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Article

Effects of the Combination of Audio and Visual Factors on Mental Restoration in a Large-Scale Urban Greenway: Perspectives from Wuhan, China

1
Department of Urban Planning, School of Urban Design, Wuhan University, Wuhan 430071, China
2
State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430071, China
*
Authors to whom correspondence should be addressed.
Land 2022, 11(11), 2017; https://doi.org/10.3390/land11112017
Submission received: 1 October 2022 / Revised: 3 November 2022 / Accepted: 9 November 2022 / Published: 11 November 2022

Abstract

:

Highlights

What are the main findings?
  • Sound can alter the effect of visual factors on mental restoration.
  • Birdsong can significantly improve the restorative value of urban greenways.
  • The sound of water can promote the restorative value of an environment covered with greenery.
  • Human noise has a negative impact on mental restoration.
  • Place attachment is a mediator between the audio and visual factors of an urban greenway and mental restoration.

Abstract

The natural environment has been widely recognized as an important way of alleviating mental disorders. While a growing number of studies have discussed the restorative effect of the natural environment, the role of sounds in the natural environment (i.e., soundscape) on promoting mental restoration is under limited exploration. Therefore, we examined the restorative effect of visual stimuli and the combination of audio and visual factors in the natural environment. A total of 149 college students were divided into five groups, and exposed to different combinations of photos and sounds (with ‘silence’ as a control group) collected along the East Lake Greenway—the longest urban greenway in China. Structural equation modeling (SEM) was used to examine the correlation between characteristics of the natural environment and volunteers’ mental restoration, with place attachment as a mediator. Results showed that: (1) sound can alter the effect of visual factors on mental restoration; (2) birdsong can significantly enhance the restorative benefit of urban greenways; (3) an environment that is covered in greenery and consists of water sounds will contribute to a higher level of mental restoration; (4) human noise will have a negative impact on mental restoration; (5) place attachment is a mediator between the natural environment and mental restoration. This study highlights the effectiveness of sounds in the natural environment in promoting mental restoration, and broadens our understanding of the link between the natural environment and mental health. We propose that not only visual factors, but also audio-visual combinations, should be considered when creating restorative environments.

1. Introduction

While urbanization promotes economic development, it also brings urban dilemmas such as environmental pollution, the heat-island effect, and mental health crises (depression, anxiety, etc.). In 2019, a survey on the prevalence of mental disorders in China revealed that the lifetime prevalence of various mental diseases (excluding dementia) in the population over 18 years old was 16.57% [1]. The natural environment in the city, such as greenways, parks, scenic spots, etc., has been widely investigated and recognized as the key to improving the mental restoration of residents by reducing fatigue [1,2,3], regulating mood [4,5], and restoring attention [6,7]. Compared to mental health, which refers to the overall level of well-being, mental restoration usually measures transient stress recovery [8] and attention restoration [9].
A growing number of studies have concluded that exposure to nature will promote mental restoration [10,11]. Characteristics of natural environments such as green visibility [12], water space [13], quality of facilities [14], richness of species, etc. [15,16,17], have been proven to have direct effects on mental restoration. In addition, the restorative effects of the environment are also associated with demographic characteristics of people, e.g., age, gender, education background, etc. Moreover, existing studies have concluded that visitors’ physical activity, social cohesion, satisfaction, as well as place attachment are the primary pathways linking the natural environment and people’s mental restoration, especially place attachment, whose mediating role cannot be underestimated [18,19]. This refers to an individual’s strong emotional connection to a particular place or environment, usually arising from a comparative experience, and can be developed through long-term interaction [20]. The realization of mental restoration relies on the perception of the natural environment [21,22].
In fact, natural environments are not only perceived based on visual factors, but also through sounds in t nature [23,24]. Sound also has an impact on mental restoration [24]. The rhythms in natural sounds may be therapeutic and help to restore stress [25,26]. In addition, music inventions can reduce a patient’s pain and anxiety [27], while environmental noise such as transportation noise, human noise (i.e., sleeping disturbance), may increase heart disease, diabetes, obesity, anxiety and depression [28].
Moreover, our senses are rarely used independently; instead, they usually function in conjunction with one another [27,29,30,31]. Several studies have shown that sound can modify the effect of visual factors on mental restoration; in other words, the effects of vision and sound on mental restoration may reinforce or interfere with each other [18,32,33]. Deng et al. [24] conducted comparative experiments regarding visual and auditory stimuli, and results suggested that participants’ feelings towards the environment changed with the different groups. Therefore, a high-quality audio-visual environment may enhance wellbeing and quality of life [23].
A number of studies have examined the impact of visual factors (e.g., green or water space) in a natural environment on visitors’ mental restoration. Currently, most studies are concerned with the overall effect of sound (positive or negative), and few studies have examined the restorative effects of sound in different landscape settings. Taking a large-scale urban greenway as an example, this study aims to explore how audio and visual factors of the natural environment affect mental restoration. We took photos as visual materials and used four common sounds (birdsong, water, human noise, and music) of the East Lake Greenway as audio materials (see Supplementary Materials). Moreover, we hypothesized that place attachment is a mediator between characteristics of the urban greenway and mental restoration. Results were expected to contribute to a better understanding of the mechanisms behind the influence of restorative environments, and to establish reliable guidelines for city planners and landscape designers with regard to how to enhance the value of a restorative environment from the perspective of audio-visual combinations.

2. Materials and Methods

2.1. Study Area

The East Lake Greenway, located in Wuhan City, China (Figure 1), has a total length of 101.98 km. In 2019, the permanent resident population of Wuhan was 11.1 million, while the East Lake greenway received a total of 23 million visitors [34]. As a large-scale inner-city greenway, the East Lake Greenway plays an important role in providing recreational places, and has great potential for improving residents’ mental health.

2.2. The Combination of Audio-Visual Stimuli

In the pre-survey in November 2020, a total of 507 photos were taken at the East Lake Greenway, using a digital camera (NIKON D5300, focal length: 28 mm), under the following condition: (a) at eye-level, approximately 1.55 m above the ground; (b) time 9:00–10:00 a.m. or 4:00–5:00 p.m. (similar lighting conditions [33]). The most representative 20 sites on the East Lake Greenway were selected and divided into five groups, according to the type of landscape (grassland, wetland, lake, forest, and mountain) [35]. In order to ensure that the photos represent the characteristics of the sites, we took multiple photos at each location from different angles (keeping the same height of the person’s viewpoint). Finally, we chose the most representative photo for each site.
Meanwhile, we also carried out an online survey from November to December 2020. We collected the ratings of 20 photos from 263 volunteers who had been to the East Lake Greenway. We selected the five highest- and five lowest-scoring photos in each category as visual material, because they could produce significantly different restoration results (see Figure 1). Meanwhile, in order to obtain the types of sounds common in the East Lake greenway, volunteers were also asked to report the sound they heard on the East Lake Greenway. The results showed that human noise (96%), birdsong (95%), water (61%), music (59%), wind sound (48%), insect sound (41%) and traffic noise (36%) were common sounds on the East Lake Greenway. To reduce the length of the questionnaire, we compared only the first four voices with the control group ‘silence’. We then selected clear and high-quality recordings of human noise, birdsong, water and music from an open-access sound library on a Chinese social platform, as audio materials (Table 1). Five postgraduate students who had participated in the pre-survey were invited to evaluate which version was the best to represent the corresponding sound, and the best version was used. Five sounds (including ‘silence’) and 10 photos were collated, to create 50 (5 × 10) sets of audio-visual combination.

2.3. The Audio-Visual Experiment

Since the audio-visual experiment needed to be conducted indoors, we recruited undergraduate students with self-reported normal eyesight and hearing from Wuhan University, which is adjacent to the East Lake Greenway, as volunteers. This method was widely used in previous studies [2]. During April and May 2021, a total of 149 volunteers were divided into five groups, (‘silence’, ‘birdsong’, ‘water sound’, ‘human noise’, and ‘music’). Five groups were available for volunteers to choose from, each with no more than 45 volunteers. In each group, 10 photos attached to a certain type of sound were shown one by one on slides using PowerPoint, and each was played for 15 s. The audio-visual experiment was conducted in a multimedia classroom with a 150-inch screen at 22–25 °C. Speakers were hung in the four corners of the classroom, to ensure that the sound could be heard clearly from every direction. According to Yiping et al. [18], the sound pressure level (SPL) was regulated between 43 and 47 db (A), which is similar to the SPL of the ambient sound in a forest.
Immediately after watching the material, the volunteers were asked to fill out the questionnaire. Mental restoration was investigated by short-version revised restoration scale (SRRS) (Table 2), a self-reported measurement developed by Wang et al. [36]. Inspired by Cheng and Kuo [37], we measures visitors’ place attachment using three items developed by Raymond et al. [38]. The items were rephrased to fit the study objectives as follows:
  • Nature bonding: I am familiar with the East Lake Greenway;
  • Place identity: I have a lot of fond memories of the East Lake Greenway;
  • Place dependence: doing my activities in the East Lake Greenway is more important to me than doing them in any other place.

2.4. Visual Characteristics of Natural Environment

First, this paper used Photoshop CC 2017 to pixelate the 10 photos selected by volunteers in the pre-survey, and divided each photo into 1200 (30 × 40) grids. Taking ‘openness’ as an example, according to the manual visual interpretation, the proportion of the grid containing the sky in relation to the total grid, was openness (Figure 2). Next, the photo was processed using the “Mosaic” tool of Photoshop CC 2017, which consists of several mosaic grids with a pixel size of 120 × 120 (Figure 3). Among them, the colors covering more than 200,000 pixels were assigned as primary colors, while their number was calculated as “‘colorfulness’”. Then, ‘plant richness’ was assessed by five landscape architects familiar with the study area. Finally, the visual characteristics in Table 3 were further calculated and standardized before statistical analysis (Figure 4).

2.5. Statistics

Statistical analysis was carried out using AMOS (26.0) software. We employed the structural equation model (SEM) to examine the differences in correlations between visitors’ mental restoration and the characteristics of the natural environment under different sound scenarios. We also investigated the mediating role of place attachment in linking the natural environment and mental restoration (Figure 5). The interclass reliability of the mental restoration scores was tested using Cronbach’s alpha. Standardized root-mean-square residual (SRMSR), root-mean-square error of approximation (RMSEA), and comparative fit index (CFI) were used to assess the goodness of fit of the model.

3. Results

3.1. Basic Descriptions

We collected 149 valid questionnaires, of which 69 and 80 were from males and females, respectively. Undergraduate students aged 19–22, coming from a wide range of majors, e.g., architecture, urban and rural planning, machinery, literature, and environmental design accounted for 86% of the total participants. As shown in Figure 6, photos with the ‘birdsong’ always had higher restoration scores, while the ‘water’ sound only played a positive role in photos four, five and nine. Compared with the ‘silence’ scenario, both ‘human noise’ and ‘music’ had lower restoration scores among all photos.

3.2. Reliability

The interclass reliability of mental restoration in different scenarios was calculated. Cronbach’s alpha was ‘silence’ 0.937, ‘birdsong’ 0.947, ‘water’ 0.961, ‘human noise’ 0.962, and ‘music’ 0.961, indicating good internal reliability. In addition, the goodness of fit of all models under different scenarios reached the standard (Table 4).

3.3. Effects of Environmental Characteristics on Mental Restoration

As shown in Figure 7, in the ‘silence’ scenario, the number of plant species was positively associated with participants’ mental restoration (β = 0.016, SE = 0.027). In the ‘birdsong’ scenario, ‘water space’ (β = 0.071, SE = 0.025), ‘openness’ (β = 0.092, SE = 0.031), ‘pavement area’ (β = 0.071, SE = 0.025), ‘trees and shrubs area’ (β = 0.092, SE = 0.032), ‘plant richness’ (β = 0.075, SE = 0.074) and ‘lawn area’ (β = 0.09, SE = 1.13) was positively associated with participants’ mental restoration.
Table 5 and Table 6 presents the standardized direct and indirect effect of the environmental characteristics on mental restoration, respectively. In the ‘silent’ group, ‘plant richness’ improved participants’ mental restoration significantly. In the ‘birdsong’ group, ‘water space’, ‘openness’, ‘pavement area’, ‘trees and shrubs area’, ‘plant richness’, and ‘lawn area’ promoted participants’ mental restoration. In contrast, in the ‘water sound’ group, ‘water space’, ‘openness’, ‘pavement area’, ‘colorfulness’, ‘trees and shrubs area’, and ‘lawn area’ weakened participants’ restorative score. However, the ‘water sound’ combined with an environment with more greenery (a high level of ‘green visibility’) effectively awoke participants’ mental restoration. In the ‘human noise’ group, ‘pavement area’ and ‘trees and shrubs area’ affected the restorative score negatively. Surprisingly, the combination of ‘music’ and any photos did not improve the level of mental restoration.
The results of indirect effect confirmed our hypothesis that place attachment was a mediator between the characteristics of the natural environment and people’s mental restoration (Table 6, Figure 7). In the ‘silent’ group, only plant richness had a significant direct impact on mental restoration, while other visual characteristics did not show any significance, but indirectly affected mental restoration through place attachment. Compared with the ‘silence’ group, the combination of ‘birdsong’ and photos enhanced the direct influence of visual characteristics on mental restoration. Combined with ‘water sound’ and ‘human noise’, most of the visual factors had a direct negative impact on mental restoration, while the visual factors (green visual rate, blue visual rate, and openness) that initially contributed positively to place attachment now became negative. In the ‘music’ group, there was only an indirect path instead of a direct path linking environmental characteristics and mental restoration.

4. Discussion

4.1. Sound Could Alter the Effect of Visual Factors on Mental Restoration

In the ‘silence’ group, results showed that ‘plant richness’ may positively predict mental restoration. There is evidence that abundant plant species can enhance the wildlife attraction of the surrounding environment, thereby providing people with a refreshing experience, and also triggering associations with nature’s vitality, improving their mental well-being [39,40].
Adding birdsong to the environment can significantly improve the restorative value of the environment. Birdsong was the sound most often associated with people’s restorative experiences in nature [41]. By evoking thoughts or perceptions associated with biodiversity, a natural environment with birdsong can attract people and promote mental restoration [42,43,44,45], and enhance their landscape perception, thereby allowing them to connect to nature and achieve restoration [21].
In the ‘water’ group, the smaller the water area in the photo, the smaller the positive effect of underwater sound. When people hear the sound of water, they may unconsciously associate it with water. In other words, the inconsistency between visual and audio factors led to negative recovery effects. It is also worth noting that ‘water sound with water space’ is also a negative predictor. In spite of the fact that the photo depicted a water body, it was still water, such as ponds or lakes, which resulted in the visual association of the flowing water sound, thus being incongruent with the photo.
In addition, ‘human noise’ was identified as a negative predictor of the restorative value of the environment. In the ‘human noise’ group, both natural factors (‘blue vision’, ‘green vision’, ‘openness’, ‘tree and shrub area’) and artificial factors (‘pavement area’) aggravated the participants’ stress. Human noise may adversely affect people’s experience of visiting the environment, thereby hindering mental restoration [33].
The music used in the experiment was common Chinese classical music that is commonly heard in Chinese parks, it did not change the mental restoration of people in the environment. Compared with other sounds, music is a cultural product. The influence of music depends more on demographic variables such as age, education background, etc. The diverse experience leads to the volunteers’ different understanding of music.

4.2. Place Attachment: Linking Environmental Characteristic and Mental Restoration

Results validated the idea that place attachment is a mediator linking the natural environment and mental restoration in all groups. Place attachment refers to an individual’s strong emotional connection to a particular place or environment, usually arising from comparative experience, and can be developed through long-term interaction [20], which has also been conceptualized as a sense of place bonding, or place identity [46,47]. Studies have shown that place attachment has a positive effect on mental restoration [22,48,49].
In all groups, place attachment is an active mediating factor, and the most obvious paths are ‘plant richness → place attachment → mental restoration’ and ‘pavement area → place attachment → mental restoration’. ‘Plant richness’ represents multiple plant arrangements, and ‘pavement area’ represents the area of hard surface area, both of which are man-made landscapes. In an environment full of natural elements, a suitable artificial landscape can effectively evoke people’s familiarity and identification with the environment, which in turn strengthens people’s mental restoration.

4.3. Application for Building a Restorative Environment

City decision makers have been trying to find effective ways to build restorative environments [50,51]. A significant trend has been the shift from visual dominance to a multi-sensory approach to user experience. Firstly, the combination of birdsong and landscape could enhance people’s mental restoration; thus, birdsong can be incorporated into the design of a restorative environment. Planners could apply ecological restoration and other means to construct a bird-friendly environment for attracting birdsong [41]. Secondly, water sound does not fit all landscape features, but the combination of rich green species and water sound would make people feel restored in the environment. Therefore, water features should be designed in combination with vegetation to maximize the restorative mental value of soundscapes and landscapes. In addition, the role of “place attachment” also deserves attention. By imbuing a place with a spiritual connotation and context, landscape designers can facilitate a sense of belonging and familiarity for individuals or groups, as well as increasing positive emotions and mental restoration.
Likewise, it is worthwhile to discuss what types of audio-visual combinations should be avoided in landscape design. It is critical for landscape designers to consider the harmony and unity of sound and scenery in an environment with a waterscape. In order to improve connectivity between sound sources, they should decrease the blockage of unnecessary structures and buildings between the waterscape and people. This will eliminate the negative impact caused by the disharmony between visual and sound scenes as much as possible. In addition, human noise is unavoidable in the environment, and children are a common source of human noise. In order to minimize the negative impact of human noise on mental restoration, the natural environment can be divided into different functional areas, such as a quiet rest area, a children’s activity area, a sports activity area, and an elderly activity area, thus minimizing the disturbance of human noise.

4.4. Limitations and Future Study

Using a combination of audiovisual materials of the real environment for indoor experiments can reduce the interference of non-experimental factors such as weather and other noises. However, photographs are not a complete substitute for a full view of the actual scene. In future studies, virtual reality and other wearable devices can be considered in combination with video images to more accurately simulate the participant’s visit experience and other senses (smell, memory and touch) [10]. In addition, other potentially restorative environments, such as roadside green spaces and community gardens, could be further discussed [52]. For example, in a roadside green space environment, congested roads can cause psychological stress to commuters, and streets vary in noise levels due to different traffic volumes. There is a need to explore the psychological recovery of commuters as they pass along the streets, in order to improve the restorative mental benefits of roadside green spaces.

5. Conclusions

This study explored the effects of sound on mental restoration, and investigated the mediating role of place attachment between the natural environment and mental restoration. In addition, the inclusion of different sounds in the environment can have different effects on mental restoration. For example, birdsong enhances environmental recovery, water sounds work better in environments with more greenery, while human noise has a negative effect on people. In addition, a mediating role of place attachment was found, which was present in all sound scenes in this study. We also conclude with recommendations for improving the design of restorative environments. In the future, visual and auditory senses should be considered together in the design and planning of restorative environments. Based on the multisensory experience of visitors in the environment, it is reasonable to utilize audio-visual combinations in our urban environments as a viable way to provide relief from the current mental health crisis in the city.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/land11112017/s1, Supplementary Material S1: Sound; Supplementary Material S2: Image colors and plants.

Author Contributions

Conceptualization, S.G.; Formal analysis, J.Y.; Investigation, L.Y.; Methodology, Y.Z. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by Construction Science and Technology Plan Project of Hubei Provincial Department of Housing and Construction grant number 2022-118, Special Project for Basic Research Funds of Central Universities grant number 2020HW007, National Natural Science Foundation of China grant number 72174158.

Data Availability Statement

The data presented in this study are available on request from the author.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. The study area and ranking of image collection; the figure shows the position of 20 images, of which 10 red ones were selected for audio-visual stimulation.
Figure 1. The study area and ranking of image collection; the figure shows the position of 20 images, of which 10 red ones were selected for audio-visual stimulation.
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Figure 2. The extraction of environmental elements from the sample photo. Blue = water space; white = sky; gray = pavement; light green = trees and shrubs; dark green = lawn.
Figure 2. The extraction of environmental elements from the sample photo. Blue = water space; white = sky; gray = pavement; light green = trees and shrubs; dark green = lawn.
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Figure 3. The extraction of main colors from the sample photo.
Figure 3. The extraction of main colors from the sample photo.
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Figure 4. The physical characteristic of the sample photos. GV = Green Visibility; WS = Water Space; O = Openness; PA = Pavement Area; TS = Tree and Shrub area; LA = Lawn Area; C = Colorfulness; PR = Plant Richness.
Figure 4. The physical characteristic of the sample photos. GV = Green Visibility; WS = Water Space; O = Openness; PA = Pavement Area; TS = Tree and Shrub area; LA = Lawn Area; C = Colorfulness; PR = Plant Richness.
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Figure 5. Theoretical framework of the Structural Equation Model (SEM).
Figure 5. Theoretical framework of the Structural Equation Model (SEM).
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Figure 6. The restoration scores of visual stimuli (10 photos under ‘silence’) and audio-visual stimuli (combinations of ten photos and four sounds: ‘birdsong’, ‘water sound’, ‘human noise’, ‘music’).
Figure 6. The restoration scores of visual stimuli (10 photos under ‘silence’) and audio-visual stimuli (combinations of ten photos and four sounds: ‘birdsong’, ‘water sound’, ‘human noise’, ‘music’).
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Figure 7. Standardized path coefficients of the SEM ((a) is the result of the structural equation model under silence scenario, (b) is the result of the structural equation model under bird song scenario, (c) is the results of the structural equation model under water sound scenario, (d) is the results of the structural equation model under human sound scenario, and (e) is the results of the structural equation model under music scenario.) significance levels: ** p < 0.05, *** p < 0.01.
Figure 7. Standardized path coefficients of the SEM ((a) is the result of the structural equation model under silence scenario, (b) is the result of the structural equation model under bird song scenario, (c) is the results of the structural equation model under water sound scenario, (d) is the results of the structural equation model under human sound scenario, and (e) is the results of the structural equation model under music scenario.) significance levels: ** p < 0.05, *** p < 0.01.
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Table 1. Descriptions and sources of each sound type.
Table 1. Descriptions and sources of each sound type.
SoundsDescriptions
BirdsongClear and melodious birdsong
Water soundFlowing streams
Human noisePlaying children and chatting adults
MusicA Chinese classical song entitled ‘Moon over the Peaceful Lake’
Table 2. Short-version Revised Restoration Scale on mental restoration.
Table 2. Short-version Revised Restoration Scale on mental restoration.
VariableNegativeRangePositive
FascinationNo interesting thing attracts me.1–5Interesting things attract my attention.
CompatibilityI would get away from here because I can’t enjoy myself in this setting.1–5I would stay here longer, because I can enjoy myself in this setting.
Being awayIn this place, I still think about the things that I must get done.1–5Spending time in this setting gives me a good break from my day-to-day routine.
ExtentThe content or structure of this place is very simple, so that people can see everything at a glance.1–5The setting has sufficient content and structure that it can occupy the mind for a significant period.
Table 3. Descriptions of visual characteristics.
Table 3. Descriptions of visual characteristics.
Physical CharacteristicsDescriptions
Green Visibility (GV)The area of green space in the photo.
Water Space (WS)The area of water space in the photo.
Openness (O)The area of the sky in the photo.
Pavement Area (PA)The area of hard pavement in the photo.
Trees and Shrubs (TS)The area of trees and shrubs in the photo.
Lawn Area (LA)The area of lawn in the photo.
Colorfulness (C)The number of main colors in the photo.
Plant Richness (PR)The species of plants in the photo.
Table 4. The fitting degree index of the models under different scenarios.
Table 4. The fitting degree index of the models under different scenarios.
ModelCMIN/DF (<3)RMSEA (<0.08) CFI (>0.9)GFI (>0.9) IFI (>0.9)
Silence1.8520.0240.9990.9960.999
Birdsong1.3060.01410.9971
Water sound2.9620.0360.0980.0940.098
Human noise2.1120.0270.9990.9940.999
Music1.4670.0180.9990.9960.999
Table 5. Standardized direct effects of environmental characteristic on mental restoration.
Table 5. Standardized direct effects of environmental characteristic on mental restoration.
CharacteristicSilenceBirdsongWaterHuman NoiseMusic
Green Visibility0.0020.0010.015 ***−0.013 **−0.005
Water space0.0230.071 **−0.126 **−0.084 **0.015
Openness0.0150.092 **−0.174 ***−0.092 **−0.005
Pavement Area0.0350.071 **−0.175 **−0.082 **0.013
Colorfulness−0.0410.083−0.292 **0.014−0.082
Tree and Shrub area0.0120.092 **−0.123 **−0.09 **0.007
Plant Richness0.106 ***0.075 **0.084 ***0.041−0.057
Lawn Area0.0170.09 **−0.188 **−0.0820.011
** p < 0.05, *** p < 0.01.
Table 6. Standardized indirect effects of environmental characteristic on mental restoration (** p < 0.05).
Table 6. Standardized indirect effects of environmental characteristic on mental restoration (** p < 0.05).
PathwaySilenceBirdsongWater SoundHuman NoiseMusic
Green Visibility→ Place Attachment → Mental Restoration0.007 **0.004 **0.003 **0.002 **0.002 **
Water space→ Place Attachment → Mental Restoration0.076 **0.044 **0.031 **0.025 **0.019 **
Openness→Place Attachment→ Mental Restoration0.065 **0.038 **0.026 **0.022 **0.017 **
Pavement Area→Place Attachment→ Mental Restoration0.086 **0.05 **0.035 **0.029 **0.022 **
Colorfulness→ Place Attachment → Mental Restoration0.062 **0.036 **0.025 **0.021 **0.016 **
Trees and Shrubs → Place Attachment → Mental Restoration−0.211 **−0.122 **−0.083 **−0.071 **−0.053 **
Plant Richness→ Place Attachment → Mental Restoration0.135 **0.078 **0.053 **0.045 **0.034 **
Lawn Area→ Place Attachment → Mental Restoration0.064 **0.037 **0.026 **0.021 **0.016 **
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Guo, S.; Zhou, Y.; Yu, J.; Yang, L. Effects of the Combination of Audio and Visual Factors on Mental Restoration in a Large-Scale Urban Greenway: Perspectives from Wuhan, China. Land 2022, 11, 2017. https://doi.org/10.3390/land11112017

AMA Style

Guo S, Zhou Y, Yu J, Yang L. Effects of the Combination of Audio and Visual Factors on Mental Restoration in a Large-Scale Urban Greenway: Perspectives from Wuhan, China. Land. 2022; 11(11):2017. https://doi.org/10.3390/land11112017

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Guo, Shiyi, Yan Zhou, Jianing Yu, and Liuqi Yang. 2022. "Effects of the Combination of Audio and Visual Factors on Mental Restoration in a Large-Scale Urban Greenway: Perspectives from Wuhan, China" Land 11, no. 11: 2017. https://doi.org/10.3390/land11112017

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