Published on in Vol 25 (2023)

Preprints (earlier versions) of this paper are available at, first published .
Defining Misinformation and Related Terms in Health-Related Literature: Scoping Review

Defining Misinformation and Related Terms in Health-Related Literature: Scoping Review

Defining Misinformation and Related Terms in Health-Related Literature: Scoping Review


1Outcomes and Implementation Research Unit, Department of Internal Medicine, University of Kansas Medical Center, Kansas City, KS, United States

2Clinical Research Institute, Faculty of Medicine, American University of Beirut, Beirut, Lebanon

3Division of Cardiology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, United States

4University Libraries, American University of Beirut, Beirut, Lebanon

5Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON, Canada

6Department of Family Medicine, Queens University, Kingston, ON, Canada

7Institute of Media Research and Training, Lebanese American University, Beirut, Lebanon

8Department of Internal Medicine, American University of Beirut, Beirut, Lebanon

*these authors contributed equally

Corresponding Author:

Reem A Mustafa, MD, PhD

Outcomes and Implementation Research Unit

Department of Internal Medicine

University of Kansas Medical Center

3901 Rainbow Blvd, MS3002

Kansas City, KS, 66160

United States

Phone: 1 913 588 6048


Background: Misinformation poses a serious challenge to clinical and policy decision-making in the health field. The COVID-19 pandemic amplified interest in misinformation and related terms and witnessed a proliferation of definitions.

Objective: We aim to assess the definitions of misinformation and related terms used in health-related literature.

Methods: We conducted a scoping review of systematic reviews by searching Ovid MEDLINE, Embase, Cochrane, and Epistemonikos databases for articles published within the last 5 years up till March 2023. Eligible studies were systematic reviews that stated misinformation or related terms as part of their objectives, conducted a systematic search of at least one database, and reported at least 1 definition for misinformation or related terms. We extracted definitions for the terms misinformation, disinformation, fake news, infodemic, and malinformation. Within each definition, we identified concepts and mapped them across misinformation-related terms.

Results: We included 41 eligible systematic reviews, out of which 32 (78%) reviews addressed the topic of public health emergencies (including the COVID-19 pandemic) and contained 75 definitions for misinformation and related terms. The definitions consisted of 20 for misinformation, 19 for disinformation, 10 for fake news, 24 for infodemic, and 2 for malinformation. “False/inaccurate/incorrect” was mentioned in 15 of 20 definitions of misinformation, 13 of 19 definitions of disinformation, 5 of 10 definitions of fake news, 6 of 24 definitions of infodemic, and 0 of 2 definitions of malinformation. Infodemic had 19 of 24 definitions addressing “information overload” and malinformation had 2 of 2 definitions with “accurate” and 1 definition “used in the wrong context.” Out of all the definitions, 56 (75%) were referenced from other sources.

Conclusions: While the definitions of misinformation and related terms in the health field had inconstancies and variability, they were largely consistent. Inconstancies related to the intentionality in misinformation definitions (7 definitions mention “unintentional,” while 5 definitions have “intentional”). They also related to the content of infodemic (9 definitions mention “valid and invalid info,” while 6 definitions have “false/inaccurate/incorrect”). The inclusion of concepts such as “intentional” may be difficult to operationalize as it is difficult to ascertain one’s intentions. This scoping review has the strength of using a systematic method for retrieving articles but does not cover all definitions in the extant literature outside the field of health. This scoping review of the health literature identified several definitions for misinformation and related terms, which showed variability and included concepts that are difficult to operationalize. Health practitioners need to exert caution before labeling a piece of information as misinformation or any other related term and only do so after ascertaining accurateness and sometimes intentionality. Additional efforts are needed to allow future consensus around clear and operational definitions.

J Med Internet Res 2023;25:e45731



Misinformation has long plagued both the public sphere and the scientific community, but it has become particularly ubiquitous after the advent of social media [1]. Scientists and policy makers have recognized its rise and harmful effects as major challenges in the 21st century [2,3]. Misinformation has exacerbated political and religious persecution, hate crimes, climate change, interference in elections, and most recently, the global response to the COVID-19 pandemic [4-8].

Considering people from various social groupings increasingly consume health information via web-based platforms [9], their exposure to health misinformation increases [1,10,11]. Although these platforms can be valuable for health promotion, they can spread false and misleading health information faster than scientific knowledge, raising serious public health concerns [10,12-14]. A recent systematic review found 6 main categories of health misinformation spreading on social media: vaccinations (32%), drugs or smoking (22%), noncommunicable diseases (19%), pandemics (10%), eating disorders (9%), and medical treatments (7%) [10].

Over the past 2 years, the COVID-19 pandemic was associated with what the World Health Organization (WHO) called “an infodemic” [15]. The Director General of the WHO noted [16]:

We’re not just fighting an epidemic; we’re fighting an infodemic, [that] spreads faster and more easily than this virus.

Despite social media organizations’ efforts to limit false health information on the internet [17], COVID-19 misinformation spread unabated [1]. This prompted United Nations agencies to issue warnings against the rapid dissemination of myths, hazardous and untested prevention methods, and fictitious cures that threaten global mitigation plans and put many people’s lives in peril [18-20]. The phenomenon prompted an increase in scientific research about countering and mitigating health misinformation.

Although it dates back to the late 1500s, the term misinformation was selected as the word of the year in 2018 [21]. The Merriam-Webster Dictionary defines it as “false information that is spread, regardless of whether there is intent to mislead.” However, researchers use a growing vocabulary to describe this phenomenon, which includes disinformation, infodemic, malinformation, inaccurate information, misleading information, and conspiracy theories. Inconsistent definitions have also proliferated, which may negatively affect scientific communication and research conceptualization [22]. The objective of this study is to assess definitions of misinformation and related terms used in health research.

Search Strategy

We searched the following 4 electronic databases up till March 6, 2023: MEDLINE (using Ovid), Embase, Cochrane, and Epistemonikos. The search strategy included both controlled vocabularies (eg, MeSH and Emtree) and keywords related to (1) the term “misinformation,” which included “infodemic,” “false news,” “disinformation” and (2) “systematic reviews.” We limited the search to reviews addressing misinformation and published within the past 5 years, starting from January 1, 2017. The final search strategies were developed with the help of an expert librarian after pilot testing with seed articles. The full search strategy for each database is provided in Multimedia Appendix 1.

Eligibility Criteria

In this study, we included review articles that stated misinformation or related terms as part of their objectives. A review was eligible if it conducted a systematic search of at least 1 database and reported on at least 1 definition for misinformation or related terms. Although the search was not restricted to English reviews, all of the eligible reviews were in English. We included qualitative and quantitative reviews. We excluded all abstracts, nonreviews, narrative reviews without any database search, studies not focusing on misinformation or related terms, studies unrelated to health, and reviews not providing any definition. Textbox 1 summarizes the eligibility criteria used in this scoping review.

Textbox 1. Eligibility criteria for scoping review.

Inclusion criteria

  • Review articles
  • No restrictions to language
  • No restriction to type (qualitative/quantitative)
  • Stating misinformation or related terms as part of review objectives
  • Systematic search of at least 1 database
  • Reported on at least 1 definition for misinformation or related terms
  • Related to health

Exclusion criteria

  • Abstracts and nonreviews
  • Studies that do not address misinformation or related terms or with minimal mentioning
  • Narrative reviews without any database search
  • Reviews not providing any definition
  • Unrelated to health

Study Selection

Three reviewers (IKE, RH, and TH) worked in teams of 2, in duplicate and independently, to screen for potential eligibility of the titles and abstracts of the articles captured by the search. After obtaining the full texts of articles judged as potentially eligible, reviewers included eligible reviews. The principal investigator served as a third independent reviewer for resolving disagreements.

Data Extraction

Teams of 2 review authors extracted the data from each included review in duplicate and independently. We used a standardized data abstraction form in Excel (Microsoft Corp). We met regularly to discuss progress and resolve any discrepancy through discussion. We abstracted definitions for misinformation and related terms (see Multimedia Appendix 2 [23-61]). We also abstracted the following information for each review: specific health topic, number of searched databases, and the misinformation themes addressed (see Table 1).

Table 1. General characteristics of the included systematic reviews (N=41).
Variablen (%)
Health topic

Public health emergencies (including COVID-19)32 (78)

General health7 (18)

Smoking and vaping1 (2)

Atopic dermatitis1 (2)
Number of databases searcheda

≥232 (78)

19 (22)
Terms for which a definition was providedb

Misinformation20 (49)

Disinformation19 (46)

Fake news10 (24)

Infodemic24 (59)

Malinformation2 (5)
Misinformation themes addressedb

Pathway of misinformationc13 (32)

Implications of misinformation8 (20)

Solutions or interventions16 (39)

Epidemiology of misinformation3 (7)

Topic-specific examples of misinformation2 (5)

aGoogle and Google Scholar searches were considered gray literature and not as database.

bNumbers add up to more than 41 as some reviews address more than 1 theme and concept.

cThis theme addresses the mechanisms from the creation to the dissemination of misinformation.

Data Synthesis

We used content data analysis to identify concepts within the identified definitions. After reading through the definitions several times to obtain a sense of all the definitions, we derived codes that captured key concepts [62]. We used deductive coding to map the definition concepts for each of the misinformation-related terms (see Table 2). Refinements to the language of the definition featured were done after discussions with all authors. When available, the source of the reported definition was noted, and the most used source was tracked (see Table 3).

Table 2. Mapping definition concepts to terms of misinformation, disinformation, fake news, infodemic, and malinformation.
Definition conceptaMisinformation (20 definitions), nDisinformation (19 definitions), nFake news (10 definitions), nInfodemic (24 definitions), nMalinformation (2 definition), n
Information overloadb119
Valid and invalid info9
Clearly unsubstantiated/verifiably false331
Based on expert opinion2
Used in the wrong context1
Political reasons52
Purpose to instill doubt21
Purpose to manipulate42
Format of official news4
During a health outbreak, epidemic, or crisis10
Epidemic-like spread4
Causes confusion2

aThe same paper may include more than 1 definition concept.

bNot available.

Table 3. Source of reported definitions around misinformation and related terms from eligible systematic reviews.

Misinformation (20 definitions), n/NDisinformation (19 definitions), n/NFake news (10 definitions), n/NInfodemic (24 definitions), n/NMalinformation (2 definitions), n/NTotal, n/N
Definition not referenced5/206/192/101/241/215/75
Definition referenced+modified1/202/191/100/240/14/75
Definition referenced14/2011/197/1023/241/256/75

Merriam-Webster Dictionary2/142/110/71/230/15/56


Other sources12/149/117/75/231/134/56

aWHO: World Health Organization.

Out of 3633 articles, the study included 41 systematic reviews [23-61,63]. Figure 1 shows the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) flow diagram detailing the results of the search and selection process (refer to Multimedia Appendix 3 for a PRISMA checklist). Thirty-two (78%) reviews addressed the misinformation-related health of public health emergencies (including COVID-19), with other health topics including general health (18%), smoking and vaping (2%), and atopic dermatitis (2%). Thirty-two (78%) reviews included more than 2 databases for retrieving misinformation-related articles. The reviews addressed many misinformation themes, the most common being solutions/interventions (39%), and the least common being topic-specific examples of misinformation in health topics (5%; Table 1). The definitions extracted from the 41 included reviews consisted of 20 for misinformation, 19 for disinformation, 10 for fake news, 24 for infodemic, and 2 for malinformation (see Multimedia Appendix 2).

Figure 1. PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) 2020 flow diagram.

The definitions of each misinformation-related term contained definition concepts. Out of the 20 misinformation definitions, 15 definitions mentioned “false/inaccurate/incorrect,” 7 mentioned “unintentional,” and 5 mentioned “intentional.” Out of the 19 definitions for disinformation, 13 mentioned “false/inaccurate/incorrect” and 15 mentioned “intentional.” For fake news, out of the 10 definitions, 5 mentioned “false/inaccurate/incorrect,” 4 mentioned “fabricated,” and 4 mentioned “format of official news.” As for infodemic, out of the 24 definitions, 19 mentioned “information overload,” 9 mentioned “valid and invalid info,” 6 mentioned “false/inaccurate/incorrect” and 10 mentioned “during health outbreak/epidemic/crisis.” Finally, for malinformation, there were 2 definitions and they both mentioned “accurate” and “intentional,” with 1 definition having “used in the wrong context.” For each of the misinformation-related terms, there were additional definition concepts that were less frequently used. This included “fraudulent,” “clearly unsubstantiated/verifiably false,” “misleading,” “based on expert opinion,” “political reasons,” “purpose to instill doubt,” “epidemic-like spread,” and “causes confusion.” Table 2 maps specific concepts of definitions against the different terms being defined.

Out of the 75 definitions used in the reviews, 56 (75%) were referenced from other sources, 15 (20%) were not referenced, and 4 (5%) were referenced from other sources and modified. Out of the 56 referenced definitions, there were 17 (30%) definitions referenced from the WHO and 5 (9%) definitions from the Merriam-Webster Dictionary, with the others being varied resources. The references from WHO all related to the term “infodemic” and accounted for 74% out of the 23 referenced definitions for “infodemic.” None of the reviews provided guidance on operationalizing the reported definitions (eg, further clarifying concepts such as accuracy and intentionality).

Principal Findings

Misinformation poses a challenge to decision-making. In the field of health, this can affect the clinical decision shared by the caregiver and patient and can affect health care policy making if any of the involved parties is misinformed. In this paper, we assess available definitions of misinformation and related terms used in health research systematic reviews. Across the reviews, there were concepts that were generally agreed upon. Misinformation includes false information that may or may not be intentional. Disinformation, on the other hand, includes intentional dissemination of false information. Fake news includes fabricated, false information disseminated in the format of official news. Infodemic is the information overload that happens in the setting of outbreaks or crises. Finally, malinformation includes accurate information that is used in the wrong context.

The definitions of misinformation and related terms in the literature on health are only 1 part of the extant literature. Fields such as political sciences and media have been well aware of this phenomenon and have studied it extensively. The effect of misinformation on the field of health has become clearer with the recent prominent public health crises including climate change and the COVID-19 pandemic. Our results showed that the definitions used in the field of health are consistent in key concepts but continue to show variability and inconsistency in others.

Definitions of misinformation and related terms vary in definition concepts. One of the clear variabilities in the health literature is related to the intentionality of misinformation. Seven definitions characterized misinformation as unintentional, while 5 definitions characterized it oppositely to be intentional. Another example is the definition of infodemic. Although almost all definitions mentioned the information overload concept, 6 definitions restricted it to false information while 9 definitions attributed it to a mix of valid and invalid information. A third example is the “based on expert opinion” definition concept. Only 2 definitions of misinformation included this concept and this is problematic since expert opinion can be considered a form of evidence. This observed variability and discrepancy highlights the importance of performing a formal consensus process in the field of health to reach a consensus around those definitions.

Definitions of misinformation and related terms contain concepts that require operationalization and clarity. Take for example the concepts of “false/inaccurate/incorrect” and the concept of “intentional.” The label of “false/inaccurate/incorrect” depends on how one defines accuracy and whether the certainty or quality of the evidence is considered. Evidence based on low certainty evidence (eg, a single observational case series) would differ from a higher level of certainty (eg, a systematic review of randomized controlled trials). As for intentionality, it is difficult to assess this as it relates to the intentions of the originator. To reliably assign intentionality to a published piece of false information, a researcher would need to investigate the original source and discern their intentions and purposes. This is not possible for much of the circulating misinformation, particularly those with unverifiable sources. These issues highlight that in addition to the need for a formal consensus process to agree on definitions, these definitions need to be clear and operationalized.

This scoping review has its own strengths and limitations. First, we followed a standard methodology for retrieving relevant articles using 4 distinct databases: Ovid MEDLINE, Embase, Cochrane, and Epistemonikos. Second, we used content data analysis to identify concepts of the retrieved definitions and map them across the misinformation-related terms. This scoping review, however, does not represent all definitions of misinformation in the extant literature, particularly from outside the health field. Also, limiting the search to the past 5 years may have resulted in missing relevant reviews published before that timeframe. However, since reviews published in the last 5 years should have included all the previously published original articles and since we are interested in looking at the current issues and definitions related to misinformation, we are not concerned about this limitation.

As for the implications of this work, our assessment of the definitions highlighted the presence of inconsistencies in the available definitions and some concepts that are difficult to operationalize. Health practitioners need to exert caution before labeling a piece of information as misinformation or any other related terms and only do so after ascertaining few characteristics of the piece of information at hand. A question one should ask is “How certain am I that this information is incorrect?” For disinformation, another question to ask is “How certain am I that this information is disseminated with the knowledge that it is incorrect?” Future work is needed to reach a consensus around clear and operational definitions of misinformation and related terms. This includes performing efforts to reach a formal consensus around those definitions and possibly undergoing qualitative exploratory efforts and interviews with stakeholders.


Misinformation poses a serious challenge to clinical and policy decision-making in the health field, both of which rely on accurate and reliable information. In this scoping review, we aimed to assess definitions of misinformation and related terms used in the health-related literature. We identified several definitions for misinformation and related terms that showed variability and included concepts that are not conducive to operationalization. Health practitioners need to exert caution before labeling a piece of information as misinformation or any other related term and only do so after ascertaining few characteristics of the piece of information at hand including the accurateness. Additional research is needed to reach a consensus around clear and operational definitions of misinformation and related terms, in order to more effectively study how misinformation affects health policies and research.


The article processing charges related to the publication of this article were supported by The University of Kansas One University Open Access Author Fund sponsored jointly by the KU Provost, KU Vice Chancellor for Research, and KUMC Vice Chancellor for Research and managed jointly by the Libraries at the Medical Center and KU—Lawrence. The study was conducted without external funding.

Data Availability

All data used for this manuscript can be found in the Multimedia Appendices, including a table of included reviews (Multimedia Appendix 4), a table of excluded reviews (Multimedia Appendix 5), and a table of extracted definitions (Multimedia Appendix 2). RAM affirms that this manuscript is an honest, accurate, and transparent account of the study being reported; that no important aspects of the study have been omitted; and that any discrepancies from the study as planned have been explained.

Conflicts of Interest

None declared.

Multimedia Appendix 1

Search strategies for MEDLINE (using Ovid), Embase, Cochrane, and Epistemonikos.

DOCX File , 34 KB

Multimedia Appendix 2

Extracted definitions of misinformation and related terms from eligible systematic reviews.

DOCX File , 120 KB

Multimedia Appendix 3

PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) checklist.

PDF File (Adobe PDF File), 130 KB

Multimedia Appendix 4

List of included systematic reviews that address misinformation and related terms in health.

DOCX File , 39 KB

Multimedia Appendix 5

List of excluded systematic reviews that address misinformation and related terms in health but do not provide related definitions.

DOCX File , 42 KB

  1. Mian A, Khan S. Coronavirus: the spread of misinformation. BMC Med. Mar 18, 2020;18(1):89. [FREE Full text] [CrossRef] [Medline]
  2. Lewandowsky S, Ecker UKH, Cook J. Beyond misinformation: understanding and coping with the “post-truth” era. J Appl Res Mem Cogn. 2017;6(4):353-369. [CrossRef]
  3. Zarocostas J. How to fight an infodemic. Lancet. 2020;395(10225):676. [FREE Full text] [CrossRef] [Medline]
  4. Bennett WL, Livingston S. The disinformation order: disruptive communication and the decline of democratic institutions. Eur J Commun. 2018;33(2):122-139. [CrossRef]
  5. Roozenbeek J, Schneider CR, Dryhurst S, Kerr J, Freeman ALJ, Recchia G, et al. Susceptibility to misinformation about COVID-19 around the world. R Soc Open Sci. 2020;7(10):201199. [FREE Full text] [CrossRef] [Medline]
  6. Whitten-Woodring J, Kleinberg MS, Thawnghmung A, Thitsar MT. Poison if you don‘t know how to use it: Facebook, democracy, and human rights in Myanmar. Int J Press/Politics. 2020;25(3):407-425. [CrossRef]
  7. Ecker UKH, Lewandowsky S, Cook J, Schmid P, Fazio LK, Brashier N, et al. The psychological drivers of misinformation belief and its resistance to correction. Nat Rev Psychol. 2022;1(1):13-29. [FREE Full text] [CrossRef]
  8. Lewandowsky S. Climate change disinformation and how to combat it. Annu Rev Public Health. 2021;42:1-21. [FREE Full text] [CrossRef] [Medline]
  9. Xiong F, Liu Y. Opinion formation on social media: an empirical approach. Chaos. 2014;24(1):013130. [FREE Full text] [CrossRef] [Medline]
  10. Suarez-Lledo V, Alvarez-Galvez J. Prevalence of health misinformation on social media: systematic review. J Med Internet Res. 2021;23(1):e17187. [FREE Full text] [CrossRef] [Medline]
  11. Chou WYS, Oh A, Klein WMP. Addressing health-related misinformation on social media. JAMA. 2018;320(23):2417-2418. [CrossRef] [Medline]
  12. Cavallo DN, Chou WYS, McQueen A, Ramirez A, Riley WT. Cancer prevention and control interventions using social media: user-generated approaches. Cancer Epidemiol Biomarkers Prev. 2014;23(9):1953-1956. [FREE Full text] [CrossRef] [Medline]
  13. Vosoughi S, Roy D, Aral S. The spread of true and false news online. Science. 2018;359(6380):1146-1151. [FREE Full text] [CrossRef] [Medline]
  14. Venkatraman A, Mukhija D, Kumar N, Nagpal SJS. Zika virus misinformation on the internet. Travel Med Infect Dis. 2016;14(4):421-422. [FREE Full text] [CrossRef] [Medline]
  15. Immunizing the public against misinformation. World Health Organization. Geneva.; 2020. URL: [accessed 2023-07-14]
  16. UN tackles ‘infodemic’ of misinformation and cybercrime in COVID-19 crisis. United Nations, COVID-19 Response. 2020. URL: https:/​/www.​​en/​un-coronavirus-communications-team/​un-tackling-%E2%80%98infodemic%E2%80%99-misinformation-and-cybercrime-covid-19 [accessed 2022-11-29]
  17. Allcott H, Gentzkow M, Yu C. Trends in the diffusion of misinformation on social media. Res Politics. 2019;6(2):205316801984855. [FREE Full text] [CrossRef]
  18. Pulido CM, Villarejo-Carballido B, Redondo-Sama G, Gómez A. COVID-19 infodemic: more retweets for science-based information on coronavirus than for false information. Int Sociol. 2020;35(4):377-392. [FREE Full text] [CrossRef]
  19. Taylor J. Bat soup, dodgy cures and ‘diseasology’: the spread of coronavirus misinformation. The Guardian. 2020. URL: https:/​/www.​​world/​2020/​jan/​31/​bat-soup-dodgy-cures-and-diseasology-the-spread-of-coronavirus-bunkum [accessed 2023-07-14]
  20. Melki J, Tamim H, Hadid D, Makki M, El Amine J, Hitti E. Mitigating infodemics: the relationship between news exposure and trust and belief in COVID-19 fake news and social media spreading. PLoS One. 2021;16(6):e0252830. [FREE Full text] [CrossRef] [Medline]
  21. Why "misinformation" was's 2018 word of the year. Dictionary. 2018. URL: [accessed 2023-07-14]
  22. Vraga EK, Bode L. Defining misinformation and understanding its bounded nature: using expertise and evidence for describing misinformation. Political Commun. 2020;37(1):136-144. [CrossRef]
  23. Joseph AM, Fernandez V, Kritzman S, Eaddy I, Cook OM, Lambros S, et al. COVID-19 misinformation on social media: a scoping review. Cureus. 2022;14(4):e24601. [FREE Full text] [CrossRef] [Medline]
  24. Muhammed TS, Mathew SK. The disaster of misinformation: a review of research in social media. Int J Data Sci Anal. 2022;13(4):271-285. [FREE Full text] [CrossRef] [Medline]
  25. Clemente-Suárez VJ, Navarro-Jiménez E, Simón-Sanjurjo JA, Beltran-Velasco AI, Laborde-Cárdenas CC, Benitez-Agudelo JC, et al. Mis-dis information in COVID-19 health crisis: a narrative review. Int J Environ Res Public Health. 2022;19(9):5321. [FREE Full text] [CrossRef] [Medline]
  26. Patel SS, Moncayo OE, Conroy KM, Jordan D, Erickson TB. The landscape of disinformation on health crisis communication during the COVID-19 pandemic in Ukraine: hybrid warfare tactics, fake media news and review of evidence. JCOM J Sci Commun. 2020;19(5):AO2. [FREE Full text] [CrossRef] [Medline]
  27. Janmohamed K, Walter N, Nyhan K, Khoshnood K, Tucker JD, Sangngam N, et al. Interventions to mitigate COVID-19 misinformation: a systematic review and meta-analysis. J Health Commun. 2021;26(12):846-857. [CrossRef] [Medline]
  28. Delgado CE, Silva EA, de Castro EAB, da Costa Carbogim F, de Araújo Püschel VA, Cavalcante RB. COVID-19 infodemic and adult and elderly mental health: a scoping review. Rev Esc Enferm USP. 2021;55:e20210170. [FREE Full text] [CrossRef] [Medline]
  29. Magarini FM, Pinelli M, Sinisi A, Ferrari S, De Fazio GL, Galeazzi GM. Irrational beliefs about COVID-19: a scoping review. Int J Environ Res Public Health. 2021;18(19):9839. [FREE Full text] [CrossRef] [Medline]
  30. Wang Y, McKee M, Torbica A, Stuckler D. Systematic literature review on the spread of health-related misinformation on social media. Soc Sci Med. 2019;240:112552. [FREE Full text] [CrossRef] [Medline]
  31. Janmohamed K, Walter N, Sangngam N, Hampsher S, Nyhan K, De Choudhury M, et al. Interventions to mitigate vaping misinformation: a meta-analysis. J Health Commun. 2022;27(2):84-92. [CrossRef] [Medline]
  32. Czerniak K, Pillai R, Parmar A, Ramnath K, Krocker J, Myneni S. A scoping review of digital health interventions for combating COVID-19 misinformation and disinformation. J Am Med Inform Assoc. 2023;30(4):752-760. [FREE Full text] [CrossRef] [Medline]
  33. do Nascimento IJB, Pizarro AB, Almeida J, Azzopardi-Muscat N, Gonçalves MA, Björklund M, et al. Infodemics and health misinformation: a systematic review of reviews. Bull World Health Organ. 2022;100(9):544-561. [FREE Full text] [CrossRef] [Medline]
  34. Ravichandran BD, Keikhosrokiani P. Classification of Covid-19 misinformation on social media based on neuro-fuzzy and neural network: a systematic review. Neural Comput Appl. 2023;35(1):699-717. [FREE Full text] [CrossRef] [Medline]
  35. Sanaullah AR, Das A, Das A, Kabir MA, Shu K. Applications of machine learning for COVID-19 misinformation: a systematic review. Soc Netw Anal Min. 2022;12(1):94. [FREE Full text] [CrossRef] [Medline]
  36. Tomes N, Parry M. What are the Historical Roots of the COVID-19 Infodemic? Lessons from the Past. Copenhagen. WHO Regional Office for Europe, Health Evidence Network; 2022.
  37. Vraga EK, Brady SS, Gansen C, Khan EM, Bennis SL, Nones M, et al. HPV and HBV vaccine hesitancy, intention and uptake in the era of social media and COVID-19: a review. medRxiv. Preprint posted online on January 26, 2023. 2023 [FREE Full text] [CrossRef]
  38. Zhao S, Hu S, Zhou X, Song S, Wang Q, Zheng H, et al. The prevalence, features, influencing factors, and solutions for COVID-19 vaccine misinformation: systematic review. JMIR Public Health Surveill. 2023;9:e40201. [FREE Full text] [CrossRef] [Medline]
  39. Tentolouris A, Ntanasis-Stathopoulos I, Vlachakis PK, Tsilimigras DI, Gavriatopoulou M, Dimopoulos MA. COVID-19: time to flatten the infodemic curve. Clin Exp Med. 2021;21(2):161-165. [FREE Full text] [CrossRef] [Medline]
  40. Balakrishnan V, Ng WZ, Soo MC, Han GJ, Lee CJ. Infodemic and fake news—a comprehensive overview of its global magnitude during the COVID-19 pandemic in 2021: a scoping review. Int J Disaster Risk Reduct. 2022;78:103144. [FREE Full text] [CrossRef] [Medline]
  41. Casino G. Communication in times of pandemic: information, disinformation, and provisional lessons from the coronavirus crisis. Gac Sanit. 2022;36(Suppl 1):S97-S104. [FREE Full text] [CrossRef] [Medline]
  42. Kemei J, Alaazi DA, Tulli M, Kennedy M, Tunde-Byass M, Bailey P, et al. A scoping review of COVID-19 online mis/disinformation in black communities. J Glob Health. 2022;12:05026. [FREE Full text] [CrossRef] [Medline]
  43. Rocha YM, de Moura GA, Desidério GA, de Oliveira CH, Lourenço FD, de Figueiredo Nicolete LD. The impact of fake news on social media and its influence on health during the COVID-19 pandemic: a systematic review. Z Gesundh Wiss. 2021:1-10. [FREE Full text] [CrossRef] [Medline]
  44. Kim B, Xiong A, Lee D, Han K. A systematic review on fake news research through the lens of news creation and consumption: research efforts, challenges, and future directions. PLoS One. 2021;16(12):e0260080. [FREE Full text] [CrossRef] [Medline]
  45. Raquel CP, Ribeiro KG, Alencar NES, de Souza DFO, de Holanda Cunha Barretob IC, de Andradeb LOM. Scientific ways to confront covid-19 fake news. Saúde Soc. 2022;31(4):e210601en. [FREE Full text] [CrossRef]
  46. Chowdhury N, Khalid A, Turin TC. Understanding misinformation infodemic during public health emergencies due to large-scale disease outbreaks: a rapid review. J Public Health. 2021:1-21. [FREE Full text] [CrossRef] [Medline]
  47. Choukou MA, Sanchez-Ramirez DC, Pol M, Uddin M, Monnin C, Syed-Abdul S. COVID-19 infodemic and digital health literacy in vulnerable populations: a scoping review. Digit Health. 2022;8:20552076221076927. [FREE Full text] [CrossRef] [Medline]
  48. Caceres MMF, Sosa JP, Lawrence JA, Sestacovschi C, Tidd-Johnson A, Rasool MHU, et al. The impact of misinformation on the COVID-19 pandemic. AIMS Public Health. 2022;9(2):262-277. [FREE Full text] [CrossRef] [Medline]
  49. Corinti F, Pontillo D, Giansanti D. COVID-19 and the Infodemic: an overview of the role and impact of social media, the evolution of medical knowledge, and emerging problems. Healthcare (Basel). 2022;10(4):732. [FREE Full text] [CrossRef] [Medline]
  50. O'Connor C, Murphy M. Scratching the surface: a review of online misinformation and conspiracy theories in atopic dermatitis. Clin Exp Dermatol. 2021;46(8):1545-1547. [FREE Full text] [CrossRef] [Medline]
  51. Pian W, Chi J, Ma F. The causes, impacts and countermeasures of COVID-19 "Infodemic": a systematic review using narrative synthesis. Inf Process Manag. 2021;58(6):102713. [FREE Full text] [CrossRef] [Medline]
  52. Sasidharan S, Singh DH, Vijay S, Manalikuzhiyil B. COVID-19: Pan(info)demic. Turk J Anaesthesiol Reanim. 2020;48(6):438-442. [FREE Full text] [CrossRef] [Medline]
  53. La Bella E, Allen C, Lirussi F. Communication vs evidence: what hinders the outreach of science during an infodemic? A narrative review. Integr Med Res. 2021;10(4):100731. [FREE Full text] [CrossRef] [Medline]
  54. Oxman M, Larun L, Gaxiola GP, Alsaid D, Qasim A, Rose CJ, et al. Quality of information in news media reports about the effects of health interventions: systematic review and meta-analyses. F1000Res. 2021;10:433. [FREE Full text] [CrossRef] [Medline]
  55. Montesi M. Human information behavior during the COVID-19 health crisis. A literature review. Libr Inf Sci Res. 2021;43(4):101122. [FREE Full text] [CrossRef] [Medline]
  56. Aslani N, Behmanesh A, Davoodi F, Garavand A, Shams R. Infodemic challenges during COVID-19 pandemic and the strategies to deal with them: a review article. Arch Clin Infect Dis. 2022;17(1):e127022. [FREE Full text] [CrossRef]
  57. Bam NE. Strategies to address conspiracy beliefs and misinformation on COVID-19 in South Africa: a narrative literature review. Health SA. 2022;27:1851. [FREE Full text] [CrossRef] [Medline]
  58. Sharma LD, Joshi KJ, Acharya TA, Dwivedi MG, Sethy GB. Infodemics during era of COVID-19 pandemic: a review of literature. J Family Med Prim Care. 2022;11(8):4236-4239. [FREE Full text] [CrossRef] [Medline]
  59. Skafle I, Nordahl-Hansen A, Quintana DS, Wynn R, Gabarron E. Misinformation about COVID-19 vaccines on social media: rapid review. J Med Internet Res. 2022;24(8):e37367. [FREE Full text] [CrossRef] [Medline]
  60. Gabarron E, Oyeyemi SO, Wynn R. COVID-19-related misinformation on social media: a systematic review. Bull World Health Organ. 2021;99(6):455-463A. [FREE Full text] [CrossRef] [Medline]
  61. Whitehead HS, French CE, Caldwell DM, Letley L, Mounier-Jack S. A systematic review of communication interventions for countering vaccine misinformation. Vaccine. 2023;41(5):1018-1034. [FREE Full text] [CrossRef] [Medline]
  62. Miles MB, Huberman AM. Qualitative Data Analysis: An Expanded Sourcebook, 2nd Edition. Thousand Oaks, CA. Sage Publications, Inc; 1994.
  63. Eysenbach G. Infodemiology and infoveillance: framework for an emerging set of public health informatics methods to analyze search, communication and publication behavior on the internet. J Med Internet Res. 2009;11(1):e11. [FREE Full text] [CrossRef] [Medline]

PRISMA: Preferred Reporting Items for Systematic Reviews and Meta-Analyses
WHO: World Health Organization

Edited by A Mavragani; submitted 15.01.23; peer-reviewed by C Wardle, JF Fuertes-Bucheli; comments to author 21.02.23; revised version received 01.06.23; accepted 07.06.23; published 09.08.23.


©Ibrahim K El Mikati, Reem Hoteit, Tarek Harb, Ola El Zein, Thomas Piggott, Jad Melki, Reem A Mustafa, Elie A Akl. Originally published in the Journal of Medical Internet Research (, 09.08.2023.

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