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- Publisher
- Taylor & Francis
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- © 2022 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group on behalf of the Architectural Institute of Japan, Architectural Institute of Korea and Architectural Society of China.
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- 1347-2852
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- 1346-7581
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- 10.1080/13467581.2022.2074022
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Abstract
JOURNAL OF ASIAN ARCHITECTURE AND BUILDING ENGINEERING https://doi.org/10.1080/13467581.2022.2074022 Housing design during COVID-19: effects of psychological states on Japanese architecture students Hanui Yu and Risa Fujii Department of Architecture, Graduate school of Science and Technology for Future Life, Tokyo Denki University, Tokyo, Japan ABSTRACT ARTICLE HISTORY Received 2 March 2022 During the coronavirus disease (COVID-19) pandemic, people worldwide were psychologically Accepted 2 May 2022 affected by being limited to mostly indoor, at-home activities. This study sought to clarify how COVID-19-related psychological states and anxiety affect changes in designs and perceptions KEYWORDS of living environments. Hence, this study assigned a housing design task to architecture Architectural design; eco students – considerations included windows (window-to-wall ratio), lighting plan, color plan, design; architectural and floor area – and conducted a survey regarding the related deliverables. The results showed environment; perception; that anxiety about going out affected perceptions of openness and publicity, whereas fear of psychology of design COVID-19 infection affected impressions of space, brightness, and naturalness. These psycho- logical effects are reflected in the total floor area, window area, and color planning. These effects reveal how the psychological state of the designer affects the spatial elements in architectural design. Abbreviations: SD method - Semantic differential method SD - Standard deviation WWR - Window-to-wall ratio Df value – Degrees of freedom value 1. Introduction a significant psychological impact (Amerio et al. 2020; Motohashi and Matsuoka 2020; Rossi et al. 2020; The restrictions on going out due to the coronavirus Tsamakis et al. 2020). For example, for many, having to disease (COVID-19) pandemic have forced people in stay home all day has been reported to worsen family many countries to stay home and have had CONTACT Hanui Yu hnwind@hotmail.com Department of Architecture, Graduate school of Science and Technology for Future Life, Tokyo Denki University, 5 Senju Asahi-cho, Adachi-ku, Tokyo 120-8551, Japan © 2022 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group on behalf of the Architectural Institute of Japan, Architectural Institute of Korea and Architectural Society of China. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 2 H. YU AND R. FUJII relationships (the pandemic increased domestic vio- evidence to suggest that housing is important for psy- lence calls by 7.5% between March and May 2020 in chological health, particularly in children (Evans, Wells, Japan) (Leslie and Wilson 2020). Additionally, loneliness and Moch 2003). In addition, user preferences for hous- increased in people living by themselves who did not ing have become increasingly complex in recent years see anyone else (Berg-Weger and Morley 2020; Henry as the lifestyles of occupants have rapidly changed. In 2020). Furthermore, some people developed immense housing, especially in large houses that are not custom- anxiety about going out and now find it challenging to designed to meet the needs of individual occupants, leave their homes. Furthermore, the cramped housing discrepancies between occupants’ living needs and conditions in Japan’s major cities are commonly cited as design occur at various levels (Wong 2010). These stu- a major problem (Motohashi and Matsuoka 2020). dies show a profound link between housing and quality Previous studies have predicted that the coronavirus of life, and we need to understand the psychological outbreak will require changes in cities and construction consequences that people have experienced in the con- environments (Sharifi and Khavarian-Garmsir 2020) that text of the COVID-19 pandemic and the factors they look emphasize COVID-19 infection prevention (Megahed and for in the design of their living environment. Ghoneim 2020). Future housing designs are also pre- Prior research has emphasized the role of learning dicted to change after the COVID-19 pandemic in the design process for architecture students, the (Megahed and Ghoneim 2020), but there is a lack of target population of this study (Atman et al. 1999). clear evidence to support these predictions. Therefore, it Students who are beginning to learn design must is necessary to clarify which aspects of the COVID-19 also learn methods and develop thoughts on how to pandemic have affected housing designers. create designs, which largely reflects the students’ social context and psychological states. Thus far, no study has focused on the relationship between the social and psychological states of designers 1.1. Impact of the COVID-19 pandemic on and their designs. However, much research has been changes to housing requirements and the conducted on the psychological environmental effects psychological state of designers of windows, color planning, lighting, and color tempera- As mentioned above, throughout the COVID-19 pan- ture. Studies have investigated how spatial openings demic, people needed to reconsider how they live. affect people, including their psychological responses to Particularly significant changes in daily life include windowless environments (for instance, Hollister (1968) increased time spent at home and a new mix of private mentioned another investigator who examined employ- and public spaces due to teleworking (Okubo 2020). ees of factories in Thuringia and found a higher amount Going forward, these lifestyle transitions are expected of sick leave due to colds, stomach disorders, and nervous to result in significant changes in the functional disorders in windowless factories); whether general levels requirements for housing. In response to these social of lighting, sunlight transmission and visibility can miti- adjustments, changes in housing design are expected gate the negative effects of work stress; the direct and from developers and designers (Oxman 2004; Razzouk indirect effects of workplace windows on work satisfac- and Shute 2012). tion and general well-being (Leather et al. 1998); and There has been considerable research on housing children’s behavior and health in classrooms with and and health. To date, however, there is no general con- without windows (Küller and Lindsten 1992). sensus on the definition of a “healthy home,” and sig- Regarding the relationship between lighting, color nificant gaps remain in our knowledge of how housing temperature, and psychology, the effect of the color conditions affect health. Some studies have explored temperature of the light source on mental activity level the relationship between housing conditions and has been investigated; it was found that simple reaction health, focusing on mental health, sleep quality, indoor times were more active at a color temperature of 7500 K air quality, home safety, accessibility, obesity, mold than 3000 K (Deguchi and Sato 1992). Additionally, growth, damp heat conditions, energy consumption, regarding the relationship between student learning and perceptions of crime as important factors affecting and lighting, focus lighting led to a higher percentage housing quality. It is clear that housing is complex and of oral reading fluency performance (36%) than control housing design involves consideration of various fac- lighting (17%) (Mott et al. 2012). Regarding the effect of tors, including air quality, sound environment, safety, color on emotions, powerful and consistent effects of and neighborhood environment (Bonnefoy 2007). In saturation and brightness on emotions were demon- addition, a critical review of the existing research strated (Valdez and Mehrabian 1994). It has also been on housing and mental health, taking reported that color and colored environments affect into account housing type (e.g., single-family vs. multi- moods and emotions and produce negative or positive family housing), floor height, and housing quality (e.g., perceptions of a given environment or task (Jalil, Yunus, in terms of structural damage), presents sufficient and Said 2012). JOURNAL OF ASIAN ARCHITECTURE AND BUILDING ENGINEERING 3 From July 8 to 29 July 2020, once a week, the 1.2. Hypotheses and purpose authors gave an introductory lecture to the partici- This study aimed to examine how changes in the living pants. The contents of the lecture were designed to environment due to the COVID-19 pandemic and fear convey only a basic knowledge of housing design. The related to infectious diseases have affected housing lecture described the concepts of space volume, win- designs. It aimed to determine the physical and psy- dow planning, natural light planning, lighting, color chological factors for analysis based on student temperature, interior (interior materials, coloring), fur- designs and survey results. Thus, the following four niture, and small items. On August 24, participants hypotheses were formulated. were asked to give a design presentation after attend- ●Hypothesis 1: Comparing the pre-pandemic and ing a tutorial. To mitigate the potential influence of pandemic periods, there is a difference in the impact a tutor, the tutorial was conducted with the sole pur- on people’s lives, such as increased living time at pose of preventing design mistakes due to the partici- home. pants being students. In other words, the authors ●Hypothesis 2: The COVID-19 pandemic has impli- respected the concept and design of the participants cations for current designs of housing, such as the size and carried out esquisses (preliminary sketches). of the space and the feeling of openness. The participants made their models from August 24 ●Hypothesis 3: The COVID-19 pandemic has influ - to 27 (S = 1:30) and submitted the final design propo- enced indoor color planning, lighting design, and color sals (A3, 1–2 pages). Between August 27 and 29, parti- temperature design. cipants completed a questionnaire (see later in this ●Hypothesis 4: The changes in lifestyles and work section) on their design proposals using an online caused by the COVID-19 pandemic have affected the survey tool (Google Forms). The questionnaire took feeling of openness due to the number and design of about 40 minutes. For the statistical analysis, JMP13.0 windows and the overall size of rooms and spaces. (SAS Institute Inc.) software was used. The level of statistical significance (p) was set to 0.05 and 0.01. The influence of participants’ psychological states on 2. Materials and methods their designs was evaluated by analyzing the design 2.1. Participants proposals and survey results using t-tests, analysis of variance (ANOVA), correlation analysis, and χ tests. The participants of this study were 28 students (12 women, mean age = 18.5, SD = 0.74, aged 18– 21 years) of the Department of Architecture at a uni- 2.3. Housing design versity in Tokyo, Japan. Because 28 of the 40 students Housing planning and design had the following con- who participated in the class answered the question- ditions. Participants were asked to create a concept, naire (response rate of 70%), the data of 28 students drawn design, color design, lighting design, window were analyzed. Since the onset of the COVID-19 pan- design, furniture layout, and small items layout under demic, the university has conducted mostly online the theme of the house in which they would like to classes, although there are in-person classes for some live. The house volume was limited to 250–300 m . subjects. However, this study targeted students who The following contents were included in the final participated only in fully online classes. This study was design proposal submissions (A3, 1–2 pages): title, conducted according to a protocol approved by Tokyo concept of housing design, color scheme, material, Denki University. All participants provided informed lighting design, furniture layout, total floor area and consent before the study began. window area calculation, plan, cross-sectional view (S = 1:30), development view (including window area), 1–2 external model photos, and 4–5 interior 2.2. Procedure model photos that convey the concept well. Housing planning, design, and questionnaires were used to investigate the effects of changes in the living 2.4. Questionnaire environment and anxiety related to infection on hous- ing design associated with the spread of coronavirus The questionnaire items are shown in Table 1. The infection. As no housing designs before COVID-19 survey items were divided into seven categories: Q1. were available, it was impossible to directly compare Current situation related to COVID-19; Q2. Activity time the contents of housing designs during COVID-19 with and sleeping time in a house before and during COVID- prior examples. Therefore, self-reported information 19; Q3. Housing design title; Q4. Lighting equipment about the participants’ psychological states and life- and color temperature plan; Q5. Space evaluation in style patterns before and after the pandemic were design using the 7-level semantic differential (SD) investigated. All processes were conducted online method; Q6. Window area and total floor area; and using Zoom. Q7. Function of space. 4 H. YU AND R. FUJII Table 1. Questionnaire items, contents, and options. Survey items Survey contents and options Q1. Current situation related to COVID-19 1–1. I am fearful of COVID-19 infection 1–2. I am anxious about attending university 1–3. I am anxious about going out 1–4. I am anxious about meeting my friends in person 1–5. Anxiety disorder due to COVID-19 *The response options for items 1–1 to 1–5 were (1) disagree, (2) neither, and (3) agree. Q2. Activity time and sleeping time in a house How did your time staying at home (including sleep times) change before and during COVID-19? before and during COVID-19 2–1. Weekdays 2–2. Weekends How did your sleep time at home change before and during COVID-19? 2–3. Weekdays 2–4. Weekends *The options from 2–1 to 2–4 are as follows: (1) < 6 h, (2) 6–8 h, (3) 8–10 h, (4) 10–12 h, (5) 12–18 h, (6) 18 h or more. 2–5. Did your sleep quality change during COVID-19 compared with before COVID-19? ※ The response options for item 2–5 were (1) change, (2) neither, (3) no change. In the following examples, list the items in order of highest to lowest number of hours spent on each activity every day 2–6. Before COVID-19 2–7. After COVID-19 ※ The examples used in 2–5 and 2–6 are as follows: (1) Activities of daily living (rest, meals, etc.) (2) Sleep (3) Learning at school or cram school(face-to-face) (4) Personal learning (study, assignments, etc.) (5) Online learning (classes, studies, assignments, etc.) (6) Hobbies (dynamic: weight training, aerobic exercise, etc.) (7) Hobbies (static: reading, watching videos, etc.) (8) Interacting with others online Q3. Housing design title 3–1. Tell me the title of the housing design. Q4. Lighting equipment and color temperature 4–1. Select all the lighting fixtures used in each space. plan (1) Bracket light (2) Ceiling light (3) Chandelier (4) Downlight (5) Spotlight (6) Atrium light (7) Pendant light (8) Floor stand light (9) Task light (10) Footlight (11) Others 4–2. Select all the color temperatures of the lighting used in each space. (1) 3000 K (2) 3500 K (3) 4200 K (4) 5000 K (5) 6500 K Q5. Space evaluation in design using the 7-level 5–1. A feeling of being closed-in–A feeling of openness SD method 5–2. Narrow–Wide (Spacious) 5–3. Dark–Bright 5–4. Warm image–Cool image 5–5. Quiet–Lively 5–6. Cramped–Cozy and relaxed 5–7. Unnatural feeling–Natural feeling 5–8. Private–Public * A 7-point Likert scale was used for the first item of each pair of descriptions: (1) strong feeling (2) general feeling (3) some feeling (4) neutral or neither agree nor disagree, AND for the second item of each pair(5) some feeling (6) general feeling (7) strong feeling Q6. Window area and total floor area Tell me the area (m ) of the walls and windows close to each direction. 6–1. South 6–2. East 6–3. North 6–4. West 6–5. Ceiling wall. Q7. Function of space 7–1. Awareness of introducing daylight 7–2. Ventilation considerations 7–3. Awareness of the connection with the outside world *The options from 7–1 to 7–3 are (1) disagree or (2) agree All surveys were conducted during the COVID-19 (American Society of Heating 2004; Athalye et al. 2013; pandemic. Since Q2ʹs staying time and sleeping pat- O’Connor et al. 1997). Therefore, in this study, the WWR tern before COVID-19 are lifestyle-related, it was was used to investigate its relationship with psycholo- assumed that the measurement during COVID-19 was gical factors. The equation of the WWR is as fol- within a range of time that they could remember lows (Eq. 1): accurately and that effective results could be obtained. Total window area WWRð%Þ ¼ � 100% (1) Total wall area Six types of WWRs were used in this study: the East 2.5. Definition of terms WWR, West WWR, South WWR, North WWR, Ceiling WWR, and Total WWR (all five directions combined). 2.5.1. Window-to-wall ratio The window-to-wall ratio (WWR) was defined as the ratio of the total window area to the total exterior wall 2.5.2. CIE 1976 L*u*v* color space area. The WWR is mainly used as a reference formula The CIE defined the CIELUV uniform color space in for energy consumption accounting for daylighting 1976. Since the components are L*, u*, and v*, it is controls, visible transmittance and glazing reduction called CIE1976L*u*v* and it is used to indicate color JOURNAL OF ASIAN ARCHITECTURE AND BUILDING ENGINEERING 5 difference (International Organization for 3. Results Standardization 2009). Symbols and abbreviated 3.1. Hypothesis 1: impact of COVID-19 on terms are as follows: people’s lives X, Y, Z tristimulus values of a test stimulus calculated using the color- 3.1.1. Stay-at-home times and sleep times matching functions of the CIE 1931 standard colorimetric system (also known as the CIE 2° standard colorimetric The difference in participants’ stay-at-home times on system) 2 weekdays [χ = 33.07, df = 5, p< 0.01] and stay-at- Y tristimulus value, Y, of a specified white color stimulus calculated using the color-matching functions of the CIE 1931 home times on weekends [χ = 24.49, df = 5, p< 0.01] standard colorimetric system showed a significant difference before and during L* CIELUV lightness COVID-19. During the COVID-19 pandemic, the stay-at- u*, v* CIELUV u*, v* coordinates u′, v CIE 1976 chromaticity coordinates home period increased by more than six hours on week- 0 0 days and about five hours on weekends compared with CIE 1976 chromaticity coordinates of a specified white stimulus u ; v n n before COVID-19. However, there was no significant difference between sleep times on weekdays To analyze the psychological evaluation according [χ = 2.62, df = 3, p = 0.45] and sleep times on weekends to the color plan of the space, the base color, sub color, [χ = 4.22, df = 4, p = 0.38] before and during COVID-19. and accent color used in the housing design were used The ANOVA of changes in sleep times and sleep in the final design submitted. Using Photoshop CC quality before and during COVID-19 indicated that 2019 (Adobe), the RGB, V and C of the base color, sub there was no significant difference between before color, and accent color were extracted. By substituting COVID-19 on weekdays [χ = 8.05, df = 6, p = 0.23], RGB in Equation 2 (Fairman, Brill, and Hemmendinger during COVID-19 on weekdays [χ = 4.35, df = 6, 1997) to obtain X, Y, and Z and substituting X, Y, and p = 0.63], before COVID-19 on weekends [χ = 2.58, Z in Equations 3 and 4 (ISO, 2009) to obtain u and v, L*, df = 4, p = 0.63], and during COVID-19 on weekends u*, and v* were calculated using Equations 5, 6, and 7, [χ = 7.58, df = 8, p= 0.48]. These results confirm that respectively (Fairman, Brill, and Hemmendinger 1997). 0 sleep times and quality were not affected by COVID-19. Y, u′, and v′ describe the test color stimulus and Y , u , Figures 1 and 2 illustrate the differences in stay-at- and v describe a specified white stimulus in these home times and in activity contents before and during formulae: COVID-19. Figure 1 shows the differences in stay-at- 0 1 0 1 0 1 home times before and during COVID-19 on weekdays X 2:76883 1:75171 1:13014 R and weekends. The proportion of respondents who @ A @ A @ A Y ¼ 1:00000 4:59061 0:06007 � G stayed home longer than 18 hours during COVID-19 Z 0:00000 0:05651 5:59417 B on both weekdays and weekends was high. (2) Figure 2 shows the differences in activities before and during COVID-19. Participants were ranked from 4X the most time spent to the least time spent among the u ¼ (3) X þ 15Y þ 3Z eight activities presented. Among the rankings of the eight items, the highest-ranked activity was given 6 points, the second-highest was given 3 points and the 9X v ¼ (4) third-highest was given 2 points, as shown in Figure 2. X þ 15Y þ 3Z The results indicate significant differences in overall activity before and during COVID-19 [χ = 169.26, L ¼ 116ðY=Y Þ 16 (5) df = 7, p < 0.01], although there were no changes in the activities of daily living (rest, meals, etc.), sleep, and Where hobbies (static). However, personal learning (study, � � � � � � � � = 3 Y Y Y 6 assignments, etc.), online learning (classes, studies, f = ¼ = if = > = Y Y Y 29 n n n assignments, etc.), and interacting with others online fðY=Y Þ ¼ ðY=Y Þ ifðY=Y Þ >ð6=29Þ increased significantly, while dynamic hobbies and n n n learning at school (online or in-person) decreased significantly. fðY=Y Þ ¼ ð841=108ÞðY=Y Þþ 4=29ifðY=Y Þ n n n � ð6=29Þ 3.1.2. Feeling fearful about COVID-19 Infection and anxiety about going out The relationship between feeling fearful of COVID-19 � � 0 0 u ¼ 13L u u (6) infection and going out indicated no significant differ - ence [χ = 7.86, df = 4, p = 0.10] (proportions shown in � � 0 0 Figure 3). However, the results indicated that most of v ¼ 13L v v (7) the participants felt fearful and anxious. 6 H. YU AND R. FUJII Figure 1. Differences in stay-at-home-times before and during COVID-19, according to weekdays and weekends. Figure 2. Differences in activities before and during COVID-19. Figure 3. The proportion of participants feeling fearful of COVID-19 infection and anxiety about going out. A χ test was conducted to investigate the effects weekdays and weekends before and during COVID- of feeling fearful of COVID-19 infection and anxiety 19, but no significant difference between stay-at- about going out according to stay-at-home times and home times and feeling fearful of COVID-19 infection. sleep times on weekdays and weekends. There was There was little difference between weekdays a significant difference between stay-at-home times and weekends. Participants who were not anxious on weekdays [χ = 27.41, df = 6, p < 0.01] and week- about going out on weekdays and weekends spent ends [χ = 27.48, df = 8, p< 0.01] during COVID-19 and 11 hours at home, while participants who were anxiety about going out. There was no significant anxious about going out had a sharp increase in difference in the other items. There was also stay-at-home-times to around 18 hours. a significant difference in stay-at-home times on JOURNAL OF ASIAN ARCHITECTURE AND BUILDING ENGINEERING 7 Figure 5 shows a benefit portfolio illustrating the 3.2. Hypothesis 2: effect of COVID-19 on housing relationship with the design concept, based on the space design relationship between the contrasting pair “a feeling 3.2.1. Housing space design concept and of openness–a feeling of being closed-in” and the psychological evaluation pair “private–public” having the highest correlation of Figure 4 shows the results of the psychological evaluation the psychological evaluation items in Table 2. according to the design image of housing space. More There was an approximately equal correlation than 50% of the participants reported that they used between the paired items for the design concepts of wide spaces, warm images, “cozy and relaxed” elements, “public space with a feeling of openness,” “private “a feeling of openness,” brightness, spaces with an “unna- space with a feeling of openness,” and “private space tural feeling,” and “private” and “quiet” spaces. with a feeling of being closed-in.” By contrast, there Correlation analysis was used to determine the was a difference in the average number of spaces for associations between the psychological evaluation each feature of the space. items, as shown in Table 2. In this study, Spearman’s rank correlation coefficient was used as defined by 3.2.2. Items affected by the COVID-19 situation and Rovai, Baker, and Ponton (2013). There was psychological evaluation a correlation of r = 0.6 for “a feeling of being closed- Table 3 shows the results of the ANOVA of the psycholo- in–a feeling of openness, and private–public.” gical evaluation items according to how they were “Narrow–wide, cramped–cozy and relaxed,” “dark– affected by the COVID-19 situation. The more fearful of bright, warm image–cool image,” “dark–bright, unna- COVID-19 infection the participant was, the greater the tural feeling–natural feeling” and “quiet–lively, pri- tendency for a “warm image” [F(2,25) = 3.78, p = 0.04]. vate–public” showed low correlations (r = 0.3–0.5). Figure 4. Results of the psychological evaluation according to the design image of housing space. Table 2. Psychological evaluation according to the design image of housing space: correlations and descriptive statistics (r = Spearman’s rank correlation coefficient). Variables 1 2 3 4 5 6 7 8 1. A feeling of being closed-in–A feeling of openness 1 2. Narrow–Wide 0.27 1 3. Dark–Bright 0.03 0.10 1 4. Warm image–Cool image −0.08 −0.29 0.32 1 5. Quiet–Lively 0.14 −0.19 0.13 −0.01 1 6. Cramped–Cozy and relaxed 0.06 0.35 0.07 0.06 0.20 1 7. Unnatural feeling–Natural feeling 0.03 −0.13 0.47* 0.10 −0.05 0.01 1 8. Private–Public 0.60** −0.02 −0.02 0.11 0.31 −0.03 −0.02 1 *Significant at p≤ 0.05, **Significant at p ≤ 0.01. Bold = r > 0.3 8 H. YU AND R. FUJII Figure 5. Relationship between “a feeling of openness–a feeling of being closed-in”/“private–public” and the design concept. Table 3. ANOVA for the SD method by the items affected by the COVID-19 situation. Fearful of COVID-19 About attending Anxiety about Meeting my friends Anxiety disorder due to Source infection university going out in person COVID-19 A feeling of being closed-in–A 0.75 1.20 4.13* 6.55* 1.50 feeling of openness Narrow–Wide 2.22 1.13 0.66 0.21 1.20 Dark–Bright 1.73 1.16 1.39 0.33 1.31 Warm image–Cool image 3.78* 1.46 1.07 0.19 0.29 Quiet–Lively 1.79 1.58 1.54 1.93 2.36 Cramped–Cozy and relaxed 0.98 0.06 1.92 0.002 1.35 Unnatural feeling–Natural feeling 0.52 4.74* 0.16 1.17 1.12 Private–Public 0.48 0.66 5.12* 0.13 1.75 *Significant at p≤ 0.05, **Significant at p ≤ 0.01. The more strongly they felt “about attending university,” 3.2.3. Design situational awareness and the more their designs tended toward spaces with “nat- a psychological evaluation of housing space ural feeling” [F(2,25) = 3.78, p = 0.04]. People who had no Student’s t-test was used to investigate the relation- anxiety about going out tended to design with “a feeling ship with the psychological evaluation according to of openness” [F(2,25) = 4.74, p = 0.02], but those who had the presence or absence of design situational anxiety about going out designed spaces that felt more awareness of the housing space. The more “aware- private [F(2,25) = 5.12, p = 0.01]. Furthermore, people ness of introducing daylight” there was, the more who wanted to meet with friends in person created the “quiet” tendency appeared [t(26) = −2.41, designs with a feeling of openness [F(2,25) = 6.55, p = 0.02]. The more “awareness of the connection p = 0.02]. with the outside world” there was, the more JOURNAL OF ASIAN ARCHITECTURE AND BUILDING ENGINEERING 9 participants tended to design a “natural feeling” [t participants felt. The higher the L* [F(1,26) = 6.29, (26) = 2.32, p = 0.03]. The analysis of the relation- p = 0.02] and V [F(1,26) = 4.27, p = 0.05] of the base ship between the number of windows and WWR is color, the more the feeling of being “cozy and shown in later in this section. relaxed” decreased. Conversely, the higher the base color C was, the more “cozy and relaxed” they felt [F(1,26) = 6.51, p = 0.02]. Meanwhile, as 3.3. Hypothesis 3: color planning and the the V of the sub color increased, the “feeling of influence of lighting and color temperature being closed-in” rose [F(1,26) = 4.54, p = 0.04] and as the C of the sub color increased, the more space 3.3.1. Color planning and psychological evaluation felt “narrow” [F(1,26) = 10.73, p< 0.01]. of the space Figure 6 shows the box plot of the L* values of In this study, brightness was analyzed using L* and the base color, sub color, and accent color used in the color distribution was identified using a u*v* the design of the housing space. L* is psychometric chromaticity diagram. Table 4 shows the results of lightness, which is used as an index of brightness; the psychological evaluation by L* (psychometric the higher the value, the brighter the color. The L* lightness), V (Value), and C (Chroma), analyzed values of the base color came out high, whereas the using ANOVA. The results indicate that the higher L* values of the sub color and accent color L* [F(1,26) = 6.46, p = 0.02] and V [F(1,26) = 8.29, were low. p< 0.01] of the base color, the “brighter” Table 4. ANOVA for the SD method by L*, V, and C. L* (Psychometric lightness) V (Value) C (Chroma) Base Sub Base Sub Base Source color color Accent color color color Accent color color Sub color Accent color A feeling of being closed-in–A feeling of openness 0.93 1.86 1.16 0.44 4.54* 1.01 2.10 0.01 0.04 Narrow–Wide 1.52 0.01 0.004 1.06 1.01 0.03 0.99 10.73** 0.14 Dark–Bright 6.46* 0.56 0.31 8.26** 0.22 0.57 3.54 0.12 0.19 Warm image–Cool image 0.44 0.49 0.01 0.37 0.45 0.10 0.31 0.04 0.65 Quiet–Lively 0.003 2.49 0.41 0.03 3.32 0.22 0.93 0.43 0.27 Cramped–Cozy and relaxed 6.29* 3.27 0.26 4.27* 1.74 0.52 6.51* 3.92 0.19 Unnatural feeling–Natural feeling 0.65 0.49 0.16 0.86 0.31 0.01 0.14 0.08 0.21 Private–Public 0.80 0.30 0.11 0.77 0.49 0.09 2.76 2.15 0.01 *Significant at p≤ 0.05, **Significant at p ≤ 0.01. Figure 6. Box plot of the L* values of the base color, sub color, and accent color. 10 H. YU AND R. FUJII Figure 7. Scatterplot of u*v* (a) base color, (b) sub color, (c) accent color. Figure 7 shows the scatterplot of the u*v* of the and when the color temperature was higher, it felt base colors, sub colors, and accent colors used to “brighter” (Figure 8(a)). This study also found design the housing space. This is a color mixing system a significant difference for “warm image” in the results where u* indicates red, -u* indicates green, v* indicates [F(4,73) = 7.04, p< 0.01]. In other words, it confirmed yellow, and -v* indicates blue. The vertex protruding to that the color temperature of the lighting was reduced the right of the line in the graph corresponds to the red to produce a “warm image” in the space (Figure 8(b)). (R = 1, G = B = 0) of RGB and represents yellow, green, Figure 9 shows the correspondence analysis of the cyan, blue, and magenta in anticlockwise order. The data on the types of lighting fixtures and color tempera- center where the six lines intersect (u* = v* = 0) corre- tures. The 10 types of lighting fixtures in Table 1 were sponds to black and white, indicating achromatic col- broadly classified into general and specific lighting. In this ors. The further away from this center point, the more study, “specific lighting” refers primarily to the specific vivid the color becomes. lighting used in houses, but it also includes some task As shown in the results for the base color u*v*in lighting. The results of the correspondence analysis Figure 7(a), the base colors were primarily bright or low showed that color temperatures of 3500 K, 4200 K, and saturation. As shown in the results for the sub color 5000 K tended to be used mainly in general lighting. In u*v*in Figure 7(b), the sub colors were primarily brown addition, color temperatures of 3000 K and 6500 K were produced using specific lighting. As such, 3000 K and and beige and created using wood. As shown in the 6500 K, which are extremely low and high color tempera- result for the accent color u*v*in Figure 7(c), the accent tures, respectively, created a point within a space through colors tended to have relatively high saturation and var- specific lighting. ious colors were used to create a focal point within the space. 3.4. Hypothesis 4: effect of windows and total 3.3.2. Lighting and color temperature and floor area psychological evaluation 3.4.1. Gender and window design The results of the psychological evaluation by color The results of the analysis using Student’s t-test to temperature were analyzed using ANOVA, showing confirm the differences in the WWR and number of a significant difference from the results for “bright” [F windows by gender in the housing design showed (4,73) = 2.92, p = 0.03]. In other words, “bright” was a significant difference in the South WWR [t expressed using the color temperature of the lighting Figure 8. Relationship between color temperatures and the psychological evaluation of the lighting used in the actual design; (a) dark–bright, (b) warm image–cool image. JOURNAL OF ASIAN ARCHITECTURE AND BUILDING ENGINEERING 11 Figure 9. Results of the correspondence analysis between lighting types and color temperatures. Figure 10. WWR by gender; (a) South WWR, (b) sum of all the WWRs. (26) = −2.51, p = 0.02] and the sum of all the WWRs [t not significant, with men having a higher sum of all the (26) = 2.44, p = 0.02]. The Cohen’s d values for the WWR values than women. This indicates that the men South WWR and sum of all the WWRs were 0.98 and actively designed windows on the south side. 0.99, respectively. Figure 10 shows the results of the South WWR (Figure 10(a)) and sum of all the WWRs 3.4.2. Window design and psychological evaluation (Figure 10(b)) by gender in the housing design. Men The Shapiro–Wilk W normality test satisfied all the nor- had a higher South WWR and sum of all the WWRs than mality conditions. Therefore, ANOVA was used to inves- women. tigate the effect of the COVID-19 situation on the WWR In Figure 10, to understand the characteristics of the design. The less “fearful of COVID-19 infection,” the difference in the South WWR and the sum of all the greater the participants’ North WWR [F(2,25) = 4.44, WWRs between men and women, the values for these p = 0.02]. The more they wanted to know “about attend- ratios and number of windows were used, as shown in ing university,” the greater the North WWR [F(2,25) = 5.07, Figure 11. According to the results for the South WWR in p = 0.01]. When the sum of all the WWRs was greater, it Figure 11(a,b), women tended to design fewer than three led to higher “anxiety about going out” [F(2,25) = 3.49, windows. By contrast, for men, the South WWR tended p = 0.05]. to decrease as the number of windows increased, but the Table 5 shows the ANOVA results used to investigate overall number was higher than that of women. In the the effect of the psychological evaluation results on the sum of all the WWR results in Figure 11(c,d), the differ - WWR and number of windows. The results show the ence in the number of windows for women and men was significant difference between the East WWR and 12 H. YU AND R. FUJII Figure 11. WWR for the number of windows; (a) South WWR, women, (b) South WWR, men, (c) sum of all the WWRs, women, (d) sum of all the WWRs, men. Table 5. ANOVA for the WWR and number of windows. South East North West Ceiling Sum of all Orientation Number of Source WWR WWR WWR WWR WWR WWR Windows A feeling of being closed-in–A feeling of 0.21 2.20 1.24 0.17 0.002 2.60 0.49 openness Narrow–Wide 1.06 0.004 0.004 0.19 0.002 0.04 0.75 Dark–Bright 0.23 2.61 4.25* 0.27 0.79 1.08 1.88 Warm image–Cool image 0.30 0.45 7.76** 0.32 0.78 2.53 0.17 Quiet–Lively 1.05 1.05 2.52 0.92 1.11 1.84 3.28* Cramped–Cozy and relaxed 0.35 0.48 0.26 0.75 2.17 1.04 1.33 Unnatural feeling–Natural feeling 0.002 8.70** 0.01 1.26 2.97 0.19 1.12 Private–Public 0.04 1.10 0.85 0.00 0.81 2.38 0.71 *Significant at p≤ 0.05, **Significant at p≤ 0.01. “natural feeling” [F(1,26) = 8.70, p< 0.01]. There was a sig- [F(1,26) = 9.43, p< 0.01]. Thus, the larger the total floor area, the larger the South WWR. Additionally, nificant difference between the North WWR and “bright” a significant difference was observed in the effect of [F(1,26) = 4.25, p = 0.05] and between the North WWR the total floor area depending on the number of win- and “warm image” [F(1,26) = 7.76, p< 0.01]. In other dows [F(3,24) = 8.49, p< 0.01]. Figure 12 shows that the words, the larger the North WWR, the brighter the hous- smaller the number of windows, the larger the total ing design and warmer the image. The number of win- floor area. dows and psychological evaluation showed a significant difference with “quiet” [F(3,24) = 3.28, p = 0.04]. 3.5. Summary of the results 3.4.3. Total floor area and psychological evaluation Figure 13 summarizes the results, showing that the The ANOVA indicated that the less “anxiety about two factors that influence the housing design in the going out,” the larger the total floor area [F COVID-19 state were “anxiety about going out” and (2,25) = 3.45, p = 0.05]. Furthermore, total floor area feeling “fearful of COVID-19 infection.” and “cozy and relaxed” [F(1,26) = 5.40, p = 0.03], and total floor area and “public” [F(1,26) = 4.14, p = 0.05] 3.5.1. Anxiety about going out showed significant differences. Anxiety about going out was related to the amount of time spent at home, and the more the participants felt 3.4.4. Total floor area and window design anxious about going out, the longer they stayed at home. The ANOVA used to investigate the effect of windows This anxiety also correlated with greater feelings of being according to the total floor area showed a significant closed-in and thus, the design of more private spaces. By difference for the total floor area and the South WWR contrast, when architecture students did not feel anxious JOURNAL OF ASIAN ARCHITECTURE AND BUILDING ENGINEERING 13 Figure 12. Total floor area and the number of windows. Figure 13. Relationship between anxiety and housing design during COVID-19. about going out, their designs reflected a feeling of open- 3.5.2. Fearful of COVID-19 infection ness and used more public spaces. When their answers When participants were “fearful of COVID-19 infec- indicated they wanted to meet their friends “in person,” tion,” they designed spaces with warm images; con- they designed “a feeling of openness” space. versely, when they were not “fearful of COVID-19 Additionally, when designing “a feeling of being infection,” they designed a space with a cold image. closed-in” space, the V of the sub color used was When participants answered “I want to” about attend- high, suggesting that V was designed high to secure ing university, the final design indicated their “aware- a certain degree of brightness. In the case of “public” ness of the connection with the outside world” to and “cozy and relaxed” designs, the total floor area provide a natural feeling. Additionally, if they indicated increased. The larger the total floor area, the a willingness to “attend university” and were not “fear- larger the South WWR and the fewer the number of ful of COVID-19 infection,” they designed the North windows. WWR to be larger. 14 H. YU AND R. FUJII “Anxiety about going out” and feeling “fearful of Greater “anxiety about going out” corresponded with COVID-19 infection” acted independently of each more designs for privacy; feeling “fearful of COVID-19 other. “Anxiety about going out” was found to affect infection” corresponded with designs intended to cre- mainly “a feeling of being closed-in–a feeling of open- ate a feeling of warmth. This study also confirmed that ness” and “public–private,” whereas feeling “fearful of the more the participants had an “awareness of intro- COVID-19 infection” affected mainly “warm image–cool ducing daylight,” the quieter their design, while the image,” “dark–brightness” and “unnatural feeling–nat- more “awareness of the connection with the outside ural feeling.” In addition, “anxiety about going out” and world,” the more natural feeling there was in their feeling “fearful of COVID-19 infection” affected the psy- design. chology when designing the space, and this reflected To test Hypothesis 3, this study investigated how the total floor area, window size, base color, sub color the coronavirus situation affects indoor color planning and connection with the outside world. and the design of lighting and color temperature. When designing the brightness at the time of color planning the space, it is expressed using the base 4. Discussion color, and brown and beige wood colors were used Our research is an integrated analysis of psychological as the sub color. Wooden houses, which are part of states through actual housing design proposals and traditional Japanese architecture, are popular with a questionnaire survey that aimed to provide more Japanese people. According to Japan’s Ministry of accurate results based on qualitative and quantitative Land, Infrastructure, Transport and Tourism (2020), data. This study clarified how psychological states and the construction ratio of new wooden houses (%) has anxiety caused by COVID-19 affect changes in living not changed significantly in the last 20 years. In parti- environments and their design. To test Hypothesis 1, it cular, it was found that the preference for wooden examined the impact of living during the COVID-19 houses reached an average of 51.5% (SD = 3.4) over pandemic compared with the pre-pandemic period. the last four years. Therefore, as it has been used for The mental health of the public is affected by the a long time, it was presumed that Japanese people COVID-19 pandemic, with young people’s anxiety prefer to use wood, which has an intimate and men- higher than that of older people (Huang and Zhao tally soothing effect (2021). 2020). Therefore, it was observed that young college The brightness of the space was expressed using students, who were the participants in this study, felt a higher color temperature in the lighting, consistent a great deal of anxiety, and the result was also reflected with the results of a previous study (Yu et al. 2015) that in the housing designs. In particular, staying at home reported that a higher color temperature makes because of the COVID-19 pandemic was shown to affect a space feel brighter. By contrast, a lower color tem- mental health and lifestyle habits (Ammar et al. 2020). perature was found to create a warm image in the In prior studies, in terms of sleep quality, most space. participants over 18 years old reported that their The most used color temperature was that of gen- sleep quality had deteriorated (Ammar et al. 2020; eral lighting. An extremely low or high color tempera- Losada-Baltar et al. 2020), and there was a high prob- ture created a focal point using specific lighting. We ability that sleep quality for COVID-related medical investigated whether the change in living habits workers has decreased (Huang and Zhao 2020). according to the COVID-19 situation, as proposed in However, since this study was conducted on college Hypothesis 4, affects the WWR, number of windows, students, no change in sleep quality was observed. and total floor area of the house. Men’s South WWR The results of this study showed that stay-at-home and the sum of all the WWRs were higher than the times increased during COVID-19 compared with WWR for women, indicating that men design more before. In addition, although basic living activities, windows than women. sleep time, and sleep quality did not change, dynamic In addition, the less the designer was “fearful of activities were confirmed to have decreased, such as COVID-19 infection” and the greater the North WWR changing from in-person learning to online learning. was, the more likely they were to look into “attend- Our results also confirmed that time spent at home ing university.” This result could be due to how affected participants’ “anxiety about going out” more many students arranged workrooms and study than feeling “fearful of COVID-19 infection.” rooms in the north. Conversely, the sum of all the To test Hypothesis 2, this study investigated the WWRs was greater when there was more “anxiety impact of the design of the current living space accord- about going out.” This finding is presumed to be ing to the COVID-19 situation. Design impacts were due to “anxiety about going out,” which led to categorized as “a public space with a feeling of open- longer stay-at-home times and increased the overall ness,” “a private space with a feeling of openness,” and “a private space with a feeling of being closed-in.” window area ratio of the house. JOURNAL OF ASIAN ARCHITECTURE AND BUILDING ENGINEERING 15 The larger the floor area, the more “cozy and color data) obtained during the design process. relaxed” the design. Additionally, the larger the total Therefore, the limitation of the small sample size was floor area, the larger the South WWR. This result is overcome to some extent. Nevertheless, it is necessary considered to be due to the tendency to design living to conduct further studies using larger sample sizes in rooms in the south to ensure daylight. the future. The above results confirm that the COVID-19 pan- demic affected the requirements for the designs of 5. Conclusions people’s main living space, the “house,” which defines the most intimate parts of daily life. Therefore, archi- The purpose of this study was to reveal the substantial tectural design should consider people’s psychological changes to social aspects of modern society, living situation as well as design to prevent the spread of environments, and psychological states of designers viruses. due to the spread of COVID-19 and clarify whether According to previous studies, the importance of these are reflected in housing designs. This study designing a sustainable building environment, which found that feeling “anxiety about going out” and “fear- has antiviral properties, has been raised in the archi- ful of COVID-19 infection” influenced the psychological tectural community due to COVID-19 (Megahed and factors related to design, and therefore also the final Ghoneim 2020; Pinheiro and Luís 2020). However, it is design (total floor area, window area ratio, color plan- also important not only to design to block viruses but ning, and connection with the outside world). Notably, also to seek ways to design for psychological stability the cause of increasing stay-at-home times was con- and reduce anxiety about other people living in the firmed to be “anxiety about going out.” Therefore, it same building. This study found that the effects of was confirmed that the COVID-19 pandemic affects social background influence anxiety and affect the the requirements for the design of our main living psychological factors of design and the final design. space. In other words, the psychological state of the designer Our research will be of interest to both faculty and (architect), according to their social background (situa- researchers dedicated to the teaching of conditions tion), might influence their architectural designs. and methods of housing design, as well as students Therefore, it is important for designers in the architec- and professionals involved in housing development tural design process to include their clients in a way and management. Additionally, our research provides that allows them to reflect and protect their psycholo- crucial insights into the psychological conditions gical stability in the consultations and designs. For the affecting young designers who are subjected to pro- reasons mentioned above, the results of this study can longed lockdowns for reasons of health and safety in be used as guidelines during the architectural design the wake of the COVID-19 pandemic. process, helping both architects and clients design Our research is an integrated analysis of psycholo- buildings that will satisfy both parties. gical states assessed using actual housing design pro- However, Capolongo et al. (Capolongo et al. 2020) posals and questionnaires; thus, it is an accurate study argued that ensuring flexible and adaptable spaces in based on qualitative and quantitative data. However, indoor environments allows one to adapt to sustain- since the background of each individual designer is able and changing needs and lifestyles. To adapt to the unique and includes a variety of factors, it is presumed rapidly changing modern living environment and life- that the influence on the design is also diverse. style, flexibility in housing is required so that space can Therefore, it is necessary to verify what kind of psycho- fit the psychological state of the people living in it. The logical support is necessary for the designer. results of this study confirm that the COVID-19 pan- Additionally, it seems critical to include the way demic restrictions may have influenced housing designers need to comprehend the psychological design. Further research is needed to clarify how to needs of clients, and future studies should further design flexible and adaptable spaces to meet the social examine how the design process reflects the psychol- needs and lifestyle changes caused by future infectious ogy of the designer and clients. In addition, it is neces- diseases. sary to conduct further surveys in other universities not The main limitation of this research is its small only in Japan but also in an international context to sample size (n = 28). Mackenzie (Mackenzie 2013) con- obtain a more complete and reliable predictive model sidered the sample size as suitable if statistically sig- of the effects of pandemic restrictions on the study of nificant results were obtained. In addition, the Df value architectural design. of the error in this study was 27, which is not small. Furthermore, despite the small sample size, statistically Acknowledgments significant results were obtained. In particular, in this study, significant research results were obtained using The authors gratefully acknowledge each of the participants not only psychological data (by means of a survey) but who gave their time for this research. also objective data (total floor area, window area, and 16 H. YU AND R. FUJII Disclosure statement the Pandemic Challenge. A Decalogue of Public Health Opportunities.” Acta Biomedica 91: 13–22. doi:10.23750/ No potential conflict of interest was reported by the abm.v91i2.9615. author(s). Deguchi, T., and M. Sato. 1992. “The Effect of Color Temperature of Lighting Sources on Mental Activity Level.” The Annals of Physiological Anthropology 11 (1): 37–43. doi:10.2114/ahs1983.11.37. Notes on contributors Evans, G. W., N. M. Wells, and A. Moch. 2003. “Housing and Mental Health: A Review of the Evidence and Dr. Hanui Yu is an assistant professor in the department of A Methodological and Conceptual Critique.” Journal of architecture at Tokyo Denki University and conducts research Social Issues 59 (3): 475–500. doi:10.1111/1540-4560.00074. on lighting and visual environments, environmental plan- ning, and psychophysiology. She earned her Ph.D. in archi- Fairman, H. S., M. H. Brill, and H. Hemmendinger. 1997. tecture at The University of Tokyo and her Master's degree at “How the CIE 1931 color-matching Functions Were Hanyang University. Derived from Wright-Guild Data.” Color Research & Application 22: 11–23. doi:10.1002/(SICI)1520-6378- Dr. Risa Fujii is an assistant professor at the department of architecture at Tokyo Denki University and conducts research (199702)22:1<11::AID-COL4>3.0.CO;2-7. on architectural planning, children's facility planning, and Henry, M. 2020. “Living Alone Adds to Social Isolation during disaster preparedness for facilities. She earned her Ph.D. in COVID-19, Potentially Increasing Health Threats.” The architecture at The University of Tokyo and her Master's Columbus Dispatch. https://www.dispatch.com/story/ degree at Japan Women's University. news/2020/11/15/covid-19-coronavirus-living-alone-adds -social-isolation-during-pandemic/6224911002/ Hollister, F. 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Journal
Journal of Asian Architecture and Building Engineering – Taylor & Francis
Published: May 4, 2023
Keywords: Architectural design; eco design; architectural environment; perception; psychology of design