Interior Color and Psychological Functioning in a University Residence Hall

Abstract

The research exploited a unique architectural setting of a university residence hall composed by six separate buildings that matched for every architectural detail and differed only for the interior color (violet, blue, green, yellow, orange, and red). Four hundred and forty-three students living in the six buildings for an average of 13.33 months participated in a study that assessed color preference (hue and lightness), lightness preference, and the effects of color on studying and mood. The results showed a preference for blue interiors, followed by green, violet, orange, yellow, and red. A preference bias was found for the specific color in which the student lived. Gender differences emerged for the preference of blue and violet. Room-lightness was significantly affected by the interior color. Room ceiling was preferred white. Blue as interior color was considered to facilitate studying activity. The use of differentiated colors in the six buildings was evaluated to significantly facilitate orienting and wayfinding. A significant relation was found between a calm mood and preference for blue.

Full text

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ORIGINAL RESEARCH
published: 28 August 2018
doi: 10.3389/fpsyg.2018.01580
Edited by:
Patrik Sörqvist,
Gävle University College, Sweden
Reviewed by:
Francesca Pazzaglia,
Università degli Studi di Padova, Italy
Bernardo Hernández,
Universidad de La Laguna, Spain
*Correspondence:
Marco Costa
marco.costa@unibo.it
Specialty section:
This article was submitted to
Environmental Psychology,
a section of the journal
Frontiers in Psychology
Received: 06 April 2018
Accepted: 08 August 2018
Published: 28 August 2018
Citation:
Costa M, Frumento S, Nese M and
Predieri I (2018) Interior Color
and Psychological Functioning in a
University Residence Hall.
Front. Psychol. 9:1580.
doi: 10.3389/fpsyg.2018.01580
Interior Color and Psychological
Functioning in a University
Residence Hall
Marco Costa1*, Sergio Frumento2, Mattia Nese1and Iacopo Predieri1
1Department of Psychology, University of Bologna, Bologna, Italy, 2Department of Surgery, Medical, Molecular, and Critical
Area Pathology, University of Pisa, Pisa, Italy
The research exploited a unique architectural setting of a university residence hall
composed by six separate buildings that matched for every architectural detail and
differed only for the interior color (violet, blue, green, yellow, orange, and red).
Four hundred and forty-three students living in the six buildings for an average of
13.33 months participated in a study that assessed color preference (hue and lightness),
lightness preference, and the effects of color on studying and mood. The results
showed a preference for blue interiors, followed by green, violet, orange, yellow, and
red. A preference bias was found for the specific color in which the student lived.
Gender differences emerged for the preference of blue and violet. Room-lightness was
significantly affected by the interior color. Room ceiling was preferred white. Blue as
interior color was considered to facilitate studying activity. The use of differentiated colors
in the six buildings was evaluated to significantly facilitate orienting and wayfinding.
A significant relation was found between a calm mood and preference for blue.
Keywords: color, chromatic preference, lightness preference, architecture, interior design
INTRODUCTION
Although color is a ubiquitous property of every architectural surface, evidence-based research
on chromatic preference in architecture and psychological effects of color as a function of the
architectural design of a space is still sparse. This study exploited a unique architectural setting
of a university residence hall for long-term student accommodation, composed by six separate
buildings that matched for every design feature with the only exception of interior color. Each
building interior was characterized by a specific color for walls, ceiling, and floor in both common
spaces and students’ rooms. The colors were: violet, blue, green, yellow, orange, and red. Students
were independently assigned to the different colors by the residence administration. Therefore,
this architectural setting resulted as an in vivo experiment that allowed a controlled assessment of
students’ color preferences, their satisfaction with the color and lightness level of the building they
lived in, and their assessment of the building color effect on their mood, studying activity, orienting
within the residence.
Colors have three basic perceptual attributes: hue, saturation, and lightness (Hunt and
Pointer, 2011). Hue is the phenomenological correspondent of wavelength within the visible-light
spectrum. Saturation (chroma) describes the intensity or purity of a hue, whereas lightness (value)
varies according to the relative presence of black or white in the color. At the lower extreme of
saturation lie the achromatic colors gray, black, and white. Many models exist that map colors
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Costa et al. Interior Color in a University Residence Hall
along these attributes in two-dimensional or three-dimensional
spaces. Some of these models are perceptually uniform, and
match human-color perception (e.g., Munsell, CIE Lab), whereas
others are not perceptually uniform, and were developed to map
colors for specific technical domains (e.g., RGB, HSV, HSL, HSB,
CMYK).
Color preferences were mainly investigated manipulating hue,
starting from the pioneering work by Eysenck (1941) who
established a universal preference hierarchy in colors. According
to his study the most preferred color was blue, followed by red,
green, violet, orange, and yellow. This finding agreed with those
obtained by Granger (1952) and Guilford and Smith (1959) who
found the highest preference ratings for the blue-green hues and
the lowest for yellow and yellow-green hues. These results were
further confirmed by Granger (1955),Dittmar (2001),Bakker
et al. (2013), and Schloss et al. (2013). Hue preferences in adults
follows a relatively smooth curvilinear function in which cool
colors (green, cyan, blue) are generally preferred to warm colors
(red, orange, yellow) (Palmer et al., 2013). Focusing on color
saturation, Palmer et al. (2013), in a review on color preference
studies, concluded that, in general, more colorful and saturated
colors are preferred to less vivid color. Saturation interacts with
preferences for lightness so that yellow is preferred at high
lightness levels, red and green at medium lightness levels, and
blue and purple at low lightness levels (Guilford and Smith, 1959).
Dark shades of orange (browns) and yellow (olives) tend to be
strongly disliked relative to lighter, equally saturated oranges and
yellow (Guilford and Smith, 1959;Palmer and Schloss, 2010).
Color preference in these studies was assessed rating preselected
color patches (either as physical colored chips, or presented on
computer monitor), or asking participants to imagine colors, and
was not referred to specific objects.
The extent to which these global and abstract color preferences
could be applied to specific contexts was the focus of different
studies. For example, Taft (1997) compared the abstract semantic
ratings of color samples with those of the same colors applied
to a variety of familiar objects (e.g., sofa, modern chair, antique
chair, bicycle, cheese slicer, and computer), finding a good
correspondence between the two sets of ratings. Overall, he
found that only in the 4% of cases the color on the sample
was judged different for attractiveness from the same color on
an object. The specificity of color preference for specific objects
was explained in terms of appropriateness of the color-object
association based on people experience. Some objects, in fact,
can be found in a wide variety of colors (e.g., bicycles), whereas
many objects appear in a very limited range of colors (e.g.,
computers, smartphones). Schloss et al. (2013) showed eight
hues, each at two levels of saturation and two levels of lightness, in
addition to five achromatic colors (black, white, and three shades
of gray). Participants had to rate the preference of each color
contextless on simple patches, and with reference to different
objects, both imagined and depicted (e.g., car, t-shirt, walls, sofa
etc.). The results showed that people preferred more saturated
colors when evaluating simple patches than real objects. They
also preferred darker colors for objects (e.g., t-shirts, scarfs, and
couches) compared to participants’ general preferences, with
the exception of walls that were preferred with lighter colors.
Furthermore, wall colors were preferred lighter in the imagined
condition compared to the depicted condition. Jonauskaite et al.
(2016) investigated context-specific color preferences comparing
abstract color preferences, imagined interior walls, and imagined
t-shirts. They used an unrestricted color selection approach with
three-color dimensions (i.e., hue, chroma and lightness). Abstract
colors were preferred with more chroma, whereas lighter colors
were preferred for walls, and darker colors were preferred for
t-shirts.
In the specific architectural context, Kunishima and Yanase
(1985) investigated the visual effects of wall colors in living
rooms. Architectural students had to evaluate living room models
differing in color. A factor analysis highlighted three main
dimensions: “activity,” “evaluation,” and “warmness.” “Activity”
was mostly affected by the brightness of the wall color,
“evaluation” by the saturation, and “warmness” by the hue.
The impact of light and color on psychological mood in work
environments was investigated by Küller et al. (2006) in a large-
scale study that involved 988 persons from different countries.
The presence of some colors, in comparison to a no-color, or
neutral-color condition, resulted in a more positive worker’s
mood. The use of very saturated colors, to the contrary, had a
negative effect on mood.
Several studies investigated the role of sex and culture to test
the universality of color preference (Choungourian, 1968;Saito,
1994, 1996;Ou et al., 2004, 2012;Hurlbert and Ling, 2007;Al-
Rasheed, 2015). A study on sex differences found a peak for the
blue-green in the preference pattern of males and a peak for the
reddish-purple region for females but when Chinese and British
participants were analyzed separately the sex differences emerged
only in the British subpopulation (Hurlbert and Ling, 2007).
Taylor et al. (2013a) pointed out that previous studies focused
mainly on industrialized cultures, and they decided to compare
color preferences of British adults to those of Himba adults,
who belong to a non-industrialized culture in rural Namibia.
Results suggested that predictive models proposed in previous
studies cannot account for the differences observed in the two
populations.
Another cross-cultural study found significant differences
between a population from Poland and a population from Papua
(Sorokowski et al., 2014), even if sex patterns had a much higher
effect size than cultural difference. In fact, although preferences
observed in the two populations were different, the differences
observed in the preference patterns of males and females were
comparable in the two samples.
Some studies also investigated the relation between color
preferences and age (Teller et al., 2004;Zemach et al., 2007;
Franklin et al., 2008, 2010;Taylor et al., 2013b). For hue
preference there is good agreement between different age
categories. In particular, both infants and adults tend to show a
preference for blue and a dislike for greenish-yellow (Teller et al.,
2004;Zemach et al., 2007;Franklin et al., 2008, 2010). Palmer
and Schloss (2010) found significant differences for lightness and
saturation (infants tend to prefer saturated and light hues). In
comparative studies, the preference for blue was also confirmed
in rhesus monkeys (Humphrey, 1972;Sahgal et al., 1975), and
pigeons (Sahgal and Iversen, 1975).
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Different accounts have been proposed to explain color
preference. According to Hurlbert and Ling (2007) color
preference is rooted in the cone-opponent contrast neural
mechanisms which encode colors. Human color vision is in
fact based on two cone-opponent systems, loosely called “red-
green” and “blue-yellow.” The red-green system responds to the
difference between long-wavelength-sensitive cone responses (L)
and middle-wavelength-sensitive (M) responses (L–M), while
the blue-yellow system differences short-wavelength-sensitive (S)
cones with a combination of L and M cones [S – (L +M)]. The
blue-yellow system accounts for the greatest variance (44.5%)
for color preference across the population, with blue hues that
are preferred over yellow hues. To the contrary, the red-green
system accounts mainly for sex differences, with females that
prefer colors with “reddish” contrast against the background in
comparison to males (Hurlbert and Ling, 2007).
In another perspective, color preference could be grounded on
emotional associations of colors. Colors are strictly associated to
specific emotional states (Ou et al., 2004), and if an emotional
state is perceived as pleasant then indirectly the pleasantness is
transferred to the color. According to this theory, active, light,
and cool colors are being preferred over passive, heavy, and warm
ones. This theory, however, fails to explain why although blue
is associated with sadness it is the most preferred color, and
why yellow which is associated with joy, is less preferred than
blue.
According to the ecological valence theory (EVT, Palmer
and Schloss, 2010) color preferences arise from people’s average
affective responses to color-associated objects, so that people
like colors strongly associated with objects they like and dislike
colors strongly associated with objects they dislike. For example,
since water is important for surviving and water tends to be
blue, blue is largely appreciated; similarly, since rotten food is
dangerous for our health and rotten food tend to be greenish-
yellow, this color is largely unappreciated. The EVT is able to
explain both the universal trends and the minor variations: blue
is probably appreciated in every culture while red is generally
less appreciated, but for example the lucky effect that Chinese
culture associate to this color make it more appreciable in China
compared to other countries. The authors of the EVT estimated
that the affective valence association was able to account for the
80% of variance in color preference ratings over 32 different
colors.
Few controlled studies have investigated psychological and
physiological effects of specific color exposure. For example,
Jacobs and Hustmyer (1974) measured the physiological
activation during a 1-min exposure to four different colors.
Considering the galvanic skin response, red was significantly
more arousing than other colors. Küller et al. (2009) compared
psychological and physiological effects of a gray, red, and blue
room. The results showed that the red room increased the brain
arousal level (assessed as percentage of alpha waves). This effect
was particularly significant in introvert persons or persons that
were in a negative mood. Red was also found to be associated
with a higher probability of winning a sport competition (Hill
and Barton, 2005), to performance impairment on achievement
tasks due to avoidance motivation (Elliot et al., 2007;Mehta and
Zhu, 2009), and to performance enhancement on detail-oriented
tasks (Mehta and Zhu, 2009).
Kwallek et al. (1996) compared nine monochromatic office
interior colors in a between-subjects study in which university
students performed a proofreading task in one office for a
total permanence of 45 min. The nine office colors varied for
two levels of saturation (high/low), and two levels of lightness
(dark/light). Pre and post mood change and color preferences
were also recorded. The proofreading task performance was
not affected by office color, whereas errors were higher in
the white office in comparison to the blue and red offices,
even if it cannot be excluded that this difference could stem
from cognitive differences between the groups in the different
conditions. Higher saturated color offices resulted in higher vigor
scores for mood. Lightness and coolness or warmth of the office
color did not influence mood. Pleasantness for the office color
differed significantly between the groups. Individuals preferred
to work in beige and white rooms than in orange and purple
offices. In terms of whether they liked the office color, individuals
in the green and red offices preferred their office color more
than individuals in the yellow and orange offices. Participants in
the white, beige, blue, and gray offices liked the color of their
offices more than participants in the orange office. Concerning
the distracting effect of the color, participants in the purple,
orange, red, yellow office colors reported that their colors were
more distracting compared to participants in the green, gray,
beige, and white offices. Purple and yellow office colors were rated
as the most distracting, and white as the least distracting.
In the context of criminal detention holding cells Pellegrini
et al. (1981) found no difference in the incidence of aggressive
officer-arrestee encounters after changing the cell color from pale
blue to hot pink.
Independently from the influence of color on behavior, people
strongly tend to associate colors to specific semantic clusters
(Sutton and Altarriba, 2016). Bright colors (e.g., white, pink)
are often associated to positive emotions whereas dark colors
(e.g., black, brown) tend to be associated with negative emotions
(Hemphill, 1996). Furthermore, we tend to infer the valence
of a stimulus on the basis of brightness (Meier et al., 2004).
Individuals were faster to categorize positive words when they
appeared in white than when they appeared in black, with an
opposite trend for negative words. Color associations are often
cross-modal (Spence, 2011), and the most important cross-modal
association is the distinction between cold and warm colors (Ho
et al., 2014).
Most of the literature that we have so far reviewed defined
color effects and preferences exposing participants to colors via
computer screens or using colored patches, or asking participants
to imagine specific colors; furthermore, the exposure time to
colored settings was in general very short (Elliot and Maier,
2014). The more realistic setting in an architectural study was that
reported by Kwallek et al. (1996), but also in this case participants
remained in the experimental room only the time to complete
some tests for a total duration of about 45 min.
This is the first study that examined color preferences and the
effects of environmental color on psychological functioning in a
population that lived in mean more than 1 year in an architectural
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FIGURE 1 | The six buildings of the “I Praticelli” university residence hall with number and color assignment.
setting characterized by a strong monochromatic color interior
design. The innovative aspect of our study was the possibility
to examine color preferences and psychological effects of long-
term color exposure in a real residential context. The university
residence hall provided a setting with a high ecological validity for
the study of color influence on residential satisfaction, lightness
self-evaluation, study facilitation, and mood.
MATERIALS AND METHODS
Participants
Participants were 443 university students living in a university
residence hall. The sample included 230 males (Mage = 23.91,
SD = 2.73) and 213 females (Mage = 23.68, SD = 2.60). The
distribution of participants between the six buildings, differing
for the specific interior color, was: orange N= 74 (16.7%), blue
N= 75 (16.9%), yellow N= 74 (16.7%), red N= 87 (19.6%),
green N= 85 (19.2%), and violet N= 48 (10.9%). Student
assignment to the different buildings was performed by the
residence hall administration at the time of admission. Mean stay
at the university residence hall at the time of the research was
13.33 months (SD = 12.14). Difference between mean stay in the
six buildings was not significant.
Participants were accommodated in single (31.8%) and double
(68.2%) rooms. The proportion of students in single and double
rooms was homogeneous for the six buildings. Eight participants
were excluded because they declared a deficiency in color vision.
Participants declared to spend an average of 6.78 h (SD = 3.28)
per day in their room (excluding sleeping time).
This study was carried out in accordance with the
recommendations of the Ethics Committee of the University of
Bologna that approved the study protocol. All participants gave
written informed consent in accordance with the Declaration of
Helsinki. The data were collected in an anonymous form.
Procedure and Data Analysis
The study was conducted at the university residence hall “I
Praticelli,” located in Pisa (Italy). This setting was chosen for
its architectural properties, since the university residence hall is
divided into six identical buildings differing only for the interior
color (walls, floor, and ceiling) (Figure 1). Each building has
common areas (corridors, kitchen, and living rooms) and part
of the students’ rooms uniformly painted with one of these six
colors: violet, blue, green, yellow, orange, and red, showed in
Figures 1,2. The RAL code of each color, along with its CIE Yxy
coordinates are reported in Table 1. Artificial lighting within the
six buildings was uniform with the use of linear fluorescent bulbs
(photometrical data: color rendering index Ra ≥80, light color
830, rated color temperature 3000K).
The layout of students’ rooms included a small entrance hall
connected to the bathroom and the main room (Figure 3). The
specific color that characterized each building was applied to: (a)
walls and ceiling of all interior common spaces (i.e., corridors,
kitchens, study rooms); (b) walls and ceiling of the entrance
hall inside the student’s room; (c) one wall in the bedroom (the
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FIGURE 2 | Examples of five corridors (left) and three study rooms (right) of the university residence hall.
remaining walls and the ceiling in the bedroom were painted
in white); (d) walls of the bathroom (the ceiling was white)
(Figures 2,3). Floors, both inside the room and in the common
spaces, had a color coherent with the building but slightly
different in hue from the wall colors. Floor-color coordinates and
RAL codes for the six buildings are reported in Table 1.
Color preferences and the student’s experience with the
university hall design were investigated administering a
questionnaire structured in these sections: (a) socio-demographic
data (age, sex, province of residence), and university course
attended by the student; (b) color vision deficiency; (c) hall of
residence color in which the student lived (red, orange, yellow,
green, blue, violet); (d) hall of residence color in which the
student would prefer to live; (e) time stayed at the residence
hall since admission; (f) room type (single, double); (g) color
lightness preference for the building in which the student lived;
(h) color preference in general (Figure 4 considering both
hue and lightness); (i) color preference for the residence hall
TABLE 1 | RAL code, color sample, and CIE Yxy coordinates for walls, ceilings, and floors of the six buildings considered in the study.
Building Walls and ceiling Floor
RAL Sample CIE Yxy RAL Sample CIE Yxy
Red 3020 11.531, 0.6157, 0.3373 3016 11.650, 0.5337, 0.3472
Orange 2009 21.731, 0.5771, 0.3771 3012 29.612, 0.4168, 0.3599
Yellow 1023 52.822, 0.4772, 0.4593 1000 49.875, 0.3701, 0.3912
Green 6018 25.640, 0.3359, 0.5034 6021 29.518, 0.3293, 0.3856
Blue 5012 21.269, 0.2020, 0.2470 5024 26.333, 0.2469, 0.2864
Violet 4009 26.294, 0.3260, 0.3103 4009 26.294, 0.3260, 0.3103
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FIGURE 3 | Example of a green and orange student’s room at the university residence hall.
FIGURE 4 | Color wheel for the assessment of chromatic preference. The
wheel included 24 sectors varying in hue. Each sector included 10 levels
along the radial dimension varying in lightness.
(Figure 4, both hue and lightness); (j) room ceiling preference
(white, colored); (k) room lightness level (−2/+2); (l) room
lightness satisfaction (−2/+2); (m) hours per day spent in the
room; (n) facilitating effect of the specific building color in the
studying activity (−2/+2); (o) effect of the hall of residence color
scheme for wayfinding and orienting (0–3).
When evaluating general color preference and room color
preference the student had to choose a specific sample from the
color wheel shown in Figure 4. The color wheel was divided into
24 sectors differing in hue. Each sector was divided in 10 levels
differing in lightness along the radial dimension, for a total of
240 color samples. For each sample we considered the CIE Yxy
coordinates, and Y values were considered as a proxy of lightness
level in the range 0–100.
In addition to the questionnaire, the students were
administered the Brief Mood Introspection Scale (Mayer
and Gaschke, 1988) for an assessment of general mood.
This scale assesses mood along these dimensions: happy,
loving, calm, energetic, fearful/anxious, angry, tired, and sad.
Each dimension includes two items for a total of 16 ratings:
lively, happy, sad, tired, caring, content, gloomy, jittery,
drowsy, grouchy, peppy, nervous, calm, loving, fed up, and
active.
RESULTS
Interior Color Preference
Blue was the preferred interior color (34.7%), followed by green
(23.1%), violet (14.1%), orange (11.9%), yellow (8.7%), and red
(7.5%). The Chi-square that tested non-equality in frequency
distribution was significant: χ2= 116.52, p<0.001, ϕ= 0.55.
Interior color preference as a function of participant’s sex is
shown in Figure 5. Separate Chi-square analysis with Bonferroni
correction were performed to test the effect of sex on each
interior color preference. The difference was significant for blue
(χ2= 6.03, p= 0.01), and violet (χ2= 18.13, p<0.001), as shown
in Figure 5.
Color preference as a function of participant’s residence hall
color is shown in Table 2. The frequency cross-tabulation analysis
was significant: χ2= 364, p<0.001, ϕ= 0.89. Superimposed to
the general preference for the blue and green hall of residences,
participants showed a preference bias for the color in which they
actually lived (diagonal entries in Table 2). For example, although
red was the least preferred interior color with a mean choice of
7.5%, 28% of the participants living in the red hall of residence
preferred to stay in that color. Similarly, yellow was preferred only
by 8.7% of participants, but 31.7% of the students living in the
yellow hall of residence preferred that specific color. The effects
were summed for the most preferred interior colors: 53.6% of
the students living in the blue hall of residence preferred not to
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FIGURE 5 | Interior color preference for the six buildings in male and female participants. Asterisks show the significance level of the gender difference test.
∗∗p<0.01, ∗∗∗ p<0.001.
change, and 48.6% of those living in the green rooms preferred to
stay in that specific hall of residence.
Interior color preference was not affected by the type of
accommodation (i.e., single versus double).
General Chromatic Preference
Participants had to select the preferred color between the 240
samples included in Figure 4. The preference was general and
not referred to a specific object or context. Hue (wheel sector)
and lightness (radial axis) were separately analyzed.
Grouping the 24 hues into six main categories, color
preference in descending order was: blue (39.2%), green (18.8%),
red (18.6%), violet (9.3%), orange (8.4%), and yellow (5.7%).
These preferences were significantly affected by the specific color
in which the participant lived: t(5) = −4.71, p= 0.005, η2
p= 0.81.
The bias was in mean +5.42% (SD = 3.08%) in favor of the
color to which the student belonged, and ranged from 1.19%
for students of the red hall of residence to 9.60% for students
living in the blue hall of residence. The bias was computed
with the difference between mean preference for a specific color
for all participants and mean preference for a specific color
considering only those that lived in that color. Accommodation
in a single versus double room was not critical for general
chromatic preference.
Preference for each of the 24 hues, distinguishing between
male and female participants, is shown in Figure 6. Male
and female preferences were significantly different for hue 15
(χ2= 5.58, p= 0.001), hue 22 (χ2= 15, p<0.001), and hue 23
(χ2= 17, p<0.001) (Figure 6).
Lightness preference was tested with an ANOVA inserting hue
(24 levels) and sex as factors. Main effect for hue was significant
F(22,408) = 27,46, p<0.001, η2
p= 0.59. The preferred lightness
level for each hue is shown in Figure 7 (left). Sex and the
interaction between hue and sex were not significant.
TABLE 2 | Residence color preference (%) as a function of the actual residence color in which the student lived.
Desired hall of residence color
Participant’s actual hall of residence color
28 9.3 4 22.7 28 8
1.6 42.2 4.7 12.5 28.1 10.9
0 6.7 31.7 23.3 28.3 10
6.8 5.4 2.7 48.6 28.4 8.1
2.9 2.9 5.8 14.5 53.6 20.3
2.3 7 7 11.6 37.2 34.9
Mean 7.5 11.9 8.7 23.1 34.7 14.1
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FIGURE 6 | General chromatic preference (%) in females (left bar) and males (right bar) for the 24 hues shown in Figure 4. Lightness level of each bar matches the
mean preferred lightness level (radial axis in Figure 4). Asterisks show the significance level for the male-female comparison (∗∗p<0.01, ∗∗∗p<0.001).
FIGURE 7 | Preferred lightness level (blue frame), for each of the 24 hues, in
the general condition (left) and in the university residence hall condition
(right).
Residence Hall Chromatic Preference
Grouping the 24 hues of Figure 4 into six main categories,
specific color preferences for the university residence hall
were: blue (36.4%), green (20.8%), orange (12.5%), yellow
(11.2%), red (10.5%), and violet (8.6%). These preferences were
significantly influenced by the color in which the participant
lived: t(5) = −4.99, p= 0.004, η2
p= 0.83. The preference
bias for the own color was in mean 9.14% (SD = 4.48%),
and ranged from 3.74% for the students living in the yellow
hall to 13.70% for those living in the blue hall. The bias
was computed subtracting mean preference for a specific
color considering all participants to mean preference for
a specific color including only those living in that color.
The type of accommodation (single versus double) was not
critical.
The distribution of preferences for each of the 24 hues in males
and females is shown in Figure 8. Each bar color in Figure 8
shows also the preferred lightness level for each hue. Chromatic
preference for male and female participants differed significantly
in five hues: hue 15 (χ2= 5.90, p= 0.01), hue 17 (χ2= 3.84,
p= 0.04), hue 22 (χ2= 14.22, p<0.001), hue 23 (χ2= 7.36,
p= 0.006), and hue 24 (χ2= 4.45, p= 0.03).
Color lightness preference for the residence hall was tested
with an ANOVA inserting hue (24 levels) and sex as factors.
Main effect for hue was significant F(23,393) = 24.46, p<0.001,
η2
p= 0.59. The preferred color lightness level for each hue is
shown in Figure 7 (right). Sex and the interaction between hue
and sex were not significant.
General Versus Residence Hall Color
Lightness Preference
General color lightness preference was compared to the residence
hall color lightness preference with a matched t-test including
all the 24 hue sectors. The t-test was significant: t(23) = −2.58,
p= 0.02, η2= 0.22. Mean preferred chromatic lightness level
was 42.82 (SD = 24.23) in the general evaluation, and 46.76
(SD = 23.76) when referred specifically to the residence hall.
Preferred Color Lightness Level
Participants had first to select the hue sector matching their
building on the color wheel in Figure 9, then they had to mark
the preferred lightness level on the wheel radius. Lightness level
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FIGURE 8 | Distribution of the residence hall color preference for males (right bars) and females (left bars) for the 24 hues considered in the study. Lightness level
of each bar matches the average preferred lightness level. Asterisks show the significance level for the male-female comparison (∗p<0.05, ∗∗p<0.01,
∗∗∗p<0.001).
FIGURE 9 | Color lightness preference (blue frame) as a function of the
six-building interior color. The asterisks show the actual color lightness level in
the six buildings.
was operationalized as the Y value of the Yxy CIE coordinates of
the selected patch.
Preferred lightness level differed significantly as a function of
hue: F(5,175) = 34.03, p<0.001, η2
p= 0.49. Framed swatches in
Figure 9 show the preferred color lightness level as a function
of the building color. Mean preferred lightness for the six colors
were: Myellow =80.59 (SD = 14.11), Mviolet =46.45 (SD = 17.72),
Mgreen =45.78 (SD = 17.14), Morange =38.60 (SD = 13.88),
Mblu =32.70 (SD = 21.97), Mred =29.13 (SD = 20.74). Planned
comparisons showed that the yellow painting was preferred
lighter than all other paintings (p<0.001). Furthermore, violet
painting was preferred lighter than red painting (p= 0.008).
Preferred color lightness was compared to the actual color
lightness of the six interior colors with a paired t-test that was
significant: t(186) = 14.24, p<0.001, η2= 0.52. Mean preferred
color lightness was 45.89 (SD = 24.56), significantly higher than
the mean actual interior color lightness of the six buildings: 26.03
(SD = 14.02) (Figure 9). Being the student in a single versus
double room was not critical.
Room-Lightness Level
Self-evaluated room-lightness as a function of the room color
was tested with an ANOVA that was significant: F(5,437) = 4.25,
p= 0.001, η2
p= 0.05. On a −2/+2 scale mean room-lightness
ratings were: 1.04 (SD = 0.12) in the yellow building, 0.71
(SD = 0.12) in the orange building, 0.65 (SD = 0.11) in the green
building, 0.62 (SD = 0.15) in the violet building, 0.51 (SD = 0.11)
in the red building, and 0.29 (SD = 0.12) in the blue building.
Planned comparisons showed these significant contrasts: yellow
rooms were evaluated lighter than blue rooms (p<0.001), red
rooms (p= 0.007), and green rooms (p= 0.40). Blue rooms were
evaluated darker than orange rooms (p= 0.006), green rooms
(p= 0.02), and violet rooms (p= 0.002).
Room-Lightness Satisfaction
Room-lightness satisfaction as a function of the room interior
color was tested with an ANOVA that was significant:
F(5,437) = 4.33, p= 0.001, η2
p= 0.05. On a +2/−2 scale mean
room-lightness satisfaction was 0.95 (SD = 0.12) for yellow
rooms, 0.85 (SD = 0.15) for violet rooms, 0.71 (SD = 0.12) for
orange rooms, 0.62 (SD = 0.11) for green rooms, 0.52 (SD = 0.11)
for red rooms, and 0.25 (SD = 0.12) for blue rooms. Planned
comparisons showed these significant contrasts: orange versus
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Costa et al. Interior Color in a University Residence Hall
blue (p= 0.01), yellow versus blue (p<0.001), green versus blue
(p= 0.03), yellow versus red (p= 0.001), yellow versus green
(p= 0.02). The correlation between self-evaluated room-lightness
level and room-lightness satisfaction was 0.78 (p<0.001).
Room lightness satisfaction was not affected by the student’s
accommodation (single versus double).
White Versus Colored Ceiling
A white ceiling (84.93%) was preferred more than a colored
ceiling (15.07%): χ2= 97.09, p<0.001, ϕ= 0.44.
Spatial Orientation and Wayfinding
The use of specific colors for the six buildings was evaluated to
facilitate spatial orientation and wayfinding within the university
residence hall: M= 2.06 (SD = 0.98) on a 0 -3 scale. The rating
was not significantly affected by building color.
Mood and Interior Color
The effect of building interior color on the Brief Mood
Introspection Scale was tested with a MANOVA that was not
significant.
Mood and Color Preference
The effect of mood on color preference (coded on six levels)
was tested with a MANOVA that was significant for the “calm”
scale: F(6,400) = 2.64, p= 0.01, η2
p= 0.04. Mean ratings as a
function of the interior color were: green 1.54 (SD = 1.05), blue
1.21 (SD = 1.65), violet 1.12 (SD = 2.01), red 1.04 (SD = 1.68),
yellow 0.89 (SD = 1.53), and orange 0.61 (SD = 1.73). Blue versus
orange (p= 0.02), green versus yellow (p= 0.04), green versus
orange (p= 0.001) were the significant pairwise comparisons.
Building Interior Color and Facilitation of
Studying Activity
An ANOVA tested the interaction between building interior color
and facilitation of the studying activity (−2/+2 scale) of the
participants. The interaction was significant: F(5,434) = 2.44,
p= 0.03, η2
p= 0.03. Mean ratings as a function of the interior
color were: blue 0.34 (SD = 0.08), violet 0.19 (SD = 0.10), green
0.17 (SD = 0.07), yellow 0.13 (SD = 0.08), orange 0.01 (SD = 0.08),
and red 0.01 (SD = 0.07). Pairwise comparisons showed that the
significance was explained by the contrasts blue versus orange
(p= 0.004) and blue versus red (p= 0.003).
DISCUSSION
Whereas color on external façades influences the perception
of the overall urban design and has mainly an aesthetic
role (Mougthtin et al., 1995), color in interior design could
significantly affect residential satisfaction and psychological and
social functioning in addition to having an aesthetic value. Color
in interior design can be more easily personalized, strongly
interacts with the color of other decorating objects, and its
pleasantness could affect home attachment. In the specificity
of our study, we exploited a unique architectural setting
composed by six buildings that differed only for the interior
color, investigating pleasantness for each specific color; how this
pleasantness related to general chromatic preference, the effects
of the interior color on lightness level and lightness satisfaction,
and the effect of the color on the residents’ functioning and
mood. This is the first study that examined the effects of interior
colors in occupants who “lived in a specific color” for an
average time of more than one year, filling a void in the color
preference literature that has always focused on the effects of
brief exposures to specific colors (Palmer et al., 2013). Interior
colors, to the contrary, tend to shape the “domestic landscape”
for long-term intervals, and is therefore important to study color
preferences and color effects on a large-time scale, as in this
study.
The building with blue interior color was the most preferred,
followed by the green, violet, orange, yellow, and red building.
Blue was also the preferred color when performing general
chromatic preferences, consistently with previous literature
(Eysenck, 1941;Granger, 1952;Guilford and Smith, 1959;
Hurlbert and Ling, 2007;Palmer and Schloss, 2010). Considering
all the six buildings, cool colors (blue, violet, and green) were
preferred to warm colors (yellow, orange, and red). This pattern
of preferences could be linked to the ecological valence theory
(Palmer and Schloss, 2010) that posit a causal link between
the preference for a color and the preference for objects that
are characterized by that specific color. In this perspective the
preference for blues and cyans could emerge as a consequence
for the preference of clear sky and clean water, or for the
association of blue with serenity and calm (Ou et al., 2004),
qualities that probably are sought by students for their residential
space.
Superimposed to the preference for specific colors of the
university residence hall we found an effect of “color attachment”
in which a significant part of students expressed a preference for
the specific color in which they lived. Different elements could
concur to explain this effect. A mere exposure effect (Bornstein,
1989), due to the familiarity with the actual color, could have
contributed to increase its pleasantness. An additional cause
could be the residential attachment that the student developed
with the hall of residence in which he/she lived (Tognoli, 2003;
Rioux et al., 2017).
In general we found a considerable overlap between general
chromatic preferences and interior color preferences, with the
only exception of lightness: colors in interiors were preferred
lighter than when expressing general preferences. For each of the
six colors used in the university residence hall the participants
expressed a preference for a lighter version. The discrepancy was
maximum for yellow, intermediate for red and orange, and small
for green, blue, and violet. Interestingly yellow was preferred at
high levels of lightness, whilst blue was preferred more dark. In
general, the interior colors used in the university residence hall
were evaluated too dark and saturated, and not fully adequate to
a residential setting.
Although blue was the preferred interior color for both males
and females, the polarization for blue was less pronounced
in female participants than in males. Females, for example,
expressed a discrete preference for the violet color that most
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Costa et al. Interior Color in a University Residence Hall
males rejected. Gender differences emerged also in the general
chromatic preferences, with a lower polarization for the blue
color, and a higher preference for red, pink, and violet in
females. These results are consistent with the tendency reported
by Hurlbert and Ling (2007) who compared a British and
a Chinese sample, and by Al-Rasheed (2015) who compared
Arabic and English participants, and recently by Bonnardel et al.
(2018) who compared gender differences in color preference
among British and Indian students, finding in females a
more distributed pattern of color preference, and a secondary,
superimposed preference for pink-purple colors. However,
although these gender differences, it should be emphasized
that for both males and females blue was the most preferred
color.
The interior color influenced significantly room-lightness
level and room-lightness satisfaction. Interestingly, the colors
associated with high lightness level and satisfaction were
complementary to those associated to color preference. For
example, blue interiors were the most preferred but also
those that had the higher detrimental effect on lightness
level and satisfaction, whereas yellow, which was among the
most undesirable colors at the university residence, led to
the highest levels of lightness satisfaction. This connection
between interior color and lightness level is important
considering that the amount of daylight in a residential or
working environment is a predictor of stress reduction and
satisfaction (Alimoglu and Donmez, 2005;Yildirim et al.,
2007).
In general, there was a strong preference for rooms with
a white ceiling, probably because the perceived room height
increases with the ceiling lightness (Oberfeld et al., 2010).
The assignment of a specific color to each building was
considered to facilitate orientation and wayfinding within the
university residence hall, in line with the previous research of
Hidayetoglu et al. (2012). Interior color is the primary source
for increasing legibility and facilitating spatial navigation within
a complex architecture. Furthermore, we can suggest that the
characterization of each building with a specific color could have
promoted a higher place attachment to the own building, as
suggested also by the preference bias found for the color in which
the student lived.
The blue interior color was considered to promote and
facilitate studying activity more than lighter and warmer colors
(such as orange and red) that probably were perceived as
too arousing (Küller et al., 2009). Furthermore, we found an
association between a blue color preference and the “calm”
rating in the mood scale. These results can be explained
considering that the color blue is often associated with
openness, peace, and tranquility (Kaya and Epps, 2004),
in contrast with red that is often associated with dangers,
activation, erotic pleasure (Elliot et al., 2007). Furthermore,
Mehta and Zhu (2009), from a series of six studies,
demonstrated that blue (versus red), activated an approach
motivation and enhanced performance on creative cognitive
tasks. These results were further confirmed by Xia et al.
(2016).
The interior colors that were evaluated to have the worst
effect on studying were red and orange. This effect could
be explained considering that long-wave colors can cause
higher arousal than short-wave colors (Jacobs and Hustmyer,
1974;Walters et al., 1982). According to the Yerkes-Dodson
law (Yerkes and Dodson, 1908), this high-arousal state
could negatively affect the performance in difficult tasks, as
studying.
As guidelines for the design of university residence halls
and interiors in residential settings in general, we could suggest
preferring blue and green colors and avoid red, yellow and orange
colors. In case of a residence hall for male students it is better to
restrict the color palette to only blue and green hues, whereas in
case of female students the color palette could be more varied,
including also red-purple and violet hues. The blue color is to
be preferred in study areas. Light colors are to be preferred for
preserving an adequate lightness level, and a white ceiling is
preferred over a colored one. In general, when the university hall
has a complex layout, segregating functional spaces with specific
colors could be helpful for facilitating spatial orientation and
wayfinding.
Interior color is a ubiquitous component of every architecture
design that strongly characterizes residential, work, educational,
commercial environments, and has a significant impact on
psychological functioning and satisfaction on the people living in
these environments. The development of applied research in this
field could contribute to establish an evidence-based knowledge
that can be used by designers and architects to guide color choice
in their projects.
AUTHOR CONTRIBUTIONS
MC and SF designed and devised the study. SF acquired the data.
MC, SF, and IP analyzed the data. MC, SF, MN, and IP wrote the
manuscript.
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Conflict of Interest Statement: The authors declare that the research was
conducted in the absence of any commercial or financial relationships that could
be construed as a potential conflict of interest.
Copyright © 2018 Costa, Frumento, Nese and Predieri. This is an open-
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Frontiers in Psychology | www.frontiersin.org 13 August 2018 | Volume 9 | Article 1580