review of literature :)

  

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there are 4 articles attached below that all surround the topic (sustainability in interior design), read and write in 3 different sections like the example attached below based on the topic what studies were done, how they were done, what they found, how they are similar or different from the other studies you found, each section should be 300+ words. For each section create a creative title. The scholarly articles on the topic should be synthesized into a meaningful whole. Use a level one heading and at least three level two headings to organize your review, you may use level three headings if you choose

Don’t forget to include a discussion of the Human Ecological Theory that you are using to direct your research. If you don’t come across any formal theories in your readings, then you may use the Human Ecological Theory. Name the theory, describe it, and tell how it ties into your research.REVIEW OF LITERATURE
1
Review of Literature
Kellie J. Fernandez
California State University, Northridge
REVIEW OF LITERATURE
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Review of Literature
Fad Diets and Weight Loss Dieting from Adolescence to Adulthood
Across the lifespan, the use of fad diets and weight loss dieting is very prominent
(Banjari, Kenjeric, Mandic, & Nedeljko, 2011; Calderon, Yu, & Jambazian, 2004). High school
and college years are considered a critical period for the formation of eating behaviors (Kresic,
Jovanovic, Zezelj, Cvijanovic, & Ivezic, 2009; Neumark-Sztainer, Wall, Larson, Eisenberg, &
Loth, 2011). It has been observed that individuals who partake in dieting and disordered eating
during adolescence tend to carry this unhealthy behavior through adulthood (Neumark-Sztainer
et al., 2011). During adolescence and young adulthood, most women tend to focus on thinness
and quick weight loss, although these motives often lead to the unhealthiest eating behaviors
(Calder & Mussap, 2015). Linked with these motives is an increase in the use of diets
popularized by the media and society. Studies show that from a random sampling of high school
students, 60.1% have tried dieting (Calderon et al., 2004). Of those students, 15% dieted prior to
age 11 and 84% dieted prior to age 14. Among high school students, limiting portion sizes,
counting calories, restricting fat, and skipping meals are common dieting techniques. During
college years, 35.6% of students claim to be on fad diets (Banjari et al., 2011). Many students
also create their own diets and skip meals to lose weight. On the contrary, Kresic, Jovanovic,
Zezelj, Cvijanovic, and Ivezic (2009) found that as nutrition knowledge increased, as did
adherence to MyPlate recommendations, such as the intake of fruits, vegetables, and grains. Also
linked with this knowledge was consuming less excess food, calories, and oil and using
appropriate serving sizes. This study by Kresic et al. (2009) showed that healthier diets and
dieting behaviors among college students can be improved with greater nutrition knowledge. As
individuals age, the use of fad diets and unhealthy eating behaviors tend to decrease as
REVIEW OF LITERATURE
3
individuals place a higher value on lifelong change and understand (Calder & Mussap, 2015).
Although motivations change, it is still important to continue to educate individuals as they age,
as many are at risk of unhealthy eating behaviors due to their behavior during adolescence
(Neumark-Sztainer et al., 2011).
The Correlation Between Weight Loss Dieting and Actual Weight Change
Dieting is a common practice and is used often to try to control weight (Calderon et al.,
2004). But, despite individuals’ best efforts, dieting is not always successful or a predictor of
weight loss (Calder & Mussap, 2015). Of a group of university students studied, only 14% of
females never gained back the weight they had lost while dieting, which shows little long-term
success (Banjari et al., 2011). Through various studies, it has been concluded that dieting
methods and motives are not significant determinants in weight outcomes (Calder & Mussap,
2015). Demonstrating little success, it has been found that males are frequently unwilling to give
up fast food and females consistently indulge in sweets even while dieting (Banjari et al., 2011).
These behaviors could be one of the causes of unsuccess in dieting among college students.
Although results are conflicting, some studies have shown that restraint, overeating, and BMI do
not predict weight change (Lowe et al., 2006). In contrast, weight suppression and a history of
dieting did lead to weight gain over time. But, it should be noted that both weight suppression
and dieting are more common among already overweight individuals and those predisposed to
weight gain. Furthermore, research has shown that among first-year college students, current
dieters gain double the weight of former dieters and triple that of girls who have never dieted
(Lowe et al., 2006). This shows a strong link between dieting and weight gain. On the other
hand, the amount of expected total weight loss prior to dieting has been seen to predict actual
weight loss among obese individuals (Calugi, Marchesini, Marwan, Gavasso, & Grave, 2016).
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4
Within the same population, weight loss satisfaction and actual weight loss are also common
predictors of weight-loss maintenance. Although dieting is not an exact science, it has been
observed that dieting does not cause weight gain but, it is also not successful in preventing it
(Lowe et al., 2006).
The Impact of Body Image and Perception on Eating Behavior
Weight loss dieting was seen to be significantly more common among women than men
(Banjari et al., 2011). Females tend to view themselves as more overweight than they are or are
not and men tend to underestimate their weight. About two-thirds of female, high school students
who choose to diet, are considered to have a normal or healthy body weight (Calderon et al.,
2004). Body weight perception is poorly correlated with actual BMI. In a study on a Croatian
student group, 11.8% of females were actually overweight but 22.7% self-reported themselves as
overweight (Banjari et al., 2011). In contrast, 16.7% of males viewed themselves as overweight
but, in reality, 33.3% had a BMI over twenty-five. Research has shown that there is frequently no
difference between the BMI of individuals with and without a dieting history (Lowe et al., 2006).
For most young women, their efforts are focused on appearance, thinness, and quick weight loss
(Calder & Mussap, 2015). This quick, easy, and thin dieting is the most common, but also the
most destructive. Due to the prominence of dieting, researchers are looking into the physical and
psychological effects of poor body perception and dieting, as there is a correlation (NeumarkSztainer et al., 2011; Banjari et al., 2011). More than 40% of high school students report
consciously eating less or skipping meals to control their weight (Calderon et al., 2004). Also
linked to poor body image and dieting is calorie counting, the use of supplements, and restraint
(Banjari et al., 2011). Although more research needs to be done, poor self-image has the
potential to lead to depression, binge eating, and weight gain (Neumark-Sztainer et al., 2011). On
REVIEW OF LITERATURE
5
the contrary, weight loss satisfaction and actual weight loss can lead to higher self-esteem and
greater success in long-term weight management (Calugi et al., 2016). Body perception can
influence individuals towards positive or negatives behaviors, although negative behaviors are
far more common (Neumark-Sztainer et al., 2011; Banjari et al., 2011).
Human Ecological Theory
Diets are changing and developing from the moment individuals are brought into the
world through the time they leave. Individuals’ diets are directly or indirectly affected by the five
factors of the Human Ecological Theory. On a large scale, the change of dieting techniques and
popularized diets over time play a major role in dieting choices and long-term health outcomes.
Similarly, diets change across the lifespan. As infants, diets consist of breastmilk and then
transition to simple foods. With age, diets gain variety and food preferences develop. During
high school years, diets are directly affected by parents’ economic status, geographic location,
and food resources. Cafeteria food, vending machines, and restaurants nearby are major factors
in high school students’ food choices. In high school, nutrition education is not always offered,
which can give students a false assumption on what a balanced meal is. Students are also highly
influenced by society and advertisements they see, including fad diets, celebrities, and
popularized weight loss techniques. Furthermore, appearance and clothing styles play a part in
body image, therefore affecting eating behaviors. Poor eating behavior outcomes include
skipping meals, choosing low fat options, laxatives, and over the counter drugs. Other influences
could be culture, tradition, and the state of the economy. Many families have different cultural
values that influence the food brought into the home, therefore influencing one’s diet. Tradition
and religious practices such as kosher, halal, vegan, and vegetarianism play a part in what food is
consumed. Specific restaurants cater to these needs, but are not widely available in certain
REVIEW OF LITERATURE
6
geographical regions, which may limit the variety within one’s diet. In conclusion, there are
many factors that influence one’s diet, including, but not limited to media, economy and cultural
values.
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7
References
Banjari, I., Kenjeric, D., Mandic, M. L., & Nedeljko, M. (2011). Is a fad diet a quick fix? An
observational study on a Croatian student group. Periodicum Biologorum, 113(3), 377381. Retrieved from https://hrcak.srce.hr/74086
Calder, R. K., & Mussap, A.J. (2015). Factors influencing women’s choice on weight-loss diet.
Journal of Health Psychology, 20(5), 612-624. doi:10.1177/1359105315573435
Calderon, L. L., Yu, K. C., & Jambazian, P. (2004). Dieting practices in high school students.
The American Dietetic Association. (104)(9), 1369-1374. doi:10.1016/j.jada.2004.06.017
Calugi, S., Marchesini, G., Marwan, G.E., Gavasso. I., & Grave, D.R. (2016) The influence of
weight-loss expectations on weight loss and of weight-loss satisfaction on weight
management in severe obesity. The Academy of Nutrition and Dietetics, 2212-2672.
doi:10.1016/j.jand.2016.09.001.
Kresic, G., Jovanovic, G. K., Zezelj, S. P., Cvijanovic, O., & Ivezic, G. (2009). The effect of
nutrition knowledge on dietary intake among Croatian university students. Collegium
Antropologicum, 33(4), 1047-1056. Retrieved from https://hrcak.srce.hr/51453
Lowe, M. R., Annunziato, R. A., Markowitz, J. T., Didie, E., Bellace, D. L., Riddell, L.,…Stice,
E. (2006). Multiple types of dieting prospectively predict weight gain during the
freshman year of college. Appetite, 47, 83-90. doi:10.1016/j.appet.2006.03.160
McComb, S., Jones, C., Smith, A., Collins, W., & Pope, B. (2016). Designing incentives to
change behaviors: Examining college student intent toward healthy diets. Western Journal
of Nursing Research, 38(9), 1094-1113. doi:10.1177/0193945916644705
Neumark-Sztainer, D., Wall, M., Larson, N. I., Eisenberg, M. E., & Loth K. (2011) Dieting and
REVIEW OF LITERATURE
disordered eating behaviors from adolescence to young adulthood: Findings from a 10year longitudinal study. Journal of the American Dietetic Association, 111(7), 10041011. doi:10.1016/j.jada.2011.04.012.
8
buildings
Article
Influence of Classroom Colour Environment on College
Students’ Emotions during Campus Lockdown in the
COVID-19 Post-Pandemic Era—A Case Study in Harbin, China
Weiyi Tao, Yue Wu *, Weifeng Li and Fangfang Liu *
Key Laboratory of Cold Region Urban and Rural Human Settlement Environment Science and Technology,
Ministry of Industry and Information Technology, School of Architecture, Harbin Institute of Technology,
Harbin 150001, China
* Correspondence: wuyuehit@hit.edu.cn (Y.W.); liufangfang@hit.edu.cn (F.L.)
Citation: Tao, W.; Wu, Y.; Li, W.; Liu,
F. Influence of Classroom Colour
Environment on College Students’
Emotions during Campus Lockdown
Abstract: Campus lockdown during COVID-19 and the post-pandemic era has had a huge negative
effect on college students. As a vital part of interior teaching spaces, colour deeply influences college
students’ mental health and can be used for healing. Nevertheless, research on this topic has been
limited. Based on colour psychology and colour therapy, this paper discusses the relationship between
interior teaching space colours (hue and brightness) and emotions among college students. The HAD
scale and questionnaire survey method were used. It was concluded that: (1) Anxiety and depression
were prominent among the college student population during the quarantine of the university due to
the epidemic. (2) Warm colours have an advantage over both cold and neutral colours in creating
pleasure, relaxation, and mental attention, with the second in line being the cold and the last being the
neutral. Warm colours make it pleasant for individuals while cold colours boost attention. (3) When
subjects have higher values of anxiety and depression, they are less satisfied with the colour of the
teaching space. (4) In most cases, there is no significant difference in the colour preference of teaching
spaces across the gender, grade, and major groups, with females having a higher preference for
warm high-brightness classrooms than males. These findings provide crucial ideas for future interior
teaching space design and enrich the theories in colour psychology.
in the COVID-19 Post-Pandemic
Era—A Case Study in Harbin, China.
Keywords: COVID-19; classroom colour environment; college students’ mental health; HAD scale
Buildings 2022, 12, 1873. https://
doi.org/10.3390/buildings12111873
Academic Editor: Diego Pablo Ruiz
Padillo
Received: 29 August 2022
Accepted: 26 October 2022
Published: 3 November 2022
Publisher’s Note: MDPI stays neutral
with regard to jurisdictional claims in
published maps and institutional affiliations.
Copyright: © 2022 by the authors.
Licensee MDPI, Basel, Switzerland.
This article is an open access article
distributed under the terms and
conditions of the Creative Commons
Attribution (CC BY) license (https://
creativecommons.org/licenses/by/
4.0/).
1. Introduction
Since its emergence, the new coronavirus has had various adverse effects on the mental
health of the general public. In the first year of COVID-19, the prevalence of depression
and anxiety disorders is estimated to have increased by 25% [1,2]. Studies [3] show that
people have had varied degrees of psychological problems throughout the outbreak. Stress,
anxiety, and depression values remained high after two weeks and did not decrease over
time. This was exacerbated by the isolation and confinement caused by the epidemic, with
symptoms such as mood disorders, depression, stress, poor mood, irritability, insomnia,
and post-traumatic stress disorder [4]. Of all populations, students are among the most
prone to have severe psychological problems [5]. A comparative study found that children
who experienced isolation had post-traumatic stress values four times higher than those
who did not [6]. In an Italian study [7], late bedtimes and late wakeups were particularly
common among the student population, and sleep quality was also affected during the
period of isolation, with 27.8% reporting depression symptoms and 34.3% showing anxiety
symptoms. In a pre-and post-closure survey of Chinese university students, the mean
PANAS-NA (negative affect) scale score fell from 2.38 (0.79) to 2.24 (0.80), and the mean
anxiety-depression score on the PHQ-4 scale changed from 0.95 (0.65) to 0.76 (0.61), with
significant reductions in both values. This indicates that there is a significant increase
in anxiety and depression symptoms among students, and the negative effects of school
Buildings 2022, 12, 1873. https://doi.org/10.3390/buildings12111873
https://www.mdpi.com/journal/buildings
Buildings 2022, 12, 1873
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closure are becoming more prominent [8]. The epidemic school closure greatly harms the
mental health of college students and requires urgent interventions.
China has been implementing the “Dynamic Zero-COVID” approach since the pandemic outbreak in 2020. In the context of that, universities in China have also been
undergoing a dynamic lockdown for nearly three years. Because of numerous elements
like Chinese universities offering practically every student housing and the Chinese population figure being relatively significant, Chinese universities also have a higher volume of
students living on campus than foreign universities. Therefore, if no protection measure is
conducted, the virus is more likely to transmit on the Chinese campus and cause a disastrous outcome. Based on all the facts and according to policies in districts, the university
operates in closure, resulting in students being forced to stay in campus walls. During
the closure, students reside in dormitories and can wander around inside the university,
conducting ordinary tasks including studying indoors and playing sports outside, etc. If
needed, medical resources are supplied. This action is temporary, and the campus will be
reopened once the external epidemic is under control. However, we can observe complaints
from students on social media like Weibo, writing about anxiety from long-time closure.
Some mention that their psychological condition gets worse because of the feeling of being
restricted on campus. College students’ mental health is affected by campus lockdown.
However, there is a lack of post-pandemic closure studies with Chinese characteristics. The
current studies globally on epidemic closure mostly focus on two contexts—home isolation
and confinement [4]—whereas there is a lack of discussion on campus lockdown when
students are required to stay in university. In addition, most of the studies focus on the early
stage of the new corona outbreak [3,5], and there is a lack of studies on the normalization
of closure in the post-epidemic period. Furthermore, studies focusing on college students’
mental health during post-pandemic college lockdown are also relatively few; the existing
literature mostly analyses the changes in the psychological state of adolescents [9,10] during
school closure or isolation. Some studies have focused on the psychological changes of
college students [8], but also failed to suggest creative strategies of mitigation.
Existing literature indicates that colour can relieve pressure to some extent. Colour
psychology is a branch of psychological science that believes that colour has various
psychological and behavioural effects [11]. Some psychologists [12] have shown that 83% of
the information humans obtain is from visual sources, and that colour predominates in this
visual information. Extensive research discusses the psychological, cognitive, physiological,
and behavioural effects of colour [13,14]. Some studies indicate the psychological impact of
colour in terms of dynamism, size and quantity, and warmth and coolness [15,16]. Since
each colour has its own wavelength and frequency, when the body absorbs its specific
energy, it might change the original energy in the body. Therefore, colour can be used
for the treatment of physical illnesses and psychological problems [17], which has led
to the concept of colour healing. Colour therapy, derived from colour psychology, is a
technique of psychotherapy that promotes recovery by allowing the patient to see and feel
a colourful environment that causes stimulation of the brain and emotions [18]. Colour has
been found to have features that affect the patients’ physiological activities, emotions in
daily life, cognitive processing, and other changes in mental activity [19]. In addition to the
use of colour in the medical environment, the use of colour as an adjuvant to therapy to
relieve the psychological distress of patients has been increasingly recognized and applied
in existing research [20]. It has been shown [17] that colour therapy can have the same or a
similar effect on any group of people, regardless of the cultural background. It is known
that colour preference could be influenced by differences in age, sex, and geographical
region. Additionally, factor analysis and cluster analysis indicated some relation between
colour preference and the subjects’ lifestyles [21]. For instance, Great Britain has a strong
preference for G categories and a warm-greyish colour image is preferred. Italy has a
preference for R and Y categories and a warm-clear image is preferred [22]. However,
Chinese people have specific colour preferences. For example, black on red signifies
happiness to Chinese people, and therefore the colour combination is commonly used for
Buildings 2022, 12, 1873
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wedding invitations [23]. Red is not only consistently associated with “active,” “hot”, and
“vibrant”, but it also conveys additional meaning (“pleasant”) in China [23]. There are
also some scholars who point out that the “red preference” phenomenon is observed in
Chinese adults. Light colours are preferred the most in terms of chroma-lightness level [24].
Based on all the facts, colour therapy has great potential in reality. However, the current
application of colour healing in China is limited. Although there are now discussions
on the application of colour psychology for campus space design [25], they are failing to
incorporate the current state of college student’s mental health and failing to apply various
theories of colour healing. Therefore, we must consider the possibility of applying colour
therapy in the teaching space to alleviate the anxiety and depression of college students. If
the environmental colours of interior teaching spaces can be used to reduce anxiety and
depression values, it will considerably enhance the mental health of college students.
To assess students’ psychological condition, the HAD scale is used as the measurement
tool. The Hospital Anxiety and Depression Scale (HAD) was created by Zigmond and
Snaith in 1983 to screen for anxiety and depression in general hospital patients. The scale
consists of two separate scales. One is the Hospital Anxiety Scale (HADA) and the other is
the Hospital Depression Scale (HADD). It has been translated into several national versions
and is widely used in medical assessment. There are studies of national versions of the scale,
such as in Spanish [26], Chinese [27], Norwegian [28], and Arabic [29], as well as studies
of applicable populations, such as patients with fibromyalgia syndrome [30], tinnitus [31],
office workers [32], the elderly [27], and patients with oral burning syndrome [33]. In a
Spanish study [30], the subscales “anxiety” and “depression” were evaluated separately,
and both scales were found to be highly reliable and accurate (HADA = 0.80, HADD = 0.85).
Some studies have found that the HAD scale has 80% sensitivity and 90% specificity,
considering it a good screening tool for anxiety and depression in older adults in Cantonesespeaking areas [27]. It has also been suggested that the HAD scale is more useful in
the assessment of depression [31]. A Norwegian study [28] revealed the high internal
consistency of the scale with a substantial sample size (65,648 participants). In summary,
most of the studies corroborate the scientific validity, reliability, and validity of the HAD
scale and therefore support the application of the scale in the assessment of anxiety and
depression in various domains. Yet there are few cases of applying the HAD scale to
research in China, more focus being on particular patients [34,35] and application in the
field of education being neglected. There are no examples of assessing students’ mental
health. Therefore, it is practical and feasible in this paper to apply the HAD scale to assess
anxiety and depression among college students.
The research specifically focuses on college students who must stay inside campus
because of the pandemic prevention policy. The group’s features are quite different from
those who can only stay in the dormitory or those home commuting subjects. Therefore,
this study has its speciality in geography, timing, groups, and so on. This study will
supplement the gap of existing research. Based on the mental health problems of college
students in the post-epidemic school closure normalization, using the HAD scale to assess
the relevant indicators, we lead to conclusions of colour healing to provide a reference for
subsequent space design and psychotherapy. In conclusion, this study aims to provide
references and suggestions for the development of campus teaching space environment
design in the post-epidemic era, and it is also an innovative attempt to intervene in the
mental health of college students from the perspective of colour healing. The following
hypotheses are proposed and tested:
H1. During the closure of colleges and universities due to the epidemic, there is a high prevalence of
anxiety and depression in the college student population.
H2. Neutral, warm, and cold teaching spaces and teaching spaces with adjusted lightness shifts
have different effects on college students’ emotions.
H3. There is a significant difference between different anxious and depressed groups in judging the
effect of teaching space on mood.
Buildings 2022, 12, 1873
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H4. There are significant differences between demographic characteristics in judging the effect of
instructional space on mood.
2. Methods
In this study, a questionnaire was distributed and filled out through the “Questionnaire
Star” platform to collect the subjects’ emotional evaluation of the teaching space with
different colour characteristics. The research idea is shown in Figure 1.
Figure 1. Research scheme.
2.1. Questionnaire Setting
The questionnaire (Appendix A) for this investigation consisted of three parts. Part I:
The subjects were asked about their demographic information, including gender, education,
and major. Part II: The subjects were tested on the Hospital Anxiety and Depression Scale
(HAD scale). The test contains 14 questions (Table 1), and subjects make choices based
on their past week. From the outcomes we obtained the subject’s level of anxiety and
depression. The HAD scale consists of two subscales, anxiety and depression, for anxiety
(A) and depression (D), each with 7 questions. Each item is assessed on a 4-point scale,
with single-sign ratings summing to anxiety ratings and double-sign ratings summing to
depression ratings. A single scale score of 0–7 indicates no depression or anxiety, a total
score of 8–10 indicates possible or “borderline” anxiety and depression, and a total score of
11–20 indicates possible significant anxiety or depression.
Part III: Conducting the observation of virtual teaching spaces with different colour
differences was carried out. In this experiment, two different teaching spaces were used as
prototypes. The initial model was built with Revit 2021 then rendered and post-adjusted
with Lumion 11. According to the variation of hue and lightness, 14 different virtual spaces
are constructed (Figure 2). Immediately after the observation of each set of virtual teaching
spaces, the subjects filled out a questionnaire on the level of pleasure, relaxation, and mental
attention for the scene to obtain their subjective feelings about the pictures. The chromaticity
analysis was conducted to explore the effect of neutral, warm, and cold classrooms on
human emotions. The brightness analysis was conducted to investigate the effect of warm
and cold classrooms on human emotions at both high and low brightness levels. The
reference data is the mean and standard deviation of the questionnaire scores. In the colour
and brightness selection section, three pairs of two-level adjectives, “pleasant/unpleasant”,
“relaxed/unrelaxed” and “focused/unfocused”, were used to evaluate different colour
Buildings 2022, 12, 1873
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teaching spaces. The standard is a 5-point semantic difference, using a scoring system from
1 to 5. The lower the score, the more negative is the emotion.
Table 1. HAD scale.
Title
Options
1. I feel nervous (or painful)
Not at all
Sometimes
Most of the time
Almost all the time
2. I am still interested in the
things I used to be interested in
Definitely the same
Not as much as before
Only a little
Basically no more
3. I felt some fear as if I had a
feeling that something terrible
was going to happen
Not at all
A little, but it doesn’t
bother me
Yes, but not too serious
Very sure and very serious
4. I can laugh and see the funny
side of things
I do this a lot.
I am not so much anymore.
Definitely not too much now
Not at all
5. My heart is full of worries
Occasionally so
From time to time, but
not often
Often
Most of the time
6. I feel happy
Most of the time
Sometimes
Not often.
Not at all
7. I can sit at ease and relax
Affirmation
Frequently
Not often
Not at all
8. I lose interest in my
appearance (dressing)
I still care as much as ever
I may not care very much
Not as caring as I should be
Affirmation
9. I was a little fidgety as if I felt
compelled to move
Not at all
Not much
Quite a bit
A bit too much
indeed
10. I look forward to the future
with a happy heart
Almost like this
It doesn’t quite work that way
Rarely do you do this
Almost never do this
11. I suddenly have a sense
of panic
Not at all
Not often
from time to time
Very often indeed
12. I seem to feel that people
have become dull
Not at all
Sometimes
Very often
Almost all the time
13. I feel a shivering fear
Not at all
Sometimes
Very often
Very often
14. I can enjoy a good book or a
good radio or TV program
Often
Sometimes
Not often
Rarely
2.2. Participants
One hundred and ten participants were recruited to fill out the questionnaire through
the Questionnaire Star platform in April–May 2022. During the period from 11 April to
15 May, most of the subjects were quarantined on campus due to the epidemic closure and
were unable to enter or leave the campus freely.
A total of 110 valid questionnaires were returned in this study, with an effective rate of
100%. The numerical characteristics of the demographic variables can be seen according to
the analysis results in Table 2, which reflect the distribution of the respondents in this survey
and where the mean value represents the trend among them and the standard deviation
represents the fluctuation. According to the results of the frequency analysis of each
variable, it can be seen that the distribution meets the requirements of the sample survey.
For example, among the gender survey results, the proportion of males is 65.5%, and the
proportion of females is 34.5%. This shows that the results of this survey focus on male
colour preference. In terms of academic distribution, the largest category is undergraduates,
including the highest proportion of junior students. In terms of professional distribution,
the highest proportion is engineering students, up to 73.6%, indicating that the subjects are
mainly science and technology students.
Buildings 2022, 12, x FOR PEER REVIEW
Buildings 2022, 12, 1873
6 of 21
6 of 20
Figure 2. Virtual environment modelling of teaching spaces. Note: This computer model is built
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taken from two angles which is of both eyes’ perspective, aiming to offer subjects a more immersive
are taken from two angles which is of both eyes’ perspective, aiming to offer subjects a more imexperience. Since most Chinese classrooms are decorated with coating materials/paint (Figure 3), we
mersive experience. Since most Chinese classrooms are decorated with coating materials/paint
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The
wall
up the most percentage of classroom colour, this time we only picked wall colour as the variation. is
changed
neutral
colour
to warm
andcolour
cold colour.
Then
the lightness
differentof
colours
The
wall isfrom
changed
from
neutral
colourcolour
to warm
and cold
colour.
Then theoflightness
is altered.
different
colours is altered.
Buildings 2022, 12, 1873
7 of 20
Figure 3. Teaching spaces in China (online) [36–42].
Table 2. Frequency analysis of demographic variables.
Variables
Gender
Grade
Category
Options
Frequency
Percentage
Male
Female
Freshman year
Sophomore
Junior
Senior Year
Master
PhD
Other
Humanities and
Social Sciences
Science
Engineering
Medicine
Art Studies
Other
Total
72
38
5
14
39
15
18
18
1
65.5%
34.5%
4.5%
12.7%
35.5%
13.6%
16.4%
16.4%
0.9%
16
14.5%
7
81
2
1
3
110
6.4%
73.6%
1.8%
0.9%
2.7%
100.0%
Crowd
Average Value
Standard
Deviation
1
1.35
0.48
3
4.11
1.89
3
2.76
0.95
2.3. Data Analysis
The data analysis software used for the study was SPSS 27. The reliability validity
of the dependent variables was first examined, and correlation tests were used to assess
whether there was a relationship between the dependent variables, after which the mean
and standard deviation of the data were calculated. A repeated measures ANOVA was
used to assess the effect of differences in the colour of the teaching space environment
on participants’ emotions in that context. A one-way ANOVA was used to test whether
there were significant differences in the emotional perceptions of the teaching environment
space between different anxious and depressed groups. One-way ANOVA was performed
afterwards to test whether there were significant differences in the effects of education and
major on the participants’ emotions; independent samples t-test was used to test whether
there were significant differences in the effects of gender on the participants’ emotions
in the difference of colour in the teaching space. The data obtained were presented in
graphical or tabular form.
2.4. Reliability Validity Test
SPSS 27 was used to implement the process of reliability and validity analysis. First,
we conducted reliability statistics on 14 HAD scale items and 21 questionnaire items
Buildings 2022, 12, 1873
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respectively. It was found that their standard reliability coefficients were 0.907 and 0.925,
which were very close to 1, meaning that the reliability was very high. Then, we conducted
reliability statistics on all the questions in the questionnaire. According to the results of the
reliability analysis of the overall scale, the Cronbach α coefficient based on standardized
items was 0.837. It shows that the analysis results have high reliability. The validity analysis
of the questionnaire was carried out by the test process through the approach of exploratory
factor analysis in SPSS 27. According to the results of the exploratory factor analysis, the
coefficient of the KMO test was 0.823, and the range of the coefficient of the KMO test was
between 0 and 1. The closer to 1, the better is the validity of the questionnaire. According
to the significance of the sphericity test, it can also be concluded that the significance of this
test is infinitely close to 0. The significance is significantly less than 0.005, and the original
hypothesis is rejected, indicating the questionnaire has good validity.
3. Results
3.1. Anxiety-Depression Evaluation
This paper analyses and discusses the results of the “Anxiety” and “Depression”
sub-scales. For the “Anxiety” scale, a score of 7 or below was defined as healthy and
asymptomatic, a score of 8–10 was defined as critical, and a score of 11–20 was defined
as significantly anxious. Of the 110 subjects, 64.5% were healthy and asymptomatic, 20%
were critical, and 15.5% showed serious anxiety symptoms. The “Depression” scale results
were assessed the same way as the “Anxiety” scale. Of the 110 subjects, 68% were in a
healthy state, 20% were in a critical state, and 12% had significant depressive symptoms.
From the data, it can be concluded that more than 30% of the subjects suffered from mild or
significant anxiety or depression, indicating that the phenomenon of anxiety and depression
is prominent in this group which supports the validity of the opening H1.
3.2. The Effect of Colour on Mood
3.2.1. Correlation Analysis of Colour and Mood
According to the results of the correlation analysis presented in Figure 4, it can be
observed that there are significant correlations among all variables. The correlation coefficients of the scores of all variables were more than 0, except for the negative correlation
coefficient of the depression score. So, the anxiety-depression score was negatively correlated with the rest of the hue and lightness scores and positively correlated with the
scores of all the remaining variables. For example, the correlation coefficient between
the anxiety-depression score and the warm colour score is −0.318 **, which means that
they are significantly correlated at the 99% significance level and are negatively correlated.
By analogy, this can explain the correlation between all other variables. The higher the
anxiety-depression value, the lower is the colour score. The higher the hue score, the higher
is the lightness score.
3.2.2. Analysis of the Effect of Colour on Mood
The colours were divided into two parts: hue contrast (neutral, warm, and cold
colours) and brightness contrast. The data in Tables 3 and 4 were scored according to three
emotional criteria: pleasure, relaxation, and focus, as well as the box plots in Figure 5.
According to the sphericity test results, p-value is less than 0.05, and the data does not fulfil
the sphericity hypothesis. Combined with the results obtained from the multivariate test
(p = 0.000), it can be found that the results demonstrate a statistically significant difference
(p < 0.001), indicating that there is a significant difference in the effect of different colour classrooms on mood. This corroborates the validity of H2 at the beginning of this paper. anxiety-depression score and the warm colour score is −0.318 **, which means that they are significantly correlated at the 99% significance level and are negatively correlated. By analogy, this can explain the correlation between all other variables. The higher the anxiBuildingsety-depression 2022, 12, 1873 value, the lower is the colour score. The higher the hue score, the higher is the lightness score. 9 of 20 Figure 4. Correlation test among dimensions. Note: More asterisk “*” imply a stronger correlation. Figure 4. Correlation test among dimensions. Note: More asterisk “*” imply a stronger correlation. Table 3. Colour hue mean and standard deviation. 3.2.2. Analysis of the Effect of Colour on Mood Hue The colours were divided into two parts: hue contrast (neutral, warm, and cold colNeutral Warm Cold ours) and brightness contrast. The M data in Tables SD 3 and 4Mwere scored SD according M to threeSD emotional criteria: pleasure, Pleasant/ relaxation, and focus, as well as the box plots in Figure 5. 2.945 0.887 3.381 0.846 2.954 0.892 According to the sphericity Unpleasanttest results, p-value is less than 0.05, and the data does not Relaxed/ fulfil the sphericity hypothesis. Combined with the results obtained0.795 from the multivariate 2.81 0.869 3.427 3.009 0.914 Unrelaxed test (p = 0.000), it can Focused/ be found that the results demonstrate a statistically significant dif3.063 0.793 3.327 0.779 3.109 0.922 Unfocused that there is a significant difference in the effect of different ference (p < 0.001), indicating Note: OptionsThis are scored on a 5-point scale, scores 1–5of corresponding negative to positive emotions. colour classrooms on mood. corroborates thewith validity H2 at theto beginning of this paper. As can be observed from Table 3, for the three emotional criteria of pleasure, relaxation, As can be observed from Table 3, for the three emotional criteria of pleasure, relaxaand attention, the subjects’ scores all showed with the mean values: warm classroom (WC) tion, and attention, the subjects’ scores showed with the mean warm classroom > cold
classroom
(CC) all
> neutral
classroom
(NC).
Thisvalues:
indicated
that the
healing effect of
(WC) > cold classroom
(CC)
> neutral
classroom
(NC).
This indicated
that the
healing
warm
colours
is greater
than that of
cold colours,
and the healing
effect
of coldefcolours is
greater
than
that
of
neutral
colours.
Combined
with
Table
4,
it
can
be
seen
that
the mean
fect of warm colours is greater than that of cold colours, and the healing effect of cold
values of subjects’ scores showed a trend of warm colour high brightness (WC-H) > cold
colours is greater than that of neutral colours. Combined with Table 4, it can be seen that
colour high brightness (CC-H) > warm colour low brightness (WC-L) > cold colour low
the mean values of subjects’ scores showed a trend of warm colour high brightness (WCH) > cold colour high brightness (CC-H) > warm colour low brightness (WC-L) > cold
Buildings 2022, 12, 1873
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brightness (CC-L), indicating that the healing effect of high brightness is greater than that
of low brightness based on colour hue.
Table 4. Mean and standard deviation of brightness.
Brightness
Pleasant/
Unpleasant
Relaxed/
UnRelaxed
Focus/
Unfocused
Warm
High Brightness
Warm
Low Brightness
Cold
High Brightness
Cold
Low Brightness
M
SD
M
SD
M
SD
M
SD
3.518
0.993
2.981
0.878
3.173
0.876
2.764
1.013
3.554
0.915
3.063
0.827
3.218
0.860
2.754
0.969
3.427
0.893
3.082
0.920
3.255
0.818
2.836
0.934
Figure 5. Box plot of emotion scores. Note: More asterisks “*” imply a stronger correlation.
Warm classrooms have the highest mean value of 3.381 in the “pleasant/unpleasant”
category while cold classrooms do not differ significantly from neutral classrooms. The
difference between the mean scores of warm and cold colours after adjusting the brightness
is large (almost 0.1–0.2 points), and the mean value of 3.518 in warm high-brightness
classrooms even exceeds that of warm classrooms itself. It is clear that warm colours play a
pleasurable role in the emotional state, and higher brightness colours also make the mood
more pleasant.
In the “relaxed/unrelaxed” category, warm colours have a significant relaxation effect,
with a mean value of 3.427. Meanwhile, cold colours have a mean value of almost 0.2
points higher than neutral colours, which is a substantial difference. In terms of brightness,
although the difference was still significant, the difference between the mean value of high
brightness for cold colours and low brightness for warm colours decreased, while the mean
value of low brightness for cool colours dropped to a minimum of 2.754.
Buildings 2022, 12, 1873
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In the “focused/unfocused” category, although the highest mean value was still for
warm colours, the score decreased compared to the previous two moods (3.327). The
difference between the cold and neutral colour classrooms was again not significant. The
mean score for warm high luminosity also declined in this item. Relatively speaking, cold
high luminosity scored 3.255 and it is the highest score among the three moods. The same
is true for cold colours with low luminance, indicating that cool colours are easier to focus
on mentally.
3.3. Different Effectiveness under Demographic Factors
3.3.1. Degree of Anxiety and Depression
Based on the results of the one-way ANOVA in Table 5, it can be seen that among the
seven score dimensions, scores were significantly different across the anxiety population,
as the significance tests were 0.02, 0.013, 0.016, 0.044, and 0.044. However, there was no
significant difference in the cold-coloured low brightness classroom (p = 0.476 > 0.05). This
corroborates the validity of H2 at the beginning of this paper.
Table 5. Results of the differences in the scores of each classroom on the three anxiety populations.
Variables
Neutral colour score
Warm colour score
Cold colour score
Warm colour high
brightness score
Warm colour low
brightness score
Cold colour high
brightness score
Cold colour, low
brightness score
Options
N
Average Value
Standard Deviation
1
2
3
1
2
3
1
2
3
1
2
3
1
2
3
1
2
3
1
2
3
71
22
17
71
22
17
71
22
17
71
22
17
71
22
17
71
22
17
71
22
17
9.04
9.18
7.47
10.46
10.14
8.76
9.28
9.59
7.53
10.87
10.18
9.35
9.28
9.59
7.88
9.65
10.45
8.59
8.35
8.82
7.76
2.12
2.11
2.32
2.2
1.39
2.36
2.44
1.76
2.85
2.37
2.24
2.83
2.36
1.89
2.23
2.42
1.79
2.24
2.7
2.24
3.03
F
Significance
Multiple
Comparisons
4.04
0.02
1 > 3, 2 > 3
4.519
0.013
1 > 3, 2 > 3
4.328
0.016
1 > 3, 2 > 3
2.952
0.057
/
3.214
0.044
1 > 3, 2 > 3
3.216
0.044
2>3
0.747
0.476
/
Note: Where 1 represents people with no anxiety symptoms, 2 represents people with “critical” anxiety symptoms,
and 3 represents people with significant anxiety symptoms. Value in bold means significant.
From the results of the multiple comparisons, it can be seen that, for different groups,
the scores of “people without anxiety symptoms” are higher than those of “people with
severe anxiety symptoms” and the scores of “people with possible anxiety symptoms” were
also higher than those of “people with significant anxiety symptoms”. Therefore, it can be
concluded that the emotional satisfaction of “people with significant anxiety symptoms”
with different colour spaces is significantly lower than that of the other two categories
of anxious people, which is probably due to their high anxiety values. In the cold high
brightness classroom, the scores of those with possible anxiety symptoms were greater than
those with significant anxiety symptoms. Based on this result, it can be seen that “people
with ‘borderline’ anxiety” feel pleasanter with the cold high brightness colour space than
“people with severe anxiety”.
According to the results of the one-way ANOVA in Table 6, it can be seen that among
the seven score dimensions, the three categories of colour classroom scores, neutral colour
Buildings 2022, 12, 1873
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score, warm colour score and warm high brightness, also differed significantly across
depressed populations with significance tests of 0.041, 0.001, and 0.013, respectively, all
significantly smaller than 0.05.
Table 6. Results of the differences in the scores of each classroom on the three depressed populations.
Variables
Neutral colour score
Warm colour score
Cold colour score
Warm colour high
brightness score
Warm colour low
brightness score
Cold colour high
brightness score
Cold colour, low
brightness score
Options
N
Average Value
Standard Deviation
1
2
3
1
2
3
1
2
3
1
2
3
1
2
3
1
2
3
1
2
3
75
22
13
75
22
13
75
22
13
75
22
13
75
22
13
75
22
13
75
22
13
9.04
8.95
7.38
10.57
9.73
8.31
9.33
9.09
7.54
10.93
9.91
9
9.43
8.68
8.15
9.88
9.5
8.54
8.37
8.86
7.38
2.19
1.91
2.4
2.05
2.07
1.97
2.37
2.29
2.9
2.42
2.11
2.58
2.41
1.52
2.51
2.48
1.57
2.26
2.74
2.15
2.96
F
Significance
Multiple
Comparisons
3.29
0.041
1 > 3, 2 > 3
7.35
0.001
1 > 3, 2 > 3
3.053
0.051
/
4.485
0.013
1>3
2.257
0.11
/
1.931
0.15
/
1.272
0.284
/
Note: 1 represents people with no depressive symptoms, 2 represents people with “borderline” depressive
symptoms, and 3 represents people with significant depressive symptoms. Value in bold means significant.
Based on the results of the multiple comparisons, it can be seen that for both the
neutral and warm colour scores, the scores of “people without depression symptoms” and
“people with ‘borderline’ depression symptoms scores were higher than the “people with
significant depression symptoms” scores. It shows that “people with significant depression
symptoms” are significantly less happy with neutral and warm colour spaces than the other
two anxious groups, probably due to their high depression values. The “no depression
symptoms” group scored higher than the “with significant depression symptoms” group
for the high brightness classroom scores of warm colours. Based on this result, it can be
seen that the “non-depressed” group felt pleasanter with the warm, high-light colour space
than the “significantly anxious” group.
3.3.2. Gender
According to the results of the independent samples t-test in Table 7, it can be seen that
there is no significant difference in most of the different colour and brightness classroom
scores by gender, but only in the warm colour high brightness classrooms. The significance
test for the difference between the scores of warm colour high brightness classrooms by
gender is 0.033, which is less than 0.05, indicating that there is a difference in the degree of
preference for warm colour high brightness classrooms among students of different genders.
Based on the mean values, it can be seen that females rated slightly higher than males,
thus females have a higher preference for warm-coloured high-brightness classrooms than
males. The remaining variables are not statistically significantly different in terms of gender
because the significance is greater than the standard 0.05, so the original hypothesis cannot
be rejected.
Buildings 2022, 12, 1873
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Table 7. Analysis of the differences between dimensions in terms of gender.
Variables
Anxiety and Depression score
Neutral colour score (18–20)
Warm colour score (21–23)
Cold colour score (24–26)
Warm colour high brightness score (27–29)
Warm colour low brightness score (30–32)
Cold colour high brightness score (33–35)
Cold colour low brightness score (36–38)
Gender
Number of Cases
Average Value
Standard Deviation
Male
Female
Male
Female
Male
Female
Male
Female
Male
Female
Male
Female
Male
Female
Male
Female
72
38
72
38
72
38
72
38
72
38
72
38
72
38
72
38
13.22
11.32
8.92
8.66
10.03
10.34
9.25
8.74
10.14
11.18
9.11
9.16
9.69
9.55
8.6
7.89
7.575
7.697
2.336
1.963
2.195
2.109
2.281
2.777
2.44
2.381
2.243
2.444
2.329
2.345
2.51
2.911
t
Significance
1.248
0.215
0.583
0.561
−0.724
0.471
1.039
0.301
−2.155
0.033
−0.101
0.92
0.303
0.763
1.32
0.19
Note: Bold means significant.
3.3.3. Education Background
We divided the education into undergraduate and master’s degrees for comparison
and the majors into science and non-science disciplines for analysis. According to the
results of the one-way ANOVA in Tables 8 and 9, it can be seen that because the significance
is greater than the standard 0.05 for all, there is no significant difference in each dimension
score in both education and major, so the original hypothesis cannot be rejected. That
means, there is no significant difference in judging the influence of teaching space on
emotion among different academic majors, and the opening H4 is overturned.
Table 8. Results of the variance analysis of each dimension in terms of education.
Variables
Anxiety and Depression score
Neutral colour score (18–20)
Warm colour score (21–23)
Cold colour score (24–26)
Warm colour high brightness
score (27–29)
Warm colour low brightness
score (30–32)
Cold colour high brightness
score (33–35)
Cold colour low brightness
score (36–38)
Options
N
Average Value
Standard Deviation
Undergraduate
Master’s degree
Undergraduate
Master’s degree
Undergraduate
Master’s degree
Undergraduate
Master’s degree
Undergraduate
Master’s degree
Undergraduate
Master’s degree
Undergraduate
Master’s degree
Undergraduate
Master’s degree
73
37
73
37
73
37
73
37
73
37
73
37
73
37
73
37
12.79
12.11
9.03
8.43
10.07
10.27
9.03
9.16
10.77
9.97
9.08
9.22
9.64
9.65
8.4
8.27
7.636
7.724
2.134
2.328
2.03
2.423
2.374
2.662
2.378
2.566
2.139
2.626
2.33
2.348
2.454
3.07
F
Significance Multiple Comparisons
0.197
0.658
/
1.795
0.183
/
0.213
0.646
/
0.073
0.788
/
2.597
0.11
/
0.082
0.775
/
0
0.992
/
0.055
0.814
/
Table 9. Results of the analysis of the differences between the dimensions in terms of profession.
Variables
Options
N
Average Value
Standard Deviation
Anxiety and Depression
score
Non-Scientific
Science and
Engineering
Non-Scientific
Science and
Engineering
Non-Scientific
Science and
Engineering
Non-Scientific
Science and
Engineering
Non-Scientific
Science and
Engineering
Non-Scientific
Science and
Engineering
22
11.91
8.28
88
12.73
7.509
22
9.14
2.315
88
8.75
2.188
22
10.73
2.492
88
9.99
2.059
22
9.05
2.968
88
9.08
2.34
22
11.09
2.348
88
10.35
2.478
22
9.36
2.498
88
9.07
2.263
Neutral colour score
(18–20)
Warm colour score
(21–23)
Cold colour score
(24–26)
Warm colour high
brightness score (27–29)
Warm colour low
brightness score (30–32)
F
Significance
Multiple Comparisons
0.201
0.655
/
0.536
0.466
/
2.077
0.152
/
0.003
0.954
/
1.596
0.209
/
0.288
0.593
/
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Table 9. Cont.
Variables
Options
N
Average Value
Standard Deviation
Cold colour high
brightness score (33–35)
Non-Scientific
Science and
Engineering
Non-Scientific
Science and
Engineering
22
9.82
2.954
88
9.6
2.158
22
8.77
3.038
88
8.25
2.57
Cold colour low
brightness score (36–38)
F
Significance
Multiple Comparisons
0.151
0.699
/
0.676
0.413
/
According to the analysis of the results, the different demographic variables do not
differ significantly in judging the influence of teaching space on emotions, overturning the
opening H4.
4. Discussion
4.1. Anxiety and Depression
There has been some investigations about the effects of quarantine on psychology. One
study [43] compared psychological outcomes during quarantine with later outcomes and
found that during quarantine, 7% (126 of 1656) showed anxiety symptoms. A study [44] of
hospital staff who might have come into contact with SARS found that immediately after the
quarantine period (9 days) ended, having been quarantined was the factor most predictive
of symptoms of acute stress disorder. Some scholars did a review [4] of the psychological
impact of quarantine using three electronic databases. Most reviewed studies reported negative psychological effects including post-traumatic stress symptoms, confusion, and anger.
And conclusion 1, indicating prominent anxiety and depression among college students
during campus lockdown, is in accord with existing findings. However, one study [45]
compared undergraduates who had been quarantined with those not quarantined immediately after the quarantine period and found no significant difference between the groups in
terms of post-traumatic stress symptoms or general mental health problems. Although this
is inconsistent with our conclusion 1, it provides a new perspective for our future research,
which can compare the students’ psychological state before and after lockdown.
4.2. Colour and Mood
Though no research has revealed a one-to-one relationship between mood and colour [46], it
is believed that different colours have corresponding emotional preferences and different
degrees of health effects [47]. For example, warm colours stimulate the spirits and help
relieve depression, while cool colours are more calming and relaxing for nerv-ousness [48,
49]. Conclusion 2 agrees with the basic theories of colour psychology. In addition, in the
view of colour psychology, colours with higher brightness are more popular than those with
lower brightness. Conclusion 2 verifies this theory and is consistent with prior studies [50].
The study of Costa Marco et al. [50] on the colour of college students’ dorm rooms indicated
that blue interior spaces facilitate various learning activities and make it easier for students
to be calm and concentrated. Chong Gao et al. [51] found that patients with depression
symptoms find it harder to recover when in blue interior spaces, compared with white
and warm interior spaces. Yildirim et al. [52] in their study of living room colours also
showed that warm colours were highly stimulating to evoke mood, while cool colours
were more associated with “expanding space” and “resting”. Bilal et al. [53] suggest that
neutral colours, such as grey, can reduce the feeling of pleasure for guests in hotel rooms.
Thus conclusion 3 correlates with existing studies.
In addition, existing studies related to colour psychology have indicated that there
are significant differences in colour preferences between genders. For example, Costa
Marco et al. [50] discovered substantial disparities between men and women in their preference for blue and purple dormitory spaces. Al-Rasheed [54] concluded that gender-specific
preferences for colour exist in both Arabic and English cultural circles, with men preferring
blue green. However, conclusion 4 is not fully consistent with the existing studies. In
addition to gender, other studies focused on demographic elements such as age and income,
Buildings 2022, 12, 1873
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like Cho [55] who identified substantial disparities in household income and age in terms
of satisfaction with the interior colours of luxury stores.
4.3. Limitation
In addition, there are some limitations in this study.
This study is based on a relatively homogeneous geographical and cultural background, with subjects mostly coming from college students in Harbin, China, who are
enrolled in universities with excellent academic reputations and good public images. In
other regions, traits like language, lifestyle, weather, and ethnic background are all different. Comparison studies on different regions in China can be supplemented in the future.
Additionally, this study mainly collected questionnaires during the school closure period.
In future investigation, the range of subjects could be further expanded. A wide variety
of students such as home commuting students, resident students, and even senior/junior
students could also be considered.
This paper used the HAD scale to assess and classify the subjects’ anxiety and depression symptoms. Future studies can increase the psychological assessment dimensions
(e.g., the combination of multiple scales) to increase the credibility and accuracy of the
evaluation. Apart from that, this study focused on the subjective feelings of the subjects,
so the data obtained are subjective emotions. In the future, the physiological indicators
of the subjects can be monitored and analysed in conjunction with real-life experiments.
Moreover, only three emotional criteria, “pleasant/unpleasant”, “relaxed/unrelaxed”,
and “focused/unfocused”, were selected for evaluation, and there were few emotional
indicators. Future studies can add emotional indicators to improve the evaluation.
In this study, for the sake of the controllability of the experiment and the accuracy of
the results, other environmental components that affect indoor colour (e.g., light [56,57],
furniture, material, etc.) were not discussed. Future studies may try to add relevant
elements as variables to increase the exploration of more dimensions of colour in indoor
teaching spaces. Furthermore, three hues and two kinds of lightness were selected for
the study. The classification was simple and lacked specific colour values for support.
In future, studies can take more colours and more colour dimensions (e.g., grey scale)
into consideration, apply more detailed and specific classification methods, and combine
colour parameters.
5. Conclusions
In this paper, a study was conducted on the emotional impact of environmental colour
on college students in the indoor teaching space during the epidemic closure through a
questionnaire survey method. The conclusions are as follows:
1.
2.
3.
In the context of the “Dynamic Zero-Covid” policy, constant campus lockdown leads
to prominent anxiety and depression among college students. More than 30% of the
subject group suffered from mild or significant anxiety or depressive symptoms.
Chinese college students have colour preferences in teaching spaces. In the three
teaching spaces of warm, cold, and neutral colours, warm colours have an advantage over both cold and neutral colours in creating pleasure, relaxation, and mental
focus. Among the three types of teaching spaces, neutral colours provide the worst
experience in terms of obtaining a positive mood. It is concluded that warm-coloured
classrooms are more healing than cold-coloured classrooms, and cold-coloured classrooms are more healing than neutral-coloured classrooms. With the same colour hue,
high brightness classrooms tend to have better healing effects than low brightness
classrooms. The results might correlate with the Chinese colour preference for red
and light colours.
There is a correlation between the teaching space colour score and the level of anxiety
and depression of the subjects. When subjects have higher degrees of anxiety and
depression, they are less satisfied with the colour of the teaching space. There are
Buildings 2022, 12, 1873
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4.
some differences in the experiences of people with different anxiety and depression
symptoms in different colours of teaching spaces.
In most cases, there is no significant difference in the colour preference of teaching
spaces between the gender groups. However, there is a significant difference between
males and females in warm high-brightness teaching spaces, with females having
a higher preference for warm high-brightness classrooms than males. There is no
significant difference in colour preference of teaching space among the different
education groups.
Author Contributions: Conceptualization, Y.W. and W.T.; methodology, Y.W. and W.T.; software,
W.L.; validation, W.T. and W.L.; formal analysis, W.T.; investigation, W.T. and W.L.; resources, W.T.
and W.L.; data curation, W.L.; writing—original draft preparation, W.T. and W.L.; writing—review
and editing, W.T., Y.W. and W.L.; visualization, W.L.; supervision, Y.W. and F.L.; project administration, W.T.; funding acquisition, F.L. All authors have read and agreed to the published version of
the manuscript.
Funding: The research was funded by [the Ministry of Science and Technology of China] grant
number [G2021179030L].
Conflicts of Interest: The authors declare no conflict of interest.
Appendix A
Table A1. The Colour Evaluation Questionnaire of Teaching Spaces.
1. Your gender is ( )
2. Your current grade is ( )
3. Your major category is ( )
Male
Female
Freshman
Sophomore
Junior year
Master’s
degree
Doctor
Others
Humanities and
Social
Sciences
Natural
Sciences
Engineering
Senior year
Grade five
Medicine
Arts
Others
4–17. HAD Scale (Table 1)
Please observe photo group 1 carefully and answer questions 18–20 truthfully according to your feelings
18. This set of photos makes you feel ( )
19. This set of photos makes you feel ( )
20. This set of photos makes you feel ( )
very
unpleasant
very
unrelaxed
very
unfocused
unpleasant
general
pleasure
unrelaxed
general
relaxed
unfocused
general
focused
very
pleasant
very
relaxed
very
focused
Buildings 2022, 12, 1873
17 of 20
Table A1. Cont.
Please observe photo group 2 carefully and answer questions 21–23 truthfully according to your feelings
21. This set of photos makes you feel ( )
22. This set of photos makes you feel ( )
23. This set of photos makes you feel ( )
very
unpleasant
very
unrelaxed
very
unfocused
unpleasant
general
pleasure
unrelaxed
general
relaxed
unfocused
general
focused
very
pleasant
very
relaxed
very
focused
Please observe photo group 3 carefully and answer questions 24–26 truthfully according to your feelings
24. This set of photos makes you feel ( )
25. This set of photos makes you feel ( )
26. This set of photos makes you feel ( )
very
unpleasant
very
unrelaxed
very
unfocused
unpleasant
general
pleasure
unrelaxed
general
relaxed
unfocused
general
focused
very
pleasant
very
relaxed
very
focused
Please observe photo group 4 carefully and answer questions 27–29 truthfully according to your feelings
27. This set of photos makes you feel ( )
28. This set of photos makes you feel ( )
29. This set of photos makes you feel ( )
very
unpleasant
very
unrelaxed
very
unfocused
unpleasant
general
pleasure
unrelaxed
general
relaxed
unfocused
general
focused
very
pleasant
very
relaxed
very
focused
Buildings 2022, 12, 1873
18 of 20
Table A1. Cont.
Please observe photo group 5 carefully and answer questions 30–32 truthfully according to your feelings
30. This set of photos makes you feel ( )
31. This set of photos makes you feel ( )
32. This set of photos makes you feel ( )
very
unpleasant
very
unrelaxed
very
unfocused
unpleasant
general
pleasure
unrelaxed
general
relaxed
unfocused
general
focused
very
pleasant
very
relaxed
very
focused
Please observe photo group 1 carefully and answer questions 33–35 truthfully according to your feelings
33. This set of photos makes you feel ( )
34. This set of photos makes you feel ( )
35. This set of photos makes you feel ( )
very
unpleasant
very
unrelaxed
very
unfocused
unpleasant
general
pleasure
unrelaxed
general
relaxed
unfocused
general
focused
very
pleasant
very
relaxed
very
focused
Please observe photo group 1 carefully and answer questions 36–38 truthfully according to your feelings
36. This set of photos makes you feel ( )
37. This set of photos makes you feel ( )
38. This set of photos makes you feel ( )
very
unpleasant
very
unrelaxed
very
unfocused
unpleasant
general
pleasure
unrelaxed
general
relaxed
unfocused
general
focused
very
pleasant
very
relaxed
very
focused
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Reproduced with permission of copyright owner. Further reproduction
prohibited without permission.
Tiiu Poldma, Ph.D.
Université de Montréal
ABSTRACT
Interior environments and their design are profoundly influenced by how designers integrate
color and light with form and space. In our increasingly global world, new lighting
technologies are changing our perception of color and light and subsequently our interrelationships with one another and with interior space. This alters the choices that we have
as designers when we make both color and light decisions. Traditional light and color
theories are being challenged with new lighting approaches that are complex, dynamic,
and that are changing people’s immediate experiences within spaces. Currently, new light
technologies alter our perceptual relationships with people and forms, as light, its spectral
color, and the forms its affects are more interactive and modulated in real time.
Usually, in interior design coursework, students learn about color and light as static
theories that they are then asked to apply within the interior design of spaces in subsequent
design studios. Through a presentation and examination of the course “Color and Light
in Interior Design,” this paper proposes considering integrating color and light theories
with new contexts of dynamic, integrated human experiences of color and light in interior
space. Students acquire learning experiences that integrate theory and practice by understanding the complex interrelationships of light, color, and objects in interior spaces as
interactive, and by exploring design concepts in actual environments as a laboratory
where they can test theories and their own ideas. The course structure is described and
the theories underlying the course goals are explored. Color and light theories are considered in the context of emerging technologies and how phenomenological approaches
affect our perceptions and experiences in spaces. Student examples of two of the four course
projects are presented as these put theories into practice. The discussion shows that light
and color theory, when explored in this way, stimulates both comprehensive and creative
responses that integrate new technology with aesthetic theory and functional aspects of
well-designed light/color solutions. The integrating of practice into theory stimulates reflective
thinking and an understanding of situated contexts in interior design problem solving. The
course develops emerging necessities of understanding dynamic color/light concepts
that contribute to broadening interior design applied knowledge.
The control of light has aspects that are
both functional … and expressive, the latter
considerably predating the former. That is,
long before studies were conducted on taskperformance, ocular fatigue, and seasonal
affective disorder, light served in the manipulation of spatial effect. (p. 250)
Introduction
Light and color are ephemeral aspects of designing interior environments. They mediate space and add life
and texture to the spaces we inhabit. However, usually light and color concepts are taught separately in
interior design courses. If we consider light as a design
element, Malnar and Vodvarka (1992) suggest that
light is first and foremost a design element to be controlled and used primarily for spatial effect:
Journal of Interior Design
While light does create spatial effects, it does not
exist without light’s own spectral emission acting
on objects and environments that we experience and
19
© Copyright 2009, Interior Design Educators Council,
Journal of Interior Design 34(2)
19391668, 2009, 2, Downloaded from https://onlinelibrary.wiley.com/doi/10.1111/j.1939-1668.2008.01017.x by Csu – Northridge, Wiley Online Library on [16/02/2023]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License
Learning the Dynamic Processes of Color
and Light in Interior Design
POLDMA
To be able to understand the theories of color and light in the practice of interior design,
we need to learn the concepts of color and light as integral to the design process.
integrate the more subjective and dynamic aspects of
color/light interactions or how light and color are integral design elements in the earliest design process
stages and not necessarily only applied elements introduced after planning may already be completed.
receive through our vision and perception. Light and
color work together with form and spatial effect to
modulate interior space, add drama and intrigue,
help us in our daily tasks, or set the mood or scene for
various types of activities. All subjectively enhance our
responses within interiors while objectively satisfying
visual and functional needs.
These experiences and color/light dynamic relationships are explored in a baccalaureate second year
theory course entitled Color and Light in Interior
Design. Students put theory into practice with projects that theorize the issues using pragmatic interior
space situations and where they can experiment
directly with the effects of color on light and vice
versa. The classroom process is one of theory examination, application into practice, and then reflection back in theory on both the practices explored
and the critical ideas that become understood in
learning by doing.
To be able to understand the theories of color and
light in the practice of interior design, we need to
learn the concepts of color and light as integral to the
design process. This means understanding how light
and color intersect in the interior environment in the
earliest design stages. We also need to experience the
actual interactions between color and light as dynamic and sensual and to understand how the artistic, psychological, perceptual or dynamic aspects of light and
color principles are actualized in real settings. How
does the color/light interrelationship form the perceptions that we have of our interior environments as we
experience spaces actively or in movement? How can
we use ideas learned in color and light theory to stimulate first concepts in design thinking? How can we
integrate new concepts about emerging dynamic aspects of light into current curriculum practices?
We cannot ignore how color and light intersect and
what theories and concepts might be omitted when
these theories are taught as separate design foundations.
By integrating the two and moving the theory into
practice immediately through theory course exercises,
students learn how they can affect designed space
through color and light integration and how they can
design concepts with light and color.
This paper argues for an integration of new ways of
dealing with dynamic light–color relationships in
interior spatial designs. Dynamic and situated color
and light concepts can be taught using both theory
and real-time exploration within actual environments
of different scales. Too often light and color elements
and theories are taught in separate courses or might
be treated as separate design features within spaces.
For example, students might learn theories about light
as objective performance-related tasks, physical properties, and systems applications through calculations
and engineering practices. They may also study color
theories and principles and learn to select and apply
color using materials and finishes. The pedagogical
goals in both cases include (and certainly are not limited to) developing an understanding of how to manipulate interior spaces through the application of the
theoretical concepts. However, students also need to
acquire skills that allow them to understand how to
Journal of Interior Design
The Theoretical Framework
Contexts of Learning Color and Light: About
Theory and Practice
The interior design of spaces is the result of a pragmatic
mix of design problem solving, design process thinking,
and the integration of various technical processes
that add depth and analysis to the design problem. An
integral part of these processes is the integration of
light, color, form, and material into the creation of
interior design concepts. Quite often teachers are
frustrated in the design studio, as students tend to
add the color and light elements toward the end of the
design process as applied and separate design elements, rather than introduce these elements earlier
20
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Number 2
2009
19391668, 2009, 2, Downloaded from https://onlinelibrary.wiley.com/doi/10.1111/j.1939-1668.2008.01017.x by Csu – Northridge, Wiley Online Library on [16/02/2023]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License
COLOR AND LIGHT IN INTERIOR DESIGN
POLDMA
When design theories such as light or color are taught as separate theoretical entities, then
students apply the principles separately as well.
during the creative idea generation stage or as integral components of the spatial organization elements
within the design (Poldma, in press). To make matters worse, students often give priority to studio
courses at the expense of learning theory or technical
subjects and often have different motives for learning
theory course content altogether. As Fontein (1997)
suggests, this is due in part to the nature of theory
courses themselves:
Table 1 shows a traditional model of fundamental
concepts of light and concepts as they might be
learned in separate theory classes.
When design theories such as light or color are taught
as separate theoretical entities, then students apply
the principles separately as well: we select luminaires
and lighting systems or we choose materials and
colors for walls and ceilings and objects within spaces. Subsequently, students learn to deal with light and
color as separate entities that they apply into spaces
when they design the interiors in design studios and
too often after the spaces are already conceived.
In contrast to the dynamic situation of the design studio, the support courses follow a more
conventional lecture format. … The students
tend to put their best energy into the studio
project and have little time for their other
courses. The technology courses are often perceived as providing information that places
limitations upon the impulses. … (p. 179)
The Dynamic Nature of Color and Light in
Interior Space
By contrast, the actual experience of the interior space
is dynamic. The idea of an interior as “dynamic”
means that people move constantly within spaces
with experiences that are bound in their immediate
and perceptual experience of that space in a series
of moments that are not static (Merleau-Ponty,
1945/1958; Rewi, 2005). People navigate interior
Learning about color and light theory often falls within this type of theory class format, and light and color
are often treated as separate theoretical concepts altogether. On the one hand, lighting theory might emphasize physical properties of light and lighting calculations,
lighting systems, and luminaire selection procedures
(Cuttle, 2003; Gordon, 2003; Karlen & Benya, 2004;
Kellogg-Smith & Bertolone, 1986; Winchip, 2005).
On the other hand, color theory is often taught by presenting color wheels, color contrasts, and various color
chips or materials arranged together to demonstrate
these concepts in applied interior situations. Color
theories inform students about the properties of color,
spectral values, and the differences between pigmented
or spectral color in color theory and may also include
how physiological, cultural, or psychological contexts
affect human perception (Birren, 1978, 1997; Pile,
1997; Poore, 1994; Sargent, 1964). Learning about
color theory in color courses and light theory in lighting courses means that there is no interactive means to
see how these theoretical concepts are applied together
within the lived experiences within interior spaces.
Furthermore, students benefit from the real-time experience of the actual effects of these properties in real
settings, where they can see how light and object color
relationships intersect and affect perception, form
modulation, or spatial manipulation (Winchip, 2005,
pp. 107–119).
Journal of Interior Design
Table 1. Traditional model of a theory course using
the fundamental concepts of light and color
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COLOR AND LIGHT IN INTERIOR DESIGN
POLDMA
People experience both light and color as a series of multiple, complex, interrelated
concepts and spaces, and these experiences are subjective.
space and respond to it through a series of quick impressions that are received and acted upon based on
the various changing conditions of the space itself.
Dynamic conditions include how natural light moves
from day to night, how restaurants might change atmosphere from lunch to dinner, and how colorchanging lighting can enhance every movement we
make or change color at different times we program
into computer software using light-emitting diodes
(LEDs), often within a few seconds. As Miller (1997)
suggests, this means that applying traditional light or
color theories can be tricky, as these are often based
on predicting through decision and application:
The Human Aspect of Color and Light
Interrelationships in Interior Space
We cannot know how people will react to, and
ultimately experience, the space. The human element
is unpredictable and we need to factor this into the
learning experience. How the space is actually used
by people is as important as how we design the interior as a space. Let’s consider the example of color
and light selection for an institutional environment.
When colors are selected, for example, for a design
concept, they are usually chosen without accounting
for the lighting conditions, the lighting proposal, or
the added human dimension of the occupied space.
They are often selected based on studies of best practices or science that supports a particular reaction to
a particular color. Alternatively, the lighting requirements for the same space might include choosing a
lighting “system,” which is installed using lighting
calculations and systems selections without considering
materials beyond their reflectance values (and these
usually only in terms of walls, floors, or ceilings). We
then select colors considering the surrounding spaces
and their features, often without considering the effects
of the light spectral color or the active movement of
people and equipment. It is important to understand
how to consider the more dynamic aspects of the
space to be used by considering the “real, lived space.”
Mahnke and Mahnke (1993) suggest that choosing
colors for an institutional environment must include
understanding the reality of the “lived space”:
Each interior is unique because of variability
of both light conditions and the reflective
qualities of materials. Interactions between
color, light and materials make predicting
how color will appear on an interior surface
a risky undertaking at best. Color decisions
therefore, cannot be based on formulas or
rigid guidelines; ultimately, they are a matter
of the designer’s intuition based on skill and
experience. (p. 117)
Risky because unless we can predict how lighting and
color choices will be experienced, we cannot know how
the particular combinations that we select will be accepted by the users. People experience both light and
color as a series of multiple, complex, interrelated concepts and spaces, and these experiences are subjective.
We also experience the space alone or with other people,
clothes, and other objects that add color and texture to
the designed environment and change our best “predictions.” As designers we must also make choices that
might be considered somewhat intuitive, as we must be
able to combine color and material with lighting choices
to conceive of interior concepts coherently, while doing
so for an unpredictable user: people. Light properties
and physics, color in light, and color pigment all interact
with our perceptual responses, while reflectance of materials, color of both material, and light source interact
with space and form to produce sensations that we experience (Miller, 1997, pp. 117–118). As designers, we
must develop a feel for choosing how these elements interact with forms and spaces through intuitive decisions
as much as rational ones.
Journal of Interior Design
With large areas, such as corridors, a common
mistake is choosing color and pattern for an
empty space. Let us assume a hypothetical
situation. A designer is asked to design a hospital corridor … a logical step would be to
add interest … in the form of designs or patterns on the walls, or maybe different-colored
wall sections … in attention producing hues…
… This plan would have impact and be aesthetically pleasing. … But now let us add
people to that corridor—nurses, busily going
about their tasks, carts and equipment being
pulled from one area to another, unsteady patients trying to navigate a path. The once-empty
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COLOR AND LIGHT IN INTERIOR DESIGN
POLDMA
Color and light can be viewed as a network of interrelated concepts that translate into
experiences we perceive and respond to when we navigate space.
corridor … abounds in pattern, activity and
visual information. … (p. 87)
Second, while we move in and through spaces and
experience interior environments, we do so over time
and in space during all hours of the day and night.
Our circadian rhythms are affected by our exposure
to spectral (colored) light and the more variety and
the more supportive the lighting conditions are, the
more apt we are to be positively affected by our environment (Mahnke, 1996; Poldma & Wesolkowska,
2005). Light does more to affect our senses than material choices alone, and we react to the combinations
of light and color that we experience immediately.
Material contrasts, spatial forms, material reflections,
and a multitude of dynamic changes occur when
we put color, light, material, and space interactively together, affecting both our physical movements
and our psychological and physiological responses
(Mahnke, 1996; Malnar & Vodvarka, 1992; MerleauPonty, 1945/1958).
While Mahnke and Mahnke (1993) point out the issues that arise when we forget the dynamics of the
space, their example limits the discussion to considerations of color selection only. And yet, lighting
also affects the color choices made, the movement of
people, and the problems of glare produced by the
fluorescent light from ceilings bouncing off the floor.
Current research shows that too many different
color–light contrasts and effects add to incidents of
falling and prevent people from adequately
negotiating pathways—in particular in regard to
poorly integrated light and color conditions in institutional corridors in elder-care institutions and hospitals (Poldma, 2004, 2006; Poldma & Samuelson,
2004). As Mahnke and Mahnke (1993) suggest, the
added dimensions of people, equipment, and multiple elements such as color–light interrelationships
are all considerations that need to be made and that
make the interior space a dynamic and lived place
that changes at all times of the day and night.
A Phenomenological Approach to
Color and Light
When color and light act well together, this creates an
emotional resonance with the user and perceptually
adds to a positive spatial experience, while satisfying
the functional and situational needs within the space;
when color and light are incoherent, people fall, materials are poorly deciphered, and people may reject
the space altogether.
On a more subjective and personal level, our perceptions of color and light are mediated by our subjective reactions to the forms and spaces we experience
in real time. These experiences are also affected by
the sum total of objects and people who also move
within the space as active agents that transform our
visual perception in the phenomenological sense
(Merleau-Ponty, 1945/1958; Miller, 1997). We see
and experience interior environments in real time and
through our simultaneous responses to light, color
relationships, others we see within the space, the multiple sensual experiences that we have as we move
through the space, and what cues we are given by the
interaction of the color and light with forms, visual,
and focal elements that guide us (Cuttle, 2003; Mahnke,
1996). Color and light can be viewed as a network of
interrelated concepts that translate into experiences
we perceive and respond to when we navigate space.
Each one of us has a different and subjective response
as we move in and around spaces. This is an essentially phenomenological stance, wherein the immediate sensual and physiological responses to color,
How Do Light and Color Intersect Actively
With Spaces and People?
Light and color intersect with people and within space
in several ways. First, the physical forms of the space
modulate light as it leaves the source, while materials
and their reflective properties modulate the reflected
color of the light through the object that captures the
light. This lit environment mediates both subtractive
and additive color interrelationships. The color of
light interacts with the color of all the interior elements, including materials, people, objects, and accessories (Miller, 1997; Winchip, 2005, 2007).
Journal of Interior Design
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COLOR AND LIGHT IN INTERIOR DESIGN
POLDMA
We move through a space in real time, responding subjectively or physiologically to the
color/light/form interrelationships as simultaneous (and not static) experiences.
form, and light ambiances and effects occur in realtime, lived experiences.
Not only do we “perceive” light and then objects and
space, we simultaneously interact with the light and its
color effects as we perceive the surrounding environment (Merleau-Ponty, 1945/1958). A “quality-lit environment” simultaneously supports human activities
and needs and excites and mediates human use of
space, while satisfying psychological, social, temporal,
and physical functions (Winchip, 2005). These perceptual and emotional responses to the lit interior environment are in part, what give the environment its
dynamic characteristics.
If we consider a phenomenological view of color, for
example, this means that we cannot “s…
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