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Effects of Office Interior Color on Workers' Mood and Productivity

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Abstract and Figures

36 adults completed a typing task in either a red or blue office environment and were administered the Eight State Questionnaire. The procedure was then repeated in either the same- or a different-colored office with alternate typing and questionnaire forms. Results indicate that Ss who moved to a different-colored office made more typing errors than Ss who remained in the same-colored office. Anxiety and stress scores were higher for Ss who remained in the red office, while depression scores were higher for Ss who remained in the blue office. Arousal scores were higher for Ss who were switched to different offices. (PsycINFO Database Record (c) 2012 APA, all rights reserved)
Content may be subject to copyright.
Impact of Three Interior Color
Schemes on Worker Mood and
Performance Relative to
Individual Environmental
Sensitivity
N. Kwallek,* H. Woodson, C. M. Lewis,
C. Sales
The University of Texas at Austin, Division of Interior Design, 117 GEA, Austin, Texas 78712
Received 6 April 1996; accepted 14 August 1996
Abstract: Effects of three office color schemes (red, blue- made environment has been meeting our basic shelter
needs for centuries. Today, buildings serve other pur-green, and white) were examined for 90 workers’ mood
and productivity, taking into account individual differ- poses, such as education, entertainment, and work activi-
ties. Even with an affinity for nature, it has become in-ences in environmental sensitivity (high screeners vs. low
screeners). Matched on relevant variables, subjects were creasingly important to realize that individuals exist
within enclosed structures for most of their lives. There-assigned to one of three offices. Workers performed office
tasks for 4 consecutive workdays. Workers in the red fore, understanding how spaces affect individuals is nec-
office reported more dysphoria than workers in the blue- essary for personal well-being. Perhaps, most important
green office. Low screeners reported more dysphoria in are the effects of the work environment, the place where
the red and white offices than high screeners. High individuals spend most of their waking hours.
screeners performed better on office tasks in the red office This research was begun with the hope of being able to
and poorer in the blue-green office than low screeners. understand more fully how color within the work environ-
The results for performance are discussed as an extension ment affects worker mood and performance. The purpose
of the YerkesDodson principle, while the results for was to determine the effects of three different interior color
mood tended to support previous findings.
q
1997 John
schemes on mood, speed, and accuracy on proofreading
Wiley & Sons, Inc. Col Res Appl, 22, 121–132, 1997.
clerical tasks administered to office workers on a Monday
and again on a Thursday of a four-day work week.
Key words: color schemes; performance and productiv- One goal was to counteract the design limitations of
ity; mood; environmental sensitivity; office workers; other color research by making the study as realistic as
NASA possible. Psychological experiments on color rarely return
unequivocal results. Previous color studies have been lim-
INTRODUCTION
ited to a single color or a few bright monochromatic
colors where subjects had limited exposure to the color.
There is an increasing desire to protect the environment In other instances, subjective judgments were rendered
through cleanup activities and legislation. Most of the from subjects by viewing color slides, swatches, light, or
focus has been on the natural environment, yet the person- color pictures of roomsand not by actually viewing the
color by users in the interior or from actual exposure to
a color when performing tasks. However, this is not how
Correspondence to: Nancy Kwallek; PhD
color is seen in the interior environment. By simply view-
Contract grant sponsor: Institute of Business Designers Foundation
ing color pictures or slides of interiors, individuals are not
Contract grant sponsor: BASF Corporation
exposed to intervening variables that could affect color in
Contract grant sponsor: Interface Flooring Systems, Inc.
q
1997 John Wiley & Sons, Inc.
the interior, such as different furniture styles, accessories,
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textures, and the natural or artificial light, which are more anxiety scores were obtained in the red and yellow vs.
the green and blue conditions. In a similar study, Jacobsrepresentative of an office space.
Furthermore, interior color is not often highly saturated. and Blandino
7
found that color affected mood states with
different colored papers (yellow, red, green, blue, andContrast of value, saturation, and the interrelationship of
adjacent colors are what subjects perceive when viewing white). The only significant result was that high scores
on fatigue were associated with green, while low scoresor working in an interior. Such color quality dimensions
and their relationships within the environment may be were associated with red. Kwallek, Lewis, and Robbins
8
examined the effects of a red color environment vs. amore important than the color itself when assessing its
effects on a worker’s mood and productivity. In addition, blue one on a typing task and mood states. There were
no significant differences between the groups on moodwhen examining the effects of interior color on office
worker performance and mood, few researchers consider states. Though none of the differences between groups
was significant, subjects who remained in the red officeindividual differences when assessing the effects of inte-
rior color and light. experienced more anxiety and stress than the subjects
who remained in the blue office.As indicated, much of the past research has been incon-
clusive due to a lack of proper control measures.
1
Yet, their Thus far, research on warm and cool colors has been
reviewed because that is where most of the research hasimportance lies in the attempts to find or establish empirical
data. Among all colors, warm colors have been the most concentrated. Even when the color white has been exam-
ined, significant findings are usually among red, blue, andresearched, followed by cool colors. Warm colors, espe-
cially red, have been associated with excitement, whereas green colors. Unfortunately, white suffers from a lack of
thorough analysis. For example, Gerard
5
tested for whitecool colors, especially blue, have been associated with a
more passive and relaxed feeling. What are these associa- along with red and blue, but found that responses varied
considerably. The most that could be said was that thetions based upon? A relationship between mood and color
has longbeen a topic of speculation. Though clear associa- results for white were similar to that of the red conditions
on physiological and subjective measures of mood.tions between mood and color have not been overwhelm-
ingly accounted for, certain colors have been frequently
related with particular moods based on research data. Research on White
Little research has been conducted on the color white,
Color and Mood Associations which is often used in offices, homes, and institutions as
a neutral background. In contrast to this common applica-For instance Aaronson
2
asked subjects to rate the
names of colors with given adjectives and found red to tion, the Buffalo Organization for Social and Technologi-
cal Innovation (BOSTI) survey (Brill, Margulis, and Ko-be high in activation, whereas blue was categorized low.
Wexner
3
also tried to determine whether a similar rela- nar)
9
found that white and neutrals were ‘‘clearly re-
jected’’ as colors for walls and dividers among officetionship exists between color and mood. She selected
various adjectives that were thought to be representative workers. Most other research that examined white as a
color only investigated the effects of white light insteadof mood and displayed eight paper colors. Subjects were
asked to pair them. Although not all colors demonstrated of a white surface.
Most color studies have included subjects respondingdefinite associations, red was among the ones to exhibit
a strong link with excitement. Attempting to replicate to various color stimuli without specifying any particular
setting. As Wise et al.
1
pointed out, part of the problemWexner’s findings, Murrayand Deabler
4
found consistent
color-mood associations, although differences found with relying on these color studies for factual information
is that they frequently deal with color in isolation and areamong their three study groups may have been related to
socio-economic status. Regardless, red was still seen as not applied to an object or context. Thus, judgments are
rendered on only one color or one color pair, and colorsexciting and stimulating, and both blue and green as se-
cure and tender. In a study on male college students, are almost exclusively being judged against a neutral
background. Color and mood associations help us under-Gerard
5
tested the colors red and blue under one stimulus
condition. Except for heart rate, he found statistical sig- stand how people may be affected by their environment.
However, a thorough analysis of actual work settings withnificance between the red-blue condition for the physio-
logical measures tested, with red producing a more alert subjects performing common office tasks in various color
spaces would be more valuable and relevant in makingfeeling and blue a more relaxed one.
In these studies, red was often associated with excite- inferences about the general effects of interior color
schemes on mood and performance.ment. In other studies, warm colors in general have been
linked to anxiety and stress, while cool colors have contin- The BOSTI survey ( Brill et al.)
9
was mostly concerned
with the opinions of office workers about their workingued to exhibit tranquillity and even depression. Jacobs
and Suess
6
found that colors had an effect on people’s environment. Further interest has been shown in this area
by Oldham and Fried,
10
who studied howworkspace char-anxiety states. Color slides of red, green, blue, and yellow
were projected for five minutes between administration acteristics, suchas social density, room darkness, or num-
ber of enclosures, may affect employee reactions. Theyof a paper and pencil anxiety test. Significantly higher
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found that employees tend to withdraw under certain con- also varied with color, and blue was rejected only when
it reached a darker hue than most other colors provided.ditions, such as when it is dark, or when there are few
enclosures surrounding a work area. Unfortunately, color Wise et al.
1
reviewed many color studies to determine
which color combinations would create the mostspacious,was not part of the evaluating data.
In a more recent study, Ainsworth, Simpson, and Cas- pleasant, andproductive environment.Over the long term,
they determined that the largest surface area should besell
11
studied subjects in an office setting for one hour in
three different color office interiors (red, blue-green, and high in value (light) and low in saturation (dull), that
the second largest area should be medium in value andwhite). There were no significant findings in the three
groups for anxiety, depression, or arousal. Similarly, saturation, and that the trim and accents should be high
in saturation (bright) and either high or low in valueKwallek and Lewis
12
assessed the effects of a red, white,
or green office environment on worker productivity and (light or dark).
Based upon their conclusions, it was hypothesized thatmood. They found that while subjects working in the red
office made the fewest errors, the subjects in the white an office color scheme with the largest surface area of
the room being a bright vivid color would create an envi-office made the most errors. However, those who worked
in the red office reported that the color of their office was ronment which is more confined, unpleasant, and less
conducive to productivity. For this study, a predominantlymore distracting than the subjects who worked in the
white office. bright red color scheme was selected as an office color
scheme because of its preponderance in the literature cit-Since the quintessential office color is white and be-
cause white has been the standard color of NASA’s mock- ings as being associated with those negative effects and
because it has the greatest degree of saturation in latexup habitation space module, white was selected as one of
the office color schemes to be examined. A monochro- pigment paints.
Conversely, a third office color scheme employing amatic white office was of interest for two additional rea-
sons: to inform NASA of the effects of white on worker light color or pastel for the largest surface area in a room
was selected. The purpose was to test the Wise et al.
1
productivity and mood over a period of time in a relatively
confined space; and, to use white for contrast or compari- proposal in terms of whether productivity would be en-
hanced and if the room would be experienced as moreson with the other two office color schemes. pleasant in comparison to the red office color scheme. A
light blue-green was selected for three major reasons: to
Saturation and Value allow for a comparison of a predominantly cool color
scheme (blue-green) with a predominantly warm colorSaturation has been cited as an important factor for
determining color pleasantness. Guilford and Smith
13
per- scheme (red); because the literature citings on color pref-
erence haveindicated thatoffice workerspreferred a lightformed a thorough investigation rating 316 color papers.
They found that across all colors, with varying levels blue-green office color; and, that blue-green and red are
considered to be contrasting or complementary colors.of value, the blue-green regions generated the highest
pleasantness ratings, while the lowest were in the yellow,
yellow-green regions. As value increased, perceived Stimulus Screening
pleasantness also increased. Where there was an increase
in saturation for a given color, the greater was its per- When examining the effects of interior color on office
worker performance and mood, few researchers considerceived pleasantness. Smets
14
also found that saturation
accounted for 88% of the variation in judgment of pleas- individual differences when assessing the effects of inte-
rior color and light. One important variable that may inter-antness, while value was less important accounting for
only 12%, and color itself was negligible at 0.68%. act with how different color schemes affect an individu-
al’s mood and performance is how individuals differ inThe color blue has frequently been cited as a favorite
or preferred color by many people. In the BOSTI survey their ability to screen out irrelevant stimuli within their
environment. As Mehrabian
16
suggested, individual dif-(Brill et al.)
9
about 1000 subjects evaluated colors de-
scribed verbally. Pastel cool colors (blue-green) were ferences in arousal response to stimulation have been a
central issue for research in this area. Studies (e.g., Yer-rated as most preferred by the respondents. The color
preferences were similar for office wall and panel colors molayevaTomina)
17
that have explored the effects of
environmental stimuli on an individual’s state of arousalwith light blue and light blue-green (aqua) as among the
most preferred. and performance of tasks have found that some individu-
als are more easilydistracted by irrelevant stimuli, leadingIn one color preference study examining the extent to
which the degree of whiteness, blackness, and saturation to decrements in performance. In contrast, other individu-
als actually improved their performance in a task whenimpacts color preference, Sivik
15
found blue to be judged
positive in more instances than other colors. However, irrelevant or extraneous stimuli were introduced. Siddle
and Mangan
18
demonstrated that distractibility was asso-across all colors, he found that the degree of blackness
was negatively associated with the degree of pleasantness ciated with initial amplitude of the orienting response,
slower speed of habituation, and with neuroticismand that blue was rejected when it reached a darker hue
than most other colors provided. The degree of dislike (Eysenck and Eysenck).
19
The association with neuroti-
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cism is consistent with Eysenck’s
20
suggestion that this Data on three others were collected but not included in
the analysis because the subjects were taking psychotropicconstruct is related to individual differences in autonomic
activation. medication. Participants were paid $200 upon completion
of the experiment or an hourly rate for any hours workedMehrabian
16
concluded that individual differences in
arousability can be regarded as being related to less selec- prior to dropping out. The mean age of the workers was
33.2 years, (SD
Å
11.46). Workers were recruitedtivity on the part of more aroused persons. These individ-
ual differences may be associated with consistent differ- through the state Human Resource Center, by placement
of ads in the city newspaper, and through other job recruit-ences in the ability to automatically screen less important
aspects of stimulation in various sensory modalities. Indi- ment centers in the city.
viduals who are most adept at screening less relevant
stimuli of their environments are referred to as high Office Design
screeners, while individuals who typically cannot screen
incoming sensory information as well are referred to as Each of the three offices, 8 ft 8 in. (2.63 m) wide, 11
ft 6.5 in. (3.52 m) long, and 8 ft (2.44 m) high, was oflow screeners. With respect tothe type of task,Mehrabian
and Russell
21
concluded that decrements in performance a different color scheme, but identically furnished. Each
had an office desk and return, a posture chair, an occa-for highly aroused subjects (low screeners) are seen only
when a distracting stimulus is introduced during the per- sional chair, a memory typewriter, a wall clock, and three
framed black-printed generic certificates on the wall op-formance of a moderately or highly complex task.
Some recent studies have focused on the relationship posite the desk (see Figs. 1 and 2).
Desk accessories included a wooden paper tray andbetween the interior environment and worker perfor-
mance and/or satisfaction (e.g., Oldham; Sutton and Ra- wooden card file box, a metal tape dispenser, stapler,
and bookends. An identical book (with beige jacket) wasfaeli).
22,23
Their conclusions rested on the notion of over-
stimulation of workers in response to extraneous environ- placed in each desk’s bookends. Identical beige tele-
phones, a green (artificial) plant, a phone message pad,mental stimuli leading to negative behavioral and af-
fective responses (Baum and Paulus).
24
Other studies a clear glass cup holder for pens and pencils, and a clear
glass paper clip holder was also placed on each desk.(e.g., Oldham, Kulik, and Stepina)
25
have examined how
the ability to screen irrelevant stimuli in the environment Each individual office, including all four walls and the
back of the office door, was painted. The window in eachdepends on the complexity of the task involved. Mixed
results have been obtained concerning task complexity office was closed off with drywall and painted like the
rest of the wall so that no natural light entered the officeenvironment interactions. For example, Sundstrom, Burt,
and Kamp
26
found that task complexity had little impact to eliminate any fluctuations of natural daylight. The tem-
perature was controlled at 73–75 degrees Fahrenheiton employee responses to various environmental stimuli.
Block and Stokes
27
conducted a laboratory study, which (2224 degrees Celsius). The acoustics were buffered
with ‘‘white noise’’ machines. Small built-in circulationfound that individuals perform a simple task best when
working in a room with four people, while individuals fans kept a constant air flow and temperature. Artificial
light was measured using an Illumination Quality Meter,performing a more complex task performed best when
working alone in a room. model IQ-2 by Prime Color, Inc. At the center desk area
in each office, the light was identically set at 600620
lux (6062 foot-candles). Glass fiber luminance ceiling
Hypotheses panels were rearranged with opaque acoustic ceiling pan-
els in a drop ceiling framework so that the light could be
For this study, it was predicted that workers in the red measured as identical foot-candles at the center of the
office color scheme would be more adversely affected in desk work area of each office. General Electric Chroma
terms of their productivity and mood than workers in the 50 daylight fluorescent lamps were used, having a color
blue-green office color scheme, who would experience a temperature of 5000 Kelvin and a color rendering index
more positive effect on productivity and mood. Second, of 90.
it was hypothesized that low screeners would be more All paint colors in the experiment are identified using
adversely affected in the red office color scheme in terms the Munsell Color Notation System and/or CIE Notation
of productivity and mood than high screeners, who can and/or Inter-Society Color CouncilNational Bureau of
more easily ignore environmental stimuli. Standards (ISCC-NBS) color designation. An attempt
was made to use pure pigments for all latex paint colors
without blending in any other adjacent color on the color
METHOD
wheel. A Munsell Notation of 5 for the color provides
Subjects the purest possible color.
To further interpretcolor notations,the value (lightnessA total of 90 office workers (67 females, 74%; and 23
males, 26%) completed a four-day work week experi- or darkness) of a color precedes the slash mark while the
saturation, chroma, or intensity (brightness or dullness)ment. Nine additional subjects began the experiment, and
six dropped out before the end of the fourth work day. is designated by the number following the slash mark.
124 COLOR research and application
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FIG. 1. Reception/pretest area showing three enclosed offices.
The value range of a color is nine steps between pure intensity steps selected were /12, /7, and /2 for red and /
8, /5, and /2 for blue-green.white and pure black. In designing the color schemes for
value, an attempt was made to create colors having an Office #1 was painted white (Munsell Color Notation
2GY 9/.5) on all four walls and door including the deskequal distance of separation between the lightest, medium,
and darkest values chosen for the three colors for each returns and appointments. The white chosen was govern-
ment standard #595b-27875, the same white used by NASA.scheme. Selecting a darker value than 5 was not feasible,
because the pigment of the color neutralized too much in The red selected for the top two-thirds of the wall area
in Office #2 (including the inside of the office door) wasthe artificial light used in the offices. Thus, for the colors
coordinated on the walls in the red and blue-green offices, Munsell Color Notation 5R 5/12. The complement of
red, blue-green, was selected for the lower third of thethe values selected were 9/ for the lightest value, 7/ for
the median value, and 5/ for the darkest value. walls, desk, and return (Munsell Color Notation 5BG 7/
5). For accent and trim molding, the selected color wasIntensity, chroma, or saturation is designated by the
number following the slash mark. As the number in- Munsell Color Notation 5R 9/2 (ISCC-NBS generic
name, Pale Pink).creases, the color becomes brighter. Conversely, as the
number decreases, the color becomes duller. However, Utilizing the Munsell Color Notation System, red’s
complement, a light blue-green was selected as predomi-
due to a color’s wavelength, some colors at the same nant in Office #3 (Munsell Notation 5BG 9/2). It was
value level appear more intense than other colors. For selected for the top two-thirds of the wall area, including
example, because red has a longer wavelength, it appears the inside of the office door. Medium red was selected
more intense than its opposite color (blue-green) at the for the lower third of the wall, desk, and return (Munsell
same degree of intensity. Based on Munsell color theory, Color Notation 5R 7/7). For accent on wood and metal
red reaches its maximum intensity at /14 of the intensity accessories, and trim molding, a strong bluish-green was
scale, whereas, due to its shorter wave length, blue-green selected (Munsell Color Notation of 5BG 5/8).
reaches its maximum intensity at /10. To generate the
most intense red color in latex paints, /12 intensity was Materials
the brightest achieved while the brightest for the blue-
green was /8. Thus, to create a three-step spread of inten- The Jenkins Achievement Striving Activity Scale (JA-
SAS; Helmrich, Spence, and Pred)
28
is a 7-item, 5-pointsity for red and blue-green from brightest to dullest, the
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FIG. 2. Offices #1 white, #2 red, and #3 blue-green. Each office shows views upon entering or working in each office.
Likert-type instrument. The scale assesses for the pres- bility is on a continuum representing the general emo-
tional responsiveness and lability with respect to internalence of achievement-related behaviors and attitudes in
individuals from ‘‘much less’’ to ‘‘much more than oth- and external stressors. In addition, the EPI contains a Lie
Scale, which may be used to identify subjects exhibitingers.’’ Scores can range from 735 points summed over
all 7 items. The scale was originally derived from an a ‘‘desirability response set.’’ Each personality scale has
24 items and each item is scored 0 (no) or 1 (yes) de-exploratory factoranalysis of the Jenkins Activity Survey
(Jenkins, Zyzanski, and Rosenman),
29
and subsequently pending on how it is answered. Scores are summed and
can range from 024 on each scale. The Lie Scale has 9replicated for a second sample in a confirmatory factor
analysis. For both sexes, all items assigned to this scale items. A summed score of 4 or 5 on this scale suggests
that the test results may not be a valid indicator of eitherloaded 0.30 or higher, and Cronbach’s alpha was 0.79.
The Eysenck Personality Inventory ( EPI; Eysenck and personality dimension. Form A was used for the study and
test-retest reliabilities range from 0.82 to 0.97. Factorial,Eysenck)
19
is a 57-item, dichotomous response (yes or
no) instrument. The EPI consists of two independent construct, and concurrent validity has been well estab-
lished for these personality scales (Eysenck andscales, which measure pervasive personality traits identi-
fied as extroversionintroversion and neuroticismstabil- Eysenck ).
19
Mehrabian’s Stimulus Screening Questionnaire (SSQ;ity. Extroversionintroversion is on a continuum defining
an individual’s general level of engagement or inhibition Mehrabian)
16
is a 40-item, 9-point scale instrument,
which measures individual differences in the degree ofwith respect to his or her environment. Neuroticismsta-
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the circles of dots are distinguishable if the individual has
normal color vision. Only the first 11 plates are used to
detect general color deficiency. If 10 or more plates are
read correctly, then color vision is regarded as normal.
The Profile of Mood States (POMS; McNair, Lorr and
Droppleman)
31
is a paper-and-pencil multi-state battery
that provides a profile of 6 mood factors: TensionAnxi-
ety, DepressionDejection, AngerHostility, VigorAc-
tivity, FatigueInertia, and ConfusionBewilderment.
The items on the POMS are adjectives denoting a particu-
lar feeling. Subjects indicate the degree to which each
adjective describes how they are feeling on a 5-point scale
of 04, from ‘‘not at all’’ to ‘‘extremely.’’ Scores for
items representing each subscale are summed to produce
a total score for each subscale. Internal consistency
reliabilities for the subscales range from 0.84 to 0.92.
Test-retest reliabilities range from 0.65 to 0.74
(McNair et al.).
31
Evidence of predictive, concurrent,
and construct validity has been established for the
POMS (McNair et al.).
31
The Minnesota Clerical Test (MCT; Andrew, Paterson,
and Longstaff)
32
is designed to measure elements of per-
ceptual speed and accuracy relevant to various clerical
tasks. The test consists of two parts, a number comparison
task and a names comparison task. There are 100 pairs
of items in each part, which are either identical or slightly
dissimilar. The subject is asked to mark which items are
exactly alike. The numbers comparison is an 8-min timed
test and the names comparison is a 7-min test. The raw
score for each part is the total number of items correct
minus the total number of items incorrect. The scores for
each subtest can range from 0200. Test-retest reliabili-
ties are above 0.80 for the numbers comparison test and
above 0.85 for the names comparison test. The MCT is
highly correlated with other measures of clerical ability
FIG. 2. (Continued)
and not as well correlated with other measures of general
ability (Andrew et al.),
32
which is indicative of the instru-
ment’s construct and discriminant validity.
automatic screening of and habituation to irrelevant stim- Procedure
uli in the environment. Responses on each item range
from
/
4 (very strong agreement) to
0
4 (very strong All prospective subjects were screened on a Friday
prior to being assigned to the experiment. They weredisagreement) with a score of 0 denoting ‘‘neither agree-
ment or disagreement.’’ Scores are summed and can range administered the JASAS, EPI, SSQ, ICBT, and a timed
typing task. After screening, subjects were eliminatedfrom
/
160 to
0
160 with more positive scores denoting
higher stimulus screening ability and more negative from the experiment if they: typed fewer than 40 words
per minute with 5 or more errors (Mitchell),
33
werescores indicating the reverse. For the present study, scores
of
0
25 and above denoted ‘‘high screeners,’’ while scores deemed color deficient by the ICBT; scored above five
on the social-desirability scale of the EPI; were dyslexic;of
0
24 and below represented ‘‘low screeners.’’ The
KuderRichardson reliability coefficient for the question- experienced physical impairments interfering with perfor-
mance of office tasks; or indicated prior knowledge ofnaire is 0.92. Discriminant, convergent, and construct va-
lidity have been demonstrated for the questionnaire (Meh- the purpose of the experiment (see Table I). Although
over 400 subjects were scheduled for screening, only 200rabian).
16
The Ishihara Color Blindness Test (ICBT: Ishihara)
30
or so appeared. A total of 120 subjects passed the screen-
ing tests, but due to cancellations, no shows, and otheris designed to provide an accurate assessment of color
vision deficiency of congenital origin. The test consists circumstances, 90 subjects completed the experiment, ac-
counting for a 75% attrition rate.of 14 plates, each with a circular image consisting of
colored dots as in a pointillist painting. Numerals within Initially, subjects were randomly assigned to one of
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TABLE I. Characteristics of matched workers for three offices.
White office Red office Blue-green office
nRange MSDn Range MSDnRange MSD
Typed words per
minute 30 41–76 55.20 10.70 30 41–86 57.26 11.00 30 40– 86 58.20 11.92
Mehrabian’s stimulus
screening
scores
a
30 087 to /69 014.40 34.76 30 098 to /119 016.43 45.47 30 083 to /91 015.63 38.57
Jenkin’s
achievement
striving activity
scores
b
30 7–32 24.96 4.64 30 20– 35 25.33 3.81 30 14 31 25.16 3.96
Sex
Male 8 21–30 24.50 3.02 7 20–32 24.85 4.59 8 19– 31 24.37 3.58
Female 22 7–32 25.13 5.15 23 20– 35 25.47 3.65 22 14 31 25.45 4.13
Age 30 20–56 32.03 10.78 30 20–68 33.13 11.71 30 18– 59 34.53 12.08
Male 8 21–49 30.62 10.30 7 20–40 24.71 7.47 8 18– 53 28.12 12.78
Female 22 20–56 32.54 11.14 23 20–68 35.69 11.69 22 20– 59 36.86 11.21
Handedness
Lefthanded 2 2 4
Righthanded 28 28 26
Eysenck’s
Extroversion
introversion
score
c
30 1–16 10.66 3.33 30 2–17 11.10 3.95 30 2–19 11.20 3.40
Neuroticism
scores
d
30 1–24 8.20 5.12 30 0–20 7.46 5.50 30 1– 17 8.10 4.62
Social desirability
lie scores
e
30 0–4 2.30 1.26 30 0 4 2.43 1.13 30 1–4 2.40 .85
a
Test norms are considered a mean Å024 and standard deviation Å39 (Mehrahian, 1976).
b
For a sample of 1035 college students, the mean was 23.96 for males and 24.44 for females (Pred, Helmreich, & Spence, 1986).
c
Test norms are those considered between a raw score of 10 and 14. Individuals scoring above or below cutting points would be depicted
as above or below average on this trait (EPI; Eysenck, 1968).
d
Test norms are those considered between a raw score of 7 and 12. Individuals scoring above or below cutting points would be depicted
as above or below average on this trait (EPI; Eysenck, 1968).
e
Individuals scoring ú4 were not selected for the study and were not deemed truthful in their responses (EPI; Eysenck, 1968).
the three offices. After having tested approximately 30 the office. The MCT was administered in the offices on
the morning of the first day and in the afternoon of thesubjects, the participants were matched across office con-
ditions on nine performance, demographic, and mood- 4th day. Additional questionnaires were administered at
the end of each day and at the end of the experiment;related characteristics ranked according to importance:
typing speed, scores on the SSQ, scores on the JASAS, these assessments are not part of the data analyzed for
this report.sex, age, handedness, and the three-part inventory scores
on the EPI.
Subjects performed a variety of office tasks throughout
RESULTS
a 4-day (Monday through Thursday), 8-hr work week (9
a.m. to 5:30 p.m.). During each working day, subjects Regression models were used with office color scheme
as the independent variable and with mood states andwere permitted two 15-min breaks and a 1-hr lunch break.
On any given day, all three workers in each office per- productivity as dependent variables. Stimulus screening
ability (high screeners vs. low screeners) was treated as aformed the same tasks in the same order and time frame.
However, office tasks were organized into two weekly covariate. Preplanned comparisons were used to examine
differences between color schemes. The alpha level forschedules, A and B, which alternated from one week to
the next. Though the daily schedules within both weekly statistical tests was 0.05.
schedules were identical, the weekly schedules differed
in terms of which daily schedule applied from one day Performance
to the next. Two office tasks totaling 15 min in duration
were performed by the workers at the beginning of the On day 1, the overall regression model reached signifi-
cance for proofreading names, F(3, 86)
Å
2.92, p
õ
work day and after breaks and lunch to acclimate the
workers to the office environment. 0.05, R
2
Å
0.09 (see Table II). A significant interaction
occurred for stimulus screening and office environmentThe workers filled out the POMS questionnaire twice
each day, first at the beginning of the day in the reception- between the red and blue-green offices, F(1, 86)
Å
5.62,
p
õ
0.05. Among those who scored low on the stimulusist area, and then as a post-test at the end of the day in
128 COLOR research and application
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TABLE II. Minnesota clerical test results.
White office Red office Blue-green office
Scores
a
Range MSDRange MSDRange MSD
Monday–day 1
Name 53–165 115.60 28.77 48 158 111.33 23.78 73– 181 121.46 26.64
Number 68–162 113.23 23.88 87 181 110.90 22.10 72– 156 109.63 22.94
Thursday–day 4
Name 73–188 138.53 32.94 84 178 130.90 28.09 73– 192 143.53 30.36
Number 98–192 139.26 26.85 82 196 135.96 31.46 83– 192 133.30 28.83
a
nÅ30 subjects for each office.
screening measure (low screeners), workers in the red ing scores and office environment between the white and
blue-green offices. The interaction suggests that lowoffice scored lower on proofreading names than subjects
working in the blue-green office. The reverse was true for screeners tended to score higher on Depression in the
white office than high screeners.those who scored high on the stimulus screening measure
(high screeners). On average, they scored higher on In general, workers in the red office reported higher
levels of dysphoria in terms of Confusion, Tension, andproofreading names in the red office than subjects work-
ing in the blue-green office. less Vigor as compared to that of workers in the blue-
green office at the end of the first day. Greater levels ofOn day 4, the overall model approached significance
for proofreading names, F(3,86)
Å
2.41, p
õ
0.07, R
2
Å
dysphoria in terms of Depression and Anger were re-
ported for low screeners as compared to that of high0.08 (see Table II). As with day 1, a similar significant
interaction effect between stimulus screening and office screeners in the red and white offices, while workers in
the blue-green office reported similar levels of dysphoria,environment was found when comparing red and blue-
green, F(1, 86)
Å
4.10, p
õ
0.05. These interaction ef- (Depression and Anger) regardless of stimulus screening
ability. These effects were found at the end of the 1st andfects suggest that environmental/screening may be a
moderating factor in the effect of office environment on 4th days.
performance.
Mood and Performance
Mood Specific hypotheses were not made about the possible
On the 1st day, the overall regression models for office relationships between mood and performance. Since anec-
environment reached significance on Confusion, F
Å
dotal and research evidence has tried to link the two vari-
6.50, (3, 86), p
õ
0.05, R
2
Å
0.18; Tension, F
Å
5.93, ables, usually hypothesizing that either positive mood
(3, 86), p
õ
0.05, R
2
Å
0.17; Vigor F
Å
3.46, (3, 86), states lead to higher productivity or that some other vari-
p
õ
0.05, R
2
Å
0.11; Depression, F
Å
6.35, (3, 86), p
õ
able causes both variables to change in the same direction,
0.05, R
2
Å
0.18; and Anger, F
Å
8.38, (3, 86), p
õ
0.05, the study examined the relationships between both vari-
R
2
Å
0.23 (see Table III). ables. No significant correlations were found between any
Significant main effects for office environment were of the mood state subscales and either task comparison
found on Confusion, F
Å
7.42, (1, 86), p
õ
0.05; Ten- subtests.
sion, F
Å
4.30, (1, 86), p
õ
0.05; and Vigor, F
Å
4.60,
(1, 86), p
õ
0.05. On average, higher scores for Confu-
sion and Tension were reported by workers in the red
office than in the blue-green office, while higher scores
DISCUSSION
for Vigor were reported in the blue-green office than in Performance
the red office.
Significant interaction effects for office environment The study provided no evidence for the first hypothesis
predicting that workers in the red office would be moreand stimulus screening were found on Depression, F
Å
5.69, (1, 86), p
õ
0.05; and Anger, F
Å
6.89, (1, 86), adversely affected in terms of productivity than workers
in the blue-green office scheme. However, the hypothesisp
õ
0.05. Low screeners reported more Anger in the
white office than high screeners. In the red office, low that stated that workers who scored low on stimulus
screening ability (low screeners) would perform morescreeners reported more Depression than high screeners.
On the 4th day, the overall regression model for De- poorly in the red office than those who scored high on
stimulus screening (high screeners) was supported by thepression reached significance, F(3,86)
Å
3.46, p
õ
0.05,
R
2
Å
0.11 (see Table III). A significant interaction effect, study (see Fig. 3). Furthermore, the reverse was true for
workers in the blue-green office. High screeners per-F
Å
4.01, (1, 86), p
õ
0.05, occurred for stimulus screen-
129Volume 22, Number 2, April 1997
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TABLE III. Means for profiles of Mood States Questionnaire at the beginning and end of the 1st and 4th days.
All subjects White office Red office Blue-green office
POMS Scale nÅ90 MSDnÅ30 MSDnÅ30 MSDnÅ30 MSD
Anger-hostility
day 1 morning 2.21 4.79 3.33 6.15 1.90 3.73 1.40 4.08
day 1 afternoon 3.01 5.94 3.43 7.47 3.90 6.27 1.70 3.19
day 4 morning 2.42 5.29 3.26 7.60 1.77 3.55 2.23 3.78
day 4 afternoon 2.83 6.80 4.03 8.16 3.20 7.96 1.27 2.79
Confusion-bewilderment
day 1 morning 4.39 3.59 4.43 3.16 5.33 4.54 3.40 2.62
day 1 afternoon 5.26 3.94 5.40 4.31 6.47 4.43 3.90 2.43
day 4 morning 4.01 3.44 4.03 3.90 4.47 3.52 3.53 2.87
day 4 afternoon 5.17 4.31 5.30 4.67 5.93 5.20 4.27 2.61
Depression-dejection
day 1 morning 3.58 7.11 3.93 5.83 4.17 9.95 2.63 4.55
day 1 afternoon 3.44 7.37 3.67 5.90 4.67 10.87 2.00 3.13
day 4 morning 2.39 4.67 2.93 6.23 1.70 2.93 2.53 4.31
day 4 afternoon 2.49 6.26 3.90 8.73 1.73 5.51 1.83 3.24
Fatigue-inertia
day 1 morning 4.73 5.19 4.70 4.33 5.23 6.15 4.27 5.07
day 1 afternoon 9.26 6.93 10.16 8.54 9.83 5.24 7.77 6.61
day 4 morning 3.91 5.56 3.90 5.30 3.47 5.59 4.37 5.94
day 4 afternoon 7.46 6.76 8.0 8.31 7.90 5.68 6.47 6.13
Tension-anxiety
day 1 morning 6.47 4.72 6.50 4.00 7.67 5.71 5.23 4.10
day 1 afternoon 6.87 5.24 7.03 5.15 8.10 6.21 5.47 3.94
day 4 morning 4.94 5.19 5.23 6.73 4.73 4.27 4.87 4.35
day 4 afternoon 7.03 5.91 8.27 6.76 6.80 6.08 6.03 4.69
Vigor-activity
day 1 morning 14.70 5.91 14.70 6.02 14.13 5.70 15.27 6.14
day 1 afternoon 11.29 6.34 11.13 7.27 9.67 4.82 13.07 6.41
day 4 morning 13.27 7.20 13.50 7.18 12.43 7.22 13.87 7.37
day 4 afternoon 10.98 6.87 11.50 7.11 9.27 6.77 12.17 6.62
formed more poorly in the blue-green office than low does performance up to a point. After reaching that opti-
mal level of arousal, any increase in arousal will lead toscreeners (see Fig. 4).
One explanation for these findings may be related to the decreased performance. How much arousal is optimal for
maximum performance depends on the task (Stennett).
35
YerkesDodson
34
principle, which proposes that there is
a curvilinear relationship between arousal and perfor- Generally, more cognitively complex tasks require less
arousal to reach optimal performance and, hence, the be-mance. As an individual’s level of arousal increases, so
FIG. 4. High Screener and arousal levels in blue-green of-
FIG. 3. High Screener and low screener arousal levels in fice: day 1 and day 4.
red office: day 1 and day 4.
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ginning of deterioration in performance. Conversely, less colors for office interiors, may have played a role in the
subjects’ experience of a light blue-green office as morecomplex tasks can be performed well, even at very high
levels of arousal. Other factors, such as environment and pleasant than the red office.
As expected, low screeners reported more dysphoriaindividual differences, may affect where an individual’s
optimal point of arousal is for a given task. with respect to depression in the red office than high
screeners. Surprisingly, individuals with low stimulusThe literature on color has consistently supported the
notion of warm colors, especially red, to be more physio- screening ability in the white office reported more dys-
phoria with respect to anger and depression than individu-logically and psychologically arousing than cool colors,
in particular blue, which are associated with low levels als who were high on this ability. One explanation for
these findings may be that the starkness of the white officeof arousal or increased relaxation. If the red office envi-
ronment is inherently arousing, then high screeners are with respect to the lack of contrast and pigment was more
disturbing for low screeners than high screeners wholess likely to feel overwhelmed in terms of arousal. As
a result, those individuals may perform better than low could more easily ignore the overall visual impact of that
office environment.screeners, because such individuals are more likely to feel
overwhelmed to the point where their performance begins
to deteriorate.
CONCLUSIONS
In contrast, if the blue-green office environment is in-
herently relaxing, then high screeners may not experience In examining the effects of three different color schemes
on productivity, the results suggest that color schemesenough arousal in order to reach a higher level of produc-
tivity. However, low screeners may be nearer to their alone may have no discernible impact on productivity.
The contrasting color schemes (bright red vs. light blue-optimal level of arousal and hence perform better than
those with a higher level of stimulus screening ability. green) derived from Wise and his colleagues’ proposal
concerning value and saturation did not differentially im-Differences in performance were found for the names
comparison task, but notfor the numberscomparison task. pact productivity, nor did the white color scheme as uti-
lized by NASA differ from the red or blue-green colorIn a study by Smith
36
examining the effect of increased
arousal on the performance of subjects, the numbers com- scheme. Only when individual differences in the ability
to screen irrelevant environmental stimuli are taken intoparison task also revealed no significant result. In contrast,
a significant result was found for the names comparison account did the color schemes exhibit a differential impact
on productivity.One important implication is that alteringtask in which the level of arousal heightened by an audi-
tory stimulus was negatively related to performance on a specific interior environment to enhance productivity
may be quite difficult, because the impact of that interiorthat task. A plausible explanation may be that the numbers
comparison task is cognitively simpler to perform than may vary from person to person depending on each per-
son’s individual characteristics. As a result, employersthe names task. In the numbers task the main cognitive
operation is checking whether each numeral in a row may need to concern themselves more with screening
potential employees with similar relevant characteristics.of numerals matches that of a second row of numerals.
Similarly, in the names task, the aim is to check whether Attempting to create the ideal environmental ambiance
through interior color across all individuals, who mayeach letter in a row of letters is identical to that of a
second row of letters. However, an additional cognitive differ in several pertinent characteristics, may be impossi-
ble. Alternatively, interiors could be designed with maxi-operation confounds the task where each set of letters can
be read as a proper name. This may make the task more mum flexibility to allow for variations within the same
general space according to each individual’s relevantcomplex than the numbers task. The ceiling for maximum
performance of the numbers task may have been too low characteristics.
The findings on mood definitely suggest that colorand relatively insensitive to arousal level to detect any
differences in performance on this subtask. scheme alone may impact mood states in accordance with
previous findings. Furthermore, individual stimulus
screening ability may act as a moderating variable that
Mood can influence how people experience a particular interior
color scheme. These results may indicate that individualConsistent with the first hypothesis concerning mood
states, workers in the red office color scheme reported characteristics will need to be examined more closely in
trying to understand the impact of various color schemesmore dysphoria than workers in the blue-green office
color scheme. The results seem to follow the proposals on an individual’s affective experience.
Not surprisingly, mood and productivity had no rela-of Wise et al.,
1
who suggested that a color scheme embod-
ying the color qualities (value and saturation) represented tionship, suggesting that the impact of color schemes and
stimulus screening on both of these variables are indepen-by the blue-green office would be experienced as more
pleasant than a hypothetical color scheme with opposite dent. One prevalent assumption in studying employee per-
formance in the workplace is that the employee’s affectivecolor qualities, such as the red office color scheme. In
addition, the choice of a light blue-green, which the state is related to his or her performance on tasks. How-
ever, the results of thisstudy did not support this hypothe-BOSTI survey reported to be among the most preferred
131Volume 22, Number 2, April 1997
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Residential interiors (RIs) have been designed by anonymous designers throughout his- tory and have reflected their users’ identity, culture, and habits until modern times, although design and architecture courses rarely involve residential interiors in their curriculums. Therefore, decision-makers (architects, interior architects, designers, and users) took them for granted. However, COVID-19 forced revisiting this approach towards RIs and they faced a gap in the literature helping them to design these interiors, especially workspaces, in order to improve their users’ experience. In connection with previous studies, which explored creativity in workspaces, this study aims to compile colour-related literature work on workspaces in RIs (WRI) which will require further attention from interior architects to reconsider the discipline under new normal conditions. Providing a framework for WRIs in terms of function and activity might lead to the semantics of RIs in future studies. This study’s findings contribute to the interpretation and understanding of new normal workspace interiors after the COVID-19 pandemic so it will be beneficial for decision-makers in addition to researchers who aim to investigate this topic in future studies.
... Kwallek ve ark. [19] ofis iç mekân renginin çalışanların performans ve verimliliği üzerindeki etkilerini araştırmıştır. Çalışma sonuçlarına göre; kırmızı ofiste kalanların ortalama anksiyete ve stres değeri yüksekken, mavi ofiste kalanların depresyon değeri yüksek bulunmuştur. ...
... Renk algısının kullanıcı üzerindeki etkisinin varlığı çalışmalarla ispatlanmış bir yargıdır. Özet halinde verilen çalışmaların bulgularına göre renklerin psikolojik ve fizyolojik etkileri; kırmızı rengin uyarıcı [24,30], heyecan verici [29] olduğu mekânda kullanıcının fizyolojik tepkisini arttırdığı [24,45] fakat stres ve anksiyete eğilimi yarattığı [19,37] görülmektedir. Bu nitelikleri çağrıştıran diğer renkler ise sarı [21,29] ve turuncu gibi sıcak renklerdir. ...
... Bu nitelikleri çağrıştıran diğer renkler ise sarı [21,29] ve turuncu gibi sıcak renklerdir. Mavi ve türevi soğuk renklerin sakinleştirici, ferahlık, dinginlik ve huzur [30] veren etkileri olduğu, sağlık yapılarında [55,56] tercih edildiği buna karşılık mekânda depresyon eğilimi yaratabileceği [19,24] durumlara da rastlanmaktadır. Yeşil güven, saflık hissi ve dinamizm ile nitelendirilmiş, konut iç mekânlarında tercih edilen renklerden olmuştur [22,56]. ...
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Conference Paper
Özet-Bu çalışmada, iç mekânda kullanılan rengin kullanıcı algısal değerlendirmesi üzerine yapılan literatür çalışmaları gruplandırılarak analiz edilmiştir. Yapılan çalışmalar yüksek oranda renklerin mekân genelindeki algısı üzerinedir. Fakat mekândaki renk birlikteliği ve rengin mekândaki kullanım oranının kullanıcı üzerinde farklı algılar oluşturabileceği düşünülmektedir. Çalışmanın amacı mevcut literatür yayınlarını gruplandırıp analiz ederek elde edilen bulgular ışığında ortaya atılan düşüncenin literatür kaynaklarındaki eksikliğini kanıtlamak ve gelecek çalışmalara kaynak sağlamaktır. Araştırma kapsamında renk algısı üzerine çeşitli akademik mecralarda yayınlanmış 49 makale/teze yer verilmiştir. Yayınlar amaçlarına, yöntemlerine, değerlendirilen değişkenlerine göre gruplandırılarak incelenmiştir. Renk algısı araştırmaları psikolojik yönden ve mekânsal yönden iki gruba ayrılmıştır. Mekânsal yönden renk algısı araştırmaları kendi içerisinde araştırma mekânına göre; sanal, gerçek ve sanal gerçeklik olarak, araştırma sorularına göre; mekânsal kalite değerlendirme, görev tamamlama, fizyolojik tepki ölçümü olarak ve bağımsız değişkenlerine göre: cinsiyet, yaş, mesleki eğitim, kültür, mekânsal deneyim-çağrışım olarak alt gruplara ayrılmıştır. İncelenen yayınlar ilgili başlık altında sonuçlarıyla birlikte verilmiştir. Ayrıca araştırma sonucunda ortaya çıkan bulgular iç mekânda renk birlikteliği ve rengin kullanım yoğunluğu ile ilgili çalışmaların yetersiz olduğunu göstermektedir.
... Kwallek ve ark. [19] ofis iç mekân renginin çalışanların performans ve verimliliği üzerindeki etkilerini araştırmıştır. Çalışma sonuçlarına göre; kırmızı ofiste kalanların ortalama anksiyete ve stres değeri yüksekken, mavi ofiste kalanların depresyon değeri yüksek bulunmuştur. ...
... Renk algısının kullanıcı üzerindeki etkisinin varlığı çalışmalarla ispatlanmış bir yargıdır. Özet halinde verilen çalışmaların bulgularına göre renklerin psikolojik ve fizyolojik etkileri; kırmızı rengin uyarıcı [24,30], heyecan verici [29] olduğu mekânda kullanıcının fizyolojik tepkisini arttırdığı [24,45] fakat stres ve anksiyete eğilimi yarattığı [19,37] görülmektedir. Bu nitelikleri çağrıştıran diğer renkler ise sarı [21,29] ve turuncu gibi sıcak renklerdir. ...
... Bu nitelikleri çağrıştıran diğer renkler ise sarı [21,29] ve turuncu gibi sıcak renklerdir. Mavi ve türevi soğuk renklerin sakinleştirici, ferahlık, dinginlik ve huzur [30] veren etkileri olduğu, sağlık yapılarında [55,56] tercih edildiği buna karşılık mekânda depresyon eğilimi yaratabileceği [19,24] durumlara da rastlanmaktadır. Yeşil güven, saflık hissi ve dinamizm ile nitelendirilmiş, konut iç mekânlarında tercih edilen renklerden olmuştur [22,56]. ...
Conference Paper
Özet-Bu çalışmada, iç mekânda kullanılan rengin kullanıcı algısal değerlendirmesi üzerine yapılan literatür çalışmaları gruplandırılarak analiz edilmiştir. Yapılan çalışmalar yüksek oranda renklerin mekân genelindeki algısı üzerinedir. Fakat mekândaki renk birlikteliği ve rengin mekândaki kullanım oranının kullanıcı üzerinde farklı algılar oluşturabileceği düşünülmektedir. Çalışmanın amacı mevcut literatür yayınlarını gruplandırıp analiz ederek elde edilen bulgular ışığında ortaya atılan düşüncenin literatür kaynaklarındaki eksikliğini kanıtlamak ve gelecek çalışmalara kaynak sağlamaktır. Araştırma kapsamında renk algısı üzerine çeşitli akademik mecralarda yayınlanmış 49 makale/teze yer verilmiştir. Yayınlar amaçlarına, yöntemlerine, değerlendirilen değişkenlerine göre gruplandırılarak incelenmiştir. Renk algısı araştırmaları psikolojik yönden ve mekânsal yönden iki gruba ayrılmıştır. Mekânsal yönden renk algısı araştırmaları kendi içerisinde araştırma mekânına göre; sanal, gerçek ve sanal gerçeklik olarak, araştırma sorularına göre; mekânsal kalite değerlendirme, görev tamamlama, fizyolojik tepki ölçümü olarak ve bağımsız değişkenlerine göre: cinsiyet, yaş, mesleki eğitim, kültür, mekânsal deneyim-çağrışım olarak alt gruplara ayrılmıştır. İncelenen yayınlar ilgili başlık altında sonuçlarıyla birlikte verilmiştir. Ayrıca araştırma sonucunda ortaya çıkan bulgular iç mekânda renk birlikteliği ve rengin kullanım yoğunluğu ile ilgili çalışmaların yetersiz olduğunu göstermektedir. Anahtar Kelimeler-Mekân, mekânsal algı, renk, renk algısı, renk yoğunluğu Abstract-In this study, the literature review on the user perceptual assessment of the colour used in the interior space is analyzed and grouped. Most of the studies are about the perception of colours throughout the space. However, it is thought that the colour combination in the space and the use of colour in the space may create different perceptions on the user. The aim of this study is to group and analyze existing literature publications, to prove the lack of literature in the light of the findings and to provide a source for future studies. Within the scope of the research, 49 articles / thesis on colour perception have been published in various academic media. The studies are grouped according to their aims, methods and evaluated variables. Colour perception research is divided into two groups as psychological and spatial. Studies of spatial color perception is divided into subgroups: According to the research location; virtual, real and virtual reality, according to research questions; spatial quality assessment, task completion, physiological response measurement and according to independent variables: gender, age, vocational education, culture, spatial experience-connotation. The studies reviewed are given with the results under the related title. Results of the research shows that the studies related to the colour combination and the density of colour use in the interior are insufficient.
... Anything needs color decoration. Color can directly or indirectly affect people's emotions [6][7][8][9][10]. In the long-term life of human beings, the application of color makes it a visual symbol system, and it has certain symbolism and stability. ...
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As a bridge of human-computer communication, the color design of intelligent vehicle HMI interactive interface is particularly important. It is also the first guide to the driver during the driving process. The quality of its design will also directly affect the driver’s senses and the driving safety of the vehicle. Therefore, this paper introduces the current situation, design principle, and future development of the vehicle interaction interface from multiple perspectives. Through the neural network system (condition generation countermeasure network model) of visual recognition, the color of the intelligent vehicle HMI interactive interface under the user experience is analyzed. According to the analysis of the psychological cognition and behavior operation of the automobile user, the correlation analysis of the human, vehicle, environment, and various elements of the interface is carried out, and how the vehicle interactive interface can meet the expected physiological and psychological needs of the user more and improve the operability is discussed in order to design an on-board HMI interactive interface that can be intelligently perceived according to weather, driver’s interests, and other factors and then improve the current backward operation mode of the on-board interactive interface, so that the interaction between people and vehicles is more smooth and pleasant.
... e surrounding environment or "atmosphere" affects human perception. Many studies have shown that the environment affects the occupants' mood and performance, and even their physical and mental health [31][32][33][34][35][36]. Factors that influence occupants' perception of the environment include light, color, temperature, noise, or smells [24,37,38]. ...
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The environment is one of the factors that may influence occupants’ perception of floor vibration and the assessment of floor serviceability. In this study, laboratory tests were conducted on a 3-ply CLT floor. Occupants’ assessment of the floor serviceability under human-induced vibration was investigated. Virtual reality (VR) technique was used as a research method, simulating two common environments in life. First, the correlation between the occupants’ annoyance rating and serviceability indicators (response factor and vibration dose value (VDV)) was compared with existing standards. The results show that the response factor method in ISO 10137:2007 is conservative for timber floors in both bedroom and gym environments. The VDV method in BS 6472-1:2008 can generally reflect the vibration acceptability of timber floor vibration. Then, the effect of acceleration and environment on the floor serviceability assessment was investigated through statistical methods, respectively. A weak positive correlation between the annoyance rating and the acceleration was found. The effect of the environment on floor vibration assessment was found to be significant.
... These findings match the results from all prioritized demographics (See Figure 6). This is also aligned with our findings from our first study [15], and previous literature, where red had been repeatedly associated with activity and stimulation, and increased levels of anxiety and excitement [17][18][19][20][21][22][23][24]. ...
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Colors influence our daily perceptions and expectations that manifest in a variety of ways. This research has three main objectives: to demonstrate the relationship between the colors of pills and their expected efficacies, to test this effect on a wide variety of demographics, thereby demonstrating their influence on choices made by participants. Finally, to understand the reasoning behind the choices made by participants, and the color associations exhibited. The results of a series of surveys showed clear similarities and differences across various demographics. The strongest and most consistent color associations were those of white with pain relief and red with stimulant efficacies. The color associations found were red with aggression and power, blue with calmness and serenity, white with calm and purity, yellow with energy, and green with environment and health. The findings of this study can help pharmaceutical companies, and medical practitioners, to better make, market, and prescribe pills, depending on the geographical location, ethnicity, and age group of the patient. This may also strengthen the perceived effects of the pills on patients overall by increasing their compliance rates.
... As color is indispensable to individuals' perceptual experiences of the world, its effect has been the subject of research since the early history of psychology. Studies show that colors surrounding us in our daily lives profoundly affect bodily functions, including mood and behavior [1,2]. The potential effect of color on our bodily functions has been extensively discussed after Hill and Barton reported that competitors wearing red clothing or body protection had a significantly higher chance of winning the 2004 Olympic Games in Athens [3]. ...
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As time plays a fundamental role in our social activities, scholars have studied temporal perception since the earliest days of experimental psychology. Since the 1960s, the ubiquity of color has been driving research on the potential effects of the colors red and blue on temporal perception and on its underlying mechanism. However, the results have been inconsistent, which could be attributed to the difficulty of controlling physical properties such as hue and luminance within and between studies. Therefore, we conducted a two-interval duration-discrimination task to evaluate the perceived duration of color stimuli under different equiluminant conditions: subjective or pupillary light reflex (PLR)-based equiluminance. The results, based on psychometric functional analyses and simultaneous pupillary recordings, showed that the perceived duration of red was overestimated compared with blue even when the intensity of the stimulus was controlled based on subjective equiluminance (Experiment 1). However, since blue is known to induce a larger PLR than red despite equiluminance, we conducted a controlled study to distinguish the indirect effect of pupillary response to temporal perception. Interestingly, the effect observed in Experiment 1 faded when the luminance levels of the two stimuli were matched based on PLR response (Experiment 2). These results indicate that duration judgement can be affected not only by the hue but also by different equiluminance methods. Furthermore, this causality between the equiluminance method and temporal perception can be explained by the fluctuations in incident light entering the pupil.
... The relationship between blue/green wall colours and stress is in contrast with previous research, in which blue and green were associated with peace, openness, concentration, comfort, and harmony (Mehta and Zhu 2009;Nag 2019). While previous studies mainly focussed on the office-environment with white as an appropriate wall-colour (Kwallek, Lewis, and Robbins 1988), van der Voordt, Bakker, and de Boon (2017) argued that people might be less aware of the wall colours at home, because they experience the colours unconsciously. However, during the pandemic, when employees were forced to WFH, they might have become more conscious of the wall colours again due to different use of rooms (e.g. ...
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Previous research showed that office workers are mainly distracted by noise, influencing their mental health. Little investigation has been done into the influence of other workspace characteristics (i.e. temperature, amount of space, visual privacy, adjustability of furniture, wall colours, and workspace cleanliness) on distractions at the office, and even fewer while working from home (WFH). The influence of home-workspace distractions on mental health also received limited attention. This research aims to investigate relationships between home-workspace and personal characteristics, distraction, and mental health while WFH during COVID-19. A path analysis approach was used, to find that, at home, employees were distracted by noise and when having a small desk. Those with a dedicated workroom were less distracted. Distractions mediated most relationships between home-workspace characteristics and mental health, while personal characteristics influenced mental health directly. Employers can use these results to redesign policies regarding home-and-office working to stimulate a healthy work environment. Practitioner summary: The investigation of the influence of home-workspace characteristics on distractions and mental health while WFH during COVID-19 appears to be limited. This research filled this gap by performing a path analysis, using a holistic definition of mental health. Findings showed that distractions mediate relationships between home-workspace characteristics and mental health.
Chapter
Research background: Material Intelligence is a widely discussed topic in recent years. With the promotion of the manufacture, designers enable design patterns to create or change materials performance for their creative works. Material properties such as the color, texture and luster could show specific effects in different conditions. In the field, this paper focuses on the material color and human behaviors, and proposes a design method for creating a better interior environment.Research question: Color is a significant part of our life. Many design cases use color widely to affect emotions to realize special functions. However, the dye is difficult to change in real-time, which unable to adapt to different emotion requires. Artificial lights are difficult to keep vivid in sunny conditions, and large-scale use of artificial light could also cause uncomfortable to people.Approach: To implement the purpose in research, using laser films materials as the basic research object. Analyzing relationships between color produced through rotating films and the rotation angle, which transform programs to realize digital twin. Then, the overall equipment is fabricated by structural design and 3D printing technology, and the Arduino Open-source hardware control the device. Moreover, analyzing different postures of people by motion capture technique, realize positively change color by user-behavior.Results: In this paper designing a color-interactive device to positively change color based on programmable physical color-changing materials and user-behavior analysis, which actively adapt human’s behavior. And this creates a way for the interior environment of adaptive design.Contributions: This research attempt to connect microstructures of materials and macro performance by programmable technology. From principles to design application, it is a practice of using design thinking to realize design innovation in longitudinal research. In this study, the color generated based on the principle of structure-color materials, compared with artificial light, this physical color-changing material has good display effect and real color in outdoor or strong light environment. And it can save energy of artificial light, which is also an exploration and experiment of sustainable intelligent design.KeywordsStructural-color materialsPhysical interaction designMotion capture.
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The literature on environmental color to enhance habitability in the design of Space Station interiors is reviewed. Some 200 studies were examined to determine the relative contributions of the three dimensions of color (hue, saturation, and brightness or lightness) to responses to environmental colorations. Implications of the study for color usage in novel settings and locales include: (1) There are no hard-wired linkages between environmental colors and particular judgmental or emotional states; (2) Perceptual impressions of color applications can, however, affect experiences and performances in settings; (3) Color behavior studies cannot yet specify an optimal color scheme, but instead must consider differing objectives, the relative importance of each, and design features such as the coordination of geometry, color, texture, etc.; (4) Some color-behavior effects are governed by low-level retinal and limbal mechanisms as well as by cognitive processes; and (5) Colors should first be specified in terms of what they are to do instead of what they are. Some exercise of choice is therefore needed to establish a sense of personal competence in the setting, since color must be ultimately be accepted by the people who are to live with it.
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Effects of the four psychological primary colors were assessed by randomly assigning 40 undergraduates (13 male, 27 female) to 4 treatment groups, with each group receiving either red, yellow, green, or blue illumination. Anxiety state was assessed at 5-min. intervals using the State-Trait Anxiety Inventory. The red and yellow groups had significantly higher A-state scores than the blue and green groups, and these values did not change significantly during the 15-min. testing session.
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-Judges selected from ISCC-NBS patches those colors which were most representative of red, yellow, green, and blue. These colors were presented for 1 min. each with GSR, heart rate, and respiration being recorded. There was a significant color effect on GSR but not on the other measures. Red was significantly more arousing than blue or yellow and green more than blue. Early research on the psychological aspects of color was concerned with such subjective aspects as individual color preferences. Guilford ( 1931) found hue to be the most important factor in color preference. Hevner ( 1935) found that college students described various colors in emotional terms with red usually described as happy or exciting and blue described as serene or dignified. In an experimental study of the effect of red and green surroundings on psychomotor tasks and judgment the results were inconclusive (Nakshian, 1964). Another approach to color effect is to investigate the differential effect on GSR, heart rate, respiration, and other autonomic nervous system functions. Wilson ( 1966) found red significantly more arousing than green (GSR) . This finding was consistent with subjective reports following the experimental session. Red was variously described as more stimulating, awakening, and attentiondrawing. Nourse and Welch ( 1971) studied the GSR as a function of violet and green illumination and found a significant difference for the first trial but this difference did not appear in the later trials. A spectral analysis of the violet used showed the spectral components were a 455 mm. (blue) and 677 mm. (red). So these results may only confirm the Wilson (1966) finding of red be:ng more arousing than green. Gerard (1958) reported that the autonomic nervous system and the visual cortex were significantly less aroused during blue than during red or white illumination. Red, blue, and white lights were projected on a screen, and the results indicated a significant color effect on GSR, respiration rate, frequency of eye blink, systolic blood pressure, heart rate, and EEG measures. A wide variety of colors have been used in previous studies. Gerard ( 1958) made an arbitrary selection of colors and earlier researchers used colors specified in the Munsell notation but when these color patches are examined it can be seen that they are neither virid or strong colors. This study used colors which were selected by judges as being red, blue, green, and yellow rather than using a 'Reprint requests should be addressed to: K. W. Jacobs, Sourhern Station Box 5238, University of Southern Mississippi, Hartiesburg, Mississippi 39401.
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A technique for evaluating the relative effects of hue, brightness and saturation on color pleasantness is explored. 24 colors, specified by their Munsell notation, are dichotomized in pleasant and unpleasant ones by 36 female and 42 male subjects. A discriminant analysis indicates a major effect of saturation, which determines 88.36% of the variation judgments of pleasantness. Brightness is less important (11.56%) and hue is almost irrelevant (0.68%). The question had never been investigated before, perhaps because the Munsell notation for hue is not metric. We overcame this difficulty by transforming the hue notations into metric scores using Indow and Uchizono's (1960) multidimensional mapping of Munsell colors. It has to be emphasized that this paper describes a tool for measuring the relative contributions of hue, brightness, and saturation to the attribute of color pleasantness, but that the findings of this investigation may not generalize to a set of colors different from the ones used currently.
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"A test of the hypothesis that an inverted-U relationship exists between the level of arousal and performance level was made by comparing the performance of 31 Ss on an auditory tracking task under different conditions of incentive . . . the data of this study give strong support to the hypothesis. The hypothesis held regardless of whether palmar conductance level or the EMG response of any one of four different muscle groups was used as the criterion of arousal." (PsycINFO Database Record (c) 2006 APA, all rights reserved).