A Meta-Analytic Review of Campus Open Spaces in Relation to Student Well-Being

Abstract

Spatial environments influence users’ behavioral patterns and psychological perceptions, affecting health outcomes—a professional consensus in architecture, particularly within healthy buildings. Growing attention to spatial design’s health benefits has rapidly increased quantitative research. Relationships between spatial elements (e.g., green spaces, water features, facilities) and health indicators (e.g., emotional state, mental health, physical activity) are increasingly clear. Due to collective behavior patterns on campuses, the space–health relationship is particularly pronounced. This paper examines campus open spaces via meta-analysis to explore spatial elements’ relative influence on health outcomes. After a chronological review of qualitative research, it cross-sectionally extracts quantitative data. The independent variable (“campus open space”) is categorized into natural landscapes, service facilities, and built environment (design organization). The dependent variable (“health”) is subdivided into physical health, mental health, and positive social adaptation. The main conclusions of the study are as follows: Campus open spaces significantly impact student health, with the built environment exerting the strongest influence. Combining landscape/facility elements with spatial guidance yields more significant results. Furthermore, based on the calculated impact factor data for each element, this study has developed an evaluation scale that could serve as an empirical foundation for future assessments of campus health benefits, thereby guiding health-oriented campus spatial design.

1. Background

Currently, the world still faces a complex situation characterized by the coexistence of multiple disease threats and the intertwining of various health-influencing factors. Extensive research confirms that mortality rates, epidemics, physical function, and mental health status are all associated with built environments. The Healthy China Initiative (2019–2030) states that individual behavior and lifestyle account for 60% of health-influencing factors, while environmental factors (including natural and built environments) account for 17%.

Throughout the history of public health, spatial responses to human health issues have evolved through phases: “imitating nature (pre–1500)—functional decomposition (1501–1875)—systemic organization (1875–present)” toward multidimensional interaction. The earliest De Architectura favored the positive health effects of natural elements; the Renaissance period focused on facilities to satisfy human needs; CIAM theory emphasized systematic organization to create health-conducive spaces; and Situationist International proposed architecture altering daily behaviors to avoid “sick building syndrome.” After 1990, with gradual refinement of spatial health benefit evaluation methods and tools (e.g., WHO’s “15 Principles for Healthy Housing”), a shift occurred from past government-led or healthcare-centered health practices to academic focus on health promotion.

2. Introduction

2.1. Spatial Impacts on Health and Health Promotion

Spatial design promotes health by influencing user awareness and facilitating healthy behaviors. Studies confirm that modifying everyday spaces (e.g., sidewalk design) yields significant health outcomes (e.g., exercise impacting cardiovascular health). Architecture proposes active health-promoting spaces that improve spatial experiences to facilitate the emergence of health-enhancing human behaviors [1]. Driven by growing interdisciplinary integration, contemporary studies prioritize impact mechanisms through combined methodologies from landscape architecture, public administration, psychology, public health, and preventive medicine. These approaches use quantitative data to examine how spatial elements enhance user health outcomes [2].

Current digital monitoring systems and other informatization tools serve as powerful enablers for quantitative research. These systems assess infrastructure components—such as exercise pathways, recreational parks, civic squares, and adaptable sports facilities—to preempt hazards, holistically quantify health promotion efficacy, and ultimately advance equitable health outcomes.

2.2. Evidence-Based Design

In recent years, growing scholarly attention to the relationship between built environments and health has spurred a resurgence of evidence-based design (EBD). Originally applied in healthcare architecture, EBD now extends to diverse typologies—including landscape architecture and public spaces. The core of EBD lies in its evidence-following process: collecting and analyzing empirical data to formulate design hypotheses. Quantitative research serves as a robust EBD instrument, integrating data-gathering methods, such as structured surveys and wearable sensors. Statistical analysis of this evidence ultimately generates validated design foundations [3].

The campus, as a “health cell project,” provides robust data for evidence-based design of healthy spaces, as it exhibits the following characteristics: (1) Campuses exhibit holistic consistency in spatial composition under educational institutional frameworks, while maintaining elemental specificity; (2) the spatial users (students) exhibit homogeneity in age, social consciousness, and behavioral patterns, rendering the facts reflected by the “health”-dependent variable more controlled; and (3) users exhibit high spatial dependency, with nearly 80% of behaviors and experiences occurring on campus, rendering them more susceptible to environmental influences. Consequently, examining campus space–health relationships excludes confounding variables, like modernization levels, policy support, and regional governance, yielding clearer insights.

2.3. Review of Healthy Campus Research

In previous research on population health, campuses have garnered significant attention due to their unique user groups and management models. From a health perspective, campus evolution comprises three phases. The pre-1990s featured centralized layouts under industrial efficiency paradigms. Early 20th-century tuberculosis epidemics necessitated open-air designs prioritizing ventilation and sunlight for infection control. By the 1930s, the modernist shift toward unrestricted campuses redefined functional zoning—prioritizing integrated outdoor sports areas to foster collective well-being [4]. Public health research profoundly influenced contemporaneous spatial design.

A search of the Web of Science database using “healthy space” or “healthy environment” as the keyword yielded 1190 publications. Keyword co-occurrence analysis via VOS viewer (Figure 1) identified hotspots, including elderly care, schools, and communities. Among these, 171 publications focused specifically on campuses, with publication dates concentrated between 2019 and 2025. The literature examining campus spaces’ health impacts on students primarily addresses landscape, planning layouts, and circulation paths—directly/indirectly affecting physical activity, mental health, and social engagement. Additional research foci include cold-region campus spatial adaptations [5], architectural technology studies on ventilation optimization and thermal comfort, and psychological assessments based on students’ spatial perception [6].

Current research is progressively transitioning from qualitative analysis to quantitative approaches, reflecting a disciplinary trend toward rational analysis of inter-factor relationships. However, statistical analysis methods have yet to be systematically incorporated to synthesize existing quantitative findings. This study conducts a meta-analysis of current quantitative research, leveraging sufficient sample data to refine spatial elements impacting student health and providing evidence for “healthy campus” design.

3. Materials and Methods

3.1. Meta-Analysis

Meta-analysis is maturely applied in fields such as public health, psychology, and evidence-based medicine. It quantitatively synthesizes the results of multiple studies with “the same purpose” and “mutual independence,” fits the sample sizes collected by different studies, and scientifically calculates the effect relationship between independent variables and dependent variables.

Based on the increase in the quantitative research literature on the relationship between campus environment and health in recent years, this study innovatively adopts the meta-analysis method to explore the impact of campus open spaces on the health of students, providing a theoretical basis for future campus space design.

3.2. Literature Screening

This paper used keywords, such as “campus space,” “schoolyard,” “landscape,” “facilities,” “built environments,” “health benefits,” “health,” “physical activity,” and “stress,” to conduct cross-searches in the CNKI database and the Web of Science database. Simultaneously, it used the keywords “campus design” and “health” to search for the literature from 2000 to 2025 in the domestic conference paper database and the IEEE conference paper database.

As of May 2025, there were 10,003 literature searches initially identified (2858 from CNKI, 6399 from Web of Science, 545 from IEEE proceedings, and 201 from domestic conferences). After removal of duplicate literature using EndNote 21 software, including duplicate publications of the same experimental results by identical research teams or bilingual duplicate publications of identical articles, 7852 publications remained.

Based on the meta-analysis objectives of this study, literature selection criteria required the following:

 I

Indicators from two aspects: “campus open space” and “health”;

II

Quantitative investigation of associations between campus open space elements and health indicators.

In total, 487 Chinese publications (CNKI/open access conferences) and 253 international publications were selected. After subsequent full-text review, 43 articles demonstrating statistically significant associations between “spatial elements” and “health” were identified. Most authors directly modeled spatial elements as independent variables against health-dependent variables, while others, like Saheb et al. (2021), emphasized behavioral mediation (space → behavior → health) [7]. Kiers et al. (2023) reported animal interactions (e.g., urban sheep grazing) affecting student health [8], and Meng and Xu (2023) documented emotional restoration through feline interactions (“cat petting”) during campus closures [9]. Concurrently, several studies address gender disparities, as exemplified by He (2012) discussing female participants’ heightened spatial sensitivity and more nuanced environmental requirements [10]. These studies provide refined research pathways, prompting this paper’s focus on primary spatial health mechanisms, with subsequent subgroup heterogeneity analysis in later sections.

Based on the requirements of the meta-analysis software used in this study (Comprehensive Meta-Analysis V3) regarding input for sample size and Pearson correlation coefficients, studies meeting the following criteria were excluded:

  I

Articles whose evaluation data could not be converted to correlation coefficients (e.g., variance data);

 II

Studies where the impact mechanism relied on mediating variables (e.g., behavior);

III

Research excessively focused on a single element (e.g., animals on campus).

Two independent coders applied the aforementioned inclusion/exclusion criteria to conduct a two-phase review of article abstracts and full texts, as illustrated in Figure 2. The literature ultimately selected for analysis achieved 91% inter-coder reliability, confirming valid and accurate results, as presented in

Table 1. List of literature information included in the meta-analysis computation [4,5,6,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29]. (source: Author).

Author	Year	Study Design	Sample Size	Gender (M/F)	Spatial Variables	Health Metrics	Title
Kim et al. [11]	2021	Interviews	38	1.714	①	②	The Influence of Forest Activities in a University Campus Forest on Student’s Psychological Effects
Liu et al. [12]	2025	Surveys	818	1.353	①②	②	Assessing the Restorative Effects of Campus Greenness on Student Depression: A Comparative Study Across Three Distinct University Campus Types in Maca
Nie et al. [13]	2024	Surveys	2528	1.212	①	②	The Varied Restorative Values of Campus Landscapes to Students’ Well-Being: Evidence from a Chinese University
Peng et al. [14]	2024	Interviews	139	0.527	①②③	②	A Study on the Relationship between Campus Environment and College Students’ Emotional Perception: A Case Study of Yuelu Mountain National University Science and Technology City
Wen et al. [15]	2025	Surveys	630	1.432	①②③	①②③	Analysis of the Characteristics of University Common Spaces That Affect University Students’ Psychological Restoration
Yin et al. [16]	2024	Smart Devices	320	0.778	①	①②	Exploring the Impact of Autumn Color and Bare Tree Landscapes in Virtual Environments on Human Well-Being and Therapeutic Effects across Different Sensory Modalities
Zeng et al. [17]	2025	Smart Devices	8	1	①	②	Exploring the Impact of Daytime and Nighttime Campus Lighting on Emotional Responses and Perceived Restorativeness
Liu and Gan [4]	2020	Government Data	2913	-	②③	①	Exploring Campus Design from a Health Promotion Perspective
Lu [18]	2023	Surveys	164	0.763	①③	C	Research on Outdoor Space Design of University Campuses Guided by “Active Health”
Wu [6]	2021	Surveys	487	1	①③	②③	Research on Healing Landscape Design in Middle School Campuses Based on Biophilic Theory
Sun et al. [19]	2023	Surveys	819	-	①②	②	Impact of Campus Environment on Psychological Restoration of University Students in the Post-Pandemic Era
Cui [20]	2021	Surveys	389	1.275	①③	①②③	Research on Landscape Evaluation of University Campus External Spaces under Health Demands
Zhang [21]	2022	Surveys	207	0.897	①②③	①②③	Research on Design Strategies for University Campuses in Guangzhou from a Health Promotion Perspective
Zhang [22]	2024	Surveys	213	0.762	①③	②	Research on the Impact Pathway of Campus Green Spaces on University Students’ Mental Health
Zhang [23]	2022	Surveys	299	0.89	②③	C	Promotion Mechanism of Supportive Campus Environments for Adolescent Health Behaviors in High-Density Settings
Zhang [24]	2018	Surveys	192	1	①②③	C	Research on the Restorative Impact of Healthy Landscapes in University Campuses on College Students
Xu et al. [25]	2024	Surveys	295	1.174	①②③	C	Impact of Secondary School Environments on Adolescent Health Promotion: Empirical Test Using Physical Activity as Mediating Variable
Li [26]	2023	Smart Devices	24	1	①③	①②	Research on Outdoor Space Characteristics of University Campuses Based on Emotional Mapping
Gan and Liu [27]	2024	Surveys	2158	-	①②③	C	Impact Mechanism and Empirical Research of “Space-Health” in Primary and Secondary Schools
Chen [5]	2019	Surveys	343	0.695	①②③	C	Construction of an Evaluation Index System for Open Spaces in Cold-Region Campuses Affecting University Students’ Health
Ma [28]	2024	Smart Devices	60	0.875	①②③	①②	Research on the Influence of Audiovisual Environmental Factors in Campus Pedestrian Spaces on Emotional Perception
Wei [29]	2020	Surveys	644	-	①②③	C	Research on the Impact of Restorative Environments in University Campuses on Student Health: Case Study of Jinshan Campus, Fujian Agriculture and Forestry University

Note: Spatial variables include ① natural landscape, ② service facilities, and ③ built environment (design organization). Health metrics include ① physical well-being, ② mental well-being, and ③ social well-being.

.

3.3. Data Extraction

Combining professional background knowledge, the element indicators associated with the independent variable (campus open space) and the dependent variable (health status) were analyzed as follows.

Regarding the independent variable “campus open space”: I. As stated in the background, the author conducted a diachronic study of historical spatial responses to health issues. The theoretical model identifies nature, function, and systematic organization as core approaches architects historically developed by integrating cognition and technology. II. Qualitative literature findings also explicitly point to these three directions, as evidenced by the following studies: Aghabozorgi et al. (2024) [30] demonstrated nature’s irrefutable effects on healing emotions and guiding behaviors. Li (2020) [2] proved that detaching functions and providing facilities promote health. Zhang (2016) [1] demonstrated that designed spatial experiences facilitate health-enhancing behaviors through playful guidance. III. Current quantitative articles use diverse methods—subjective surveys, statistical analysis, literature review, interviews, focus groups, and Delphi expert evaluation—to categorize campus elements impacting health, reaching largely consistent conclusions. This will be elaborated in Section 4.1 (Data Analysis).

Regarding the dependent variable “health,” nearly all the reviewed literature relies on WHO’s definition: physical health, mental health, and positive social adaptation. Measurement approaches include subjective descriptions, questionnaire responses, and smart device data collection. All processed data were categorized into these three dimensions.

4. Results

4.1. Data Analysis

In addition to the basic study information (author, year, sample size) presented in the list, there is variability in how different studies describe the involved variables and indicators. In the current literature, Wei (2020) [29] used subjective survey methods for independent variable selection, conducting field visits to target campuses to perceive spatial elements on-site and categorize them into natural elements, artificial elements, and perceptual elements. Zhang (2022) [21] used statistical analysis methods, consolidating environmental elements mentioned in the qualitative literature into four categories: built environment, perceptual environment, natural environment, and socio-cultural factors. Lu (2023) [18] adopted literature review plus interview methods, extracting 24 evaluation indicators from 84 campus elements, classified into natural elements, facility elements, and spatial elements. Chen (2019) [5] supplemented these with focus groups and Delphi method expert evaluations, assessing indicator comprehensibility from participants’ perspectives and variable necessity from experts’ viewpoints. Campus space elements were categorized as landscape elements, public facilities, and design methods. Zhang (2018) [24] deduced spatial elements from health demand theory, enumerating corresponding indicators across natural and built space and facility demands. Gan and Liu (2024) [27] reverse-engineered environmental determinants using empirical disease causation data from medical and public health research. Though methodologies differ across studies, results show substantial consistency—likely attributable to the three aforementioned characteristics of campus open spaces as research subjects.

After synthesizing the sub-elements under these different classifications from various studies [30,31], the input data were grouped into three major categories, ① natural landscape, ② service facilities, and ③ built environment (design organization), which are identified in Table 1.

Assessment of health benefits is now well established, with current research across disciplines, including medical science, public health, and spatial sociology, uniformly adopting WHO’s multidimensional health framework comprising ① physical well-being, ② mental well-being, and ③ social well-being. Simultaneously, within environmental-behavioral research, academician Li Daozeng proposed the concepts of physical functional disorder, psychological maladjustment, and socio-environmental dysfunction. This study also uses these three output indicators for assessment. Multiple studies, drawing on research such as the “biophilia hypothesis,” “attention restoration theory,” and “stress recovery theory,” have used data like activity intensity, lung capacity compliance, restorative assessment, self-rated anxiety, self-rated stress, root mean square of successive differences (RMSSD), standard deviation of NN intervals (SDNN), and positive and negative affect schedule (PANAS) to express health status. Some research literature directly used the concept of “health” to calibrate variables, with data based on subjects’ overall self-assessment of their health status, identified as C (combine) in Table 1.

Based on the aforementioned findings, this paper proposes the following hypotheses regarding the relationship between campus spaces and student health, grounded in professional expertise and literature data:

H1. 

Well-designed campus spaces exert a significantly positive effect on student health outcomes.

H2. 

Spatial elements are ranked as follows in terms of health impact efficacy: natural landscapes > built environments (designed organization) > public facilities. During spatial experiences, implicit cues prove more impactful than installed fitness equipment.

H3. 

Regarding health benefits, campus open spaces directly facilitate outdoor social activities and health-promoting behaviors. Deliberately designed spaces enhance students’ willingness to engage outdoors. Under collective living patterns, spaces contribute more to social and physical health than to psychological comfort.

4.2. Effect Size Calculation

Given that various cross-sectional studies have independently sampled spatial and health factors, the findings are subject to influences such as the richness of campus spaces, student disciplinary distribution, and data collection methods, resulting in substantial heterogeneity (I² > 75%). Drawing on analytical models for similar variables in the academic literature, this paper uses a random-effects model to conduct a revised analysis of the results.

Some literature used the regression coefficient (β) with the t-statistic and the F-statistic to express effect sizes. These were all converted to Pearson correlation coefficients (r) using Formulas (1) and (2). Additionally, for cases where multiple similar indicators existed under the same element category (e.g., spatial enclosure and the D/H ratio), the author calculated their weighted average after merging and then input the data into the software.

$$r=\frac{F}{\sqrt{F+N-2}} (\mathrm{N}=\mathrm{sample} \mathrm{size})$$

(1)

$$r=\frac{t}{\sqrt{t^2+N-2}} (\mathrm{N}=\mathrm{sample} \mathrm{size})$$

(2)

In summary, the total input sample size for this computation was 66. The reported correlation coefficient is 0.416, with a lower limit of 0.338 and an upper limit of 0.488. This value, falling between 0.3 and 0.5, indicates a moderate correlation between campus space and the health status of students on campus. The reported Z-value is 9.559, and the reported p-value is 0.000 < 0.005, indicating that the result is statistically significant. The reported Tau squared is 0.133, with a standard error of 0.039. The between-study variance (tau) is 0.365. The effect sizes of individual studies and their 95% confidence intervals are shown in Figure 3.

Based on the calculations, hypothesis 1 is supported. Campus space has a significant positive impact on the health status of students on campus, with a correlation coefficient of 0.416 (p = 0.000). Hypothesis 2 is not fully supported. According to the reported results, the effect sizes for health benefits across subgroups are as follows: service facilities (r = 0.242, p = 0.003) < natural landscape (r = 0.439, p = 0.000) < built environment (design organization) (r = 0.510, p = 0.000). This indicates that the design of built space is, to some extent, more important than providing students with access to nature. This conclusion is corroborated by the study “Health-Promoting Behaviors and Psychosocial Well-Being of University Students in Hong Kong” (Lee and Loke 2005) [32], which mentions that natural landscapes need to be integrated with path guidance to exhibit more pronounced health promotion effects.

Hypothesis 3 is substantiated. Analysis using the dependent variable indicators (physical health, mental health, good social adaptation) as grouping criteria shows the following sample distribution: physical health (n = 16), mental health (n = 23), good social adaptation (n = 8), and undifferentiated combined input (combine, n = 19). The calculated effect sizes are physical health 0.521 (Z-value 7.104, p-value 0.000), mental health 0.315 (Z-value 4.625, p-value 0.000), good social adaptation 0.746 (Z-value 3.349, p-value 0.001), and combine data 0.252 (Z-value 6.241, p-value 0.000). Regarding the magnitude of influence on dependent variables, campus open spaces demonstrate stronger effects on social adaptation (r = 0.746) and physical health (r = 0.521). Diverse campus spaces primarily attract students to leave dormitories and spontaneously organize activities. Even simple walks with friends subtly modify daily behaviors, while natural landscapes further facilitate psychological restoration.

4.3. Publication Bias Test

Based on the publication bias test results, the Figure 4 (Funnel plot of standard error by Fisher’s Z) was generated. It can be observed that the current distribution of the literature is relatively symmetric around the mean effect size and concentrated at the top of the funnel plot, indicating no significant publication bias was detected. Further data from the classic fail-safe N showed that the current conclusion would only potentially change after the inclusion of an additional 5027 unpublished studies. Given that this study has conducted a comprehensive search of databases up to May 2025, no significant publication bias exists in the current literature.

5. Discussion

5.1. Differences in Subgroup Analysis Results

Based on the discussion of differences in factor extraction methods across studies in Section 3.1 and the discussion of sample heterogeneity across studies in Section 3.2, this study further discusses the influencing factors of sub-elements separately to more accurately present the content of elements and provide a framework for future research. In the current literature, Zhang (2018) [24] surveyed environmental perceptions of 825 space users, forming a list of 25 spatial elements; Chen (2019) [5] developed 23 spatial element indicators based on scoring results from three-round Delphi expert questionnaires; Lu (2023) [18] adopted literature reviews combined with interviews, extracting 24 evaluation indicators from 84 campus-covered elements, etc. [33,34,35,36,37]. These extracted independent variable elements do not fully overlap. This paper conducts translational coding on overlapping samples to further derive the following conclusions.

Regarding natural landscape elements in the literature, the most frequently mentioned are paths (n = 27) and landscape ratio (n = 20), followed by plant species (n = 11), sound (n = 11), topography (n = 7), and water features (n = 7). Fewer papers mention color richness (n = 5), animals (n = 3), and sunlight conditions (n = 2), as demonstrated in Figure 5. Due to insufficient dependent variable data, the correlation coefficients for the latter three items are not representative and have been omitted. Analyzing the correlation coefficients reported in different studies using the software, the health benefit values for the top six elements are as follows: water features (0.633) > green space ratio (0.532) > paths (0.484) > sound (0.464) > plant species (0.447) > topography (0.228). This suggests that in the creation of natural environments, blue space (water features) plays a significant regulatory role, while the landscape ratio remains the primary overall consideration, and the planning of landscape paths greatly influences users’ health benefits. However, the p-value for topography is 0.106, indicating non-significance (p > 0.05).

Regarding service facility elements, the most frequently mentioned are facility accessibility (n = 24), facility quantity (n = 16), and pavement (n = 8), as demonstrated in Figure 6. Results generally indicate that the overall correlation between service facilities and health (0.369) is lower than that between natural landscape and health. Among these, pavement has a low correlation (0.044) and is non-significant. Facility accessibility (0.386) and facility quantity (0.369) show similar values. Notably, multiple studies have mentioned that the rational use of guiding facilities is more important than increasing their quantity, which aligns with the calculation results. The placement of facility zones on campus, such as playgrounds and sports equipment, should focus more on their intersection with students’ daily circulation routes to facilitate access with minimal effort.

Regarding the extraction of built environment (design organization) elements, consistent with architectural knowledge frameworks, the elements mentioned include building enclosure (n = 19), privacy (n = 4), safety (n = 9), building density (n = 3), diversity (n = 24), and artistic merit (n = 20), as demonstrated in Figure 7. Contrary to what architects typically focus on in campus design, the building density indicator is deprioritized. The author attributes this to the predominant use of questionnaire surveys in current research, where questions are primarily designed from a personal experience perspective, making it difficult to incorporate macro-level discussions on “building density.” Consequently, results need to be interpreted through elements like enclosure and safety/shelter. Calculations generally indicate that design organization elements have a greater impact on health than natural landscape elements, with the ranking being privacy (0.639) > artistic merit (0.577) > spatial diversity (0.574) > building enclosure (0.517) > safety/shelter (0.462) > density (0.197). The analysis reveals that within spatial experiences, discrete spaces exhibit significantly stronger correlations with health benefits in terms of privacy, artistic merit, and diversity. While building density reflects whole planning layouts to some extent, it is these discrete spaces that catalyze behavioral engagement—thereby enhancing users’ physical activity and psychological well-being, ultimately fostering diverse social interactions within their boundaries.

Based on the correlation coefficients reported by the software, the subgroups are summarized and ranked in

Table 2. Health benefits calculated by component. (source: Author).

Spatial Variables	Subgroups	Correlation	p-Value
Natural landscape	Landscape ratio	0.532	0.000 ***
	Paths	0.484	0.000 ***
	Water features	0.633	0.000 ***
	Plant species	0.447	0.000 ***
	Sound	0.464	0.005 **
	Topography	0.228	0.106
Service facility	Facility quantity	0.393	0.000 ***
	Facility accessibility	0.386	0.000 ***
	Pavement	0.044	0.865
Built environment (design organization)	Building enclosure	0.517	0.000 ***
	Safety/shelter	0.462	0.000 ***
	Privacy	0.639	0.001 **
	Density	0.197	0.000 ***
	Spatial diversity	0.574	0.000 ***
	Artistic merit	0.577	0.000 ***

Note: ** p < 0.01, and *** p < 0.001 (p > 0.05 defined as non-significant).

.

5.2. Practical Guidance for Campus Open Spaces

Based on the calculation data in Table 2, this section provides the following interpretation of the spatial elements with the greatest health benefits in campus open spaces. Under collective living patterns, the creation of private spaces on campus most effectively triggers students’ participation in outdoor activities. Chen (2019) [5] defined this as “a feeling of being able to observe without being noticed.” Ma (2024) [28] termed it “visual entropy,” referring to more variations presented in small-scale spaces. Lu (2023) [18] described it as a strong sense of spatial definition, while Cui (2021) [20] characterized it as non-open spaces suitable for activity scales of different intimate groups. Such private spaces respond to students’ preference for “personal space,” making them feel outdoor activities are relaxing and free from scrutiny, thereby greatly enhancing activity initiative.

The author confirmed this through field research, as demonstrated in

Table 3. Privacy in open spaces across three universities. (source: Author).

Time Square at the Beijing University of Posts and Telecommunications	South Gate Square at Beijing Jiaotong University	The vast open square in front of the main building at Beijing Normal University

: Small-scale squares attract more students to linger, such as the Time Square at the Beijing University of Posts and Telecommunications and the South Gate Square at Beijing Jiaotong University. In contrast, the vast open square in front of the main building at Beijing Normal University remains nearly deserted due to its excessively unobstructed sightlines.

Water features rank second in health benefit value, surpassing green spaces, which the author believes may be related to their scarcity on campuses. A GIS survey of 28 universities in Haidian District, Beijing, revealed that only five have permanent water bodies (excluding intermittent artificial fountains or temporary installations): Peking University’s Weiming Lake (68,869.6 sq m), Tsinghua University’s Lotus Pond (77,790.92 sq m), Renmin University of China’s Ladle Pond (1526.86 sq m), Beihang University’s Lotus Pool (4322.8 sq m), and Beijing Jiaotong University’s Ming Lake (4834.32 sq m). Iconic lawns, however, cover almost all campuses. Within these universities, water features, indeed, become preferred activity spaces, forming unique spatial memories.

Next are artistic merit, spatial diversity, and green space percentage, exemplified in

Table 4. Artistic merit, spatial diversity, and percentage of green space in two universities. (source: Author).

University	Artistic Merit	Spatial Diversity	Green Space Percentage
Beijing Normal University
Beijing Jiaotong University

. The author notes that spaces containing landmark nodes often serve as meeting points for student outdoor activities, suggesting that campus cultural identity plays a role in promoting outdoor engagement.

Overall, based on health benefit values calculated per element, campus health assessments should rely more on architects’ meticulous spatial experience design than on blind pursuit of quantifiable metrics, like density, pavement ratio, or facility quantity—elements that show low correlation in this study. The necessary paths for student movement are classroom buildings–canteens–dormitories. Activity venues intersecting these paths help trigger random health-promoting behaviors, such as post-meal walks on sports fields or post-class activities.

5.3. Limitations of the Study

The limitations of this study lie in the constraints imposed by the current base of quantitative research literature. The data screening and related calculations in various studies exhibit a degree of randomness, and the academic community has not yet established a unified variable classification system or standardized health assessment methodology. Furthermore, while this study notes that using intelligent collection equipment to acquire heart-rate-related data (such as the RR, mean, RMSSD, and SDNN) can eliminate interference from subjects’ subjective bias and enhance the reliability of conclusions, the current experimental sample size remains small. Only three papers mention such data, involving fewer than 100 subjects. Consequently, the method of questionnaires combined with interviews remains the primary pathway for data acquisition in this research domain.

Another limitation lies in the insufficient gender-disaggregated data in current foundational literature. However, preliminary conclusions indicate female behavior and emotions are more susceptible to the external environment, aligning with conclusions from the study “Research on the Emotional and Behavioral Experience of Female Users in University Outdoor Spaces” (He, 2012) [10]. The study involved samples with near-equal gender ratios or unspecified ratios (n = 19), group I (female subjects > male subjects, n = 29), and group II (male subjects > female subjects, n = 18). The reported effect size for group I is 0.379 and for group II is 0.302. The reason for the similar effect sizes may be the relatively small difference in sample sizes and the fact that the research literature represents random sampling outcomes, which did not specifically focus on investigating the impact of gender differences. In future research, greater attention to female needs in spatial design may be an effective pathway to improving overall health benefits.

6. Conclusions

This study conducted a meta-analysis of the existing literature on “the influence of campus open spaces on student health.” First, we identified consistent campus open space elements from the literature to form consensus-based groupings. Second, we calculated health benefit impact factors for each element and subgrouping using Comprehensive Meta-Analysis V3 software. Finally, by integrating architectural expertise and campus design practices, we translated these elements into the implementable design solutions presented in

Table 5. Campus spatial element evaluation form. (source: Author).

Spatial Variables	Design Consideration Weighting	Subgroups	Component Weighting	Actionable Items
Natural landscape	0.439	A1 Landscape Ratio	0.532	A1.1 Visual Green Space
				A1.2 Accessible Green Space
		A2 Paths	0.484	A2.1 Connectivity
				A2.2 Path Curvature
				A2.3 Walkability Index
		A3 Water Features	0.633	A3.1 Water Surface Area
				A3.2 Shoreline Morphology
				A3.3 Hydrophilic Design
		A4 Plant Species	0.447	A4.1 Tree Species Diversity
				A4.2 Chromatic Diversity
		A5 Sound	0.464	A5.1 Natural Sounds
				A5.2 Noise Buffering
		A6 Topography	0.228	A6.1 Elevation Change
				A6.2 Terrain Configuration
Service facility	0.242	B1 Facility quantity	0.393	B1.1 Campus Clinic Configuration
				B1.2 Municipal Hospital Configuration
				B1.3 Gymnasium Configuration
				B1.4 Sports Field Area
				B1.5 Quantity of Activity Facilities
				B1.6 Quantity of Benches
		B2 Facility Accessibility	0.386	B2.1 Dorm–Cafeteria–Classroom Path Intersection with Sports Fields
				B2.2 Walking Distance Between Sites
				B2.3 Road Attraction
		B3 Pavement	0.044	B3.1 Hard Surfacing Degree
Built environment (design organization)	0.510	C1 Building Enclosure	0.517	C1.1 Space D/H Ratio
				C1.2 Enclosure Ratio
				C1.3 Visual Permeability
		C2 Safety/Shelter	0.462	C2.1 Safety Perception
				C2.2 School Distance from Main Road
				C2.3 Dorm–Cafeteria–Classroom Path Intersection with Parking Lot Path
		C3 Privacy	0.639	C3.1 Sightline Design
		C4 Density	0.197	C4.1 Sky View Factor
				C4.2 Density
		C5 Spatial Diversity	0.574	C5.1 Spatial Hierarchy
				C5.2 Elevation Design
				C5.3 Skyline Variation Index
				C5.4 Functional Zoning
		C6 Artistic Merit	0.577	C6.1 Spatial Identity
				C6.2 Theme of Structures
				C6.3 Aesthetic Characteristics

. This table serves as a foundational framework for future campus health benefit assessments, effectively mitigating research gaps through comprehensive element inclusion. Building upon this foundation, the content will undergo progressive refinement as additional campus sample data become available, thereby providing substantiated evidence to advance spatial design solutions.

Computational findings demonstrate that campus design must foreground the role of built environments (design organization) in guiding student social interactions—specifically through creating spaces with privacy and artistic qualities, such as deploying visual barriers to mitigate administrative oversight. This conclusion resonates with societal perceptions of university-aged individuals pursuing spiritual selfhood and distinctiveness. Engineering practice reveals that establishing iconic campus spaces to strengthen student identity, coupled with integrating aesthetic and thematic structures, stimulates self-expression among youth, which, in turn, directly catalyzes diverse outdoor behavioral patterns.

Adequate green spaces and dynamic water features correspond to conventional perceptions of healthy outdoor elements. Design implementation requires careful attention to the ratio between A1.1 Visual Green Space and A1.2 Accessible Green Space—for instance, supplementing large ceremonial lawns (often inaccessible during non-events) with accessible groves and shrubbery. Regarding water features, while blue space size (A3.1 Water Surface Area) matters, waterfront activity diversity is more directly influenced by A3.2 Shoreline Morphology and A3.3 Hydrophilic Design.

Service facilities (e.g., fitness equipment, sports amenities, venue areas), traditionally emphasized in policy and management, yield limited benefits when implemented in isolation. Integrating them with pathway systems significantly enhances health promotion effectiveness. This study innovatively proposes quantifying B2.1 Dorm–Cafeteria–Classroom Path Intersection with Sports Fields to explore opportunities for triggering health behaviors along essential routes.

Beyond these explicit practical recommendations, the table quantitatively deconstructs every health-benefit-assigned component—exemplified by A2 Paths with A2.1 Connectivity, measured by road area to site area ratio; A2.2 Path Curvature, expressed as path length divided by straight-line distance; and A2.3 Walkability Index assessed through questionnaire scoring—though defining optimal ranges for these metrics requires further research. These quantified options standardize case studies to a uniform granularity, providing a foundation for future integration of research findings (e.g., meta-analysis).

It bears re-emphasizing that campus design should recognize that the influence of spatial guidance on behavior occurs in a larger proportion in daily (non-exercise) activities, such as walking, club activities, and discussions. The student population has a high demand for social interaction. Promoting social interaction behaviors can reduce the probability of occurrences of physical functional disorder and psychological maladjustment.