False and misleading information tends to surge during major societal crises, and social media has made that surge faster, wider, and harder to contain. These “mega-crises”—events that shake whole societies, like pandemics, natural disasters, terrorist attacks, or wars—create conditions of fear, uncertainty, and information overload, which are exactly the conditions under which falsehoods thrive. During the COVID-19 pandemic, for instance, false claims about the virus’s origins, its deadliness, and the motives behind government policies spread across platforms at staggering speed. Yet despite the obvious importance of understanding this problem, research has remained oddly fragmented. Scholars in psychology, computer science, medicine, journalism, and communication have all studied false and misleading information, but they often work in isolation, rarely citing one another or borrowing theories from crisis research. This fragmentation, combined with inconsistent terminology, makes it difficult to build a clear, shared picture of what drives the spread of false information during crises and what happens when people are exposed to it. To address that gap, the authors of this review set out to map the field. They conducted a scoping review, a method designed to identify patterns, key concepts, and gaps across a broad body of literature, rather than to test a narrow hypothesis. In total, they analyzed 179 peer-reviewed studies published between 2014 and 2024, using a citation-based sampling strategy that selected the most influential fifteen percent of studies within each research field. The goal was to answer two overarching questions: what factors contribute to the spread of false and misleading information on social media during crises, and what effects does exposure to such information have on individuals and society? Think of it as stepping back to see the whole messy landscape rather than zooming in on any single tree.
Before diving into the findings, it helps to understand the vocabulary, because much of the confusion in this field is linguistic. The terms misinformation and disinformation are foundational, but they differ mainly in intent. Misinformation is false information shared without malicious intent—someone passing along a scary but untrue warning because they genuinely believe it might help. Disinformation, on the other hand, is deliberately created and spread to deceive or harm, often by political actors, interest groups, or foreign influence operations. Of course, information can start as disinformation and then spread as misinformation, as people unknowingly share something that was engineered to mislead. The term fake news has also become prominent, especially in political and media studies, but it is notoriously slippery: it can refer to fabricated stories presented as legitimate news, or it can be used as a weaponized label to discredit trusted journalism. Relatedly, alternative facts and post-truth describe efforts to construct alternative realities that reject established evidence and mainstream expertise. During crises, the term infodemic has gained renewed attention, especially after COVID-19. Coined during the SARS outbreak in 2003, it describes the overwhelming flood of information—both accurate and inaccurate—that makes it difficult for people to find trustworthy sources and know what to believe. This concept overlaps with information pollution, which refers to situations where the information environment is contaminated with low-quality, irrelevant, or inaccurate material. Then there are conspiracy theories, which attempt to explain major events as the secret, malevolent actions of powerful groups; these often carry misinformation and disinformation and became particularly visible during the pandemic. Finally, rumors—unverified information that spreads in situations of ambiguity or perceived threat—have long been studied in crisis contexts. The key point is that these terms overlap and are often used interchangeably, even though they highlight different facets of the phenomenon. That is why the authors deliberately use the umbrella term “false and misleading information” to encompass all of these concepts. It is a practical choice, one that allows them to synthesize a highly scattered research area without getting stuck in endless definitional debates.
Looking at the big picture, the review reveals several clear patterns in how research on false and misleading information has developed over the past decade. First, the field is dominated by three disciplines: the social sciences make up about 26.5 percent of the analyzed publications, data and computer science about 18.2 percent, and medicine about 17.1 percent. Smaller contributions come from engineering, arts and humanities, mathematics, psychology, decision science, environmental science, and business economics. Geographically, the research is concentrated in the United States, followed by the United Kingdom and China; authors from these three countries account for roughly half of all publications. Second, the type of crisis studied is strikingly one-sided. A full 86 percent of the studies focus on global health crises, and within that category, COVID-19 dominates almost completely. Natural disasters such as earthquakes and hurricanes come in a distant second at about 3.9 percent, followed by terrorism, political crises, war, and organizational crises. This heavy emphasis on the pandemic makes sense given its global impact and the sheer volume of misinformation it generated, but it also raises a critical question: how much of what we learned during COVID-19 can be applied to other kinds of crises, which may involve different emotional dynamics, information ecosystems, and political contexts? Third, research tends to treat social media as a single, homogeneous thing. About 64 percent of the studies refer to “social media” without specifying a platform, even though different platforms have different affordances, user demographics, and algorithmic logics. When platforms are specified, X (formerly Twitter) is by far the most studied, appearing in 46.8 percent of platform-specific studies, followed by Facebook at 17.7 percent and the Chinese platform Sina Weibo at 10 percent. Newer platforms like TikTok and Snapchat are almost entirely absent. Fourth, and perhaps most importantly, the methodological toolkit is narrow. The most common methods are cross-sectional surveys and quantitative content analysis, which together account for nearly half of all studies. Experimental studies, panel surveys, and longitudinal designs—methods that could actually establish causal relationships—are rare. This means that while researchers have identified many correlations, they often cannot say with confidence whether false information causes certain behaviors or beliefs, or whether people who already hold certain beliefs are simply more likely to encounter and share false information.
When it comes to the first research question—what factors contribute to the spread of false and misleading information during crises—the review finds that the vast majority of research focuses on individual-level explanations. About 69 percent of the variables examined relate to characteristics of individuals, while content-related factors account for 19.3 percent, platform-specific factors for 7.6 percent, and societal-level factors for just 3.4 percent. Among individual-level factors, perceptions are the most frequently studied, making up 25.2 percent of all spread-related variables. These studies often focus on political attitudes, trust in institutions, and ideological alignment. For example, people who distrust mainstream media or scientists are more likely to believe and share false claims, and fact-checking can sometimes backfire, reinforcing false beliefs among those whose identity is tied to them. Cognitive factors, such as information overload and low analytical thinking, account for 11.8 percent, while emotions like anxiety and anger account for 10.1 percent. Interestingly, emotions are rarely studied as central drivers on their own; they are more often treated as secondary variables that interact with perceptions or cognition. Behavioral factors, such as media consumption habits, account for 8.4 percent, and personality traits, such as altruism, account for 5.9 percent. Some studies have found that people share false information out of a genuine desire to warn or protect others, which complicates the simple assumption that sharing is always driven by malice or political bias. Beyond the individual level, content-related factors focus on how false information is framed and packaged—for example, the emotional tone of a message, whether it includes guidance on how to respond to the crisis, or whether it appears to come from a credible source. Platform-specific factors, which account for a small share of the research, look at affordances like the ease of sharing across platforms and the role of positive feedback mechanisms such as likes. Structural factors, such as political or economic contexts, are almost entirely missing. This is a significant gap because crises unfold within specific media systems, political climates, and power structures that shape what information spreads and why.
The second research question concerns the effects of false and misleading information, and here the pattern is even more skewed toward the individual. A full 87.4 percent of the variables examined focus on effects on individuals, while only 12.6 percent focus on societal-level effects, and no organizational effects were identified at all. At the individual level, behavioral effects are the most commonly studied, accounting for 39 percent of the effect-related variables. In the context of COVID-19, this often means examining whether exposure to, or belief in, false information reduces adherence to public health measures like mask-wearing, social distancing, or vaccination. Numerous studies have linked conspiracy beliefs to vaccine hesitancy, and some have investigated the impact of coordinated disinformation campaigns such as “Plandemic,” which promoted the idea that the pandemic was a planned hoax. Perceptual effects come next, at 27.4 percent. These include politically motivated reasoning—the tendency to accept information that fits preexisting beliefs—as well as threat perceptions and the third-person effect, where people believe that others are more susceptible to false information than they are themselves. Emotional effects, such as increased anxiety, stress, and fear, account for 11.6 percent, while cognitive effects, such as reduced knowledge about the crisis, account for 9.5 percent. Some studies have explored the role of self-reported media literacy in protecting against false beliefs, but this remains an underexplored area. At the societal level, the most frequently studied effect is economic, accounting for 6.3 percent, followed by political effects at 2.1 percent. This could include, for example, the economic cost of health misinformation or the erosion of public trust in democratic institutions. However, the review notes that the search strategy may have inadvertently excluded some studies that examined both the effects and the management of false information, so societal-level effects might be underrepresented. Overall, the dominance of individual-level effects is striking. It reflects a broader trend in the field toward psychological explanations and away from sociological, institutional, or structural analysis. Yet the consequences of false and misleading information are rarely confined to individuals; they ripple through communities, public health systems, economies, and democratic processes.
Taken together, the findings point to several urgent needs for future research. First, the overwhelming focus on COVID-19 means that we simply do not know whether the patterns identified during the pandemic hold for other types of crises, such as natural disasters, terrorist attacks, or armed conflicts. These crises evoke different emotions, unfold over different timescales, and involve different types of official communication. Researchers should test the transferability of pandemic-era findings to other contexts. Second, the field needs more varied and rigorous methodologies. Cross-sectional surveys can tell us who believes and shares what, but they cannot establish causality. Panel studies and experiments, which track the same people over time or manipulate exposure to information under controlled conditions, are much better suited to understanding cause and effect. Third, research must move beyond the individual level. The spread and effects of false information are shaped not only by individual psychology but also by media systems, political institutions, platform algorithms, and structural inequalities. These societal factors remain largely invisible in the current literature, and future work should examine how they interact with individual behaviors and perceptions. Fourth, emotions deserve more attention. Crises are intensely emotional events, and anxiety, anger, fear, and hope likely play a powerful role in both the spread and the impact of false information. Yet emotions are rarely the central focus of research. Fifth, technological developments are dangerously understudied. The review found almost no research on artificial intelligence, and deepfakes were entirely absent. Given how quickly generative AI has advanced, this is a glaring gap. Finally, the authors call for a genuinely interdisciplinary agenda. False and misleading information during crises is not just a psychology problem, a computer science problem, or a communication problem; it is all of these at once. Researchers need to build frameworks that combine insights from different fields and integrate context-specific crisis dynamics with broader theoretical mechanisms. The review itself has limitations—most notably, the search string included COVID-19, which may have inflated the proportion of health crisis studies, and the citation-based sampling may have excluded important but less-cited work. Nevertheless, this review offers a valuable roadmap. It shows how far the field has come, how far it still has to go, and why we need a more connected, methodologically diverse, and socially aware approach to understanding false and misleading information in times of crisis.