Influences of High School Physical Learning Environments on Students’ Anxiety in China

Abstract

Background:

High school students are at an increased risk of developing generalized anxiety disorder (GAD) due to significant pressure to achieve academic success.

Aim:

Although it is known that a school’s physical learning environment can influence students’ GAD, there is limited research examining this relationship. To fill this knowledge gap, a cross-sectional study was conducted among 230 students from two high schools in China.

Methods:

A survey questionnaire captured students’ GAD self-evaluations (dependent variables), perceptions/preferences of their school physical environment (independent variables), and social and personal conditions (confounding variables). Bivariate analysis showed that students’ GAD scores were associated with multiple factors related to the learning environment, physical activities, and personal characteristics. The multivariate analysis examined the relationship between GAD scores and physical learning environment variables while controlling for confounding variables.

Results:

The results indicated that adequate lighting (B = −0.154, p = .029) and perceived effectiveness of using self-service cafeterias in reducing anxiety (B = −0.138, p = .044) were significantly associated with GAD scores.

Conclusions:

These findings provide evidence for the importance of designing high schools with students’ mental health in mind. Specifically, school administrators and designers should consider how to improve the physical learning environment by incorporating natural light, a self-service cafeteria, and spaces for physical activities to promote students’ mental well-being.

Keywords

healthy environment high school environment generalized anxiety disorder students’ mental health physical learning environment learning space design high school campus planning

Introduction

Mental health issues are among the primary illnesses and disabilities affecting adolescents, with approximately 13% of individuals aged 10–19 experiencing conditions such as depression and anxiety disorders (World Health Organization [WHO], 2021). School-aged individuals often encounter stressors and anxiety-evoking stimuli, including parental pressure for significant academic achievement, classroom competition, frustration, teachers’ disapproval, peer conflicts, social isolation, bullying, and verbal aggression (Frank-Briggs & Alikor, 2010; Schutz & Pekrun, 2007). Failing to address mental health conditions can harm students’ physical, psychological, and intellectual development, limiting their ability to lead fulfilling adult lives (WHO, 2021).

Generalized anxiety disorder (GAD) is one of the most common anxiety disorders in adolescents (Caporino et al., 2013; Sakthivel et al., 2021; Wittchen, 2002). GAD is characterized by persistent excessive worry and difficulty controlling anxiety for at least 6 months (Anxiety & Depression Association of America, 2021). Along with memory impairment and decline of cognitive functions, GAD symptoms can negatively affect students’ general well-being, social life, and development of social skills (Bernstein et al., 1996; Daleiden, 1998; Kessler et al., 2005; Pine et al., 1998). Moreover, adolescent GAD contributes to poor school performance and academic failure (Godovich et al., 2020), leading to further psychiatric disturbances (Masi et al., 2001) and impeding future adaptive psychosocial development (Maldonado et al., 2013). Therefore, understanding GAD determinants is crucial to help adolescents cope with related issues.

GAD in Children and Adolescents

GAD affects children and adolescents worldwide. A survey conducted in children aged 5–16 years in the United Kingdom estimated that 0.7% of the targeted population had GAD (Green, 2005). The U.S. National Replication Survey revealed a lifetime prevalence of 3% for GAD among participants aged 13–18 (Burstein, 2014). Although GAD among children and adolescents is mainly linked to school performance (Wagner, 2001), high expectations for success in the national university entrance examination are the most common anxiety source among Chinese high school students (Zhang et al., 2021). A study involving 1,533 Chinese high school students revealed that 15.8% reported moderate to severe anxiety levels, while 84.2% experienced minimal to mild anxiety (Zhu et al., 2021). In addition, Zhou et al. (2020) conducted a study during the COVID-19 pandemic and found that 37% of students reported anxiety symptoms.

Factors Influencing GAD

Several factors can impact students’ GAD. Sociodemographic factors (age, gender, mother’s history of psychiatric hospitalization and education, parenting behaviors, and residence) are associated with children and adolescents’ GAD (Mohammadi et al., 2020; Spitzer et al., 2006). Osborn et al. (2020) reported that female high school students and minority group members experienced higher anxiety levels than male and majority group members. Mazzone et al. (2007) observed an increase in anxiety symptoms with grade level and a negative association with school performance.

Social factors also contribute to GAD. Students with underperforming peers and stressful family relationships are more prone to GAD (Newman, 2000). Physical activity and sleep positively impact GAD, as moderate or vigorous physical activity and adequate sleep can reduce the risk of depression and anxiety in adolescents (Carter et al., 2021; McDowell et al., 2017; Ogawa et al., 2019). Lastly, physical environments, including school campuses and residential neighborhoods, significantly affect students’ anxiety levels (Mueller et al., 2019).

PLE Factors Influencing GAD

School plays a critical part in students’ development as they spend significant time on campus (Yadusky-Holahan & Holahan, 1983). The school environment serves not only as a space for learning but also as a place that caters to student needs such as comfort and relaxation (Nair, 2019). Research increasingly demonstrates the impact of physical learning environments (PLEs) such as temperature, air quality, lighting, acoustic conditions, color schemes, furnishings, and natural elements on student health (Higgins et al., 2005; Okcu et al., 2011; Schutte et al., 2017). Characteristics of classroom space, including seating arrangements, density, privacy, and the presence of windows, affect student behaviors, attitudes, and performance (Dockrell & Shield, 2006; Weinstein, 1979). Baepler (2021) discovered that excessive indoor lighting and ambient noise in classrooms could be irritating and distracting, leading to increased anxiety. Baepler also reported that seating arrangements promoting social interactions could decrease anxiety. Therefore, PLE, both indoor and outdoor environments, are closely related to student health and well-being (Akpinar et al., 2016; Bell & Dyment, 2008; Chawla et al., 2014; Foellmer et al., 2021; Li & Sullivan, 2016; Mueller et al., 2019; Sakthivel et al., 2021). Moreover, PLE is considered as a distinct causal factor that can interact with learner traits, learning-task characteristics, or a combination thereof (Choi et al., 2014).

Despite the literature suggesting that certain PLE features might affect students’ anxiety levels, many studies investigating GAD have focused on social and individual factors rather than PLE factors. This study aims to fill this knowledge gap by examining the relationship between students’ GAD and PLE factors. The research question to be addressed is, which features of high school PLE affect students’ GAD?

Preliminary Study

Prior to the main project, the researchers conducted a preliminary study to explore high school students’ GAD and its potential causes. The results were expected to inform the development of research instruments (e.g., survey questionnaires) for the main project. The interviews were exploratory and semi-structured, focusing on anxiety sources, activities that helped alleviate anxiety, relaxation methods during breaks, and preferred learning environments. The researchers interviewed 12 students (five males and seven females) from two high schools. with each interview lasting approximately 20 min on average. Notes were taken during the interviews and the data were analyzed. The key results are summarized in the below subsections.

Sources of Anxiety

Students indicated that their anxiety was mainly stemmed from concerns about academic performance. Other anxiety triggers included drowsiness, hunger, fatigue, and rambling thoughts. Moreover, high family expectations and unsatisfactory peer relationships contributed to elevated anxiety levels.

Activities That Helped Alleviate Anxiety

Students reported that staying in the classroom for extended periods could induce anxiety. To alleviate anxiety, they preferred walking around the playground or along green trails and conversing with friends. Participating in physical exercise and art classes also helped them relax.

Means to Relax During Recess

During short breaks (10 min), students favored walking or viewing outdoor scenery through windows. In longer recess periods (20–30 min), they enjoyed outdoor recreational activities such as jogging or playing basketball.

Learning Environment Preferences

Students valued the abundance of natural elements such as sunlight, trees, and flowers. They deemed comfort (e.g., comfortable lighting and temperature) crucial for the indoor learning environment.

The preliminary interviews reinforced the notion that PLE featuring natural elements, comfortable sensory factors, facilities promoting physical activities and breaks, and aesthetic aspects would affect students’ GAD.

Literature Review

A literature review was conducted to identify factors that potentially influencing GAD, which were categorized as follows: natural elements, aesthetic factors, sensory factors, facilities, and personal and social factors.

Natural Elements

Attention restoration theory and stress recovery theory suggest that natural environments play a vital role in personal mental health, fostering attention recovery and stress reduction (Hartig & Kahn, 2016; Ulrich et al., 1991; Wilson, 1984). Enhancing the frequency of connecting with nature may help alleviate anxiety (Martyn & Brymer, 2016). Yin et al. (2020) found that participants in biophilic indoor environments experienced a consistent decrease in anxiety compared to those in nonbiophilic settings. Moreover, nature-based interventions have been proven effective in treating student anxiety (Rian & Coll, 2021). Providing access to natural elements, strengthening visual and nonvisual connections with nature, utilizing biomorphic forms and patterns, and selecting natural materials are practical approaches to finding relief and reducing anxiety (Kellert, 2008; Salingaros, 2015).

Aesthetic Factors

Artwork offers anxiety-reducing benefits (Karnik et al., 2014; Mastandrea et al., 2019). Elements like paintings and sculptures, as well as activities like drawing, serve as visual stimulation that can divert students’ attention from anxiety (Montgomery, 2018; Yu, 2021). Furthermore, Barrett et al. (2015) indicated that balancing complexity and colors in the classroom through student artwork displays could help students feel at home in the space.

Sensory Factors

A perceived lack of security and cleanliness can contribute to adolescent anxiety (McLaughlin & Hatzenbuehler, 2009). Studies have shown that incorporating ample natural light, good air quality, thermal comfort, favorable sound conditions, opportunities for movement, and restorative qualities in PLE can enhance students’ well-being and cognitive performance (DiSarno et al., 2002; Earthman, 2002; Han, 2009; Keis et al., 2014; Vandewalle et al., 2009; Wannarka & Ruhl, 2008).

Facilities

The presence of school facilities, such as self-service cafeterias, on-campus grocery stores, sports facilities, drinking water dispensers, movable furniture, power banks, and wireless networks, may have an impact on students’ GAD. Social withdrawal theory implies that inactivity leads to anxiety and depression (Thompson et al., 2001). Conn (2010) reported that as per a meta-analysis of 3,289 subjects, physical activity was found to lower students’ depression, stress, negative feelings, and anxiety. Access to activity facilities (e.g., indoor sports facilities and outdoor playgrounds) may boost students’ physical activity levels, resulting in lower GAD (Biddle et al., 2019).

Personal and Social Factors

Evidence indicates that personal factors such as students’ gender, ethnicity, grade level, mood, academic performance, sleep duration, focus time, and physical activity levels can impact their levels of anxiety (Carter et al., 2021; Mazzone et al., 2007; McDowell et al., 2017; Mohammadi et al., 2020; Ogawa et al., 2019; Osborn et al., 2020; Juan & Chen, 2022). Additionally, the social environment is tied to students’ mental health development. Social factors including peer relationships, student–faculty relationships, family relationships, family expectations, and self-expectations are linked to students’ GAD (Holmes & Newman, 2006).

Conceptual Framework

Drawing on the preliminary study and the literature review, the present study proposes the following research framework (see Figure 1). GAD, as a dependent variable, could be affected by independent variables (school physical environment) and confounding variables (students’ personal factors and social factors). School physical environment factors are divided into four categories: natural elements, aesthetic factors, sensory factors, and facilities. Students’ personal factors serve as confounding variables in this study. Figure 1 illustrates the conceptual framework of these variables.

Figure 1.

Conceptual framework.

Method

To compare the effects of PLE on students’ anxiety, a cross-sectional study was conducted in two Chinese high schools in July 2021. Questionnaires were used to measure dependent variables, independent variables, and confounding variables. A 7-point rating scale measured PLE, while the GAD-7 Scale evaluated GAD. In addition, students’ personal factors and social factors were assessed through fill-in-the-blank and multiple-choice questions. The Institutional Review Board of the first author’s university reviewed and approved the research protocol.

Survey Questionnaire

The survey questionnaire was developed based on the preliminary study results and the literature review. The questionnaire comprised five sections with 27 questions: (1) basic information (gender, ethnicity, grade, school, etc.), (2) anxiety and relaxation (sources of anxiety, GAD scores, etc.), (3) activities (duration and locations), (4) perceptions and/or preference of learning environment and facility features (PLE factors), and (5) personal assessment (academic performance, sleep duration, health conditions, etc.).

The Generalized Anxiety Disorder-7 (GAD-7) is a brief self-report questionnaire used to assess GAD and its severity in clinical practice and research (Adjorlolo, 2019; Spitzer et al., 2006). The Chinese version of GAD-7 employed in this study has been tested in multiple studies with good reliability and validity results (Cronbach’s α = .90) (Sun et al., 2021; Tong et al., 2016). It measures seven symptoms experienced by participants during the previous 2 weeks, each rated on a 4-point scale from 0 (not at all) to 3 (nearly every day). GAD levels can be categorized as Level 1 (score of 0–4) or normal status; Level 2 (score of 5–9) or mild anxiety; Level 3 (score of 10–14) or moderate anxiety; and Level 4 (score of 15–21) or severe anxiety. In the present study, Cronbach’s α for the GAD-7 Scale was .925. School PLE variables were measured by students’ ratings on a 7-point scale from 1 (very bad or unimportant) to 7 (very good or very important). Respondents were asked how PLE features affect their anxiety on campus. Other information (confounding variables) such as students’ sociodemographic status, social factors, activities, and additional personal factors were also collected via the questionnaire.

School Settings

School A and School B (Figures 2 and 3) were located in the suburbs of two major Chinese cities, one with a population of 2.968 million (2021) in Shandong Province and the other with 2.269 million (2021) in Shaanxi Province. School A’s campus was considerably larger than that of School B as shown in the figures below. Both schools featured plazas, gardens, walking trails, playgrounds, indoor sports facilities, and so on. Evaluations of detailed PLE features for both schools were scored using the Likert-type scale and tabulated in Table 1. School A’s PLE received a higher overall rating than School B’s.

Figure 2.

The master plan of School A.

Figure 3.

The master plan of School B.

Table 1.

Physical Environment Characteristics of School A and School B.

Characteristics	School A	School B
Basic information
Province	Shandong	Shaanxi
Location	Suburban	Suburban
Land area	23.629 acres (95,625 m²)	6.627 acres (26,817 m²)
Number of grade levels	3	3
Number of classes	60	27
Approximate number of students in each class	50	50
Number of buildings on the campus	8	6
Facilities
Availability of plazas	Yes	Yes
Availability of gardens	Yes	Yes
Availability of walking trails	Yes	Yes
Availability of playgrounds	Yes	Yes
Availability of indoor sports facilities	Yes	Yes
Availability of on-campus grocery stores	Yes	Yes
Availability of cafeterias	Yes	Yes
Availability of a library	Yes	Yes
Availability of water dispensers	Yes	Yes
Availability of roof gardens	No	No
Physical learning environment (Likert-type scale ^a)
Colors of space are various but not cluttered	3	4
Availability of personal storage space	5	4
Comfortable and flexible furniture	5	4
Flexible learning spaces	3	1
Informal learning spaces	4	3
Availability of wireless networks	4	3
Good acoustics	3	2
Display students’ works	4	5
Adequate natural light	4	5
Plenty of space without overcrowding	4	3
Viewing natural elements to relieve anxiety	4	3
Design and aesthetics make people feel at home	3	2
Windows connecting with nature	4	2
Spaces support a variety of learning formats	4	1
Learning area allows for a variety of activities	4	4
Available electronic devices to search or display	4	2
Teachers’ workspaces for collaboration	4	2
Fields for activities, exercise, and sports	4	1
Total scores	70	51

^a 1 = Strongly disagree; 2 = disagree; 3 = neutral; 4 = agree; and 5 = strongly agree.

Participants

Participants were convenient samples recruited from two senior high schools. Of the 230 students who participated in the survey, 121 students attended School A, and 109 students attended School B.

Data Collection

One head teacher from each school responded to invitation emails and distributed the questionnaire to students. Participation was voluntary, and nonparticipation had no impact on students’ performance evaluations. The questionnaires were administered to students in the classroom and collected on-site immediately after completion. Among the 230 returned questionnaires, 219 were included for analysis; 11 were excluded due to incomplete information.

Data Analysis

Descriptive, t-test, bivariate, and multivariate analyses were applied in this study. A t-test was performed to compare the mean difference of a variable between two groups (e.g., students’ GAD scores between the two schools). Bivariate analyses (e.g., Pearson correlation and Spearman correlation) were applied to test the relationships between GAD scores and PLE factors, personal factors, and social factors and assisted in selecting variables for the multivariate model. Multiple linear regression was used to examine relationships between GAD scores and selected PLE factors, with individual and social factors as controls. The level of significance was set at 0.05 (two sided). Data analysis was conducted using SPSS Version 26.0 (IBM SPSS, IBM Corp., Armonk, NY, USA).

Results

Participant Characteristics

Among the 219 student participants, 138 (63%) were male, and 81 (37%) were female. Their ages ranged from 15 to 18 years (mean [M] = 16.69 years; standard deviation [SD] = 0.66). They represented all 3 years of senior high school, with 102 students in the 1st year (K–10), 69 students in the 2nd year (K–11), and 46 students in the 3rd year (K–12). Except for two students, all were of Han ethnicity, which accounts for 91% of China’s population. The mean GAD score was 13.52; 40.2% of students scored at GAD Level 3 (moderate anxiety), and 35.6% scored at Level 4 (severe anxiety; see Table 2).

Table 2.

Student Demographic Characteristics.

Characteristics	Frequency	Valid Percent (%)
Gender
Female	81	37
Male	138	63
Total	219	100
Ethnicity
Han	217	99.1
Minority	2	0.9
Total	219	100
Grade
First Year (K–10)	101	46.8
Second Year (K–11)	69	31.9
Third Year (K–12)	46	21.3
Total	216	100
Generalized anxiety disorder level
Level 1 (0–4 scores)	3	1.4
Level 2 (5–9 scores)	50	22.8
Level 3 (10–14 scores)	88	40.2
Level 4 (15–27 scores)	78	35.6
Total	219	100

Bivariate Analysis of GAD and Factors

A bivariate analysis was used to examine the correlation between GAD scores and (1) sociodemographic characteristics, (2) PLE factors, (3) activities, (4) personal factors, and (5) social factors, respectively.

GAD Scores and Sociodemographic Characteristics

The correlations between participants’ sociodemographic characteristics and GAD scores are shown in Table 3. No significant correlation was found between GAD scores and age, gender, height, or weight variables. However, GAD scores were significantly related to grade levels. Analysis of variance (not shown in the table) indicated that 1st-year students had significantly higher GAD scores than 2nd-year students. Moreover, t-test results indicated that students in School B exhibited a higher mean GAD score than those in School A (p value = .055, marginally significant, see Table 4).

Table 3.

Sociodemographic Factor Correlations.

Variables	Indicators	Gender	Age	Grade	Height	Weight	School
Generalized anxiety disorder scores	Correlation coefficient	0.067	−0.108	−0.157^a	−0.060	−0.025	0.189^b
	Sig. (two-tailed)	0.323	0.111	0.021	0.384	0.716	0.005
	N (valid)	218	218	215	216	213	218

^a Spearman correlation is significant at the .05 level (two-tailed).

^b Spearman correlation is significant at the .01 level (two-tailed).

Table 4.

t-Test for Generalized Anxiety Disorder (GAD) Scores of Two Schools.

t	df	Significance (Two-Tailed)	Mean Difference	Standard Error Difference	95% Confidence Interval of the Difference [Lower Upper]
−1.928	213.588	0.055	−1.332	0.691	[−2.693, 0.03]

Note. The mean GAD scores of School B is 12.91 and School A is 14.24.

GAD Scores and PLE Factors

GAD scores were negatively correlated with participants’ perceived effectiveness of using school facilities and amenities for anxiety reduction, including outdoor playgrounds, indoor sports facilities, self-service cafeterias, on-campus grocery stores, and so on. Furthermore, GAD scores were significantly related to two sensory factors: adequate lighting and ample natural light. A clean and tidy learning environment was negatively associated with GAD scores. However, high-level noise and poor natural ventilation demonstrated a positive association with GAD scores (see Table 5).

Table 5.

Correlations Between Generalized Anxiety Disorder Scores and Physical Learning Environments Factors.

Variables	r	Sig.	Variables	r	Sig.
Uncomfortable temperature and humidity	−.021	.8	Available power banks and wireless networks	−.220^b	.008
Lighting is too dark or bright	.005	.953	Adequate lighting	−.242^b	<.001
High-level noise	.192^a	.012	Comfortable furniture	−.116	.09
Poor natural ventilation	.162^a	.044	Fresh smell	−.129	.059
Air is not fresh	.058	.476	Clean and tidy learning environment	−.166^a	.014
Uncomfortable tables and chairs	.089	.285	Ample natural light	−.136^a	.047
Convenient water dispensers	−.170^a	.013	Sky view	–.057	.404
Clean restrooms	−.233^b	.001	Green plants	−.076	.27
Artwork (paintings and sculptures)	−.075	.278	Small animals	−.054	.439
Display of homework/photos	−.090	.194	Open green space	−.098	.151
Perceived effectiveness of using a self-service cafeteria in reducing anxiety	−.277^b	<.001	Perceived effectiveness of using indoor sports facilities in reducing anxiety	−.287^b	<.001
Perceived effectiveness of using outdoor playgrounds in reducing anxiety	−.297^b	<.001	Perceived effectiveness of using on-campus grocery stores in reducing anxiety	−.246^b	<.001
Perceived effectiveness of using semi-outdoor learning space in reducing anxiety	−.235^b	.002	Perceived effectiveness of using open roof terrace in reducing anxiety	−.073	.289

^a Pearson correlation is significant at the .05 level (two-tailed).

^b Pearson correlation is significant at the .01 level (two-tailed).

GAD Scores and Activities

The relationship between GAD scores and activities was analyzed using the Spearman correlation (see Table 6). Among these activities, only playing basketball showed a statistically significant association. A t-test analyzing the gender comparison in playing basketball revealed a significant difference (see Table 7). Regarding preferences of activity locations, the trail and plaza were significantly related to GAD scores. Classrooms, the recreation center, and the library also exhibited significant associations with GAD scores. Areas with foot traffic, such as the stairwell, lobby, and sky corridor, were significantly correlated with GAD scores as well (Table 8).

Table 6.

Correlation Among Activities.

Variables	r	Sig.	Variables	r	Sig.
Sit and rest	–.045	.509	Walking	.097	.151
People watching	–.054	.430	Recess exercise	–.003	.967
Nap for a while	.042	.535	Chess and card games	–.113	.097
Walk outdoors	.002	.976	Running	–.070	.300
Look out the window	–.006	.925	Basketball	–.138^a	.041
Get some water	–.036	.593	Football	.008	.906
Exercise	–.091	.180	Volleyball	–.130	.056
Listen to music	.061	.367	Badminton	.112	.098
Go to restroom	–.104	.127	Table tennis	–.014	.842
Chat with friends	–.015	.830	Tennis	–.076	.263
Eat snacks	.022	.747	Tai Chi	–.065	.339
Go to grocery store	.071	.300	Yoga	–.090	.188
Read magazines/novels	–.026	.700	Fitness	–.027	.689
Play electronic games	–.101	.138	Skating	–.100	.142
Dancing	–.050	.461	Swimming	–.083	.224

^a Spearman correlation is significant at the .05 level (two-tailed).

Table 7.

t-Test for Playing Basketball.

t	df	Sig. (Two-Tailed)	Mean Difference	Standard Error Difference	95% Confidence Interval of the Difference [Lower, Upper]
−5.684	119.058	<0.001	−0.353	0.062	[−0.476, −0.230]

Note. Group 1 is male; Group 2 is female.

Table 8.

Correlation Among Preferences of Activity Locations when Students Feel Anxious.

Variables	r	Sig.	Variables	r	Sig.
Track and field	.013	.849	Corridor	−.083	.221
Outdoor sports field	−.125	.066	Stairwell	−.163^a	.016
Trail	−.150^a	.026	Washroom	.030	.662
Green space	−.083	.223	Lobby	−.180^b	.008
Waterfront landscape	−.061	.370	Sky corridor	−.155^a	.022
Plaza	−.257^b	<.001	Cafeteria	.027	.688
Courtyard	−.096	.160	Recreation center	−.211^b	.002
Semi-outdoor terrace	−.064	.348	On-campus grocery store	−.034	.616
Rooftop	−.094	.168	Library	−.174^b	.010
Classroom	−.153^a	.024	Multifunctional activity center	−.102	.135
Ɖ??			Dormitory	−.044	.514

^a Spearman correlation is significant at the .05 level (two-tailed).

^b Spearman correlation is significant at the .01 level (two-tailed).

Activities during recess were categorized into five types: (1) rest, (2) recreation, (3) utilitarian, (4) entertainment, and (5) social. The duration of these activities is shown in Table 9. Rest (119.22 min/person) constituted the longest type of activity during the school day. The average duration of recreational activity was 22.95 min. During recess, students spent time engaging in various activities before the first class (60.90 min) and during the lunch break (31.46 min). Participation in activities before the first class or during morning recess was found to be the most helpful in terms of anxiety reduction.

Table 9.

Duration of Recess Activities in One School Day (Unit: Minutes).

	Rest	Recreation	Utilitarian	Entertainment	Social	Total
Before first class	54.75	3.27	1.41	0.49	0.97	60.90
Morning mini recess	5.89	2.53	2.07	0.47	2.68	13.66
Morning recess	3.48	6.10	2.27	0.84	1.42	14.12
Lunch break	26.11	1.53	2.23	0.54	1.04	31.46
Afternoon mini recess	4.54	3.26	2.51	0.78	1.35	12.44
Dinner break	13.88	4.83	2.58	0.80	2.26	24.36
Evening study recess	10.56	1.43	2.21	1.91	1.86	17.98
Total	119.22	22.95	15.30	5.84	11.59

Note. Rest activities: meditation, people watching, napping, looking out the window, and eating snacks; recreational activities: outdoor walks and playing sports; utilitarian activities: getting water, going to the restroom, changing classrooms, and going to the grocery store; entertainment activities: listening to music, reading leisure books (magazines/novels), and playing electronic games; and social activities: chatting with good friends.

GAD Scores and Personal Factors

Regarding personal factors, there were significant correlations between GAD and several factors including sleep duration, food cravings, unstable mood, mental fatigue, and length of time focused on learning (see Table 10).

Table 10.

Correlation Among Personal Factors.

Variables	r	Sig.	Variables	r	Sig.
Wearing glasses or not	−.068	.316	Length of time focused on study	−.137^a	.049
Academic performance	.010	.886	Commute mode	.071	.307
Age to start wearing glasses	.001	.991	Unstable mood	.251^b	<.001
Sleep duration	−.326^b	<.001	Commute time	0	.997
Time spent learning	−.105	.120	Mental fatigue	.228^b	.002
Frequency of hospital visits	−.102	.133	Frequency of absence	−.098	.152
Health condition	.122	.145	Food cravings	.278^b	<.001
Late arrival	−.038	.577

^a Spearman correlation is significant at the .05 level (two-tailed).

^b Spearman correlation is significant at the .01 level (two-tailed).

GAD Scores and Social Factors

Social factors such as family expectations and family relationships were significantly correlated with GAD scores. Other factors such as peer relationships, student–faculty relationships, romantic relationships, and school bullying did not show significant correlations with GAD scores (see Table 11).

Table 11.

Correlation Among Social Factors.

Variables	r	Sig.	Variables	r	Sig.
Family expectations	−.213^a	.002	Family relationships	−.205^a	.002
Peer relationships	−.130	.055	Romantic relationships	−.098	.149
Student–faculty relationships	−.053	.433	School bullying	.021	.762

^aSpearman correlation is significant at the .01 level (two-tailed).

Multivariate Analysis: GAD Scores and Environmental Factors

The final model incorporated the bivariate analysis results and the assumption that school, grade, gender, family expectations, sleep duration, and unstable mood would affect students’ GAD. The relationship between GAD scores and PLE was assessed using multiple linear regression analyses, while controlling for social and personal factors. The model included control variables and PLE variables. After the backward stepwise selection, nine variables remained in the final model (see Table 12). Students’ GAD scores (higher GAD scores = greater anxiety) were negatively associated with “perceived effectiveness of using a self-service cafeteria in reducing anxiety,” “adequate lighting,” “hours of sleep,” and “family expectations.” Conversely, factors such as “perceived effectiveness of using plazas in reducing anxiety” and “unstable mood” were positively associated with GAD scores. The adjusted R ² was .3, signifying that the variables in the model accounted for 30% of the variance of the GAD scores.

Table 12.

Multiple Regression Results: GAD Scores as the Dependent Variable.

Variables	Coefficients (β)	Standard Error	t	Sig.
School (A = 2, B = 1)	−.088	1.566	−0.568	.571
Grade (1st year = 1)	−.062	1.566	−0.411	.682
Gender (male = 1, female = 2)	.022	0.724	0.317	.752
Level of family expectations	−.255	0.703	−3.675	<.001
Sleep duration	−.35	0.356	−5.075	<.001
Unstable mood	.201	0.173	2.965	.004
Adequate lighting	−.154	0.212	−2.202	.029
Perceived effectiveness of using a “self-service cafeteria in reducing anxiety”	−.138	0.186	−2.029	.044
Perceived effectiveness of using plazas in reducing anxiety	.166	1.048	2.366	.019

Note. Dependent variable: Generalized anxiety disorder (GAD) scores. Adjusted R ² = .300.

Discussion

This study examined the impact of PLE features and confounding variables on students’ GAD scores in two Chinese high schools. The results indicated that PLE factors, including “adequate lighting”, “physical activity”, and “the perceived effectiveness of using a self-service cafeteria in reducing anxiety” significantly influenced students’ mental and behavioral health, resulting in different GAD scores.

PLE factors, including “adequate lighting”, “physical activity”, and “the perceived effectiveness of using a self-service cafeteria in reducing anxiety” significantly influenced students’ mental and behavioral health, resulting in different GAD scores.

School A, with larger campus and higher rated fields and facilities than School B (see Table 1), potentially contributed to lower student GAD scores. The bivariate results revealed that “the perceived effectiveness of using outdoor playgrounds, semi-outdoor spaces, and indoor sports fields in reducing anxiety” was negatively associated with GAD scores. This may be attributed to students’ engagement in physical activities, which can help reduce anxiety (Biddle et al., 2019). Another finding was that “the perceived effectiveness of using food and water-related amenities,” such as self-service cafeterias, drinking water dispensers, and on-campus grocery stores during recess or break time, potentially lowered students’ GAD scores. “This aligns with Mikolajczyk’s (2009) study, which revealed that food consumption, especially healthy food, reduced depressive symptoms, and stress among students. Interestingly, GAD scores were positively related to “perceived effectiveness of using plazas in reducing anxiety,” contradicting previous studies that favored outdoor activities for restoring attention (Weng, 2014). The authors of the present study speculated that highly stressed students might have intentionally used plazas for relaxation purposes.

“the perceived effectiveness of using outdoor playgrounds, semi-outdoor spaces, and indoor sports fields in reducing anxiety” was negatively associated with GAD scores.

The results also indicated that rest activities, including socializing with friends, people-watching, napping, viewing the outdoors from inside, and eating snacks, contributed to reduced anxiety in students. Among all the activities investigated in the present study, only playing basketball was significantly related to students’ GAD. However, a gender discrepancy in participation was observed, with fewer female students participating. A previous study showed that yoga could help lower anxiety levels in females (Shreve et al., 2021). Therefore, high schools should consider providing facilities and spaces (such as yoga studios) to promote activities that might be more appealing to female students.

…socializing with friends, people-watching, napping, viewing the outdoors from inside, and eating snacks, contributed to reduced anxiety in students.

Sensory factors such as lighting, acoustics, and ventilation were found to be essential for reducing GAD, aligning with the existing literature. Previous studies have indicated that spaces filled with natural light decreased anxiety (Heschong et al., 2002). In addition to lighting, other sensory factors such as noise significantly affected anxiety levels (Juan & Chen, 2022). Najafi et al. (2019) found that opening classroom windows for ventilation could reduce anxiety among female high school students. The present study also found that adequate natural light significantly decreased students’ GAD scores. Consequently, incorporating natural light in classroom design is an essential consideration for reducing students’ anxiety.

Sensory factors such as lighting, acoustics, and ventilation were found to be essential for reducing GAD

…adequate natural light significantly decreased students’ GAD scores

Previous studies have demonstrated that sociodemographic variables (gender, age, ethnicity, and grade) affected GAD (Mohammadi et al., 2020; Osborn et al., 2020). However, the present study showed that these factors were not correlated with GAD scores, except for students’ grade levels. According to Mazzone et al. (2007), students in higher grade levels tended to be more anxious than those in lower levels. Contrarily, this study found that 1st-year high school students (the lowest grade level) exhibited higher GAD scores, possibly due to the recent transition to a new, unfamiliar environment (Estell et al., 2007). Though increased academic pressure among students in higher grade levels may not lead to higher GAD scores, the school PLE did still affect these students’ GAD scores. Moreover, the social environment impacted students’ GAD scores in multiple ways. According to the study results, family expectations were negatively correlated with GAD, which contradicts Mueller et al.’s (2019) argument that family expectations of students’ academic performance increased students’ anxiety. The authors speculated that higher family expectations may lead to better academic performance, reducing anxiety for students in the two Chinese high schools. Though previous studies have highlighted the importance of peer relationships as an essential social factor affecting students’ GAD, (Sakthivel et al., 2021), it was not significant in the present study.

Limitations

The limitations of this study pertained to the nature of the research design. First, the cross-sectional study precluded the detection of causal relationships between specific PLE factors and students’ GAD scores. Second, the results would have been more robust if a larger and more diverse sample of schools with varied PLE characteristics had participated. Third, since not all students from each school participated in the survey, the results may be biased, as those who were interested in the study could have had higher GAD scores than nonparticipants. Lastly, although the survey questionnaire was developed based on a preliminary study, the literature review, and previously validated questions, the authors might have overlooked certain critical factors, such as habituation effects on students’ stress and anxiety.

Future Research Directions

Several research directions have emerged from this study: (1) the relationship between biophilic designs and GAD, (2) the mediating effects of activities and social relationships on the association between PLE features and GAD, and (3) PLE features that facilitate activities appealing to female students. Future research should (1) employ experimental and/or longitudinal methods to identify causal relationships between PLE factors and GAD, (2) increase the sample size of both schools and students, and (3) develop and use reliable and valid measurement methods and instruments.

Conclusion

This study examined the impact of PLE factors on Chinese high school students’ GAD scores. The findings revealed that adequate lighting, as well as students’ perceived “effectiveness of using self-service cafeterias, sports facilities, and plazas to alleviate anxiety,” influenced their GAD scores. This study provided empirical evidence to promote high school design that could enhance students’ mental health.

Implications for Practice

According to the study, adequate lighting, perceived effectiveness of using a self-service cafeteria in reducing anxiety, and spaces for physical activities can effectively reduce GAD among high school students.

Design strategies for lighting: To achieve optimal natural lighting, it is recommended that a solar analysis be conducted during the early planning and design stage. This analysis should determine the appropriate building orientation, type of window design, and classroom layout to maximize exposure to natural light. Furthermore, frequently used spaces such as classrooms should have windows that provide adequate access to natural light, and skylights should be placed at a certain height to allow for natural light without causing glare in the classroom.

Design strategies for activity spaces: Designing shared common areas that connect classrooms, corridors, stairwells, and lobbies is important to school design because they offer students opportunities to interact with others and rest. Students should also have access to activity spaces such as sports fields, gymnasiums, and recreation centers to engage in moderate physical activities. For instance, if basketball is a popular activity among students during recess, more than one court could be built if the school budget and site permit.

Design strategies for cafeterias: To offer students a break from a potentially stressful classroom learning environment, a cafeteria or food stands should be easily accessible from classrooms and outdoor gathering spaces such as plazas and courtyards. Furniture such as tables and chairs that provide shade should be arranged to encourage students to use these spaces. Designers should also create enjoyable environments within and beyond these areas to promote positive social interaction and active anxiety reduction.

Footnotes

Authors’ Note

Mengqi Li and Zhipeng Lu are the co-first authors. They have equal contributions to this article. Mengqi Li and Leiqing Xu are co-corresponding authors. Tongji university ethics review system completed an ethical review of this work following the ethics policy governing research involving human participants, personal data, and human tissue.

Acknowledgments

The researchers wish to express their gratitude to everyone who contributed to this work, including the students who completed the survey, the teachers who distributed the questionnaires, and their fellow researchers who provided input to this study.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

ORCID iDs

Mengqi Li

Zhipeng Lu

References

Adjorlolo

(2019). Generalized anxiety disorder in adolescents in Ghana: Examination of the psychometric properties of the Generalised Anxiety Disorder-7 scale. African Journal of Psychological Assessment, 1(1), 7. https://doi.org/10.4102/ajopa.v1i0.10

Akpinar

Barbosa-Leiker

Brooks

K. R.

(2016). Does green space matter? Exploring relationships between green space type and health indicators. Urban Forestry & Urban Greening, 20, 407–418. https://doi.org/10.1016/j.ufug.2016.10.013

Anxiety & Depression Association of America. (2021, July 28). Understanding GAD. https://adaa.org/understanding-anxiety/generalized-anxiety-disorder-gad

Baepler

(2021). Student anxiety in active learning classrooms: Apprehensions and acceptance of formal learning environments. Journal of Learning Spaces, 10(2), 36–47. https://files.eric.ed.gov/fulltext/EJ1298353.pdf

Barrett

Davies

Zhang

Barrett

(2015). The impact of classroom design on pupils’ learning: Final results of a holistic, multi-level analysis. Building and Environment, 89, 118–133. https://doi.org/10.1016/j.buildenv.2015.02.013

Bell

A. C.

Dyment

J. E.

(2008). Grounds for health: The intersection of green school grounds and health-promoting schools. Environmental Education Research, 14(1), 77–90. https://doi.org/10.1080/13504620701843426

Bernstein

G. A.

Borchardt

C. M.

Perwien

A. R.

(1996). Anxiety disorders in children and adolescents: A review of the past 10 years. Journal of the American Academy of Child & Adolescent Psychiatry, 35(9), 1110–1119. https://doi.org/10.1097/00004583-199609000-00008

Biddle

S. J.

Ciaccioni

Thomas

Vergeer

(2019). Physical activity and mental health in children and adolescents: An updated review of reviews and an analysis of causality. Psychology of Sport and Exercise, 42, 146–155. https://doi.org/10.1016/j.psychsport.2018.08.011

Burstein

Beesdo-Baum

J. P.

Merikangas

K. R.

(2014). Threshold and subthreshold generalized anxiety disorder among US adolescents: prevalence, sociodemographic, and clinical characteristics. Psychological medicine, 44(11), 2351–2362. https://doi.org/10.1017/S0033291713002997

10.

Caporino

N. E.

Brodman

D. M.

Kendall

P. C.

Albano

A. M.

Sherrill

Piacentini

Sakolsky

Birmaher

Compton

S. N.

Ginsburg

(2013). Defining treatment response and remission in child anxiety: Signal detection analysis using the pediatric anxiety rating scale. Journal of the American Academy of Child & Adolescent Psychiatry, 52(1), 57–67. https://doi.org/10.1016/j.jaac.2012.10.006

11.

Carter

Pascoe

Bastounis

Morres

I. D.

Callaghan

Parker

A. G.

(2021). The effect of physical activity on anxiety in children and young people: A systematic review and meta-analysis. Journal of Affective Disorders, 285, 10–21. https://doi.org/10.1016/j.jad.2021.02.026

12.

Chawla

Keena

Pevec

Stanley

(2014). Green schoolyards as havens from stress and resources for resilience in childhood and adolescence. Health & Place, 28, 1–13. https://doi.org/10.1016/j.healthplace.2014.03.001

13.

Choi

H. H.

Van Merriënboer

J. J.

Paas

(2014). Effects of the physical environment on cognitive load and learning: Towards a new model of cognitive load. Educational Psychology Review, 26(2), 225–244. https://doi.org/10.1007/s10648-014-9262-6

14.

Conn

V. S.

(2010). Anxiety outcomes after physical activity interventions: Meta-analysis findings. Nursing Research, 59(3), 224–231. https://doi.org/10.1097/nnr.0b013e3181dbb2f8

15.

Daleiden

E. L.

(1998). Childhood anxiety and memory functioning: A comparison of systemic and processing accounts. Journal of Experimental Child Psychology, 68(3), 216–235. https://doi.org/10.1006/jecp.1997.2429

16.

DiSarno

N. J.

Schowalter

Grassa

(2002). Classroom amplification to enhance student performance. Teaching Exceptional Children, 34(6), 20–25. https://doi.org/10.1177/004005990203400603

17.

Dockrell

J. E.

Shield

B. M.

(2006). Acoustical barriers in classrooms: The impact of noise on performance in the classroom. British Educational Research Journal, 32(3), 509–525. https://doi.org/10.1080/01411920600635494

18.

Earthman

G. I.

(2002). School facility conditions and student academic achievement. UCLA’s Institute for Democracy, Education, and Access. https://escholarship.org/uc/item/5sw56439

19.

Estell

D. B.

Farmer

T. W.

Irvin

M. J.

Thompson

J. H.

Hutchins

B. C.

McDonough

E. M.

(2007). Patterns of middle school adjustment and ninth grade adaptation of rural African American youth: Grades and substance use. Journal of Youth and Adolescence, 36(4), 477–487. https://doi.org/10.1007/s10964-007-9167-5

20.

Foellmer

Kistemann

Anthonj

(2021). Academic greenspace and well-being—Can campus landscape be therapeutic? Evidence from a German University. Wellbeing, Space and Society, 2, 100003. https://doi.org/10.1016/j.wss.2020.100003

21.

Frank-Briggs

A. I.

Alikor

(2010). Anxiety disorder amongst secondary school children in an urban city in Nigeria. International Journal of Biomedical Science, 6(3), 246–251. https://pubmed.ncbi.nlm.nih.gov/23675199/

22.

Godovich

S. A.

Senior

C. J.

Degnan

K. A.

Cummings

Shiffrin

N. D.

Alvord

M. K.

Rich

B. A.

(2020). The role of executive functioning in treatment outcome for child anxiety. Evidence-Based Practice in Child and Adolescent Mental Health, 5(1), 53–66. https://doi.org/10.1080/23794925.2020.1727794

23.

Green

McGinnity

Meltzer

Ford

Goodman

(2005). Mental health of children and young people in Great Britain, 2004. Retrieved October 26, 2015, from http://www.hscic.gov.uk/catalogue/PUB06116/ment-heal-chil-youn-peop-gb-2004-rep1.pdff

24.

Han

K.-T.

(2009). Influence of limitedly visible leafy indoor plants on the psychology, behavior, and health of students at a junior high school in Taiwan. Environment and Behavior, 41(5), 658–692. https://doi.org/10.1177/0013916508314476

25.

Hartig

Kahn

P. H.

Jr. (2016). Living in cities, naturally. Science, 352(6288), 938–940. https://doi.org/10.1126/science.aaf3759

26.

Heschong

Wright

R. L.

Okura

(2002). Daylighting impacts on human performance in school. Journal of the Illuminating Engineering Society, 31(2), 101–114. https://doi.org/10.1080/00994480.2002.10748396

27.

Higgins

Hall

Wall

Woolner

McCaughey

(2005). The impact of school environments: A literature review. Design Council. https://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.231.7213&rep=rep1&type=pdf

28.

Juan

Y.-K.

Chen

(2022). The influence of indoor environmental factors on learning: An experiment combining physiological and psychological measurements. Building and Environment, 221, 109299. https://doi.org/10.1016/j.buildenv.2022.109299

29.

Karnik

Printz

Finkel

(2014). A hospital’s contemporary art collection: Effects on patient mood, stress, comfort, and expectations. Health Environments Research & Design Journal, 7(3), 60–77. https://doi.org/10.1177/193758671400700305

30.

Keis

Helbig

Streb

Hille

(2014). Influence of blue-enriched classroom lighting on students’ cognitive performance. Trends in Neuroscience and Education, 3(3–4), 86–92. https://doi.org/10.1016/j.tine.2014.09.001

31.

Kellert

S. R.

(2008). Biophilia. In Jørgensen

S. E.

Fath

B. D.

(Eds.), Encylcopedia of ecology (pp. 462–466). Elsevier Science. https://doi.org/10.1016/b978-008045405-4.00636-4

32.

Kessler

R. C.

Berglund

Demler

Jin

Merikangas

K. R.

Walters

E. E.

(2005). Lifetime prevalence and age-of-onset distributions of DSM-IV disorders in the National Comorbidity Survey Replication. Archives of General Psychiatry, 62(6), 593–602. https://doi.org/10.1001/archpsyc.62.6.593

33.

Sullivan

W. C.

(2016). Impact of views to school landscapes on recovery from stress and mental fatigue. Landscape and Urban Planning, 148, 149–158. https://doi.org/10.1016/j.landurbplan.2015.12.015

34.

Maldonado

Huang

Chen

Kasen

Cohen

Chen

(2013). Impact of early adolescent anxiety disorders on self-esteem development from adolescence to young adulthood. Journal of Adolescent Health, 53(2), 287–292. https://doi.org/10.1016/j.jadohealth.2013.02.025

35.

Martyn

Brymer

(2016). The relationship between nature relatedness and anxiety. Journal of Health Psychology, 21(7), 1436–1445. https://doi.org/10.1177/1359105314555169

36.

Masi

Mucci

Millepiedi

(2001). Separation anxiety disorder in children and adolescents. CNS Drugs, 15(2), 93–104. https://doi.org/10.2165/00023210-200115020-00002

37.

Mastandrea

Fagioli

Biasi

(2019). Art and psychological well-being: Linking the brain to the aesthetic emotion. Frontiers in Psychology, 10, 739. https://doi.org/10.3389/fpsyg.2019.00739

38.

Mazzone

Ducci

Scoto

M. C.

Passaniti

D’Arrigo

V. G.

Vitiello

(2007). The role of anxiety symptoms in school performance in a community sample of children and adolescents. BMC Public Health, 7(1), 1–6. https://doi.org/10.1186/1471-2458-7-347

39.

McDowell

C. P.

MacDonncha

Herring

M. P.

(2017). Brief report: Associations of physical activity with anxiety and depression symptoms and status among adolescents. Journal of Adolescence, 55, 1–4. https://doi.org/10.1016/j.adolescence.2016.12.004

40.

McLaughlin

K. A.

Hatzenbuehler

M. L.

(2009). Stressful life events, anxiety sensitivity, and internalizing symptoms in adolescents. Journal of Abnormal Psychology, 118(3), 659–669. https://doi.org/10.1037/a0016499

41.

Mikolajczyk

R. T.

El Ansari

Maxwell

A. E.

(2009). Food consumption frequency and perceived stress and depressive symptoms among students in three European countries. Nutrition journal, 8(1), 1–8. https://doi.org/10.1186/1475-2891-8-31

42.

Mohammadi

M. R.

Pourdehghan

Mostafavi

S.-A.

Hooshyari

Ahmadi

Khaleghi

(2020). Generalized anxiety disorder: Prevalence, predictors, and comorbidity in children and adolescents. Journal of Anxiety Disorders, 73, 102234. https://doi.org/10.1016/j.janxdis.2020.102234

43.

Montgomery

A. K.

(2018). Anxiety reducing drawing activities in secondary education [Master’s thesis, Moore College of Art & Design]. https://files.eric.ed.gov/fulltext/ED585255.pdf

44.

Mueller

M. A.

Flouri

Kokosi

(2019). The role of the physical environment in adolescent mental health. Health & Place, 58, 102153. https://doi.org/10.1016/j.healthplace.2019.102153

45.

Nair

(2019). Blueprint for tomorrow: Redesigning schools for student-centered learning. Harvard Education Press.

46.

Najafi

Movahed

Barzegar

Samani

(2019). The effect of ventilation by window opening on stress, anxiety, and depression of female high school students. International Journal of School Health, 6(2), 1–5. https://doi.org/10.5812/intjsh.87038

47.

Newman

M. G.

(2000). Generalized anxiety disorder. In Hersen

Biaggio

(Eds.), Effective brief therapies (pp. 157–178). Academic Press. https://doi.org/10.1016/B978-012343530-9/50010-3

48.

Ogawa

Kitagawa

Fukushima

Yonehara

Nishida

Togo

Sasaki

(2019). Interactive effect of sleep duration and physical activity on anxiety/depression in adolescents. Psychiatry Research, 273, 456–460. https://doi.org/10.1016/j.psychres.2018.12.085

49.

Okcu

Ryherd

Bayer

(2011). The role of physical environment on student health and education in green schools. Reviews on Environmental Health, 26(3), 169–179. https://doi.org/10.1515/reveh.2011.024

50.

Osborn

T. L.

Venturo-Conerly

K. E.

Wasil

A. R.

Schleider

J. L.

Weisz

J. R.

(2020). Depression and anxiety symptoms, social support, and demographic factors among Kenyan high school students. Journal of Child and Family Studies, 29(5), 1432–1443. https://doi.org/10.1007/s10826-019-01646-8

51.

Pine

D. S.

Cohen

Gurley

Brook

(1998). The risk for early-adulthood anxiety and depressive disorders in adolescents with anxiety and depressive disorders. Archives of General Psychiatry, 55(1), 56–64. https://doi.org/10.1001/archpsyc.55.1.56

52.

Rian

S. W.

Coll

K. M.

(2021). Increased exposure to nature reduces elementary students’ anxiety. Ecopsychology, 13(4), 257–264. https://doi.org/10.1089/eco.2020.0070

53.

Sakthivel

Kannappan

Panicker

A. S.

(2021). Prevalence of mental health problems among high school students. Indian Journal of Community Medicine: Official Publication of Indian Association of Preventive & Social Medicine, 46(3), 574–575. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8575203/

54.

Salingaros

N. A.

(2015). Biophilia and healing environments (pp. 1–44). Metropolis and Terrapin Bright Green, LLC. https://www.terrapinbrightgreen.com/report/biophilia-healing-environments/

55.

Schutte

A. R.

Torquati

J. C.

Beattie

H. L.

(2017). Impact of urban nature on executive functioning in early and middle childhood. Environment and Behavior, 49(1), 3–30. https://doi.org/10.1177/0013916515603095

56.

Schutz

P. A.

Pekrun

R. E.

(2007). Emotion in education. Elsevier Academic Press.

57.

Shreve

Scott

McNeill

Washburn

(2021). Using yoga to reduce anxiety in children: Exploring school-based yoga among rural third-and fourth-grade students. Journal of Pediatric Health Care, 35(1), 42–52. https://doi.org/10.1016/j.pedhc.2020.07.008

58.

Spitzer

R. L.

Kroenke

Williams

J. B.

Löwe

(2006). A brief measure for assessing generalized anxiety disorder: The GAD-7. Archives of Internal Medicine, 166(10), 1092–1097. https://doi.org/10.1001/archinte.166.10.1092

59.

Sun

Liang

Chi

Chen

(2021). Psychometric properties of the generalized anxiety disorder scale-7 item (GAD-7) in a large sample of Chinese adolescents. Healthcare (Basel, Switzerland), 9(12), 1709. https://doi.org/10.3390/healthcare9121709

60.

Thompson

R. A.

(2001). Childhood anxiety disorders from the perspective of emotion regulation. In Vasey

M. W.

Dadds

M. R.

(Eds.), The developmental psychopathology of anxiety (pp. 160–182). Oxford University Press. https://doi.org/10.1093/med:psych/9780195123630.003.0008

61.

Tong

McGonigal

Park

S.-P.

Zhou

(2016). Validation of the Generalized Anxiety Disorder-7 (GAD-7) among Chinese people with epilepsy. Epilepsy Research, 120, 31–36. https://doi.org/10.1016/j.eplepsyres.2015.11.019

62.

Ulrich

R. S.

Simons

R. F.

Losito

B. D.

Fiorito

Miles

M. A.

Zelson

(1991). Stress recovery during exposure to natural and urban environments. Journal of Environmental Psychology, 11(3), 201–230. https://doi.org/10.1016/s0272-4944(05)80184-7

63.

Vandewalle

Maquet

Dijk

D.-J.

(2009). Light as a modulator of cognitive brain function. Trends in Cognitive Sciences, 13(10), 429–438. https://doi.org/10.1016/j.tics.2009.07.004

64.

Wagner

K. D.

(2001). Generalized anxiety disorder in children and adolescents. The Psychiatric clinics of North America, 24(1), 139–153. https://doi.org/10.1016/s0193-953x(05)70210-0

65.

Wannarka

Ruhl

(2008). Seating arrangements that promote positive academic and behavioural outcomes: A review of empirical research. Support for Learning, 23(2), 89–93. https://doi.org/10.1111/j.1467-9604.2008.00375.x

66.

Weinstein

C. S.

(1979). The physical environment of the school: A review of the research. Review of Educational Research, 49(4), 577–610. https://doi.org/10.3102/00346543049004577

67.

Weng

P. Y.

Chiang

Y. C.

(2014). Psychological restoration through indoor and outdoor leisure activities. Journal of Leisure Research, 46(2), 203–217. https://doi.org/10.1080/00222216.2014.11950320

68.

Wilson

E. O.

(1984). Biophilia. Harvard University Press.

69.

Wittchen

H. U.

(2002). Generalized anxiety disorder: Prevalence, burden, and cost to society. Depression and Anxiety, 16(4), 162–171. https://doi.org/10.1002/da.10065

70.

World Health Organization. (2021, November 17). Adolescent mental health. https://www.who.int/news-room/fact-sheets/detail/adolescent-mental-health

71.

Yadusky-Holahan

Holahan

(1983). The effect of academic stress upon the anxiety and depression levels of gifted high school students. Gifted Child Quarterly, 27(1), 42–46. https://doi.org/10.1177/001698628302700107

72.

Yin

Yuan

Arfaei

Catalano

P. J.

Allen

J. G.

Spengler

J. D.

(2020). Effects of biophilic indoor environment on stress and anxiety recovery: A between-subjects experiment in virtual reality. Environment International, 136, 105427. https://doi.org/10.1016/j.envint.2019.105427

73.

(2021). Analysis of the influence of art psychology on college students’ anxiety disorder. Psychiatria Danubina, 33(suppl 8), 145–146. https://hrcak.srce.hr/file/389979

74.

Zhang

Bao

Yan

Miao

Guo

(2021). Anxiety and depression in Chinese students during the COVID-19 pandemic: A meta-analysis. Frontiers in Public Health, 9, 697642. https://doi.org/10.3389/fpubh.2021.697642

75.

Zhou

S.-J.

Zhang

L.-G.

Wang

L.-L.

Guo

Z.-C.

Wang

J.-Q.

Chen

J.-C.

Liu

Chen

J.-X.

(2020). Prevalence and sociodemographic correlates of psychological health problems in Chinese adolescents during the outbreak of COVID-19. European Child & Adolescent Psychiatry, 29(6), 749–758. https://doi.org/10.1007/s00787-020-01541-4

76.

Zhu

Haegele

J. A.

Liu

(2021). Academic stress, physical activity, sleep, and mental health among Chinese adolescents. International Journal of Environmental Research and Public Health, 18(14), 7257. https://doi.org/10.3390/ijerph18147257