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Home Exclusive Relationships and Sexual Health Attractiveness

New study shows how first impressions based on attractiveness can change

by Eric W. Dolan
January 14, 2024
in Attractiveness, Social Psychology
(Photo credit: Adobe Stock)

(Photo credit: Adobe Stock)

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A series of studies has found that first impressions based on a person’s attractiveness are not set in stone and can be significantly altered with new information. The research, published in the European Journal of Social Psychology, demonstrated that the initial assumptions we make about someone’s personality based on their looks can be updated or even reversed when we receive contrasting information about their attractiveness.

For years, scientists have been intrigued by the phenomenon known as the ‘attractiveness halo effect’, where a person perceived as physically attractive is also assumed to possess other positive traits, such as sociability and intelligence. However, the question remained: are these snap judgments irreversible, or can they be changed? Seeking an answer, researchers at Ghent University’s Learning and Implicit Processes Lab embarked on a novel investigation to determine whether and how these initial perceptions could be updated.

“We know that the attractiveness of individuals generally leads to a myriad of stereotypical attributions (e.g., attractive people are generally perceived as vain but also as sociable),” said study author Marine Rougier, a postdoctoral researcher at UCLouvain. “We also know that these attributions can influence real-life behaviors. For instance, attractive people generally receive a more positive treatment than less attractive individuals.”

“Hence, it is important to determine whether these attributions can be influenced. We were interested particularly in whether these attributions can be changed when the attractiveness of a person is updated — for instance, when a person you thought was attractive is in fact less attractive than he or she initially seemed.”

Rougier and her co-author, Professor Jan De Houwer, conducted a series of three studies to investigate this.

The first study involved 360 participants, who were shown photographs of faces with varying levels of attractiveness. The participants were initially asked to form impressions based on these photos. They were then informed that the photos might have been altered – either making attractive people look more or less attractive than they actually are, or vice versa. After receiving this new information, participants rated the people in the photos on a series of personality traits.

While it confirmed the existence of the attractiveness halo effect, where attractive faces were generally rated more positively, the updating information didn’t significantly alter these initial impressions. This was an unexpected finding and led the researchers to wonder if a more explicit updating manipulation might yield different results.

In response to the first study’s findings, a second study was conducted with 401 participants. This time, only female faces were used, and the updating information was made more explicit. Participants were shown examples of how attractiveness could be artificially enhanced or reduced using photo editing software. The researchers hoped that this would make the updating information more impactful.

The results of the second study were more conclusive. This time, the additional information provided about the faces’ attractiveness did change participants’ impressions. When the updating information suggested that a person was less attractive than initially thought, the positive attributes associated with them decreased. This halo-update effect was especially pronounced for traits typically linked to attractiveness, such as sociability.

In the third study, with 400 participants, the researchers further refined their methodology. They measured participants’ impressions of attractiveness and personality traits at two different times – before and after providing the updating information. Moreover, they did not prompt participants to consider the updating information while making their second set of ratings.

The findings of this third study were the most compelling. It demonstrated that initial positive impressions based on attractiveness could be significantly reversed after updating. For example, if participants were told that someone they initially thought was attractive was actually less so, they also rated them lower on positive personality traits. This effect occurred even though participants weren’t explicitly reminded of the updating information when making their second set of ratings.

“We observed that updating the attractiveness of a person (e.g., saying that a person is less attractive than he or she seemed to be on a picture) can change the myriad of stereotypical attributions people made,” Rougier told PsyPost. “For instance, if the attractive person was initially perceived as highly vain and sociable, then he or she will be perceived as low on these two attributes after being informed that the person is in fact not attractive. This illustrates that stereotypical attributions are malleable and can be changed when the source of these attributions is updated.”

Despite these significant findings, the research has its limitations. For one, the study relied on direct self-report measures, which might not fully capture more implicit, unconscious biases. Another area for future exploration is understanding why and how initial assumptions partially stick to targets even after updating. The durability of these updated impressions over time and their translation into real-life behaviors and decisions are areas ripe for future research.

“As noted above, we know that stereotypical attributions can influence real-life behaviors,” Rougier said. “In future work, it will be important to test whether the effects we observed can be extended to meaningful behaviors and whether the effects endure over time.”

The study, “Updating stereotypical attributions in light of new information: The attractiveness halo effect changes when attractiveness changes“, was published December 11, 2023.

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