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Table 1 Potential cognitive biases that contribute to vaccine hesitancy

From: Vaccine hesitancy: evidence from an adverse events following immunization database, and the role of cognitive biases

Category

Cognitive Bias

Definition

Example

Group 1: Cognitive biases triggered by processing vaccine-related information

Framing effect

Formulating a message with no change in the main content will affect the agent’s choice [41].

Negatively framing the outcomes of a vaccine by emphasizing the smaller portion of patients with AEs than most patients with no AEs.

Base rate neglect

The tendency to focus on specific information and ignore general information even though the general information is more important [42].

Overestimating rare AEFIs and underestimating common mild AEFIs [43].

Availability bias

The tendency to attribute higher weight to factors that are easier to recall [18].

A rare SAE report’s media coverage offers a vivid and emotionally compelling message, likely to be recalled during vaccination decision making [22].

Anchoring effect

The tendency to rely heavily on an initially presented value when making a decision [17].

Seeing an SAE following a vaccine and believe SAEs are more common with that specific vaccine [44].

Authority bias

The tendency to attribute more weight to the opinion of authoritative figures [45].

As an authoritative figure, when a medical professional spreads anti-vaccination content, it could instigate people to opt against vaccination.

Group 2: Cognitive biases triggered in vaccination decision making

Omission bias

The tendency to consider the outcomes of not doing an action (omission) as less severe than doing the action (commission), even if the result of not doing is more severe than or equal to doing the action [19].

Parents consider vaccination as commission, and when they anticipate AEFIs, they tend to omission (not vaccinating).

Ambiguity aversion

The tendency to take a known risk over the unknown risk, regardless of the outcomes [21].

People prefer a known risk from a disease rather than a more ambiguous risk of a vaccine for the same disease [23].

Loss aversion

The tendency to put greater weight on avoiding losses than achieving comparable gains [20].

When describing AEFIs, patients may only focus on a 1% chance of having AEs instead of a 99% chance of no AEs [24].

Optimism bias

The tendency to have an unrealistically optimistic view about a particular health risk, believing it is higher for other people than oneself [22].

People do not consider themselves at risk from flu, assuming themselves as healthy, not susceptible to flu, and strong enough to fight [46].

Present bias

The tendency to put more weight on the costs and benefits today and less weight on those realized in the future [22].

Vaccine AEs (as a cost) are more visible to people, so they receive more weight. Immunity to a disease as a future benefit is not visible and receives less weight.

Protected values

The tendency to protect absolute and not amenable-to-intervention values that people think should not be traded off [47].

Believing in parents’ right to refuse vaccination [38].

Group 3: Cognitive biases triggered by prior beliefs regarding vaccination

Confirmation bias

The tendency to recall and interpret information that confirms our existing beliefs [25].

Vaccine-hesitant people consider a vaccine-preventable disease as less dangerous and overestimate AEFIs [26, 48].

Belief bias

The tendency to evaluate an argument’s validity based on the believability of the conclusion [49].

Discussing vaccine safety in terms of mild AEFIs with individuals who believe vaccination policies are motivated by big corporations’ profit would be ineffective.

Shared information bias

The tendency to spend more time and energy on the information that members of a group are familiar with and less time and energy on new information [50].

Focusing on a limited number of anti-vaccine topics like the debunked MMR-autism link on online anti-vaccine echo-chambers.

False consensus effect

The tendency to overestimate the extent to which the general population share one’s belief [51].

On social media, vaccine-hesitant (vaccine-advocate) mothers are more (less) likely to engage in communication about the issue [52]. It creates online communities with high false consensus on vaccine-hesitancy.