Men ‘overestimate’ attractiveness of women – study
Researchers have found that men tend to overestimate how attractive a woman is based on just a brief glimpse, whereas women who catch a glance of a man are more likely to underestimate his handsomeness.
The findings, published last month in the Evolution and Human Behavior journal, suggests the cliche about ‘falling in love at first sight’ only goes one way. The study appears to confirm the concept of ‘first-impression bias’ in both men and women.
Conducted in Australia, researchers asked around 400 volunteers to evaluate the attractiveness of strangers from the opposite sex based on a blurry photo without a clear view of their facial features, and then again from a clear image.
The researchers also randomized the order of presentation, switching between first showing participants a blurry image or a clear image. Through this method, they were apparently able to “isolate the unique effects of uncertainty” – which was only identified when volunteers saw the blurred images first.
“When people have only incomplete information about a potential partner, they must make inferences about their desirability, leading to possible errors in judgment,” the researchers noted.
The study looked at how people “balance the risks” of these errors of misjudgment, and the differences between how men and women respond to this uncertainty.
The potential risks were described as either engaging in “regrettable mating behavior” when overestimating desirability, or “missing a valuable opportunity” when under-perceiving attractiveness.
The results showed that men, on average, give women the benefit of the doubt when it comes to judging attractiveness, while the opposite held true when the roles were reversed.
Further analysis suggested “more nuanced biases” in that men appeared to specifically overestimate the attractiveness of unattractive (but not attractive) women, while women exhibited a bias against attractive (but not unattractive) men.
While noting that this was an “important finding,” the team said these were “broad quantitative effects” that needed to be studied further to understand why “first-impression bias” existed to begin with. They also highlighted the importance of conducting algorithm-based studies into cognitive biases.
The study noted that earlier research on perception bias, including examinations of men overestimating how interested a woman was in them sexually, had emphasized “between-sex” differences.