Cosmetics as a Feature of the Extended Human
Phenotype: Modulation of the Perception of Biologically
Important Facial Signals
Nancy L. Etcoff1,2*, Shannon Stock3, Lauren E. Haley1,2, Sarah A. Vickery4, David M. House5
1Department of Psychiatry, Massachusetts General Hospital, Boston, Massachusetts, United States of America, 2Harvard Medical School, Cambridge, Massachusetts,
United States of America, 3Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, Massachusetts, United States of America,
4 Procter & Gamble Beauty & Grooming, Procter & Gamble Cosmetics, Hunt Valley, Maryland, United States of America, 5Department of Computer Sciences, Boston
University, Boston, Massachusetts, United States of America
Abstract
Research on the perception of faces has focused on the size, shape, and configuration of inherited features or the biological
phenotype, and largely ignored the effects of adornment, or the extended phenotype. Research on the evolution of signaling
has shown that animals frequently alter visual features, including color cues, to attract, intimidate or protect themselves
from conspecifics. Humans engage in conscious manipulation of visual signals using cultural tools in real time rather than
genetic changes over evolutionary time. Here, we investigate one tool, the use of color cosmetics. In two studies, we asked
viewers to rate the same female faces with or without color cosmetics, and we varied the style of makeup from minimal
(natural), to moderate (professional), to dramatic (glamorous). Each look provided increasing luminance contrast between
the facial features and surrounding skin. Faces were shown for 250 ms or for unlimited inspection time, and subjects rated
them for attractiveness, competence, likeability and trustworthiness. At 250 ms, cosmetics had significant positive effects on
all outcomes. Length of inspection time did not change the effect for competence or attractiveness. However, with longer
inspection time, the effect of cosmetics on likability and trust varied by specific makeup looks, indicating that cosmetics
could impact automatic and deliberative judgments differently. The results suggest that cosmetics can create supernormal
facial stimuli, and that one way they may do so is by exaggerating cues to sexual dimorphism. Our results provide evidence
that judgments of facial trustworthiness and attractiveness are at least partially separable, that beauty has a significant
positive effect on judgment of competence, a universal dimension of social cognition, but has a more nuanced effect on the
other universal dimension of social warmth, and that the extended phenotype significantly influences perception of
biologically important signals at first glance and at longer inspection.
Citation: Etcoff NL, Stock S, Haley LE, Vickery SA, House DM (2011) Cosmetics as a Feature of the Extended Human Phenotype: Modulation of the Perception of
Biologically Important Facial Signals. PLoS ONE 6(10): e25656. doi:10.1371/journal.pone.0025656
Editor: Satoru Suzuki, Nothwestern University, United States of America
Received April 8, 2011; Accepted September 8, 2011; Published October 3, 2011
Copyright:  2011 Etcoff et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits
unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: This study was funded by P&G Beauty and Grooming, where Sarah A. Vickery is employed as a Principal Scientist. The funders had no role in study
design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing Interests: The authors have read the journal’s policy and have the following conflicts: this study was funded by P&G Beauty and Grooming, where
SAV is employed as a Principal Scientist. This does not alter the authors’ adherence to all the PLoS ONE policies on sharing data and materials.
* E-mail: netcoff@partners.org
Introduction
First impressions based on facial appearance occur automati-
cally, are difficult to overcome, and impact decision-making.
The strong motivational influence of facial beauty has been
shown in studies of labor markets suggesting that there is a ’’beauty
premium’’ and ‘‘plainness penalty’’ [1] such that attractive indi-
viduals are more likely to be hired, promoted, and to earn higher
salaries than unattractive individuals [2–4]. Social psychologists
have identified a ‘‘halo’’ effect of beauty leading to a range of
positive inferences including that the beautiful are more socially
skilled, confident and successful [5–7]. Inferences of another
attribute, competence, gleaned from a one second exposure to
faces of unknown congressional candidates predict their electoral
success [8,9]. Players in a trust game invested more money in
individuals whose faces were rated as trustworthy, despite the fact
that there is no objective relationship between facial appearance
and actual behavior [8].
Darwinian approaches posit that features of beautiful faces are
important biological signals of mate value that motivate behavior
in others, and have identified features such as averageness,
symmetry and sexual dimorphism as key contributors to female
facial beauty [5–7,10,11]. It is less clear what visual facial
attributes lead to rapid judgments of trustworthiness, competence,
and likeability from the face. Although the ‘‘beauty halo’’ may
provide a partial explanation, it is likely that cues from facial
expressions (real or mimicked by the contours of natural features),
and facial immaturity or maturity are important drivers, the first
signaling friendly or hostile intent (positive emotion or anger), and
the latter, the perceived ability to carry out one’s intentions [12–
14]. All such facial judgments occur quickly, reliably, and change
little with inspection time, suggesting that they are effortless and
automatic. Recent models of social cognition and decision-making
distinguish between such fast operating, reflexive processes
or ‘‘system 1 processes’’ and slower, deliberate, effortful, and
reflective "system 2" processes [15,16].
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To date, face research has focused largely on the biological
phenotype, such as the shape, size, configuration and movement of
facial features, and ignored the effects of facial adornment and
grooming, or ‘‘the extended phenotype.’’ The extended phenotype
[17,18] refers to any effect of the genes beyond the organism’s
body. The spider’s web, the hermit crab’s shell, the bowerbird’s
bower and the beaver’s dam are all considered examples of the
extended phenotype. Among human artifacts, clothing, makeup
and other forms of body adornment are considered phenotypic
extensions. They are found universally and presumed to enhance
perceived biological fitness.
Research on the evolution of signaling has shown that animals
frequently alter or exaggerate visual features, including color cues,
to attract, mimic, intimidate or protect themselves from conspe-
cifics, sometimes setting off an arms race between deception and
the detection of such deception [19]. Humans engage in conscious
manipulation of visual signals using cultural tools in real time
rather than genetic changes over evolutionary time. These tools
highlight, exaggerate or conceal features of the heritable
phenotype and are intended to modulate social impressions and
confer advantages. But how effective they are, for what purposes,
and by which mechanisms, are questions that have been minimally
explored.
Experimental studies by Tinbergen first showed that it was
possible to exaggerate a visual sign stimulus and produce a super-
normal stimulus that elicits a super-normal response [20]. For
example, herring gull chicks will peck more forcefully to red
knitting needles than to a normal herring gull beak: the needles
offer exaggerations of the shape and color cues found on the
mother’s beak. Supernormal stimuli have been found for many
species. It may be that by isolating and exaggerating pre-existing
cues to attractiveness and exploiting human sensory biases,
adornments can heighten and exaggerate our normal aesthetic
responses, rendering the adorned face or body a supernormal
stimuli and our responses, supernormal responses.
Here we examine one example of the human extended
phenotype, the use of color cosmetics, a tool used primarily by
women to enhance facial attractiveness. The use of cosmetics is
ancient. Analyses of Egyptian cosmetic powders dated from 1200 to
200 BC show that very sophisticated wet chemical technology was
already being used in their creation [21]. The ancient Egyptians had
versions of most of the cosmetics that we have today [22].
Interestingly, the use of cosmetics rose precipitously with the advent
of photography [23], suggesting that both may serve as tools in an
escalating beauty arms race. Today cosmetic use is ubiquitous. In a
2010 survey, the majority (63%) of women ages 18 or older in the
United States reported that they had used some type of makeup
product during the past year [24]. The global color cosmetics
market is projected to reach $41.4 billion by the year 2015 [25].
Surprisingly few studies have investigated their effects on perceivers.
The few that have demonstrate that cosmetics can increase
attractiveness in Caucasian women in their 20s and 30s [26–29].
Research on inferences of personality and character has yielded
conflicting and inconclusive findings [28–31].
As popular agents of self-advertising, cosmetics have been
subject to shifting cultural attitudes toward their use. They were
apparently considered so good at deceiving husbands In the late
eighteenth century, and so feared by them, that the English
government proposed a law stating that, ‘‘All women…that shall
from and after this act impose upon, seduce or betray into
matrimony any of his Majesty’s subjects by the use of scents,
paints, cosmetics, washes, … shall incur the penalty of the law now
in force against witch craft and like misdemeanors and that the
marriage upon convictions shall stand null and void’’ [22]. Over
the centuries, women debated whether they were the ‘‘province of
sophisticated beauties or the downfall of wanton souls.’’ [23], or
tools used by admired and envied, or potentially untrustworthy
individuals. Cosmetics have been subject to ‘‘display rules’’ with
practices ranging from restrictive to permissive. Like fashion in
clothing, norms for what makeup looks are considered most
attractive change.
In current culture, cosmetics are seen as freely chosen and
morally neutral agents of beauty enhancement. Their use reflects
the individual’s preferences and choices, and the response to their
use reflects the perceiver’s attitudes about forms of self-presentation
and grooming practices. Thus, when viewing a face with makeup,
perceivers make inferences based not only on cosmetics’ effects on
the appearance of symmetry, clearness of skin or featural contrast,
but on their conscious ideas about makeup use and what it may
signify about the user’s personality, character, and intentions.
We hypothesize that cosmetics will impact face perception at a
system 1 and system 2 levels, engaging both a reflexive and a
reflective response. We predict that at an automatic, implicit level,
cosmetics will have uniformly positive effects on judgments of
beauty, personality and character. We predict that with longer
inspection time, cosmetics will continue to enhance attractiveness,
but may no longer uniformly enhance judgments of likability or
trust, given different social attitudes toward cosmetics use. On
longer inspection we expect to find greater beauty, but not
necessarily the halo surrounding it for all looks.
Finally, to measure one potential source of the cosmetic effect
on face perception we measured luminance contrast between the
eyes, lips, and the surrounding skin for faces without makeup and
for each of the makeup looks. Russell [26,32] has found that sex
differences in facial contrast influence the perception of facial
gender: an androgynous face can be made to appear female by
increasing the facial contrast, or to appear male by decreasing the
facial contrast. Further, female faces wearing cosmetics had
greater facial contrast than the same faces not wearing cosmetics,
suggesting that cosmetics may function in part by exaggerating a
sexually dimorphic attribute—facial contrast.
Methods
Ethics Statement
We have obtained ethics approval for our study from the
Partners Human Research Committee at Massachusetts General
Hospital, where participants were recruited and human experi-
mentation was conducted. This project meets the criteria for
exemption from further IRB review per the regulations found at
45 CFR 46.101(b) (2) Use of educational tests (cognitive,
diagnostic, aptitude, achievement), survey procedures, interview
procedures, or observation of public behavior. Instead of a consent
form, we were instructed to provide subjects with a fact sheet and
not collect a signature. The individuals/subjects pictured in this
manuscript have given written informed consent to publication of
their case details. By signing our consent form and photo release,
they permit us to publish or make other public use of their facial
digital images with the understanding that their names and/or
personal information will not be made public.
To test the impact of cosmetics on judgments of faces we
conducted two studies in which the same models were judged with
and without makeup.
Participants
Subjects in the first study included 149 adults (61 men, 88
women) of different ethnicities who were shown the faces for
250 ms. The second study included 119 adults (30 males, 89
Cosmetics: Feature of the Extended Human Phenotype
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females) of different ethnicities given unlimited time to inspect
each face.
Stimuli
The 100 high-resolution color images were of 25 women ages
20–50, self-identified as Hispanic, Caucasian, or African American
shown in a frontal headshot with a neutral facial expression, and
cropped to remove clothing and hairstyle. We used female models
only, as they represent the vast majority of facial cosmetic users. A
professional photographer took the images under uniform
conditions. Makeup was applied by a makeup artist and then
adjusted digitally. Each model was photographed without makeup
Figure 1. Models without makeup and with natural, professional and glamorous makeup.
doi:10.1371/journal.pone.0025656.g001
Table 1. Comparisons of mean outcome scores for makeup (aggregated) versus no makeup obtained from the regression models
(see Table 2).
Inspection Time Outcome Contrast Estimate SE t-Statistic DF P
250ms Competence Makeup vs. No Makeup 0.34 0.02 15.98 26506 ,0.0001
Likability Makeup vs. No Makeup 0.2 0.02 9.15 26506 ,0.0001
Attractiveness Makeup vs. No Makeup 0.66 0.02 30.5 26506 ,0.0001
Trustworthiness Makeup vs. No Makeup 0.11 0.02 5.08 26506 ,0.0001
Unlimited Competence Makeup vs. No Makeup 0.3 0.02 12.61 26506 ,0.0001
Likability Makeup vs. No Makeup 0.09 0.02 3.8 26506 0.0001
Attractiveness Makeup vs. No Makeup 0.64 0.02 26.22 26506 ,0.0001
Trustworthiness Makeup vs. No Makeup 0 0.02 0.13 26506 0.8988
doi:10.1371/journal.pone.0025656.t001
Cosmetics: Feature of the Extended Human Phenotype
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and with 3 makeup looks ranging from minimal to moderate to
dramatic, looks we informally labeled ‘‘natural’’, ‘‘professional’’ or
‘‘glamorous’’ (Figure 1). We never used these labels during our
work with models or with subjects. Finally, to eliminate demeanor
cues that may result from the models seeing themselves with
makeup, we removed all mirrors from the studio.
Procedure
Subjects were presented the stimuli on an iMac desktop. Each
subject saw all four looks for each of the 25 models in a
randomized sequence and rated them for attractiveness, likeability,
trustworthiness, and competence using a 7-point ‘‘slider scale’’
ranging from end points labeled ‘‘not at all’’ to ‘‘highly/
extremely.’’
Results
Analysis
Our statistical analyses of makeup by inspection time were
obtained from a linear mixed effects model with crossed random
effects, similar to the model described by Baayen et al. [33]. We
conducted two analyses-the first aggregated the makeup looks and
compared any use of cosmetics to no makeup. The second
compared each individual makeup look to no makeup. We used a
Table 2. Regression models aggregating the makeup looks.
Outcome Covariate Estimate SE t-Stat. DF P F-Stat.
Num. DF;
Den. DF P
Competence Intercept 3.87 0.12 33.53 65.95 ,0.0001
ModelMakeup Makeup 0.30 0.02 12.61 26506.06 ,0.0001 402.04 1;27000 ,.0001
No Makeup 0.00
length 250 ms -0.12 0.10 -1.24 300.10 0.2167 1.13 1;270 0.2889
Unlimited 0.00
ModelMakeup*length Makeup 250 ms 0.04 0.03 1.26 26506.04 0.2079 1.59 1;27000 0.2079
Unlimited 0.00
No Makeup 250 ms 0.00
Unlimited 0.00
Likability Intercept 3.74 0.14 26.50 44.19 ,0.0001
ModelMakeup Makeup 0.09 0.02 3.80 26506.06 0.0001 79.83 1;27000 ,.0001
No Makeup 0.00
length 250 ms -0.01 0.10 -0.14 304.32 0.8893 0.19 1;270 0.6673
Unlimited 0.00
ModelMakeup*length Makeup 250 ms 0.11 0.03 3.27 26506.03 0.0011 10.71 1;27000 0.0011
Unlimited 0.00
No Makeup 250 ms 0.00
Unlimited 0.00
Attractiveness Intercept 3.13 0.17 18.93 40.81 ,0.0001
ModelMakeup Makeup 0.64 0.02 26.22 26506.05 ,0.0001 1590.49 1;27000 ,.0001
No Makeup 0.00
length 250 ms -0.04 0.11 -0.37 295.32 0.7115 0.07 1;270 0.7984
Unlimited 0.00
ModelMakeup*length Makeup 250 ms 0.03 0.03 0.80 26506.03 0.4240 0.64 1;27000 0.424
Unlimited 0.00
No Makeup 250 ms 0.00
Unlimited 0.00
Trustworthiness Intercept 3.91 0.12 33.36 60.94 ,0.0001
ModelMakeup Makeup 0.00 0.02 0.13 26506.07 0.8988 12.13 1;27000 0.0005
No Makeup 0.00
length 250 ms -0.09 0.10 -0.88 302.96 0.3819 0.11 1;270 0.7389
Unlimited 0.00
ModelMakeui*length Makeup 250 ms 0.11 0.03 3.29 26506.04 0.0010 10.85 1;27000 0.001
Unlimited 0.00
No Makeup 250 ms 0.00
Unlimited 0.00
doi:10.1371/journal.pone.0025656.t002
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Bonferroni correction to preserve the overall type-1 error rate of
0.05 for the pair wise comparisons used within each analysis.
Overall, makeup (aggregated across all looks) produced a significant
positive main effect on judgments of all outcomes in the 250 ms
presentation (all p,0.0001) and on judgments of attractiveness,
p,0.0001), competence (p,0.0001), and likeability (p,0.0001) , but
not trustworthiness on longer inspection (p=0.8988) (Table 1,
Bonferroni corrected significance level =0.05/8=0.006). A signifi-
cant interaction of makeup x inspection time revealed that perceptions
of likability and trustworthiness showed a significantly larger positive
makeup effect at 250 ms presentation times than when presented with
unlimited inspection time: likeability (F(1,27000)=10.71, p=0.0011)
and trustworthiness (F(1,27000)=10.85, p=0.0010) Length of
inspection time did not modify the strength of the makeup effect for
competence or attractiveness (Table 2).
Analysis of the effects of the individual makeup ‘‘looks’’ revealed
that each had a significant positive effect on judgments of competence
and attractiveness both at 250 ms and at longer inspection times
(Table 3). With unlimited inspection time, the natural and
professional looks had significant positive effects on likability (na-
tural t(26502)=4.93, professional t(26502)= 5.18, both p,.0001,
Bonferroni corrected significance level = 0.05/24 =0.002), while
the glamorous look did not have a significant effect (t(26502) = -0.79,
p= 0.4293). The natural look also had a significant positive effect
on trustworthiness (t(26502) = 3.15, p= 0.0016), while the pro-
fessional look did not have a significant effect (t(26502) = 1.50,
p= 0.1337), and the glamorous look had a significant negative effect
(t(26502) = -4.33, p,0.0001). There was a significant makeup x
inspection time interaction for the glamorous look on all outcomes,
with significantly larger positive effects when this look was presented
for 250 ms than when presented with unlimited inspection time.
The professional look showed significantly larger positive makeup
effects at 250 ms for likeability (t(26502) = 2.4, p= 0.0162) and
trustworthiness (t(26502) = 2.33, p= 0.0198), while the judgments of
the natural look did not change significantly with inspection time
(Table 4). Figure 2 illustrates these effects for 3 of the looks: the no
makeup, natural and glamorous looks.
Finally, to determine luminosity contrasts, color images were
individually hand-labeled to define 4 regions: the eyes, including
the eye itself (the sclera, iris, and pupil), eyelashes, the skin between
the epicanthal fold and the eye; and the skin immediately below
the eye; the lips; the annuli surrounding the eyes; and an annulus
surrounding the lips. Then using a SpectraH PhoRadH Photom-
eter, luminance values in candelas per meter squared (cd/m2)
were collected from the iMac computer screen within the four
regions and averaged, yielding mean luminance values for each of
the four regions. The mean luminance for the eyes and lips were
averaged to produce the mean feature luminance, and the mean
luminance values for the eye and lip annuli were averaged to
produce the mean skin luminance. Facial contrast was calculated
as Cf = (feature luminance – skin luminance)/(feature luminance +
skin luminance) [26,32].
Table 3. Comparisons of mean outcome scores for the different makeup looks versus no makeup obtained from the regression
models (see Table 4).
Outcome Contrast Estimate SE t-Statistic DF P
250 ms Competence Glamorous vs No Makeup 0.42 0.03 16.03 26502 ,0.0001
Professional vs No Makeup 0.41 0.03 15.55 26502 ,0.0001
Natural vs No Makeup 0.2 0.03 7.64 26502 ,0.0001
Likability Glamorous vs No Makeup 0.21 0.03 7.59 26502 ,0.0001
Professional vs 0.26 0.03 9.41 26502 ,0.0001
No Makeup
Natural vs No Makeup 0.15 0.03 5.45 26502 ,0.0001
Attractiveness Glamorous vs No Makeup 0.83 0.03 31.19 26502 ,0.0001
Professional vs No Makeup 0.76 0.03 28.79 26502 ,0.0001
Natural vs No Makeup 0.4 0.03 15.28 26502 ,0.0001
Trustworthiness Glamorous vs No Makeup 0.09 0.03 3.52 26502 0.0004
Professional vs No Makeup 0.14 0.03 5.17 26502 ,0.0001
Natural vs No Makeup 0.1 0.03 3.76 26502 0.0002
Unlimited Competence Glamorous vs No Makeup 0.3 0.03 10.16 26502 ,0.0001
Professional vs No Makeup 0.37 0.03 12.54 26502 ,0.0001
Natural vs No Makeup 0.24 0.03 8.22 26502 ,0.0001
Likability Glamorous vs No Makeup -0.02 0.03 -0.79 26502 0.4293
Professional vs No Makeup 0.16 0.03 5.18 26502 ,0.0001
Natural vs No Makeup 0.15 0.03 4.93 26502 ,0.0001
Attractiveness Glamorous vs No Makeup 0.68 0.03 23.01 26502 ,0.0001
Professional vs No Makeup 0.76 0.03 25.56 26502 ,0.0001
Natural vs No Makeup 0.48 0.03 16.1 26502 ,0.0001
Trustworthiness Glamorous vs No Makeup -0.13 0.03 -4.33 26502 ,0.0001
Professional vs No Makeup 0.04 0.03 1.5 26502 0.1337
Natural vs No Makeup 0.09 0.03 3.15 26502 0.0016
doi:10.1371/journal.pone.0025656.t003
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Table 4. Regression models for the makeup looks.
Outcome Covariate Estimate SE t-Stat. DF P F-Stat.
Num
DF
Denom
DF P
Competence Intercept 3.87 0.12 33.53 65.93 ,0.0001
Model
Makeup
Glamorous 0.30 0.03 10.16 26502.03 ,0.0001 162.05 3 27000 ,0.0001
Professional 0.37 0.03 12.54 26502.09 ,0.0001
Natural 0.24 0.03 8.22 26502.03 ,0.0001
No Makeup 0.00
Length 250 ms -0.12 0.10 -1.24 299.97 0.2167 0.93 1 266 0.3369
Unlimited 0.00
Model
Makeup
*Length
Glamorous 250 ms 0.12 0.04 3.11 26502.01 0.0019 6.26 3 27000 0.0003
Unlimited 0.00
Professional 250 ms 0.04 0.04 1.01 26502.05 0.3119
Unlimited 0.00
Natural 250 ms -0.04 0.04 -1.04 26502.02 0.2993
Unlimited 0.00
No Makeup 250 ms 0.00
Unlimited 0.00
Likability Intercept 3.74 0.14 26.50 44.18 ,0.0001
Model
Makeup
Glamorous -0.02 0.03 -0.79 26502.02 0.4293 37.33 3 27000 ,0.0001
Professional 0.16 0.03 5.18 26502.09 ,0.0001
Natural 0.15 0.03 4.93 26502.03 ,0.0001
No Makeup 0.00
Length 250 ms -0.01 0.10 -0.14 304.24 0.8893 0.52 1 266 0.4725
Unlimited 0.00
Model
Makeup
*Length
Glamorous 250 ms 0.23 0.04 5.65 26502.01 ,0.0001 14.43 3 27000 ,0.0001
Unlimited 0.00
Professional 250 ms 0.10 0.04 2.40 26502.05 0.0162
Unlimited 0.00
Natural 250 ms 0.00 0.04 -0.04 26502.02 0.9674
Unlimited 0.00
No Makeup 250 ms 0.00
Unlimited 0.00
fAttractiveness Intercept 3.13 0.17 18.93 40.80 ,0.0001
Model
Makeup
Glamorous 0.68 0.03 23.01 26502.02 ,0.0001 650.34 3 27000 ,0.0001
Professional 0.76 0.03 25.56 26502.07 ,0.0001
Natural 0.48 0.03 16.10 26502.02 ,0.0001
No Makeup 0.00
Length 250 ms -0.04 0.11 -0.37 294.88 0.7114 0.04 1 266 0.8450
Unlimited 0.00
Model
Makeup
*Length
Glamorous 250 ms 0.14 0.04 3.65 26502.01 0.0003 10.42 3 27000 ,0.0001
Unlimited 0.00
Professional 250 ms 0.00 0.04 0.12 26502.04 0.9018
Unlimited 0.00
Natural 250 ms -0.07 0.04 -1.81 26502.01 0.0701
Unlimited 0.00
No Makeup 250 ms 0.00
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Analyses confirmed that each pair of looks was significantly different
in level of facial luminance contrast (all |t(72)|$5.87, p,.0001,
Bonferroni corrected significance level =0.05/18=0.003), except the
natural look versus no makeup, which was marginally non-significant
(t(72)= -1.83, p=0.0717) (Tables S1 and S2). Facial luminance
contrast increased from the face with no makeup to the face with
natural, professional, and glamorous applications, respectively.
Additional analyses not summarized here allowed for potential effect
Outcome Covariate Estimate SE t-Stat. DF P F-Stat.
Num
DF
Denom
DF P
Unlimited 0.00
Trustworthiness Intercept 3.91 0.12 33.36 60.92 ,0.0001
Model
Makeup
Glamorous -0.13 0.03 -4.33 26502.03 ,0.0001 17.96 3 27000 ,0.0001
Professional 0.04 0.03 1.50 26502.10 0.1337
Natural 0.09 0.03 3.15 26502.03 0.0016
No Makeup 0.00
Length 250 ms -0.09 0.10 -0.88 302.87 0.3819 0.00 1 266 0.9598
Unlimited 0.00
Model
Makeup
*Length
Glamorous 250 ms 0.22 0.04 5.58 26502.01 ,0.0001 13.51 3 27000 ,0.0001
Unlimited 0.00
Professional 250 ms 0.09 0.04 2.33 26502.06 0.0198
Unlimited 0.00
Natural 250 ms 0.01 0.04 0.16 26502.02 0.8699
Unlimited 0.00
No Makeup 250 ms 0.00
Unlimited 0.00
doi:10.1371/journal.pone.0025656.t004
Table 4. Cont.
Figure 2. Means for the no makeup, natural and glamorous looks at 250 ms, and unlimited inspection times.
doi:10.1371/journal.pone.0025656.g002
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modification by race, but the interaction terms were not significant. All
looks significantly decreased feature luminance (all |t(72)|$4.19,
p,0.0001), except the natural versus no makeup (t(72)= -.76,
p=0.4479), while none of the looks differed significantly from one
another with respect to skin luminosity (all |t(72)|#1.55, p.0.12).
In summary, we found evidence of significant effects of
cosmetics in both studies. All the makeup looks significantly
increased attractiveness and competence ratings at 250 ms and on
longer inspection. Ratings of likeability and trust varied with
makeup look and inspection time, suggesting that they elicited
different reflexive and reflective responses.
Discussion
Our results have a number of implications. As predicted,
makeup had significant positive effects on ratings of female facial
attractiveness at brief and longer inspection times. Ratings of
competence increased significantly with makeup look tested on
first glance and longer inspection. Effects were weaker and more
variable for ratings of likability and trustworthiness, although
generally positive.
Social psychologists have suggested that social warmth and
social competence represent two universal dimensions of social
perception by which we evaluate individuals and groups, [34] with
warmth capturing traits related to social cooperation, and power/
competence capturing cues relevant to advantage in social
competition, such as status and dominance. Here we show a
robust and positive effect of increased beauty on social power/
competence and a generally positive but more nuanced and
variable effect on social warmth.
Past studies have shown that attractive people are expected to
do better on the job, in school, and in life – and are treated that
way – by being agreed with, deferred to, helped, and granted
larger personal space [7]. In a recent experimental study using a
task for which physical attractiveness did not improve productivity,
researchers demonstrated conclusively that employers expect
physically attractive workers to perform better at their jobs and
be more competent [35].
But, as sociologists Webster and Driskell noted when first
proposing the idea of beauty as status, there are important
differences between attractiveness and other status characteristics
such as race or sex: beauty is a malleable characteristic [36]. They
predicted that, given the powerful effect of status, ‘‘attractiveness
will assume increasing significance as other characteristics such as
race and sex fall into disuse.’’ We suggest that attractiveness has
assumed increasing significance, and will continue to do so as long
as beauty remains an often unconscious proxy for status and ability.
The beauty halo effect has been called the ‘‘what is beautiful is
good’’ effect. In our study, makeup increased inferences of warmth
and cooperation (likability and trustworthiness) when faces were
presented very briefly, but did not always do so on longer inspection.
In general, there is less agreement about whether beauty invariably
signals social cooperation, with some studies suggesting that there is
a ’’dark side’’ to beauty characterized by vanity, immodesty, or
greater likelihood to cheat on a partner [37]. Our findings suggest
that it may be fruitful to disentangle the effects of beauty from
beauty enhancement, or phenotype from extended phenotype here.
It may be that natural beauty or natural appearing beauty leads to
positive inferences of social cooperation, where more obvious
beauty enhancement may lead to neutral or even negative
inferences. Finally, our results provide additional evidence that
judgments of facial trustworthiness and facial attractiveness are at
least partially separable; the highest contrast makeup (glamorous)
increased attractiveness significantly while at the same time
decreasing judgments of trustworthiness.
Our study looked at one potential source of the cosmetics effect
on face perception, increasing luminance contrast between the
features (eyes and lips) and the surrounding skin, and looked for the
first time at luminance contrast in African American and Hispanic
faces. We found that cosmetics increased luminance contrast by
significantly darkening the eyes and lips. Skin was neither
significantly lightened nor darkened. However, luminance contrast
effects for our natural look compared to a face without makeup was
only marginally significant. It is likely that cosmetics induced image
changes other than changes in luminance contrast contributed to
our effects. These include possible changes in the smoothness of skin
tone, in the redness of skin color or lip color, and in shading that
accentuates the cheekbones. Previous research has shown that
makeup can improve skin appearance, evenness, and texture to
appear healthier, fertile, and youthful [38,39], and that skin and lip
color can contribute significantly to perception of sex typicality and
attractiveness [40,41], with lip redness enhancing femininity and
attractiveness of female Caucasian faces [41].
Finally, our study included only North American subjects; we
do not know if such effects will be found in subjects from other
cultures.
In sum, we show that faces with cosmetics engage both fast,
reflexive processes, and more deliberative conscious processes.
The fast, automatic effects are uniformly strong and positive for all
outcomes. In situations where a perceiver is under a high cognitive
load or under time pressure, he or she is more likely to rely on such
automatic judgments for decision-making. Facial images appear
on ballots, job applications, websites and dating sites. Our results
underscore the malleability of judgments derived from facial
images of a single individual at zero acquaintance, judgments that
can be highly consequential. When inferring trustworthiness,
likeability, or competence from an image, we are influenced
significantly not only by the attractiveness of the inherited
phenotype but by the effects of the ‘‘extended phenotype,’’ in
this case, makeup.
Supporting Information
Table S1 Comparisons of mean luminosity measures for the
different makeup looks obtained from the luminosity analysis
regression models (see Table 2).
(DOCX)
Table S2 Regression models for the luminosity analysis.
(DOCX)
Acknowledgments
We thank Al Carlay, Christina Congleton, Angelique Dada, Igor Elman
MD, Shekhar Mitra Ph.D., James Sarzotti, Beth Twohy, Eva Wisten, the
editor and two anonymous reviewers for their assistance.
Author Contributions
Conceived and designed the experiments: NLE. Performed the experi-
ments: LEH. Analyzed the data: SS LEH. Contributed reagents/
materials/analysis tools: DMH SS SAV. Wrote the paper: NLE LEH.
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