Cognitive biases and false beliefs about COVID-19

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This column highlights certain cognitive biases in play when people adopt false beliefs regarding the COVID-19 pandemic. 

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Belief bias

by Émilie Gagnon-St-Pierre

Belief bias refers to our tendency to rely on our pre-existing beliefs to evaluate a conclusion. This leads us to overestimate the validity of a credible conclusion, independently of its true logical validity [1]. This is one of the most studied and demonstrated phenomena in the field of reasoning. The tendency is accentuated when we are obliged to reason quickly [2].

 

Experts in logic differentiate between the logical validity of a given reasoning (or argument), and the veracity of the premises and the conclusion. Logical validity depends on the logical relationship that links the premises and the conclusion within the argument. The veracity of the premises or the conclusion refers to whether the information presented in them is true in the real world. It is important to understand that an argument may be logically valid, but nonetheless contain premises or conclusions that are false, just as it may be logically invalid but arrive at a conclusion that is true.

Example

Consider the reasoning in the following two sets of statements:

Reasoning A

 

Premise 1

Sheep are people who blindly trust the government.

 

Premise 2

People who get vaccinated against COVID-19 blindly trust the government.

 

Conclusion

People who get vaccinated against COVID-19 are sheep.

Reasoning B

 

Premise 1

Prudent people trust the government.

 

Premise 2

People who get vaccinated against COVID-19 trust the government.

Conclusion

People who get vaccinated against COVID-19 are prudent people.

It is likely that you perceive one of the two reasonings to be more valid than the other depending on what content does or does not seem true to you. However, these two arguments have an identical logical form and are both invalid. Thus, the impression of veracity of the conclusions wrongly influences the assessment of the validity of reasoning.

Repetition effect

by Cloé Gratton

The repetition of a piece of information can increase its perceived credibility, compared to a new piece of information. We tend to (irrationally) reinforce our belief in information if it is presented to us multiple times. When we are not familiar with a topic, and where the situation is ambiguous, it is normal to look for clues to judge the truth or falsity of a piece of information. The source of the information, or the context wherein the information is received, can be good external markers to evaluate the truth or falsity in a given situation. However, repetition itself should not serve as a signal of truth, since it does not add anything new to the conversation in terms of credibility. For this reason, the repetition bias is also called the “illusory truth effect” [3].

Example

In 2020-2021, in the heart of the coronavirus pandemic, former U.S. President Donald Trump repeated on television, on Facebook, Twitter and at a press conference that the COVID-19 virus had been manufactured in the laboratory by Chinese scientists. These statements were repeated many times by the former president, but also by conspiratorial media and relayed in a satirical or journalistic manner on several occasions. A survey by an independent firm found that nearly three in ten Americans believe this theory. One can think that the repetition of this kind of information had some responsibility in the high percentage of the American population believing this scenario. To this day, this scenario is not supported by evidence.

Confirmation bias

by Janie Brisson

Confirmation bias is a tendency, often unconscious, to be overly supportive of information that confirms a hypothesis, to the detriment of information that contradicts it. This bias can occur in different ways. When information conforms to our hypothesis, it can be remembered more easily [4] or given more weight than information that contradicts it. Sources of information that support the hypothesis may also come under less critical scrutiny [5]. This bias can occur in a context where we are dealing with a subject related to emotions, opinions or beliefs, but also in a neutral context where these factors are not at play.

Example

Conspiracy theories regarding the COVID-19 pandemic are plentiful and varied. One of them suggests that the authorities declared a health emergency in order to force the population to accept a vaccine that they do not need, in order to promote the economic domination of the pharmaceutical industry. Several types of information can be presented in support of this theory, such as proposals for alternative treatments to COVID-19, some data taken out of context from vaccine approval protocols, or annual death rates from seasonal influenza.

 

While this information may hold some veracity, it is not sufficient to support the conspiracy theory put forward when compared to scientific studies carried out by both the pharmaceutical industry and public health authorities. Confirmation bias plays an important role in maintaining this position: the fact of favoring the information presented as supporting evidence to the detriment of any information which invalidates this hypothesis, whether through lack of access to information or lack of confidence in scientific protocols, will lead a person to have an illusion of objectivity and strengthen their belief in the conspiracy theory.

Echo chamber

by Sara Germain

In the same way that an echo repeats our own voice, the “echo chamber” phenomenon is a type of confirmation bias that occurs when we are constantly exposed to ideas or beliefs that confirm our own positions [6]. This phenomenon, inherent to the online context, happens when we voluntarily consult only content with which we already agree [6]. The information selection process constitutes a confirmation bias because it introduces a bias into the information to which we are subjected [6]. When we are constantly presented with content that echoes our own beliefs, divergent opinions start to appear marginal because of their reduced visibility [7].

Example

Despite strong enthusiasm in the early stages of the vaccination campaign, officials are noticing that people who have not yet made their vaccine appointments are increasingly reluctant to do so. The “anti-vax” movement, which was already gaining strength in digital spaces, has experienced significant growth over the past year. Due to the interactive aspect of social media,  people have been able to tailor their social media news feeds so that the information conveyed there primarily (if not only) reflects their beliefs that the COVID19 vaccine is, at best, ineffective and, at worst, dangerous. Although many studies have been done to contradict this information, this information does not pierce through the echo chambers of refractory individuals. Or if they do, they receive little credibility because of the larger number of "sources" that deny them.

Negativity bias

by Nicolaï Abramovich

Negativity bias refers to the tendency to be more affected by negative information and contingencies than by positive ones [8]. Thus, we retain more memories linked to negative emotions than positive ones [9]; the vocabulary for describing pain is richer than that for describing pleasure [8]; and the prospect of economic loss is more frightening than the prospect of potential gain is reassuring [10]. The brain reacts intensely to negative entities such as germs, while the opposite does not occur for positive entities [8]. Therefore, when it comes to reasoning, judging and acting, the negative very often outweighs the positive. This bias is considered universal [11, 12], but some studies suggest that it may decrease with age [12].

Example

Conspiracy theories argue that certain actions with serious or dangerous consequences for the community are secretly orchestrated by small groups for profit.

One of the most widely circulated conspiracy theories during the COVID-19 pandemic was that of the artificial origin of the virus. Scientists from the Institut Pasteur were said to have created it in the laboratory, then dispersed it voluntarily in the wild in order to profit from marketing the vaccine used to control it. Our brains spot this terrible accusation, and our negativity bias is activated. Not only does this theory easily attract our attention but in addition it remains very present in our memory because our brain gives priority to negative information over positive information. Therefore, the "argumentative millefeuille" so characteristic of conspiracy theory is effective because it systematically reifies complex situations into simple and negative ones. Cognitively, these simple, negative situations command more of our attention.

The thesis of the artificial origin of the virus has met with great success, in particular thanks to the massive distribution of the pseudo-documentary “Hold Up”. Today, it has collapsed since the Institut Pasteur has still not released a vaccine.

Near bias effect

by Sophie-Andrée Vinet and Cloé Gratton

The near-bias effect is defined by the tendency to be more concerned about what happens in the present than what will happen in the future. When given a choice, people are inclined to prefer immediate rewards to those available after a delay, implying that the value of delayed rewards relative to more immediate ones are discounted (i.e. are perceived to be worth less) [13]. For this reason, economists refer to this concept as temporal discounting. While economists popularized this concept, it has also been extensively studied in psychology, in individual and group settings, and it applies to several social phenomena such as drug addictions [14] and procrastination [15].

Example

Proximity bias can be reflected in movements protesting public health measures linked to COVID-19. There are many restrictions in place in different countries to limit the spread of the coronavirus: wearing a mask in public places, physical distancing, limits on the number of customers who can visit businesses at the same time, etc. Several protest movements have emerged against these measures around the world.

 

Although other factors may explain adherence to these protest movements, proximity bias may also play a role as people are not prepared to sacrifice their daily freedoms in service to a distant future goal. In other words, in this particular case, people are not ready to wear a mask today in order to lessen the spread of the virus in the longer term. They place more importance on their comfort here and now than on the long-term beneficial consequences, which include better public health and safety and less threat to the health care system.

[1] Evans, Jonathan. S. B., Julie L. Barston & Paul Pollard (1983). On the conflict between logic and belief in syllogistic reasoning. Memory & Cognition, 11(3), 295-306.

 

[2] Evans, Jonathan. S. B. & Jodie Curtis-Holmes (2005). Rapid responding increases belief bias: Evidence for the dual-process theory of reasoning. Thinking & Reasoning, 11(4), 382-389.

[3] Dechêne, Alice, Christoph Stahl, Joachim Hansen & Michaela Wänke (2010). The truth about the truth: A meta-analytic review of the truth effect. Personality and Social Psychology Review 14(2): 238-257.

[4] Frost, Peter, Bridgette Casey, Kaydee Griffin, Luis Raymundo, Christopher Farrell & Ryan Carrigan (2015). The influence of confirmation bias on memory and source monitoring. The Journal of General Psychology, 142(4), 238-252.

 

[5] Jones, Martin & Robert Sugden (2001). Positive confirmation bias in the acquisition of information. Theory and Decision, 50(1), 59-99.

[6] Sunstein, Cass R. (2018). # Republic: Divided democracy in the age of social media. Princeton University Press.


[7] Williams, Hywel T., James R. McMurray, Tim Kurz & Hugo F. Lambert (2015). Network analysis reveals open forums and echo chambers in social media discussions of climate change. Global Environmental Change, 32: 126‑138.

[8] Paul Rozin & Edward B. Royzman (2011). Negative bias, negativity dominance and contagion, Personality and Social Psychology Review, 5(4): 296-320.

[9] Amrisha Vaish, Tobias Grossmann & Amanda Woodward (2008). Not all emotions are created equal: the negativity bias in social-emotional development, Psychological Bulletin, 134(3): 383-403.

[10] Daniel Kahneman, Jack. L. Knetsch, & Richard. H. Thaler. (1990). Experimental tests of the endowment effect and the Coase theorem, Journal of Political Economy, 98: 1325-1348. 

[11] Keith Chen & Venkat Lakshminrayanan (2006). How basic are behavioral biases? Evidence from capuchin monkey trading behavior, Journal of Political Economy, 114(3): 517-537. 

[12] Michael A. Kisley, Stacey Woods & Cristina L. Burrows (2007). Looking at the sunny side of life: Age-related change in an event-related potential measure of the negativity bias, Psychological Science, 18: 838-643. 

[13] Story, Giles W., Ivo Vlaev, Ben Seymour, Ara Darzi & Raymond J. Dolan (2014). Does temporal discounting explain unhealthy behavior? A systematic review and reinforcement learning perspective. Frontiers in Behavioral Neuroscience, 8, 1-15.

 

[14] Bickel, Warren K., Amy L. Odum & Gregory J. Madden (1999). Impulsivity and cigarette smoking: delay discounting in current, never, and ex-smokers. Psychopharmacology 146, 447-454.

[15] Haiyan, Wu, Gui Danyang, Lin Wenzheng, Gu Ruolei, Zhu Xiangru & Liu Xun (2016). The procrastinators want it now: Behavioral and event-related potential evidence of the procrastination of intertemporal choices. Brain and Cognition 107:16-23.