Background

Perception bias is the tendency to be somewhat subjective about the gathering and interpretation of healthcare research and information.

There is evidence that although people believe they are making impartial judgements, in fact, they are influenced by perception biases unconsciously.

There are several subtypes:

• Implicit bias: individuals hold attitudes towards people, or associate stereotypes with them, without being aware of this.
• Fundamental attribution error: individuals tend to blame their failings on circumstances around them, but consider that others are responsible for their shortcomings.
• Selective perception: expectations about people or situations affect perception.

Example

An example is reporting of alcohol intake among young adults as drinking is influenced by perceptions of how much their peers drink. These perceptions are often wrong and overestimate drinking norms (Foxcroft et al. 2015).

Impact

In a study of students reporting fruit and vegetable consumption (Nix & Wengreen 2017), the investigators measured intake by self-report before and after receiving different information messages. Students in the low normative group (receiving the message they were in the lowest 20th percentile of intake) reported a half-cupful increase in fruit and vegetable intake and a one-cup increase in perception of peers’ consumption, while there were no significant differences in the other groups (highest 20th percentile or no message).

Preventive steps

Studies using objective measures are less likely to suffer from perception bias. Studies which rely on self-reported information, or observations that could be influenced by perception biases, should be interpreted with additional caution.