In the first study, we tested the effect of a facial mask on perception of attractiveness using a sample of young people's faces with a neutral facial expression.
Method
Participants
A total of 164 individuals (58 men and 106 women), aging between 18 and 75 years of age (M = 40.6, SD = 14.3), were recruited from TurkPrime panel as participants. A total of 92 participants (56.1%) reported being married, 1.2% reported widowed and an additional 8.5% reported being divorced or separated, while 24.4% reported being single, and 9.8% in a relationship. In terms of their highest educational degree, 30.5% had a high school diploma, 7.3% had a post-secondary diploma, 25.0% of the participants had an undergraduate degree, one reported elementary school and 36.6% had a post-graduate degree.
Stimuli and procedure
Images of 25 male and 25 female faces, aged between 19 and 31 years and with a neutral expression, were obtained from the FACES database (Ebner et al., 2010), resulting in 50 stimuli. Another set of 50 stimuli of the same identities were created by superimposing a facial mask on the original images. Each set of stimuli (masked or unmasked) were randomised and presented in separate blocks. After consenting to participate in the study, participants answered sociodemographic questions. A within-subjects design was used, and participants randomly observed either the block with facial masks first or the block without masks first. Participants were asked to respond to the question “How attractive do you find this man?” or “How attractive do you find this woman?” on a 7-point scale, from 1 (not at all) to 7 (very) (Fig. 1).
Data analysis
The average ratings of attractiveness for the original unmasked stimuli was calculated and the stimuli were grouped as above (high attractiveness) and below (low attractiveness) the average. All post hoc comparisons throughout the results of this and next studies were performed using Bonferroni correction, and this is reflected in the p values. A G*Power analysis for a 2 × 2 × 2 × 2 mixed effects design indicated that 92 participants would be sufficient to detect a small effect size (f = 0.10, β = 0.80). In our studies we recruited participants almost twice the needed size (~ 180).
Results
A linear mixed model was conducted to investigate the effect of presence/absence of facial mask, stimuli sex, participants’ sex, and attractiveness group (low and high) on the ratings of attractiveness in young people faces, with participants as a random factor. Results showed significant main effects for facial mask, stimuli sex, participant sex, and attractiveness group (see Additional file 1: Table S1 for details). The main effect of mask was further qualified by two 2-way interactions: Mask × Attractiveness Group, and Mask × Stimuli Sex.
The Mask × Attractiveness Group interaction showed that for the low attractiveness group, participants rated faces with masks (M = 4.28, SEM = 0.11) as more attractive compared to their unmasked faces (M = 3.97, SEM = 0.11, p < 0.001); while in the high attractiveness group the ratings were not significantly different between masked (M = 4.57, SEM = 0.12) and unmasked of attractive faces (M = 4.52, SEM = 0.12, p = 0.999) (Fig. 2, left panel).
The Mask × Stimuli Sex interaction (as seen in Fig. 2, right panel) reflects that as females are more attractive than males overall (ps < 0.012) and masks increase the attractiveness of both females and males (ps < 0.001), a masked male (M = 4.30, SEM = 0.12) is perceived as attractive as an unmasked female (M = 4.31, SEM = 0.11, p = 0.999), but a masked female (M = 4.55, SEM = 0.11) is significantly more attractive than an unmasked male (M = 4.18, SEM = 0.12, p < 0.001).
Discussion
Results of the first study showed that facial masks increased ratings of attractiveness for those faces that were less attractive than average, while having no effect on above average attractive faces. Such results are in contrast with those of Miyazaki and Kawahara (2016), who reported an overall negative effect of facial masks on ratings of attractiveness. However, our results converge partially with those of Orghian and Hidalgo (2020) who showed a positive bias for incomplete faces. Nonetheless, our result is limited to a sample of young faces and might not be generalized to a broader population (i.e., older adults).
Previous research has shown that individuals consider younger faces more attractive than older faces (Ebner, 2008; Kwart et al., 2012). It is suggested that age-related features in older faces such as lines, wrinkles, and furrows on skin results in their being perceived as relatively less attractive than younger faces (Berry & McArthur, 1986; Matts et al., 2007).
To the extent that our finding in Study 1 is robust, we would expect masks to increase the attractiveness only of older adult faces that are less attractive on average. Alternatively, because older adults are generally less attractive than younger faces, one might expect that masks will increase the attractiveness rating of all older faces. There is a second reason to expect this outcome. By covering the lower part of the face, wearing facial masks would reduce the evidence of age-related changes to the face, thereby making all of the older faces more attractive.