Using eye tracking to test for individual differences in attention to attractive faces

Abstract

We assessed individual differences in visual attention toward faces in relation to their attractiveness via saccadic reaction times. Motivated by the aim to understand individual differences in attention to faces, we tested three hypotheses: (a) Attractive faces hold or capture attention more effectively than less attractive faces; (b) men show a stronger bias toward attractive opposite-sex faces than women; and (c) blue-eyed men show a stronger bias toward blue-eyed than brown-eyed feminine faces. The latter test was included because prior research suggested a high effect size. Our data supported hypotheses (a) and (b) but not (c). By conducting separate tests for disengagement of attention and attention capture, we found that individual differences exist at distinct stages of attentional processing but these differences are of varying robustness and importance. In our conclusion, we also advocate the use of linear mixed effects models as the most appropriate statistical approach for studying inter-individual differences in visual attention with naturalistic stimuli.

Mechanisms for the Cognitive Processing of Attractiveness in Adult and Infant Faces: From the Evolutionary Perspective

“…Relatively, facial attractiveness in male faces is not as important for women as is facial attractiveness in female faces for men. Although women showed attention bias toward HA male faces compared with LA male faces (Silva et al, 2016), the attentional bias toward HA oppositesex faces was significantly stronger for men than that for women (Kleck and Rubenstein, 1975;Fugita et al, 1977;van Straaten et al, 2010;Valuch et al, 2015;Mitrovic et al, 2018). Nevertheless, we should notice that the attractiveness in male faces may be different for women in different situations (e.g., in the ovulatory phase or not).…”

“…Neurophysiological also revealed that HA opposite-sex faces induced a larger LPP than did LA faces among heterosexual individuals (van Hooff et al, 2011). Nevertheless, although some researchers have found attentional bias toward HA male faces among female observers, they also indicate that such an effect is much weaker than the attentional bias toward HA female faces among male observers (van Straaten et al, 2010;Valuch et al, 2015). The difference between the hypotheses of "female beauty captures attention" and "opposite-sex beauty captures attention" requires further investigation.…”

“…First, the sex of the targets may determine the effect of facial attractiveness on visual attention. Some studies have revealed that men may show a stronger attentional bias toward HA oppositesex faces than women may (Fugita et al, 1977;van Straaten et al, 2010;Valuch et al, 2015;Mitrovic et al, 2018). For example, evidence showed that heterosexual men spent less time fixating on LA faces than on HA opposite-sex faces, while there was no significant difference of fixation time between LA and HA faces among heterosexual women (van Straaten et al, 2010).…”

“…Second, from the perspective of mate selection, men but not women emphasize the physical attractiveness of the mate. Therefore, the effects of facial attractiveness on cognitive processing are greater in male observers than in female observers (Kleck and Rubenstein, 1975;Fugita et al, 1977;van Straaten et al, 2010;Valuch et al, 2015;Mitrovic et al, 2018). However, from the perspective of raising offspring, women play a more important role than do men.…”

Differences in the Evaluation of Prosocial Lies: A Cross-Cultural Study of Canadian, Chinese, and German Adults

“…Separate LME models were built for dependent variables of perceived (a) politeness, (b) appropriateness, and (c) usage. In all cases, we first defined a base model, which included only one random effect (Subject); refined models were then identified by performing comparisons using the ANOVA function in R, and systematically comparing the full model with the model reduced by random and fixed effects in turn (see similar approach in Valuch et al, 2015). Our fixed effects included Intention (LIE, BLUNT) and Cultural Group (Canadian, Chinese, German), Age, Cloze, Education, Self-Rating Language Scores, and Duration in Canada.…”