Landscape Preferences and Garden Visit Frequency of Special Education Teachers in School Gardens: A Comparative Study between Zhejiang and Shandong Provinces, China

Landscape Preferences and Garden Visit Frequency of Special Education Teachers in School Gardens: A Comparative Study between Zhejiang and Shandong Provinces, China | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Landscape Preferences and Garden Visit Frequency of Special Education Teachers in School Gardens: A Comparative Study between Zhejiang and Shandong Provinces, China Anqi Liu, Mohd Yazid Mohd Yunos, Shureen Faris Abdul Shukor, Mohd Sallehudin Mat Noor This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7896138/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Special education teachers often experience high levels of psychological stress and emotional fatigue due to demanding workloads and sustained interactions with students with disabilities. School gardens can serve as restorative environments to mitigate this stress and enhance overall well-being. However, empirical evidence on plant landscape preferences and garden use patterns among this group in China remains scarce. This study surveyed 228 teachers from four special education schools in Zhejiang and Shandong provinces to examine their preferences for eight landscape features, using a structured questionnaire and visual simulation images. The influence of visit frequency on these preferences was further examined through multinomial logistic regression analysis. Results revealed notable regional differences: teachers in Zhejiang favored larger green areas (80.7% preferred semi- or fully covered spaces) and medium to dense floral plantings, whereas those in Shandong preferred simpler, sparser designs. Frequent visitors showed a preference for open spaces with 50% − 70% shade and high spatial legibility. In Shandong, frequent visitors significantly avoided highly enclosed layouts (OR = 0.05, p = 0.002) and preferred moderate shading (OR = 0.06, p = 0.005). These findings highlight the importance of tailoring school garden designs to regional and usage patterns to support psychological restoration and encourage use among teachers. This study offers practical insights into the design of restorative green spaces in special education settings. Earth and environmental sciences/Environmental social sciences Biological sciences/Psychology Social science/Psychology special education teachers school garden landscape preference visual assessment psychological restoration regional differences Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 1. Introduction Special education teachers often face high psychological stress and emotional exhaustion due to heavy workloads and continuous interaction with students with cognitive or behavioral disorders. School gardens, often seen as restorative environments, can help alleviate psychological stress, promote overall health, and improve job satisfaction among teachers (Hoover et al., 2021 ; Ohly et al., 2016 ). Beyond offering green space, the plant landscape design plays a role in shaping aesthetic experiences, enhancing environmental appeal, and supporting social and relaxation activities (Akoumianaki-Ioannidou et al., 2016 ). While many studies have explored the benefits of urban green spaces and general school landscapes on psychological recovery (Guardino et al., 2019 ; Chen & Hamel, 2023 ; Ozturk & Ozer, 2022 ), little empirical research has examined how special education teachers use and perceive plant landscapes. Particularly in China, many special education schools lack adequate garden facilities, with insufficient diversity and refinement in design. Moreover, systematic studies focusing on this group’s specific needs and preferences remains scarce (Liu, 2024 ; Wang, 2020 ). Given the professional challenges and stress faced by special education teachers, understanding their preferences and usage patterns is crucial for improving campus design and supporting their well-being (Loukas & Mania, 2021 ; Lappa et al., 2017 ). Many studies have shown that specific landscape elements are key predictors for enhancing school garden quality and promoting psychological recovery. Larger green areas improve spatial openness, ecological atmosphere, and mental well-being (Tudorie et al., 2020 ; Kang & Jeong, 2019 ). Plant enclosures influence teachers’ relaxation and social experience by regulating privacy and visual security (Liu & Schroth, 2019 ). Diverse plant colors and rich vegetation structures enhance visual diversity, aid emotion regulation, and support biodiversity education (Sheng et al., 2023 ; Hodson & Sander, 2017 ; Wang & Zhao, 2017 ; Zhang et al., 2024 ). High floral density improves attractiveness and emotional recovery through color and fragrance (Mani et al., 2024; Nedovic & Morrissey, 2013 ). Adequate natural shading enhances microclimate comfort and encourages longer stays (Hami & Abdi, 2021 ). Water features foster psychological relaxation and spatial attachment via multisensory experiences (Bozkurt & Woolley, 2020 ; Polat & Akay, 2015 ). Diverse seating options meet needs for privacy, safety, and social interaction, shaping stay behaviors (Tao et al., 2023 ; Alataş et al., 2024 ). However, most studies on special education school gardens focus on macro layouts or greening rates (Wang et al., 2023 ; Hussein, 2015 ), lacking quantitative analysis of micro plant elements. Therefore, this study selected eight key variables and used a visual-based preference questionnaire to systematically examine their effects on teachers’ preferences, aiming to provide empirical evidence for precise garden design and mental health support. Moreover, teachers’ garden preferences are closely linked to their actual visit frequency. Visit frequency not only indicates teachers’ dependence on and motivation to use these spaces but also shapes their long-term adaptation and preferences for specific landscape features (Kim et al., 2023 ; Cai et al., 2022 ). For instance, frequent visitors often prefer open, varied, and moderately shaded spaces that feel comfortable even with repeated use. In contrast, those who visit less frequently tend to focus more on the visual impact or special features of the landscape (Yang et al., 2023 ). Yet, there is still a lack of research on how landscape preferences differ across group with different visit frequencies, especially in special education schools within in Chinese context (Xue et al., 2017 ; Zhou et al., 2023 ). Examining these differences in depth is crucial for designing campus green spaces that better meet teachers’ diverse needs and encourage participation. Zhejiang and Shandong provinces differ greatly in geography, climate, vegetation, and campus greening practices. Zhejiang has a humid subtropical monsoon climate and abundant vegetation, while Shandong experiences a temperate monsoon climate with distinct seasons and more limited greenery (Yin et al., 2023 ). These regional differences not only influence technical aspects of landscape design but may also shape teachers’ aesthetic preferences and spatial needs (Wang et al., 2021 ). Therefore, comparing teachers’ landscape preferences across regions can help reveal their diverse needs and support campus garden designs that better fit local contexts. In short, this study examines the relationship between special education teachers’ landscape preferences and their patterns of using school gardens, focusing on teachers in Zhejiang and Shandong provinces. The main objectives are: (1) to compare how often teachers in the two regions visit school gardens; (2) to analyze their preferences for different landscape elements; and (3) to explore how these preferences vary by visit frequency. By revealing the links between usage behavior and aesthetic preference, this research aims to improve garden design, support teachers’ psychological recovery, and improve space utilization. 2. Methods 2.1 Study sites This study was conducted in four public special education schools in Zhejiang and Shandong provinces, China (Fig. 1 ), with two schools in each province. Zhejiang is in eastern China, has a subtropical monsoon climate with abundant rain and rich vegetation, creating favorable conditions for school gardens. The two schools in Zhejiang Province participating in the study are in Hangzhou (30.27°N, 120.15°E) and Lishui (28.47°N, 119.92°E). Both are large public schools with well-developed green spaces and diverse plantings designed to support teaching and promote teachers’ mental well-being. In contrast, Shandong lies in northern China and has a temperate monsoon climate, featuring distinct seasons and less rainfall. The two Shandong schools are in Linyi (35.10°N, 118.35°E) and Weifang (36.71°N, 119.10°E). These schools have medium-sized gardens, used mainly for basic functions and aesthetic purposes. Choosing these four schools helps capture differences in climate, vegetation, and garden management across regions, providing a foundation for analyzing teachers’ landscape preferences in varied environmental contexts. 2.2 Sample size and distribution Using a cross-sectional comparative design, this study examined differences in campus landscaping preferences among special education teachers in Zhejiang and Shandong Provinces. Two public special education schools with similar sizes, greening conditions, and management were selected in each province for the survey. In Zhejiang, 122 questionnaires were distributed, with 114 valid responses collected (validity rate: 93.4%); in Shandong, about 120 questionnaires were distributed, aiming for 114 valid samples to ensure statistical power and comparability. Sample size was determined using Pearson’s chi-square test (α = 0.05, power = 0.80, effect size w = 0.3), requiring at least 88 samples per group (Faul et al., 2009 ). Considering possible invalid responses, the final target sample size in each province was set at 114 (Wang & Ji, 2020 ). To control confounding factors, schools were matched on teacher composition and curriculum, ensuring regional differences remained the focus. 2.3 Visual materials and preference evaluation Visual or aesthetic preferences are often assessed using photographs or images in questionnaires, surveys, or interviews, which help illustrate existing landscapes and simulate future designs, thus informing planning and design decisions (Lindemann-Matthies & Köhler, 2019 ). Following Allahyar & Kazemi’s ( 2021 ) approach, this study used a structured questionnaire with visual aids to systematically assess special education teachers’ landscape preferences. The questionnaire’s reliability and validity were confirmed by four horticulture and landscape experts and two special education experts. It consisted of two parts: teachers’ garden use frequency to understand actual space utilization, and preferences for plant landscape elements, supported by images to aid intuitive responses. The content was carefully refined to reduce response fatigue. Unlike studies using only site photographs, this study created color digital simulation images through 3D modeling in SketchUp and rendering in Adobe Photoshop, allowing precise control of landscape elements and eliminating background interference. All design elements were shown against a uniform background to minimize non-design influences on preferences, following methods by Salih et al. ( 2023 ) and Wang & Zhao ( 2017 ) to enhance respondents’ understanding. Images, presented in color with textual descriptions, were distributed via an online questionnaire to special education teachers to collect their landscape preferences. This method, effective in urban recreation and university campus studies (Wang & Rodiek, 2019 ; Hami & Abdi, 2021 ), was further adapted here to explore campus garden preferences. 2.4 Landscape features Building on research on landscape preferences and visual perception in special places and school settings (Salih et al., 2023 ; Zhang et al., 2024 ; Allahyar & Kazemi, 2021 ; Wang et al., 2023 ), this study designed eight landscape features to examine their influence on teachers’ aesthetic preferences and behavioral intentions in special education schools. These features included: green space area (Fig. 2 ), with four options: without greenery, greenery occupies 1/4 of the total space, greenery occupies half of the total space, and greenery fills the entire space; planting enclosure structure (Fig. 2 ): one-sided enclosure, two-sided enclosure, three-sided enclosure, and fully enclosed planting; plant color (Fig. 3 ): no additional color, warm colors, cool colors, and neutral colors; planting structure (Fig. 3 ): open lawn, trees only, trees with sparse shrubs, and trees with dense shrub and ground cover; flower planting density (Fig. 4 ): no flowers, sparse clusters, moderate continuous clusters, and dense continuous clusters; natural shading ratio (Fig. 4 ): less than 30% of the pathway, between 30% and 50% of the pathway, between 50% and 70% of the pathway, and more than 70% of the pathway; water feature types (Fig. 5 ): no water feature, small fountain, linear stream, and large pond or water body; and seating types (Fig. 5 ): wooden seating, wooden seating with armrests and backrests, wooden seating with overhead shelter, and wooden seating surrounded by plants. 2.5 Chi-square test and multinomial logistic regression model design Descriptive statistics were used to summarize teachers’ garden visit frequency, including the number and percentage of respondents in each group. To compare landscape preferences between teachers in Zhejiang and Shandong, a Chi-square test was conducted. In this analysis, landscape preference variables served as categorical dependent variables, while region was the independent variable. This approach examined whether the distribution of landscape feature choices differed significantly among teachers from different regions. In addition, to further examine how garden use frequency influences landscape preferences among special education teachers, separate multinomial logistic regression models were built for Zhejiang and Shandong. Four key preference variables—planting enclosure structure, natural shading ratio, flower planting density, and seating types—were analyzed as dependent variables due to their relevance for psychological recovery, privacy, and functional usability in special education schools (Hami & Abdi, 2021 ; Tao et al., 2023 ; Liu et al., 2019; Cai et al., 2022 ; Wang et al., 2021 ). Each had four categories, with the last set as the reference to interpret odds ratios (OR). The independent variable was garden use frequency (never, a few times a year, once or twice a month, once or twice a week, almost daily), with “almost daily” as the reference group. As models were run separately by region, no additional control variables were included, avoiding regional confounding. Analyses were conducted in SPSS 27.0 with p < 0.05 as the significance level. 3. Results 3.1 Garden visit frequency Table 1 summarizes garden visit frequencies among special education teachers in Zhejiang and Shandong. In Zhejiang, most teachers visited 1–2 times per week (56.14%), followed by almost daily (19.30%) and 1–2 times per month (14.04%), with few visiting only a few times a year (7.89%) or never (2.63%). In Shandong, the highest proportion visited almost daily (29.82%), followed by a few times a year (21.93%) and never (17.54%), while 16.67% visited monthly and 14.04% weekly. Overall, teachers in Zhejiang visited more regularly on a weekly basis, whereas those in Shandong showed a more polarized pattern, favoring either very frequent (almost daily) or very infrequent (never or a few times a year) use. Table 1 Respondents’ visit frequency and duration of stay in the garden. Visit frequency Zhejiang Province (N, %) Shandong Province (N, %) Never 3 (2.63%) 20 (17.54%) A few times/year 9 (7.89%) 25 (21.93%) 1–2 times/month 16 (14.04%) 19 (16.67%) 1–2 times/week 64 (56.14%) 16 (14.04%) Almost daily 22 (19.30%) 34 (29.82%) 3.2 Regional differences in teachers’ plant landscape preferences Chi-square test results showed significant differences in most landscape preferences between teachers in Zhejiang and Shandong ( Appendix A , Fig. 6 ). For green space area (χ² = 38.567, p < 0.001), Zhejiang teachers favored “half of the total space” (n = 54) and “greenery fills the entire space” (n = 38), while Shandong teachers preferred “1/4 of the total space” (n = 40) or “without greenery” (n = 23). Plant color preferences also differed (χ² = 35.947, p < 0.001), with Zhejiang teachers choosing warm (n = 43) and cool colors (n = 41), and Shandong teachers often selecting “no additional color” (n = 40). In terms of flower density (χ² = 19.291, p < 0.001), Zhejiang teachers preferred “moderate” (n = 46) or “dense continuous clusters” (n = 37), while Shandong teachers favored “sparse clusters” (n = 36) or “no flowers” (n = 24). For natural shading ratio (χ² = 22.416, p < 0.001), Zhejiang teachers preferred “50–70%” (n = 52) and “30–50%” (n = 34) shade, whereas Shandong teachers chose “50–70%” (n = 48) or “less than 30%” (n = 22) shade. Significant differences were found in water feature preferences (χ² = 27.476, p < 0.001), Zhejiang teachers favored “large pond or water body” (n = 49) and “linear stream” (n = 41), while Shandong teachers had more varied choices, including “no water feature” (n = 25). Seating type preferences also differed (χ² = 26.486, p < 0.001), with Zhejiang teachers preferring options with armrests (n = 49) or shelter (n = 42), and Shandong teachers favoring simpler (n = 19) or sheltered wooden seating (n = 54). In comparison, only planting structure showed a slightly lower significant difference (χ² = 9.985, p = 0.019), while planting enclosure structure did not differ significantly (χ² = 4.405, p = 0.221). In summary, except for planting enclosure structure, most landscape elements showed significant differences between faculty in the two regions, highlighting their distinct needs and preferences for campus landscape design. 3.3 Preference differences based on the visit frequency To examine the relationship between teachers’ garden visit frequency and their landscape preferences, separate multinomial logistic regression analyses were conducted for Zhejiang and Shandong samples (Table 2 ). Teachers visiting “almost daily” were used as the reference group, with the most inclusive option as the reference for each landscape variable. Results indicated that some landscape preferences varied significantly across visit frequency groups. Table 2 Multinomial logistic regression results for plant preference groups across different frequency categories. Variable Preference group Zhejiang Province Shandong Province OR p-value OR p-value Planting enclosure structure One-sided enclosure 3.04E-9 3.20 0.372 1.00 1.000 0.80 0.833 1.25 0.880 0.69 0.665 0.55 0.639 0.16 0.154 Two-sided enclosure 0.14 0.272 10.00 0.099 0.14 0.272 2.00 0.560 0.36 0.448 1.14 0.901 0.22 0.184 2.00 0.518 Three-sided enclosure 0.08 0.157 1.74 0.639 0.42 0.562 0.93 0.928 0.17 0.186 0.05 0.002 ** 0.18 0.122 0.17 0.036 * Flower planting density No flowers 3.28E-9 0.29 0.144 0.83 0.898 0.78 0.756 1.73E-8 0.996 0.78 0.772 0.17 0.085 0.78 0.793 Sparse clusters 2.05E-8 0.998 0.37 0.174 2.50 0.482 0.93 0.926 2.50 0.356 0.88 0.868 1.75 0.537 0.97 0.974 Moderate continuous clusters 6.29E-9 0.997 0.58 0.515 0.83 0.858 1.63 0.544 0.12 0.027 * 1.46 0.665 0.58 0.375 1.94 0.469 Natural shading ratio < 30% of the pathway 0.21 0.33 0.309 0.39 1.000 2.33 0.410 3.76E + 6 0.997 0.44 0.374 0.83 1.000 0.33 0.251 30% − 50% of the pathway 3.60E-8 0.995 1.67 0.615 0.29 0.241 2.67 0.396 0.38 0.383 1.11 0.914 0.94 0.929 1.11 0.914 50% − 70% of the pathway 0.18 0.209 0.43 0.297 0.27 0.177 1.14 0.887 1.21 0.827 0.13 0.015 * 0.70 0.597 0.06 0.005 ** Seating type Wooden seating 8.19E + 6 10.50 0.060 8.19E + 6 0.998 0.88 0.888 1.72E + 7 0.996 1.75 0.718 1.27 1.000 1.75 0.530 Wooden seating with armrests and backrests 3.69E + 7 0.996 7.00 0.148 1.55E + 7 0.993 0.39 0.461 6.00 0.137 25.67 0.010 * 1.65 0.437 1.40 0.738 Wooden seating with the shelter 1.33 1.000 3.50 0.271 9.62E + 7 0.993 0.88 0.838 4.00 0.249 2.10 0.525 1.10 0.885 0.21 0.067 Note. The rows under each group represent different visiting frequencies: Row 1 = Never, Row 2 = A few times/year, Row 3 = 1–2 times/month, Row 4 = 1–2 times/week. The reference group for frequency is “almost daily”. The odds ratios (OR) represent comparisons against this reference frequency. Asterisks indicate statistical significance (* p < 0.05; ** p < 0.01). For plant enclosure, frequent visitors in Zhejiang tended to prefer a “three-sided enclosure” layout compared to those visiting 1–2 times per month (OR = 0.17, p = 0.186), though this difference was not significant. In contrast, frequent visitors in Shandong were significantly more likely to choose the “three-sided enclosure” layout than lower-frequency visitors (1–2 times per month: OR = 0.05, p = 0.002; 1–2 times per week: OR = 0.17, p = 0.036). These findings suggest that teachers visiting almost daily generally showed lower preference for highly enclosed private spaces, favoring more open planting layouts. For flower planting density, frequent visitors in Zhejiang preferred “moderate continuous clusters” compared to those visiting 1–2 times per month (OR = 0.12, p = 0.027), indicating a preference for medium-density plantings among frequent users. No significant differences were found in Shandong. For natural shading ratio, frequent visitors in Shandong preferred “50%–70% shade” coverage, significantly more than those visiting 1–2 times per month (OR = 0.13, p = 0.015). Similarly, those visiting almost daily showed a stronger preference for this moderate shade compared to 1–2 times per week visitors (OR = 0.06, p = 0.005), suggesting that frequent users favored moderately shaded environments for greater comfort during repeated use. For seating type, frequent visitors in Shandong showed a significantly lower preference for “wooden seating with armrests and backrests” compared to those visiting 1–2 times per month (OR = 25.67, p = 0.010). This suggests that low-frequency visitors prioritized seating comfort, while frequent visitors were more flexible regarding seating functionality and placed greater emphasis on environmental integration. Overall, frequent visitors preferred open spaces with moderate floral density and shade and were less dependent on specific seating features. This suggests they value the richness and layered experience of the natural environment over individual functional amenities. 4. Discussion This study found clear differences in garden use patterns and landscape preferences between special education teachers in Zhejiang and Shandong Provinces. These differences may reflect not only environmental factors like climate and greening levels but also local educational culture, teachers’ work stress, and leisure needs (Loukas & Mania, 2021 ; Nguyen-Dinh & Zhang, 2025 ). Regarding visit patterns, teachers in Zhejiang tend to visit gardens weekly, suggesting a steady need for daily restorative experiences; in contrast, teachers in Shandong show a more extreme pattern, either using gardens almost daily or rarely entering them. This may relate to differences in campus greening infrastructure, workload, and opportunities for rest between the two regions (Yilmaz et al., 2016 ). Frequent visitors often value ongoing contact with nature to mitigate work-related stress and support psychological recovery (Yang et al., 2023 ). In terms of plant landscape preferences, Zhejiang teachers favor higher green coverage, brighter flower colors, and moderately dense floral arrangements. This aligns with their desire for richer sensory experiences and a sense of escape from daily stress (Wang et al., 2023 ; Allahyar & Kazemi, 2021 ). In contrast, teachers in Shandong tend to choose simpler and sparser landscapes, consistent with the findings of Zheng et al. ( 2010 ). This may reflect practical maintenance concerns or a preference for functional, easy-to-manage spaces. The connection between visit frequency and landscape preference further reveals the psychological process of teachers using garden space. Frequent visitors show a stronger preference for open, permeable environments with moderate shading, reflecting their need for “legibility” and “compatibility” in natural settings (Kaplan, 1995 ). Open spaces not only enhance visual coherence and reduce the feeling of confinement, but also increase environmental predictability, thereby boosting sense of safety and freedom. Additionally, frequent visitors in Zhejiang exhibit a preference for medium-density flowers, suggesting they seek a balance of freshness and complexity in visual and sensory experiences during repeated visits. This aligns with the “information processing theory,” which posits that moderate novelty and complexity enhance environmental preference (Kaplan & Kaplan, 1989 ). In Shandong, frequent visitors tend to favor 50%-70% shading, highlighting their sensitivity to comfort factors like sun protection and cooling. This shading level offers thermal comfort while maintaining a broad view, supporting findings by Tabatabaie et al. ( 2023 ). The differences in seating preferences also illustrate a trade-off between functionality and overall experience. Frequent visitors in Shandong show less preference for seats with armrests and backrests, suggesting they may prioritize the overall landscape experience over individual functional comfort needs. This aligns with Ulrich’s ( 1984 ) perspective that frequent exposure to nature gradually shifts attention toward holistic environmental perception and mental well-being rather than purely physical comfort. Overall, this study underscores the need to design school gardens that respond to local contexts and user needs. By considering different user groups and visit frequencies, gardens can integrate open spaces, moderate shade, diverse flowers, and layered planting. Such designs can better support teachers’ psychological recovery, encourage social interaction, and enrich aesthetic experiences. 5. Conclusion This study revealed significant differences in the use patterns and plant landscape preferences of special education teachers in Zhejiang and Shandong Provinces. Teachers in Zhejiang tended to show regular and moderate use with an immersive aesthetic preference, while teachers in Shandong showed more extreme use patterns and a preference for simpler landscapes. The findings not only extend the application of Attention Restoration Theory (ART) and Stress Recovery Theory (ART) to the group of special education teachers, but also confirm their effectiveness in this context, showing that plant features strongly influence perceived restorative effects and stress relief. In addition, the results provide new support for Environmental-Behavior Theory and Information Processing Theory, highlighting the role of regional culture and educational settings in shaping the preferences. On a practical level, the study emphasizes the need for school garden design to include openness, flexibility, and moderate shading, with context-based adjustments to strengthen either layering or simplicity, to support teachers’ mental recovery and encourage more frequent use. Future studies may expand to more regions and adopt longitudinal designs to strengthen the generalizability and practical value of the finding. Declarations Data Availability The datasets generated and analyzed during the current study are not publicly available due to confidentiality agreements with participating schools and teachers, as well as ethical restrictions imposed by the Ethics Committee for Research Involving Human Subjects (JKEUPM). However, de-identified data may be provided by the corresponding author upon reasonable request. Ethical Statement and Informed Consent This study was conducted in accordance with the ethical standards of Universiti Putra Malaysia and the Declaration of Helsinki. Ethical approval was obtained from the Ethics Committee for Research Involving Human Subjects of Universiti Putra Malaysia (Ref: JKEUPM-2025-504) prior to data collection. All participants were special education teachers who were fully informed of the study’s objectives, voluntary participation, anonymity, and confidentiality of their responses. Written informed consent was obtained from each participant before the commencement of the survey. The consent process was conducted by the first author between September 25–30, 2025 (Zhejiang) and October 2–6, 2025 (Shandong). Participants were asked to read and sign the consent form after being briefed on the purpose of the research and their rights to withdraw at any time without penalty. No minors or vulnerable individuals were directly involved, and no oral consent was required or applied in this study. All consent forms were collected, securely stored, and handled in accordance with institutional data protection and confidentiality guidelines. Declaration of Interest Statement The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Funding The author(s) declared that no financial support was received for the conduct of this study and/or the preparation of this article. References Allahyar M, Kazemi F (2021) Landscape preferences of a children’s hospital by children and therapists. 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16:46:53","extension":"png","order_by":30,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":123009,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage9.png","url":"https://assets-eu.researchsquare.com/files/rs-7896138/v1/028425dd64e350427305c965.png"},{"id":98430162,"identity":"d9fa450a-9611-494c-86a6-c77c941dcab0","added_by":"auto","created_at":"2025-12-17 16:44:54","extension":"xml","order_by":31,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":130894,"visible":true,"origin":"","legend":"","description":"","filename":"610bb5f6175542a6b88fa28890752d6e1structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-7896138/v1/7a0f459f30794866d04b6253.xml"},{"id":98430236,"identity":"e16e1449-8143-4b9b-a0e2-f2ca1c416cf5","added_by":"auto","created_at":"2025-12-17 16:45:01","extension":"html","order_by":32,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":140916,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7896138/v1/e310575f794cebdf739271d4.html"},{"id":98107200,"identity":"a9362d4f-8bf7-4a32-a2ad-5a0384e37bcc","added_by":"auto","created_at":"2025-12-13 00:21:51","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":169915,"visible":true,"origin":"","legend":"\u003cp\u003eLocation of the study sites. (a) Shandong Province; (b) Zhejiang Province.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7896138/v1/23cac3d1b041b455530a2151.png"},{"id":98107209,"identity":"4b4662bd-a231-4ba7-bc44-a8d4802f95b5","added_by":"auto","created_at":"2025-12-13 00:21:51","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":626769,"visible":true,"origin":"","legend":"\u003cp\u003e(1) An illustration of different green space areas presented in the survey; a: without greenery, b: 1/4 of the total space, c: half of the total space, d: greenery fills the entire space; (2) An illustration of different plant enclosures presented in the survey; a: one-sided planting enclosure creating a more open space, b: two-sided planting enclosure with partial openness, c: three-sided planting enclosure creating a relatively private space, d: fully surrounded planting enclosure forming a more private space.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7896138/v1/9b63fdb8b7647f2d630f3ca9.png"},{"id":98431084,"identity":"6d4911a9-19ba-4a7c-9294-b3549f3e5ffd","added_by":"auto","created_at":"2025-12-17 16:47:01","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":771834,"visible":true,"origin":"","legend":"\u003cp\u003e(1) An illustration of different plant colors used in the survey (option a: no additional color in the green space, not shown); b: warm colors, c: cool colors, d: neutral colors; (2) An illustration of different planting structures presented in the survey; a: open lawn space without trees or shrubs, b: trees only without underplanting, c: trees with sparse shrubs, d: trees combined with dense shrub layers and ground cover.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-7896138/v1/5a1263fca245274aea84c8ac.png"},{"id":98431088,"identity":"81b794c4-c31c-42b3-8edb-852459c1c6f0","added_by":"auto","created_at":"2025-12-17 16:47:02","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":821568,"visible":true,"origin":"","legend":"\u003cp\u003e(1)\u003cstrong\u003e \u003c/strong\u003eAn illustration of different flower planting densities used in the survey; a: no flower planting, b: sparse flower clusters, c: moderate flower clusters with partial continuity, d: dense continuous flower borders along both sides of the path; (2) An illustration of different natural shading ratios used in the survey; a: less than 30%, b: between 30% and 50% of the pathway, c: between 50% and 70% of the pathway, d: more than 70% of the pathway.\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-7896138/v1/d66fcc09288281b889f793ff.png"},{"id":98107206,"identity":"70b31e29-5b24-4222-b4a3-10b8fbfb1b7e","added_by":"auto","created_at":"2025-12-13 00:21:51","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":853910,"visible":true,"origin":"","legend":"\u003cp\u003e(1) An illustration of different water feature types used in the survey; a: no water feature, b: small fountains, c: narrow linear water stream, d: large pond or water body; (2) An illustration of different seating types used in the survey; a: simple wooden seating, b: wooden seating with armrests and backrests, c: wooden seating with overhead shelter, d: wooden seating surrounded by plants.\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-7896138/v1/b64a7dd0e464965edbd40d39.png"},{"id":98431089,"identity":"7f736641-724c-4760-ac17-9ce874f0ec10","added_by":"auto","created_at":"2025-12-17 16:47:02","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":324299,"visible":true,"origin":"","legend":"\u003cp\u003ePreference differences between Zhejiang Province and Shandong Province.\u003c/p\u003e","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-7896138/v1/cc9d013b4ddd218eb815cb12.png"},{"id":106404653,"identity":"07708c85-dd40-4a70-977c-fa3060be7238","added_by":"auto","created_at":"2026-04-08 09:16:27","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":4841772,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7896138/v1/97584adc-8e57-4e6f-a5ad-7d0cee06d09f.pdf"},{"id":98430758,"identity":"ca35a933-a5f6-4cb6-91f3-90d1af3874d3","added_by":"auto","created_at":"2025-12-17 16:46:09","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":18162,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarymaterials.docx","url":"https://assets-eu.researchsquare.com/files/rs-7896138/v1/175929a3b77e2845f993803e.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Landscape Preferences and Garden Visit Frequency of Special Education Teachers in School Gardens: A Comparative Study between Zhejiang and Shandong Provinces, China","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eSpecial education teachers often face high psychological stress and emotional exhaustion due to heavy workloads and continuous interaction with students with cognitive or behavioral disorders. School gardens, often seen as restorative environments, can help alleviate psychological stress, promote overall health, and improve job satisfaction among teachers (Hoover et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Ohly et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Beyond offering green space, the plant landscape design plays a role in shaping aesthetic experiences, enhancing environmental appeal, and supporting social and relaxation activities (Akoumianaki-Ioannidou et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). While many studies have explored the benefits of urban green spaces and general school landscapes on psychological recovery (Guardino et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Chen \u0026amp; Hamel, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Ozturk \u0026amp; Ozer, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), little empirical research has examined how special education teachers use and perceive plant landscapes. Particularly in China, many special education schools lack adequate garden facilities, with insufficient diversity and refinement in design. Moreover, systematic studies focusing on this group\u0026rsquo;s specific needs and preferences remains scarce (Liu, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Wang, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Given the professional challenges and stress faced by special education teachers, understanding their preferences and usage patterns is crucial for improving campus design and supporting their well-being (Loukas \u0026amp; Mania, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Lappa et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eMany studies have shown that specific landscape elements are key predictors for enhancing school garden quality and promoting psychological recovery. Larger green areas improve spatial openness, ecological atmosphere, and mental well-being (Tudorie et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Kang \u0026amp; Jeong, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Plant enclosures influence teachers\u0026rsquo; relaxation and social experience by regulating privacy and visual security (Liu \u0026amp; Schroth, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Diverse plant colors and rich vegetation structures enhance visual diversity, aid emotion regulation, and support biodiversity education (Sheng et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Hodson \u0026amp; Sander, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Wang \u0026amp; Zhao, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Zhang et al., \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). High floral density improves attractiveness and emotional recovery through color and fragrance (Mani et al., 2024; Nedovic \u0026amp; Morrissey, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Adequate natural shading enhances microclimate comfort and encourages longer stays (Hami \u0026amp; Abdi, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Water features foster psychological relaxation and spatial attachment via multisensory experiences (Bozkurt \u0026amp; Woolley, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Polat \u0026amp; Akay, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Diverse seating options meet needs for privacy, safety, and social interaction, shaping stay behaviors (Tao et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Alataş et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). However, most studies on special education school gardens focus on macro layouts or greening rates (Wang et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Hussein, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), lacking quantitative analysis of micro plant elements. Therefore, this study selected eight key variables and used a visual-based preference questionnaire to systematically examine their effects on teachers\u0026rsquo; preferences, aiming to provide empirical evidence for precise garden design and mental health support.\u003c/p\u003e\u003cp\u003eMoreover, teachers\u0026rsquo; garden preferences are closely linked to their actual visit frequency. Visit frequency not only indicates teachers\u0026rsquo; dependence on and motivation to use these spaces but also shapes their long-term adaptation and preferences for specific landscape features (Kim et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Cai et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). For instance, frequent visitors often prefer open, varied, and moderately shaded spaces that feel comfortable even with repeated use. In contrast, those who visit less frequently tend to focus more on the visual impact or special features of the landscape (Yang et al., \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Yet, there is still a lack of research on how landscape preferences differ across group with different visit frequencies, especially in special education schools within in Chinese context (Xue et al., \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Zhou et al., \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Examining these differences in depth is crucial for designing campus green spaces that better meet teachers\u0026rsquo; diverse needs and encourage participation.\u003c/p\u003e\u003cp\u003eZhejiang and Shandong provinces differ greatly in geography, climate, vegetation, and campus greening practices. Zhejiang has a humid subtropical monsoon climate and abundant vegetation, while Shandong experiences a temperate monsoon climate with distinct seasons and more limited greenery (Yin et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). These regional differences not only influence technical aspects of landscape design but may also shape teachers\u0026rsquo; aesthetic preferences and spatial needs (Wang et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Therefore, comparing teachers\u0026rsquo; landscape preferences across regions can help reveal their diverse needs and support campus garden designs that better fit local contexts.\u003c/p\u003e\u003cp\u003eIn short, this study examines the relationship between special education teachers\u0026rsquo; landscape preferences and their patterns of using school gardens, focusing on teachers in Zhejiang and Shandong provinces. The main objectives are: (1) to compare how often teachers in the two regions visit school gardens; (2) to analyze their preferences for different landscape elements; and (3) to explore how these preferences vary by visit frequency. By revealing the links between usage behavior and aesthetic preference, this research aims to improve garden design, support teachers\u0026rsquo; psychological recovery, and improve space utilization.\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1 Study sites\u003c/h2\u003e\u003cp\u003eThis study was conducted in four public special education schools in Zhejiang and Shandong provinces, China (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), with two schools in each province. Zhejiang is in eastern China, has a subtropical monsoon climate with abundant rain and rich vegetation, creating favorable conditions for school gardens. The two schools in Zhejiang Province participating in the study are in Hangzhou (30.27\u0026deg;N, 120.15\u0026deg;E) and Lishui (28.47\u0026deg;N, 119.92\u0026deg;E). Both are large public schools with well-developed green spaces and diverse plantings designed to support teaching and promote teachers\u0026rsquo; mental well-being. In contrast, Shandong lies in northern China and has a temperate monsoon climate, featuring distinct seasons and less rainfall. The two Shandong schools are in Linyi (35.10\u0026deg;N, 118.35\u0026deg;E) and Weifang (36.71\u0026deg;N, 119.10\u0026deg;E). These schools have medium-sized gardens, used mainly for basic functions and aesthetic purposes. Choosing these four schools helps capture differences in climate, vegetation, and garden management across regions, providing a foundation for analyzing teachers\u0026rsquo; landscape preferences in varied environmental contexts.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2 Sample size and distribution\u003c/h2\u003e\u003cp\u003eUsing a cross-sectional comparative design, this study examined differences in campus landscaping preferences among special education teachers in Zhejiang and Shandong Provinces. Two public special education schools with similar sizes, greening conditions, and management were selected in each province for the survey. In Zhejiang, 122 questionnaires were distributed, with 114 valid responses collected (validity rate: 93.4%); in Shandong, about 120 questionnaires were distributed, aiming for 114 valid samples to ensure statistical power and comparability. Sample size was determined using Pearson\u0026rsquo;s chi-square test (α\u0026thinsp;=\u0026thinsp;0.05, power\u0026thinsp;=\u0026thinsp;0.80, effect size w\u0026thinsp;=\u0026thinsp;0.3), requiring at least 88 samples per group (Faul et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). Considering possible invalid responses, the final target sample size in each province was set at 114 (Wang \u0026amp; Ji, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). To control confounding factors, schools were matched on teacher composition and curriculum, ensuring regional differences remained the focus.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.3 Visual materials and preference evaluation\u003c/h2\u003e\u003cp\u003eVisual or aesthetic preferences are often assessed using photographs or images in questionnaires, surveys, or interviews, which help illustrate existing landscapes and simulate future designs, thus informing planning and design decisions (Lindemann-Matthies \u0026amp; K\u0026ouml;hler, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Following Allahyar \u0026amp; Kazemi\u0026rsquo;s (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) approach, this study used a structured questionnaire with visual aids to systematically assess special education teachers\u0026rsquo; landscape preferences. The questionnaire\u0026rsquo;s reliability and validity were confirmed by four horticulture and landscape experts and two special education experts. It consisted of two parts: teachers\u0026rsquo; garden use frequency to understand actual space utilization, and preferences for plant landscape elements, supported by images to aid intuitive responses. The content was carefully refined to reduce response fatigue.\u003c/p\u003e\u003cp\u003eUnlike studies using only site photographs, this study created color digital simulation images through 3D modeling in SketchUp and rendering in Adobe Photoshop, allowing precise control of landscape elements and eliminating background interference. All design elements were shown against a uniform background to minimize non-design influences on preferences, following methods by Salih et al. (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) and Wang \u0026amp; Zhao (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) to enhance respondents\u0026rsquo; understanding. Images, presented in color with textual descriptions, were distributed via an online questionnaire to special education teachers to collect their landscape preferences. This method, effective in urban recreation and university campus studies (Wang \u0026amp; Rodiek, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Hami \u0026amp; Abdi, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), was further adapted here to explore campus garden preferences.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e2.4 Landscape features\u003c/h2\u003e\u003cp\u003eBuilding on research on landscape preferences and visual perception in special places and school settings (Salih et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Zhang et al., \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Allahyar \u0026amp; Kazemi, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Wang et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), this study designed eight landscape features to examine their influence on teachers\u0026rsquo; aesthetic preferences and behavioral intentions in special education schools. These features included: green space area (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e2\u003c/span\u003e), with four options: without greenery, greenery occupies 1/4 of the total space, greenery occupies half of the total space, and greenery fills the entire space; planting enclosure structure (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e2\u003c/span\u003e): one-sided enclosure, two-sided enclosure, three-sided enclosure, and fully enclosed planting; plant color (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e3\u003c/span\u003e): no additional color, warm colors, cool colors, and neutral colors; planting structure (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e3\u003c/span\u003e): open lawn, trees only, trees with sparse shrubs, and trees with dense shrub and ground cover; flower planting density (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e4\u003c/span\u003e): no flowers, sparse clusters, moderate continuous clusters, and dense continuous clusters; natural shading ratio (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e4\u003c/span\u003e): less than 30% of the pathway, between 30% and 50% of the pathway, between 50% and 70% of the pathway, and more than 70% of the pathway; water feature types (Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e5\u003c/span\u003e): no water feature, small fountain, linear stream, and large pond or water body; and seating types (Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e5\u003c/span\u003e): wooden seating, wooden seating with armrests and backrests, wooden seating with overhead shelter, and wooden seating surrounded by plants.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003e2.5 Chi-square test and multinomial logistic regression model design\u003c/h2\u003e\u003cp\u003eDescriptive statistics were used to summarize teachers\u0026rsquo; garden visit frequency, including the number and percentage of respondents in each group. To compare landscape preferences between teachers in Zhejiang and Shandong, a Chi-square test was conducted. In this analysis, landscape preference variables served as categorical dependent variables, while region was the independent variable. This approach examined whether the distribution of landscape feature choices differed significantly among teachers from different regions.\u003c/p\u003e\u003cp\u003eIn addition, to further examine how garden use frequency influences landscape preferences among special education teachers, separate multinomial logistic regression models were built for Zhejiang and Shandong. Four key preference variables\u0026mdash;planting enclosure structure, natural shading ratio, flower planting density, and seating types\u0026mdash;were analyzed as dependent variables due to their relevance for psychological recovery, privacy, and functional usability in special education schools (Hami \u0026amp; Abdi, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Tao et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Liu et al., 2019; Cai et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Wang et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Each had four categories, with the last set as the reference to interpret odds ratios (OR). The independent variable was garden use frequency (never, a few times a year, once or twice a month, once or twice a week, almost daily), with \u0026ldquo;almost daily\u0026rdquo; as the reference group. As models were run separately by region, no additional control variables were included, avoiding regional confounding. Analyses were conducted in SPSS 27.0 with p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 as the significance level.\u003c/p\u003e\u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003e3.1 Garden visit frequency\u003c/h2\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e summarizes garden visit frequencies among special education teachers in Zhejiang and Shandong. In Zhejiang, most teachers visited 1\u0026ndash;2 times per week (56.14%), followed by almost daily (19.30%) and 1\u0026ndash;2 times per month (14.04%), with few visiting only a few times a year (7.89%) or never (2.63%). In Shandong, the highest proportion visited almost daily (29.82%), followed by a few times a year (21.93%) and never (17.54%), while 16.67% visited monthly and 14.04% weekly.\u003c/p\u003e\u003cp\u003eOverall, teachers in Zhejiang visited more regularly on a weekly basis, whereas those in Shandong showed a more polarized pattern, favoring either very frequent (almost daily) or very infrequent (never or a few times a year) use.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eRespondents\u0026rsquo; visit frequency and duration of stay in the garden.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVisit frequency\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eZhejiang Province (N, %)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eShandong Province (N, %)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNever\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3 (2.63%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e20 (17.54%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eA few times/year\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e9 (7.89%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e25 (21.93%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u0026ndash;2 times/month\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e16 (14.04%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e19 (16.67%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u0026ndash;2 times/week\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e64 (56.14%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e16 (14.04%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAlmost daily\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e22 (19.30%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e34 (29.82%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003e3.2 Regional differences in teachers\u0026rsquo; plant landscape preferences\u003c/h2\u003e\u003cp\u003eChi-square test results showed significant differences in most landscape preferences between teachers in Zhejiang and Shandong (\u003cb\u003eAppendix A\u003c/b\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). For green space area (χ\u0026sup2; = 38.567, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), Zhejiang teachers favored \u0026ldquo;half of the total space\u0026rdquo; (n\u0026thinsp;=\u0026thinsp;54) and \u0026ldquo;greenery fills the entire space\u0026rdquo; (n\u0026thinsp;=\u0026thinsp;38), while Shandong teachers preferred \u0026ldquo;1/4 of the total space\u0026rdquo; (n\u0026thinsp;=\u0026thinsp;40) or \u0026ldquo;without greenery\u0026rdquo; (n\u0026thinsp;=\u0026thinsp;23). Plant color preferences also differed (χ\u0026sup2; = 35.947, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), with Zhejiang teachers choosing warm (n\u0026thinsp;=\u0026thinsp;43) and cool colors (n\u0026thinsp;=\u0026thinsp;41), and Shandong teachers often selecting \u0026ldquo;no additional color\u0026rdquo; (n\u0026thinsp;=\u0026thinsp;40). In terms of flower density (χ\u0026sup2; = 19.291, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), Zhejiang teachers preferred \u0026ldquo;moderate\u0026rdquo; (n\u0026thinsp;=\u0026thinsp;46) or \u0026ldquo;dense continuous clusters\u0026rdquo; (n\u0026thinsp;=\u0026thinsp;37), while Shandong teachers favored \u0026ldquo;sparse clusters\u0026rdquo; (n\u0026thinsp;=\u0026thinsp;36) or \u0026ldquo;no flowers\u0026rdquo; (n\u0026thinsp;=\u0026thinsp;24). For natural shading ratio (χ\u0026sup2; = 22.416, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), Zhejiang teachers preferred \u0026ldquo;50\u0026ndash;70%\u0026rdquo; (n\u0026thinsp;=\u0026thinsp;52) and \u0026ldquo;30\u0026ndash;50%\u0026rdquo; (n\u0026thinsp;=\u0026thinsp;34) shade, whereas Shandong teachers chose \u0026ldquo;50\u0026ndash;70%\u0026rdquo; (n\u0026thinsp;=\u0026thinsp;48) or \u0026ldquo;less than 30%\u0026rdquo; (n\u0026thinsp;=\u0026thinsp;22) shade. Significant differences were found in water feature preferences (χ\u0026sup2; = 27.476, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), Zhejiang teachers favored \u0026ldquo;large pond or water body\u0026rdquo; (n\u0026thinsp;=\u0026thinsp;49) and \u0026ldquo;linear stream\u0026rdquo; (n\u0026thinsp;=\u0026thinsp;41), while Shandong teachers had more varied choices, including \u0026ldquo;no water feature\u0026rdquo; (n\u0026thinsp;=\u0026thinsp;25). Seating type preferences also differed (χ\u0026sup2; = 26.486, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), with Zhejiang teachers preferring options with armrests (n\u0026thinsp;=\u0026thinsp;49) or shelter (n\u0026thinsp;=\u0026thinsp;42), and Shandong teachers favoring simpler (n\u0026thinsp;=\u0026thinsp;19) or sheltered wooden seating (n\u0026thinsp;=\u0026thinsp;54). In comparison, only planting structure showed a slightly lower significant difference (χ\u0026sup2; = 9.985, p\u0026thinsp;=\u0026thinsp;0.019), while planting enclosure structure did not differ significantly (χ\u0026sup2; = 4.405, p\u0026thinsp;=\u0026thinsp;0.221).\u003c/p\u003e\u003cp\u003eIn summary, except for planting enclosure structure, most landscape elements showed significant differences between faculty in the two regions, highlighting their distinct needs and preferences for campus landscape design.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003e3.3 Preference differences based on the visit frequency\u003c/h2\u003e\u003cp\u003eTo examine the relationship between teachers\u0026rsquo; garden visit frequency and their landscape preferences, separate multinomial logistic regression analyses were conducted for Zhejiang and Shandong samples (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Teachers visiting \u0026ldquo;almost daily\u0026rdquo; were used as the reference group, with the most inclusive option as the reference for each landscape variable. Results indicated that some landscape preferences varied significantly across visit frequency groups.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eMultinomial logistic regression results for plant preference groups across different frequency categories.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003ePreference group\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003eZhejiang Province\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003eShandong Province\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eOR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep-value\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eOR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003ep-value\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"11\" rowspan=\"12\"\u003e\u003cp\u003ePlanting enclosure structure\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003eOne-sided enclosure\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.04E-9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3.20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.372\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.80\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.833\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.880\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.69\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.665\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.55\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.639\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.154\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003eTwo-sided enclosure\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.272\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e10.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.099\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.272\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.560\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.36\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.448\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.901\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.184\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.518\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003eThree-sided enclosure\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.157\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.74\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.639\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.42\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.562\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.93\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.928\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.186\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.002 **\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.122\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.036 *\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"11\" rowspan=\"12\"\u003e\u003cp\u003eFlower planting density\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003eNo flowers\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.28E-9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.144\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.83\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.898\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.78\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.756\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.73E-8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.996\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.78\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.772\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.085\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.78\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.793\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003eSparse clusters\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.05E-8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.998\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.174\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.482\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.93\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.926\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.356\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.88\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.868\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.75\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.537\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.97\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.974\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003eModerate continuous clusters\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6.29E-9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.997\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.58\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.515\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.83\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.858\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.63\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.544\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.027 *\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.46\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.665\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.58\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.375\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.94\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.469\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"11\" rowspan=\"12\"\u003e\u003cp\u003eNatural shading ratio\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;30% of the pathway\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.309\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.410\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.76E\u0026thinsp;+\u0026thinsp;6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.997\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.44\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.374\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.83\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.251\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e30% \u0026minus;\u0026thinsp;50% of the pathway\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.60E-8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.995\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.615\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.241\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.396\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.383\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.914\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.94\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.929\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.914\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e50% \u0026minus;\u0026thinsp;70% of the pathway\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.209\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.43\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.297\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.177\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.887\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.827\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.015 *\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.70\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.597\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.005 **\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"11\" rowspan=\"12\"\u003e\u003cp\u003eSeating type\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003eWooden seating\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e8.19E\u0026thinsp;+\u0026thinsp;6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e10.50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.060\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e8.19E\u0026thinsp;+\u0026thinsp;6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.998\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.88\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.888\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.72E\u0026thinsp;+\u0026thinsp;7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.996\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.75\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.718\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.75\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.530\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003eWooden seating with armrests and backrests\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.69E\u0026thinsp;+\u0026thinsp;7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.996\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e7.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.148\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.55E\u0026thinsp;+\u0026thinsp;7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.993\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.461\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.137\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e25.67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.010 *\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.65\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.437\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.738\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003eWooden seating with the shelter\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3.50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.271\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e9.62E\u0026thinsp;+\u0026thinsp;7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.993\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.88\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.838\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.249\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.525\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.885\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.067\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"6\"\u003e\u003cem\u003eNote. The rows under each group represent different visiting frequencies: Row 1\u0026thinsp;=\u0026thinsp;Never, Row 2\u0026thinsp;=\u0026thinsp;A few times/year, Row 3\u0026thinsp;=\u0026thinsp;1\u0026ndash;2 times/month, Row 4\u0026thinsp;=\u0026thinsp;1\u0026ndash;2 times/week. The reference group for frequency is \u0026ldquo;almost daily\u0026rdquo;. The odds ratios (OR) represent comparisons against this reference frequency. Asterisks indicate statistical significance (* p\u0026thinsp;\u0026lt;\u0026thinsp;0.05; ** p\u0026thinsp;\u0026lt;\u0026thinsp;0.01).\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eFor plant enclosure, frequent visitors in Zhejiang tended to prefer a \u0026ldquo;three-sided enclosure\u0026rdquo; layout compared to those visiting 1\u0026ndash;2 times per month (OR\u0026thinsp;=\u0026thinsp;0.17, p\u0026thinsp;=\u0026thinsp;0.186), though this difference was not significant. In contrast, frequent visitors in Shandong were significantly more likely to choose the \u0026ldquo;three-sided enclosure\u0026rdquo; layout than lower-frequency visitors (1\u0026ndash;2 times per month: OR\u0026thinsp;=\u0026thinsp;0.05, p\u0026thinsp;=\u0026thinsp;0.002; 1\u0026ndash;2 times per week: OR\u0026thinsp;=\u0026thinsp;0.17, p\u0026thinsp;=\u0026thinsp;0.036). These findings suggest that teachers visiting almost daily generally showed lower preference for highly enclosed private spaces, favoring more open planting layouts.\u003c/p\u003e\u003cp\u003eFor flower planting density, frequent visitors in Zhejiang preferred \u0026ldquo;moderate continuous clusters\u0026rdquo; compared to those visiting 1\u0026ndash;2 times per month (OR\u0026thinsp;=\u0026thinsp;0.12, p\u0026thinsp;=\u0026thinsp;0.027), indicating a preference for medium-density plantings among frequent users. No significant differences were found in Shandong.\u003c/p\u003e\u003cp\u003eFor natural shading ratio, frequent visitors in Shandong preferred \u0026ldquo;50%\u0026ndash;70% shade\u0026rdquo; coverage, significantly more than those visiting 1\u0026ndash;2 times per month (OR\u0026thinsp;=\u0026thinsp;0.13, p\u0026thinsp;=\u0026thinsp;0.015). Similarly, those visiting almost daily showed a stronger preference for this moderate shade compared to 1\u0026ndash;2 times per week visitors (OR\u0026thinsp;=\u0026thinsp;0.06, p\u0026thinsp;=\u0026thinsp;0.005), suggesting that frequent users favored moderately shaded environments for greater comfort during repeated use.\u003c/p\u003e\u003cp\u003eFor seating type, frequent visitors in Shandong showed a significantly lower preference for \u0026ldquo;wooden seating with armrests and backrests\u0026rdquo; compared to those visiting 1\u0026ndash;2 times per month (OR\u0026thinsp;=\u0026thinsp;25.67, p\u0026thinsp;=\u0026thinsp;0.010). This suggests that low-frequency visitors prioritized seating comfort, while frequent visitors were more flexible regarding seating functionality and placed greater emphasis on environmental integration.\u003c/p\u003e\u003cp\u003eOverall, frequent visitors preferred open spaces with moderate floral density and shade and were less dependent on specific seating features. This suggests they value the richness and layered experience of the natural environment over individual functional amenities.\u003c/p\u003e\u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThis study found clear differences in garden use patterns and landscape preferences between special education teachers in Zhejiang and Shandong Provinces. These differences may reflect not only environmental factors like climate and greening levels but also local educational culture, teachers\u0026rsquo; work stress, and leisure needs (Loukas \u0026amp; Mania, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Nguyen-Dinh \u0026amp; Zhang, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eRegarding visit patterns, teachers in Zhejiang tend to visit gardens weekly, suggesting a steady need for daily restorative experiences; in contrast, teachers in Shandong show a more extreme pattern, either using gardens almost daily or rarely entering them. This may relate to differences in campus greening infrastructure, workload, and opportunities for rest between the two regions (Yilmaz et al., \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Frequent visitors often value ongoing contact with nature to mitigate work-related stress and support psychological recovery (Yang et al., \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eIn terms of plant landscape preferences, Zhejiang teachers favor higher green coverage, brighter flower colors, and moderately dense floral arrangements. This aligns with their desire for richer sensory experiences and a sense of escape from daily stress (Wang et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Allahyar \u0026amp; Kazemi, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). In contrast, teachers in Shandong tend to choose simpler and sparser landscapes, consistent with the findings of Zheng et al. (\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). This may reflect practical maintenance concerns or a preference for functional, easy-to-manage spaces.\u003c/p\u003e\u003cp\u003eThe connection between visit frequency and landscape preference further reveals the psychological process of teachers using garden space. Frequent visitors show a stronger preference for open, permeable environments with moderate shading, reflecting their need for \u0026ldquo;legibility\u0026rdquo; and \u0026ldquo;compatibility\u0026rdquo; in natural settings (Kaplan, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e1995\u003c/span\u003e). Open spaces not only enhance visual coherence and reduce the feeling of confinement, but also increase environmental predictability, thereby boosting sense of safety and freedom.\u003c/p\u003e\u003cp\u003eAdditionally, frequent visitors in Zhejiang exhibit a preference for medium-density flowers, suggesting they seek a balance of freshness and complexity in visual and sensory experiences during repeated visits. This aligns with the \u0026ldquo;information processing theory,\u0026rdquo; which posits that moderate novelty and complexity enhance environmental preference (Kaplan \u0026amp; Kaplan, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e1989\u003c/span\u003e). In Shandong, frequent visitors tend to favor 50%-70% shading, highlighting their sensitivity to comfort factors like sun protection and cooling. This shading level offers thermal comfort while maintaining a broad view, supporting findings by Tabatabaie et al. (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). The differences in seating preferences also illustrate a trade-off between functionality and overall experience. Frequent visitors in Shandong show less preference for seats with armrests and backrests, suggesting they may prioritize the overall landscape experience over individual functional comfort needs. This aligns with Ulrich\u0026rsquo;s (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e1984\u003c/span\u003e) perspective that frequent exposure to nature gradually shifts attention toward holistic environmental perception and mental well-being rather than purely physical comfort.\u003c/p\u003e\u003cp\u003eOverall, this study underscores the need to design school gardens that respond to local contexts and user needs. By considering different user groups and visit frequencies, gardens can integrate open spaces, moderate shade, diverse flowers, and layered planting. Such designs can better support teachers\u0026rsquo; psychological recovery, encourage social interaction, and enrich aesthetic experiences.\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eThis study revealed significant differences in the use patterns and plant landscape preferences of special education teachers in Zhejiang and Shandong Provinces. Teachers in Zhejiang tended to show regular and moderate use with an immersive aesthetic preference, while teachers in Shandong showed more extreme use patterns and a preference for simpler landscapes. The findings not only extend the application of Attention Restoration Theory (ART) and Stress Recovery Theory (ART) to the group of special education teachers, but also confirm their effectiveness in this context, showing that plant features strongly influence perceived restorative effects and stress relief. In addition, the results provide new support for Environmental-Behavior Theory and Information Processing Theory, highlighting the role of regional culture and educational settings in shaping the preferences. On a practical level, the study emphasizes the need for school garden design to include openness, flexibility, and moderate shading, with context-based adjustments to strengthen either layering or simplicity, to support teachers\u0026rsquo; mental recovery and encourage more frequent use. Future studies may expand to more regions and adopt longitudinal designs to strengthen the generalizability and practical value of the finding.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated and analyzed during the current study are not publicly available due to confidentiality agreements with participating schools and teachers, as well as ethical restrictions imposed by the Ethics Committee for Research Involving Human Subjects (JKEUPM). However, de-identified data may be provided by the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical Statement and Informed Consent\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was conducted in accordance with the ethical standards of Universiti Putra Malaysia and the Declaration of Helsinki. Ethical approval was obtained from the Ethics Committee for Research Involving Human Subjects of Universiti Putra Malaysia (Ref: JKEUPM-2025-504) prior to data collection.\u003c/p\u003e\n\u003cp\u003eAll participants were special education teachers who were fully informed of the study’s objectives, voluntary participation, anonymity, and confidentiality of their responses. Written informed consent was obtained from each participant before the commencement of the survey. The consent process was conducted by the first author between September 25–30, 2025 (Zhejiang) and October 2–6, 2025 (Shandong). Participants were asked to read and sign the consent form after being briefed on the purpose of the research and their rights to withdraw at any time without penalty.\u003c/p\u003e\n\u003cp\u003eNo minors or vulnerable individuals were directly involved, and no oral consent was required or applied in this study. All consent forms were collected, securely stored, and handled in accordance with institutional data protection and confidentiality guidelines.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclaration of Interest Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe author(s) declared that no financial support was received for the conduct of this study and/or the preparation of this article.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAllahyar M, Kazemi F (2021) Landscape preferences of a children\u0026rsquo;s hospital by children and therapists. 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Landsc Urban Plann 99(1):1\u0026ndash;8. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.landurbplan.2010.08.006\u003c/span\u003e\u003cspan address=\"10.1016/j.landurbplan.2010.08.006\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhou X, Cen Q, Qiu H (2023) Effects of urban waterfront park landscape elements on visual behavior and public preference: Evidence from eye-tracking experiments. Urban Forestry Urban Green 82(127889):127889. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.ufug.2023.127889\u003c/span\u003e\u003cspan address=\"10.1016/j.ufug.2023.127889\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"special education teachers, school garden, landscape preference, visual assessment, psychological restoration, regional differences","lastPublishedDoi":"10.21203/rs.3.rs-7896138/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7896138/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eSpecial education teachers often experience high levels of psychological stress and emotional fatigue due to demanding workloads and sustained interactions with students with disabilities. School gardens can serve as restorative environments to mitigate this stress and enhance overall well-being. However, empirical evidence on plant landscape preferences and garden use patterns among this group in China remains scarce. This study surveyed 228 teachers from four special education schools in Zhejiang and Shandong provinces to examine their preferences for eight landscape features, using a structured questionnaire and visual simulation images. The influence of visit frequency on these preferences was further examined through multinomial logistic regression analysis. Results revealed notable regional differences: teachers in Zhejiang favored larger green areas (80.7% preferred semi- or fully covered spaces) and medium to dense floral plantings, whereas those in Shandong preferred simpler, sparser designs. Frequent visitors showed a preference for open spaces with 50% \u0026minus;\u0026thinsp;70% shade and high spatial legibility. In Shandong, frequent visitors significantly avoided highly enclosed layouts (OR\u0026thinsp;=\u0026thinsp;0.05, p\u0026thinsp;=\u0026thinsp;0.002) and preferred moderate shading (OR\u0026thinsp;=\u0026thinsp;0.06, p\u0026thinsp;=\u0026thinsp;0.005). These findings highlight the importance of tailoring school garden designs to regional and usage patterns to support psychological restoration and encourage use among teachers. This study offers practical insights into the design of restorative green spaces in special education settings.\u003c/p\u003e","manuscriptTitle":"Landscape Preferences and Garden Visit Frequency of Special Education Teachers in School Gardens: A Comparative Study between Zhejiang and Shandong Provinces, China","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-13 00:21:46","doi":"10.21203/rs.3.rs-7896138/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"f7f63c23-b524-4bbf-bf06-c25b746a847d","owner":[],"postedDate":"December 13th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":59357170,"name":"Earth and environmental sciences/Environmental social sciences"},{"id":59357171,"name":"Biological sciences/Psychology"},{"id":59357172,"name":"Social science/Psychology"}],"tags":[],"updatedAt":"2026-04-07T06:57:55+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-13 00:21:46","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7896138","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7896138","identity":"rs-7896138","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}