pimenta et al., 2020 | NA | NA | To gather evidence on the impact of information about COVID-19 on the mental health of the population |
| Prabhu & Nayak, 2021 | NA | NA | To appraise what are the effects of the COVID-19 media based infodemic on mental health of general public |
| Trushna et al., 2021 | NA | NA | To undertake a mixed-methods systematic review exploring COVID-19 stigmatization, in terms of differences in experience and/or perception of different population sub-groups exposed to COVID-19, its mediators including media communications, coping strategies adopted to deal with such stigmata and the consequences in terms of health effects and health-seeking behaviour of affected individuals |
| Vass et al., 2022 | NA | NA | Awaiting classification (limited access to the full-text file) |
| Zhai et al., 2021 | NA | NA | To provide an overview of the current state of research concerning individual-level psychological and behavioural response to COVID-19-related information from different sources, as well as presenting the challenges and future research directions |
COVID-19: coronavirus disease 2019; FDA: Food and Drug Administration; NA: not applicable; WHO: World Health Organization.
a There was an inconsistency between the used databases provided in the study’s abstract and those presented in the methods section. We considered the databases shown in the methods section.
Summary of findings
| Review (disease and/or condition) | Summary of findings |
|---|---|
| Abbott et al. (SARS-CoV-2) | • Overlap of published studies related to SARS-CoV-2 between 10 and 15 June 2020 (for example, 16 reviews addressed cerebrovascular-related comorbidities and COVID-19, as well as 13 reviews evaluating the broad topic related to chloroquine and hydroxychloroquine). |
| Alvarez-Galvez et al. (SARS, H1N1 and H7N9 influenza viruses, Ebola virus, Zika virus, Dengue virus, generic diseases, poliomyelitis) | • The authors identified five determinants of infodemics: (i) information sources; (ii) online communities' structure and consensus; (iii) communication channels; (iv) message content; and (v) health emergency context. |
| Aruhomukama & Bulafu (SARS-CoV-2) | • Forty per cent of included studies showed that nearly all of the respondents had heard about COVID-19, while only one included study stated that participants had inadequate knowledge of COVID-19. |
| Bhatt et al. (neurological, gastrointestinal, cardiovascular and urological diseases) | • Based on included studies, there was a significant improvement in knowledge, awareness, compliance, and positive behaviour towards clinical practice guidelines with the use of social media dissemination compared to standard methods. |
| Eckert et al. (disaster communication) | • Each social media platform used for information streaming is beneficial during crisis communication for government agencies, implementing partners, first responders, and the public to create two-way conversations to exchange information, create situational awareness and facilitate delivery of care. |
| Gabarron et al. (SARS-CoV-2) | • Six of 22 studies that reported the proportion of misinformation related to SARS-CoV-2 showed that misinformation was presented on 0.2% (413/212 846) to 28.8% (194/673) of posts. |
| Gunasekeran et al. (SARS-CoV-2 and COVID-19) | • The exponential potential of social media for information dissemination has been strategically used for positive impact in the past. They can be applied to reinvigorate public health promotion efforts and raise awareness about diseases. |
| Lieneck et al. (SARS-CoV-2 and COVID-19) | • One of the largest barriers to vaccine promotion through social media during the COVID-19 pandemic has been misinformation spread on social media. |
| Muhammed & Mathew (COVID-19, Australian Bushfire and the USA elections) | • When a crisis occurs, affected communities often experience a lack of localized information needed for them to make emergency decisions. |
| Patel et al. (SARS-CoV-2) | • The disinformation related to crisis communication about COVID-19 was focused on eroding trust in the government’s response and the accuracy of the official health messaging or misleading the public about accessing and receiving resources or support. |
| Pian et al. (COVID-19) | • Social media use and low level of health and/or eHealth literacy were identified as the major causes of the infodemic. |
| Rocha et al. (COVID-19) | • Infodemic can cause psychological disorders and panic, fear, depression and fatigue. |
| Suarez-Lledo & Alvarez-Galvez (vaccines, smoking, drugs, noncommunicable diseases, COVID-19, diet and eating disorders) | • Health topics were ubiquitous on all social media platforms included in the study. However, the health misinformation proportion for each topic varied depending on platform characteristics. |
| Tang et al. (H1N1 and H7N9 influenza viruses, Ebola virus, West Nile virus, measles, MERS-CoV and enterohaemorrhagic | • In general, approximately 65% (225/344) of videos contained useful information (either accurate medical information or outbreak updates) across different emerging infectious diseases, while the rest of videos contained inaccurate or misleading information. Whether misleading videos had a significantly higher number of views per day is unclear. |
| Truong et al. (vaccination, H1N1 and Ebola) | • Lack of information and misinformation about vaccination against H1N1 influenced participants’ decision to vaccinate. |
| Walter et al. (countermeasures against misinformation) | • The meta-analysis showed that source of misinformation emerged as a significant moderator ( |
| Wang et al. (vaccination, Ebola virus and Zika virus, along with other conditions and topics, including nutrition, cancer and smoking) | • Misinformation is abundant on the internet and is often more popular than accurate information. |
CI: confidence interval; COVID-19: coronavirus disease 2019; H1N1: influenza A virus subtype H1N1; H7N9: Asian lineage avian influenza A H7N9; HIV: human immunodeficiency virus; MERS-CoV: Middle East respiratory syndrome coronavirus; SARS: severe acute respiratory syndrome; SARS-CoV-2: severe acute respiratory syndrome coronavirus 2.
a Numbers are reported as given in original publication despite that the percentage is inconsistent with numerator and denominator.
Quality of included systematic reviews on infodemics and health misinformation
| Review | Methodological requirements met, by domaina | Overall quality | |||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | 14 | 15 | 16 | ||
| Abbott et al. | Yes | Partly met | Yes | Partly met | Yes | No | No | Partly met | No | No | NA | NA | No | Yes | NA | Yes | Critically low |
| Alvarez-Galvez et al. | Yes | No | Yes | No | Yes | No | No | Partly met | Yes | No | NA | NA | No | No | NA | Yes | Critically low |
| Aruhomukama & Bulafu | Yes | No | No | No | Yes | No | No | Partly met | Yes | No | NA | NA | No | No | NA | Yes | Critically low |
| Bhatt et al. | Yes | Partly met | Yes | Partly met | Yes | Yes | No | Partly met | Partly met | No | NA | NA | No | No | NA | Yes | Critically low |
| Eckert et al. | Yes | No | Yes | Yes | No | No | No | Partly met | Yes | No | NA | NA | Yes | No | NA | No | Critically low |
| Gabarron et al. | Yes | Partly met | Yes | Partly met | Yes | Yes | Yes | Yes | Yes | No | NA | NA | Yes | No | NA | Yes | Low |
| Gunasekeran et al. | Yes | No | No | No | No | No | No | No | No | No | NA | NA | No | No | NA | Yes | Critically low |
| Lieneck et al. | Yes | No | Yes | No | Yes | No | No | Partly met | Yes | No | NA | NA | No | No | NA | Yes | Critically low |
| Muhammed & Mathew | Yes | No | Yes | Partly met | Yes | Yes | No | Partly met | Partly met | No | NA | NA | No | Yes | NA | Yes | Critically low |
| Patel et al. | Yes | Partly met | Yes | Partly met | No | No | No | Partly met | No | No | NA | NA | No | No | NA | No | Critically low |
| Pian et al. | Yes | No | Yes | Partly met | Yes | Yes | No | Partly met | No | Yes | NA | NA | Yes | No | NA | Yes | Critically low |
| Rocha et al. | Yes | No | Yes | Partly met | No | No | No | Partly met | No | No | NA | NA | No | No | NA | No | Critically low |
| Suarez-Lledo & Alvarez-Galvez | Yes | Partly met | Yes | Partly met | Yes | Yes | No | Partly met | Yes | No | NA | NA | No | No | NA | Yes | Critically low |
| Tang et al. | Yes | Partly met | Yes | No | No | No | No | Partly met | No | No | NA | NA | No | No | NA | No | Critically low |
| Truong et al. | Yes | No | No | No | Yes | Yes | No | No | No | No | NA | NA | No | No | NA | Yes | Critically low |
| Walter et al. | Yes | Partly met | Yes | Partly met | Yes | Yes | No | Partly met | Yes | No | Yes | Yes | No | Yes | Yes | No | Critically low |
| Wang et al. | Yes | Partly met | Yes | No | No | No | No | Partly met | No | No | NA | NA | No | No | NA | No | Critically low |
NA: not applicable.
Note: We judged studies using the AMSTAR 2 tool. For domains rated NA, the review lacked a meta-analysis.
a Domain 1: did the research questions and inclusion criteria for the review include the components of PICO (population, intervention, comparator and outcomes)? Domain 2: did the report of the review contain an explicit statement that the review methods were established before the conduct of the review and did the report justify any significant deviations from the protocol? Domain 3: did the review authors explain their selection of the study designs for inclusion in the review? Domain 4: did the review authors use a comprehensive literature search strategy? Domain 5: did the review authors perform study selection in duplicate? Domain 6: did the review authors perform data extraction in duplicate? Domain 7: did the review authors provide a list of excluded studies and justify the exclusions? Domain 8: did the review authors describe the included studies in adequate detail? Domain 9: did the review authors use a satisfactory technique for assessing the risk of bias in individual studies that were included in the review? Domain 10: did the review authors report on the sources of funding for the studies included in the review? Domain 11: if meta-analysis was performed did the review authors use appropriate methods for statistical combination of results? Domain 12: if meta-analysis was performed, did the review authors assess the potential impact of risk of bias in individual studies on the results of the meta-analysis or other evidence synthesis? Domain 13: did the review authors account for risk of bias in individual studies when interpreting/discussing the results of the review? Domain 14: did the review authors provide a satisfactory explanation for, and discussion of, any heterogeneity observed in the results of the review? Domain 15: if they performed quantitative synthesis did the review authors carry out an adequate investigation of publication bias (small study bias) and discuss its likely impact on the results of the review? Domain 16: did the review authors report any potential sources of conflict of interest, including any funding they received for conducting the review?
Certainty of the evidence of main outcomes
| Theme (no. of systematic reviews) | Certainty of the evidence (GRADE) | |||||
|---|---|---|---|---|---|---|
| Methodological limitationsa | Inconsistencyb | Indirectnessc | Imprecisionc | Publication biasd | Overall quality | |
| Negative effects of misinformation (10) | Critical | Not serious | NA | NA | Not serious | Lowe |
| Source of health misinformation (6) | Critical | Not serious | NA | NA | Not serious | Lowf |
| Proportion of health-related misinformation (4) | Critical | Serious | NA | NA | Not serious | Very lowg |
| Beneficial features of social media use (8) | Critical | Not serious | NA | NA | Not serious | Lowf |
| Corrective interventions against health misinformation (4) | Critical | Not serious | Not serious | NA | Not serious | Lowf |
| Characteristics associated with studies’ quality (3) | Critical | Not serious | NA | NA | Not serious | Lowf |
GRADE: Grading of Recommendations Assessment, Development and Evaluation; NA: not applicable.
a Methodological limitations were essentially associated with the overall AMSTAR 2 rating.
b Inconsistency was judged by evaluating the consistency of the direction and primarily the difference in the magnitude of effects across studies (since statistical measures of heterogeneity are not available). As we did not find differing results for each outcome across included studies, we considered “not serious” risk for inconsistency, except for the “Proportion of health misinformation on social media,” as previously mentioned.
c We did not downgrade the indirectness and imprecision domains for most outcomes because they were not referring to any applicable intervention on human beings or health condition. Thus, we marked it as “Not applicable.” For the only outcome associated with an intervention (Corrective interventions for health misinformation), we considered it to be at “not serious” risk of indirectness because there was an adequate association between the evidence presented and review question.
d We downgraded the publication bias domain if the body of literature appears to selectively evidence a certain topic or trend from a specific outcome.
e Downgraded due to methodological limitations of the included systematic reviews (most included reviews had an overall critically low methodological quality).
f Downgraded due to methodological limitations of the studies (most included reviews had an overall critically low methodological quality).
g Downgraded due to methodological limitations of the studies (most included reviews had an overall critically low methodological quality), and inconsistency (studies had widely differing estimates of the proportion, indicating inconsistency in reporting).
h Social media also serves as a place where health-care professionals fight against false beliefs and misinformation on emerging infectious diseases.
Note: Low certainty by the GRADE Working Group grades of evidence: the summary rating of the included studies provides some indication of the likely effect. The likelihood that the effect will be substantially different is high. Very low certainty: the summary rating of the included studies does not provide a reliable indication of the likely effect. The likelihood that the effect will be substantially different is very high.