Public Perceptions of Urban Green Spaces: Effects on Physical and Mental Health

Abstract

Urban green spaces are essential for promoting public health by encouraging physical activity, reducing stress, and enhancing overall well-being. However, the perception and utilization of these spaces vary based on socio-demographic factors and urban planning characteristics. This study investigates public perception of urban green spaces and their perceived health benefits, emphasizing their psychological, physical, and social impacts. The study involved 240 respondents who assessed the availability and quality of green spaces as well as the social and psychological aspects of their use. The survey was analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results showed that environmental awareness (β = 0.404, p < 0.001) and social interaction (β = 0.391, p < 0.001) are significant predictors of the frequency of visiting green spaces, while their availability and quality do not have a significant impact. These findings highlight the critical role of environmental education and community awareness initiatives in maximizing the health benefits derived from urban green spaces. Frequency of use is positively associated with both mental (β = 0.272, p = 0.002) and physical health (β = 0.409, p < 0.001). Surprisingly, social interaction demonstrates a negative impact on mental health (β = −0.166, p = 0.002), which requires further study. The obtained results highlight the need for an integrated approach to studying the relationship between the urban environment and population health.

1. Introduction

In the context of rapid urbanization and the growth of psycho-emotional stress in modern society, urban green spaces (UGSs) are becoming increasingly important, acting as a key resource for maintaining the physical and mental health of the population. Numerous studies have confirmed that access to natural areas in the urban environment helps reduce stress [1,2], increase physical activity [1,3], and improve overall well-being [4,5]. However, the mechanisms by which green areas influence health remain poorly researched, especially in the context of the interaction of objective environmental characteristics (such as accessibility and quality) and subjective factors (such as environmental awareness and social interaction).

The relevance of this study lies in the need for a comprehensive analysis of the role of green areas in the formation of a healthy urban space. Despite the existing research devoted to the study of the relationship between the natural environment and health, questions such as what factors have the strongest impact on the frequency of use of green areas as well as how various aspects of green areas (physical, social, psychological) mediate their positive impact on health remain unresolved.

The aim of this study is to identify key determinants of green space use and assess their impact on physical and mental health using structural equation modeling (SEM). Unlike previous studies, this article pays special attention to the role of environmental awareness and social interaction as factors mediating the relationship between the urban environment and health. This research offers a comprehensive assessment of the objective and subjective characteristics of green spaces in a single model while analyzing the direct and indirect effects of green space on residents’ health. The results of the study may be useful for municipal authorities, public health specialists, and urban planners in designing a comfortable and health-friendly urban environment.

Thus, this study contributes to the development of an interdisciplinary approach to studying the urban environment, combining the perspectives of environmental psychology, urban studies, and public health. The results obtained expand our understanding of the mechanisms by which green spaces influence health and can serve as a basis for further research in this area.

2. Literature Review

As centers for the development of the economy, society, and culture, urban areas have always been considered the epicenter of human civilization [6]. While “urban” refers to a city or town, particularly in terms of its atmosphere, culture, and way of life [7], urban green spaces can be defined as specially created or naturally formed areas of urban territory covered with vegetation [8]. Intended for the recreation, health improvement, and social activity of the population [9], these spaces may include parks, squares, gardens, green boulevards, alleys, forest park zones, and other territories characterized by the presence of vegetation and elements of the natural landscape in the urban environment.

UGSs are a key component of urban infrastructure [10] and are designed to offset the negative impact of urbanization [11], improve air quality [12], regulate microclimate [13], reduce noise pollution [14], and create a favorable environment for maintaining the physical and mental health of the population [15]. In addition, green spaces act as places of social integration and public interaction, helping to strengthen social ties and improve the quality of life of city residents.

Thus, urban green spaces are multifunctional areas that simultaneously contribute to the environmental sustainability of the urban environment [16], the well-being and health of residents [15], and also provide socially significant functions of urban space [17].

A search for a combination of “public perception” AND “urban green spaces” on Scopus and Web of Science results in a very limited number of articles (44 articles on Scopus and 16 in WOS, when limiting the search to articles published in English). When duplicates are removed, an even smaller number of articles remain (50). This demonstrates how understudied the role of public perception is when it comes to urban green spaces. Below is the analysis of forty-four of the fifty articles, since the full text was not available for six of the fifty articles. A summary of all the analyzed articles is presented in Appendix A.

Based on the information provided in Appendix A, our analysis of studies on public perceptions of urban green spaces revealed the following:

• Twenty-five studies used quantitative surveys as their primary or sole method;
• Thirteen studies employed mixed-methods approaches;
• Four studies were observational;
• Three studies were literature reviews;
• Three studies used qualitative methods (focus group interviews);
• None of the analyzed articles employed PLS-SEM method for the analysis of public perception of urban green spaces, highlighting a research gap in this area.

In terms of the primary focus of the articles, thirty-three studies focused on various aspects of public perceptions; five studies specifically examined ecosystem services; four studies investigated willingness-to-pay; four studies focused on biodiversity; and two to three studies each examined climate change, urban trees, nature-based solutions, and informal green spaces.

The analysis of the indicated papers shows that urban green spaces are widely regarded as contributors to health and well-being. Quantitative surveys and mixed-methods studies—involving samples from 40 to over 2000 participants across more than 20 countries—indicate that natural settings ease stress and promote psychological balance. Respondents in multiple studies highlight benefits that span mental health (stress reduction and improved mood), physical health (better respiratory function and increased physical activity), social well-being (enhanced community cohesion), and environmental health (improved air quality and moderated temperatures). In several studies, each benefit appears tied to specific features of urban green spaces, including biodiversity and natural aesthetics.

Quality and access drive these perceptions. Respondents note that proximity; maintenance; and an attractive, natural design boost satisfaction and use. Safety concerns and socio-demographic factors—such as age, gender, income, and cultural background—further shape how urban green spaces are valued. Reviews also record growing recognition of ecosystem services such as urban cooling and water management, supporting the view that the health benefits of urban nature depend not only on the presence of green space but on its delivery as a well-designed, accessible, and contextually sensitive resource. The main themes related to the perceived health benefits found in the analyzed papers are presented in

Table 1. Thematic analysis of the perceived health benefits from the analyzed articles.

Benefit Category	Recognition Level	Contextual Factors	Key Findings
Mental Health	High	Age, education level, cultural background	Strong emphasis on stress reduction and psychological well-being
Physical Health	Moderate to High	Accessibility and quality of UGSs	Recognition of benefits for respiratory health and physical activity
Social Well-being	Moderate	Cultural context, urban design	Appreciation for social interaction and community cohesion
Environmental Health	High	Climate change awareness, education	Strong recognition of air quality improvement and temperature regulation
Restorative Effects	High	Biodiversity, natural elements	Positive association with natural features and biodiversity

.

The restorative effects mentioned in the table refer to the health benefits derived from psychological relaxation and stress reduction provided by biodiverse environments. Biodiversity, specifically diverse plant life and natural settings, has been associated with enhanced mental well-being [18,19,20] through increased sensory stimulation [21], aesthetic enjoyment [22], and stress recovery [23].

Overall, the studies show that public perceptions of the quality and accessibility of UGSs emerged as critical factors influencing the recognition and utilization of health benefits. Key findings from the analyzed papers highlight that perceived quality significantly affects public satisfaction and willingness to use UGSs, while proximity to UGSs is positively associated with perceived benefits and frequency of use. While aesthetic appeal plays a significant role in public perceptions, natural elements are generally preferred over artificial structures. Nevertheless, the relationship between accessibility and perceived benefits is not always straightforward. On top of that, cultural differences can influence preferences for UGS features, whereas safety concerns can negatively impact the use and perceived benefits of UGSs.

While the aforementioned analysis provides interesting insights into the public perception of urban green spaces, it also shows the lack of research that focuses on factors such as environmental awareness, social interaction, and usage frequency. Additionally, as was already mentioned, none of the previous research employed the PLS-SEM methodology for analysis of the public perception of UGSs; therefore, our research addresses this gap.

3. Materials and Methods

Based on the literature review and identified gaps, a theoretical model was developed including four exogenous variables (green space accessibility, green space quality, social interaction, and environmental awareness), one mediator variable (frequency of use), and two endogenous variables (perceived physical and mental health benefits) for the PLS-SEM analysis. The following hypotheses were proposed:

H1: 

Green space accessibility has a positive effect on the frequency of green space use.

H2: 

High quality of green spaces has a positive effect on the frequency of their use.

H3: 

Opportunities for social interaction have a positive effect on the frequency of use of green spaces.

H4: 

Environmental awareness of the population has a positive effect on the frequency of use of green spaces.

H5: 

Frequency of use of green spaces has a positive effect on perceived physical health benefits.

H6: 

Frequency of green space use will have a positive effect on perceived mental health benefits.

H7: 

Accessibility of green spaces will have a direct positive effect on perceived physical and mental health benefits.

H8: 

The quality of green spaces will have a direct positive effect on perceived physical and mental health benefits.

H9: 

Opportunities for social interaction in green spaces have a direct positive effect on perceived physical and mental health benefits.

H10: 

Environmental awareness has a direct positive effect on perceived physical and mental health benefits.

To collect primary data, a survey consisting of two parts was developed and distributed online. Only the responses from the urban residents were processed in the further analysis. The first part of the survey collected demographic data, whereas the second part included questions measured on a five-point Likert scale (from 1—“completely disagree” to 5—“completely agree”). The questions of the second part of the survey, as well as the construct they are linked to, are presented in

Table 2. Survey questions in relation to the studied constructs.

Construct	Questions
Green Space Accessibility (GA)	GA1. Green spaces are easily accessible from my home.
	GA2. There are plenty of green spaces available in my neighborhood.
	GA3. I can access green spaces without much effort or cost.
Green Space Quality (GQ)	GQ1. Green spaces in my area are well-maintained and clean.
	GQ2. The biodiversity in my local green spaces is rich.
	GQ3. The aesthetic appeal of my local green spaces is high.
Social Interaction (SI)	SI1. Green spaces provide ample opportunities for social interaction.
	SI2. I often meet and interact with other people when I visit urban green spaces.
	SI3. I engage in social activities with others in green spaces.
Environmental Awareness (EA)	EA1. I am aware of the environmental benefits of green spaces.
	EA2. I believe green spaces are crucial for environmental sustainability.
	EA3. I actively promote the benefits of green spaces within my community.
Usage Frequency (UF)	UF1. I frequently visit green spaces in my area.
	UF2. I spend a significant amount of time engaging with green spaces.
	UF3. I regularly participate in activities within green spaces.
Perceived Physical Health Benefits (PHBs)	PHB1. I feel that visiting green spaces has a positive impact on my physical health.
	PHB2. Green spaces contribute to my exercise and fitness routine.
	PHB3. Spending time in green spaces improves my overall physical well-being.
Perceived Mental Health Benefits (MHBs)	MHB1. Green spaces help me reduce stress and relax.
	MHB2. Spending time in green spaces positively impacts my emotional well-being.
	MHB3. My mental health benefits significantly from visiting green spaces.

.

The measure of biodiversity richness (GQ2) depends on the respondents’ subjective understanding of biodiversity, which may vary considerably and might not align with ecological definitions or objective assessments. Therefore, this subjective measure serves as an approximate indicator of the respondents’ perception rather than an accurate ecological assessment.

The method of structural modeling with the help of SmartPLS 4.0 software was used for data processing. The analysis took into account two stages:

Measurement model development: The reliability and validity of the used constructs were checked by assessing Cronbach’s Alpha, Composite Reliability, convergent validity (average variance extracted—AVE), and discriminant validity (Fornell–Larcker criterion).

Structural model development: Evaluation and testing of path coefficients, statistical significance of relationships (bootstrapping method), and determination of model fit indicators (R², Q², and f² coefficients).

The described methodology ensures the reliability of the results and confirms or refutes the proposed research hypotheses, providing a clear understanding of the structure and nature of the studied relationships.

4. Results

Table 3. Demographic characteristics of the participants.

Variable	Category	N	%
What is your age?	<18	17	7.1%
	18–24	109	45.4%
	25–34	80	33.3%
	35–44	24	10.0%
	>45	10	4.2%
What is your gender?	Male	108	45.0%
	Female	130	54.2%
	Prefer not to say	2	0.8%
What is your highest level of education?	Less than high school	8	3.3%
	High school diploma	76	31.7%
	Bachelor’s degree	104	43.3%
	Associate’s degree	8	3.3%
	Master’s degree	40	16.7%
	Prefer not to say	4	1.7%

shows the breakdown of survey respondents by age, gender, and education level. Most participants (45.4%) were between 18 and 24 years old, followed by those aged 25–34 (33.3%), indicating a predominantly young sample. Women made up a slightly larger portion (54.2%) than men (45.0%), with a very small percentage (0.8%) choosing not to disclose their gender. In terms of education, the majority held a bachelor’s degree (43.3%) or high school diploma (31.7%), while fewer had advanced degrees like a master’s (16.7%). Only a small fraction (3.3%) reported less than a high school education. Overall, 240 people participated in the survey.

First, we ran a confirmatory factor analysis (CFA) within the SEM framework to check how well the questionnaire items measured the intended constructs. The measurement model was evaluated based on two main things: convergent validity and discriminant validity. Convergent validity tells us whether the items in the questionnaire truly measure the same underlying concept. To confirm this, we looked at three things: item reliability, internal consistency, and average variance extracted (AVE), following the guidelines from [24].

Item reliability was checked using factor loadings, which show how strongly each question relates to its assigned construct. A factor loading above 0.7 means the construct explains more than half of the item’s variance [25]. If an item has a loading below 0.7 but the overall AVE for the construct is still above 0.5, it can still be kept as long as its loading is above 0.5 [26]. Keeping weak items can make the whole construct less reliable, as noted by [27].

Next, we checked internal consistency to make sure all items in a construct reliably measure the same thing. Unlike Cronbach’s alpha, which has some flaws, PLS-based reliability measures (like composite reliability) give a better assessment [28]. Both composite reliability and Cronbach’s alpha should ideally be between 0.7 and 0.95 to confirm good internal consistency [25].

Finally, we calculated each construct’s average variance extracted (AVE). AVE shows how much of the item variance is captured by the construct rather than measurement error. A score above 0.5 means the construct explains more variance than the error, which is acceptable [29]. The current study’s measurement model is shown in Figure 1.

Table 4. Reliability and convergent validity.

Construct	Items	Loading	CA	CR	AVE
Green space accessibility (GA)	GA1	0.901	0.885	0.926	0.806
	GA2	0.927
	GA3	0.865
Green space quality (GQ)	GQ1	0.839	0.891	0.934	0.826
	GQ2	0.956
	GQ3	0.927
Social interaction (SI)	SI1	0.784	0.817	0.890	0.731
	SI2	0.923
	SI3	0.853
Environmental awareness (EA)	EA1	0.854	0.761	0.863	0.679
	EA2	0.873
	EA3	0.737
Usage frequency (UF)	UF1	0.685	0.704	0.833	0.626
	UF2	0.855
	UF3	0.822
Perceived physical health benefits (PHBs)	PHB1	0.905	0.783	0.873	0.698
	PHB2	0.797
	PHB3	0.799
Perceived mental health benefits (MHBs)	MHB1	0.939	0.931	0.956	0.879
	MHB2	0.933
	MHB3	0.940

shows that all items expressed factor loading greater than 0.7 except UF1; however, the overall AVE of the UF construct is greater than 0.5; hence, the item is retained in the measurement model. Moreover, Cronbach’s alpha and composite reliability values for all the constructs are greater than 0.7; therefore, the measurement model has no reliability issues. Similarly, AVE values for all constructs are greater than 0.5; therefore, the measurement model has no convergent validity issues.

The next step in evaluating the measurement model was checking discriminant validity, which ensures that each construct is truly different from the others. We used two methods to test this.

First, we used the heterotrait–monotrait ratio of correlations (HTMT). This method compares the average correlations between different constructs (heterotrait) to those within the same construct (monotrait). Ref. [30] suggests that an HTMT value below 0.90 is acceptable when constructs are conceptually similar, while a stricter threshold of 0.85 should be used for clearly distinct constructs. If the HTMT values stay under these limits, the constructs are truly separate and do not overlap.

Next, we applied the Fornell–Larcker criterion. This method compares the square root of the AVE for each construct with its correlations to other constructs [24]. In the correlation matrix, the square roots of the AVE values sit on the diagonal, while the correlations between constructs appear off-diagonal. For discriminant validity to hold, the square root of a construct’s AVE must be larger than any of its correlations with other constructs [31]. This confirms that the construct shares more variance with its own items than with other constructs.

The current analysis showed that all HTMT correlations (

Table 5. HTMT correlations.

	EA	GA	GQ	MHB	PHB	SI	UF
EA
GA	0.258
GQ	0.099	0.763
MHB	0.638	0.234	0.097
PHB	0.812	0.323	0.214	0.842
SI	0.288	0.429	0.5	0.121	0.338
UF	0.658	0.28	0.32	0.49	0.775	0.63

) were below 0.85, indicating no discriminant validity issues. Moreover, the Fornell–Larcker criterion (

Table 6. Fornell–Larcker criterion.

	EA	GA	GQ	MHB	PHB	SI	UF
EA	0.824
GA	0.215	0.898
GQ	0.057	0.649	0.909
MHB	0.545	0.227	0.092	0.937
PHB	0.644	0.298	0.181	0.702	0.835
SI	0.220	0.357	0.424	0.105	0.275	0.855
UF	0.481	0.225	0.247	0.418	0.611	0.499	0.791

) showed that the AVEs of all the constructs were greater than their correlations with other constructs. Hence, the measurement model has no discriminant validity issues, and the constructs can be used in the structural model for hypothesis testing.

The structural model was analyzed with bootstrapping using 5000 random samples. The structural model is presented in Figure 2. The results of the path analysis are shown in

Table 7. Path coefficients.

Hypothesis	Path	Beta	T Values	p Values	Result
H1	GA -> UF	−0.07	1.063	0.288	Not supported
H2	GQ -> UF	0.105	1.579	0.114	Not supported
H3	SI -> UF	0.391	7.201	<0.000	Supported
H4	EA -> UF	0.404	6.205	<0.000	Supported
H5	UF -> MHB	0.272	3.062	0.002	Supported
H6	UF -> PHB	0.409	4.777	<0.000	Supported
H7a	GA -> MHB	0.153	2.428	0.015	Supported
H7b	GA -> PHB	0.142	2.383	0.017	Supported
H8a	GQ -> MHB	−0.028	0.352	0.725	Not supported
H8b	GQ -> PHB	−0.003	0.048	0.962	Not supported
H9a	SI -> MHB	−0.166	3.064	0.002	Supported
H9b	SI -> PHB	−0.074	1.572	0.116	Not supported
H10a	EA -> MHB	0.42	4.534	<0.000	Supported
H10b	EA -> PHB	0.434	5.48	<0.000	Supported

.

The path analysis results show that social interaction (SI) and environmental awareness (EA) both had a significant positive influence on usage frequency (UF), with beta values of 0.391 (p < 0.000) and 0.404 (p < 0.000), respectively. However, green space accessibility (GA) and green space quality (GQ) did not show a significant relationship with UF, as their beta values were −0.07 (p = 0.288) and 0.105 (p = 0.114).

When examining the effects of UF on health outcomes, usage frequency had a significant positive impact on both mental health benefits (MHBs), with a beta of 0.272 (p = 0.002), and physical health benefits (PHBs), with a beta of 0.409 (p < 0.000). Direct effects were also observed—GA positively influenced both MHBs (beta = 0.153, p = 0.015) and PHBs (beta = 0.142, p = 0.017), while GQ showed no significant relationship with either health outcome (MHB: beta = −0.028, p = 0.725; PHB: beta = −0.003, p = 0.962). Interestingly, SI negatively affected MHBs (beta = −0.166, p = 0.002) but had no significant impact on PHBs (beta = −0.074, p = 0.116). In contrast, EA had strong positive effects on both MHBs (beta = 0.42, p < 0.000) and PHBs (beta = 0.434, p < 0.000).

5. Discussion

The current study aimed to explore the relationships between various aspects of urban green spaces—accessibility, quality, social interaction opportunities, and environmental awareness—and their impacts on usage frequency and perceived health benefits.

The results revealed that social interaction and environmental awareness significantly influenced the frequency of green space use, highlighting that both social and cognitive–affective dimensions strongly motivate individuals to engage more frequently with urban green spaces. This aligns with existing literature suggesting that social interactions facilitated by green spaces enhance their attractiveness and use. Additionally, it shows that greater awareness of environmental benefits encourages regular engagement with these areas.

Contrary to expectations, green space accessibility and quality did not significantly predict usage frequency. These findings are somewhat unexpected given previous research emphasizing proximity and quality as key determinants of green space usage. Possible explanations might include the generally high baseline accessibility and quality in the study area, potentially causing these factors to exert minimal incremental influence on residents’ decisions to visit green spaces. Nevertheless, this phenomenon requires further investigation.

Further examining the health outcomes, the study confirmed that higher usage frequency significantly enhanced both perceived physical and mental health benefits, highlighting the critical role of active and frequent engagement with green spaces in promoting individual well-being. This finding supports existing studies suggesting that regular interaction with natural environments can substantially enhance physical fitness, reduce stress, and promote emotional well-being [32,33,34].

The accessibility of UGSs positively affected both mental and physical health perceptions, emphasizing the importance of readily accessible green spaces in promoting health, independent of usage frequency. Surprisingly, green space quality did not significantly influence health outcomes, challenging the assumption that superior aesthetic or biodiversity attributes directly enhance health perceptions.

Moreover, social interaction presented a paradoxical influence, negatively impacting mental health perceptions while having no significant relationship with physical health benefits. This unexpected negative association might reflect the complexities associated with social interactions, including potential social stressors or conflicts that sometimes arise in communal spaces. Further qualitative studies could elucidate these mixed experiences.

In contrast, environmental awareness was found to be a positive predictor for both mental and physical health perceptions. This highlights the substantial role of environmental cognition in shaping individual health benefits beyond direct exposure or physical interaction with green spaces. Enhancing educational programs aimed at increasing environmental awareness could, thus, amplify the beneficial impacts of urban greenery on public health.

The findings of the current study align closely with the Theory of Planned Behavior [35,36] by highlighting the significant role of environmental awareness in influencing the frequency of green space usage. Moreover, social interaction significantly increased the frequency of green space visits, consistent with the theory of planned behavior’s emphasis on subjective norms, where community and social ties encourage behavioral intentions. However, the observed negative impact of social interaction on mental health outcomes presents a fresh perspective that could suggest social pressures or conflicts within communal spaces might sometimes lead to stress, complicating the relationship predicted by the theory of planned behavior.

Finally, the positive association found between the usage frequency of green spaces and perceived mental health benefits strongly supports the Stress Recovery Theory [37], suggesting that natural environments facilitate recovery from mental fatigue and stress by providing restorative experiences. The article’s findings confirm this theoretical assertion, demonstrating how frequent visits to urban green spaces are linked to improved mental well-being.

While the sample predominantly consists of young, educated individuals, future research should aim to include a more diverse demographic to improve the generalizability of the findings. This is particularly important as age and educational background have been shown to significantly influence environmental awareness and perceptions of urban green spaces [38,39]. Additionally, the lack of significance for green space quality in predicting usage frequency and health benefits may suggest that respondents in this study generally had high-quality green spaces available; however, this cannot be confirmed, as the quality of available green spaces was not assessed by the conducted survey.

6. Conclusions

This study confirmed the importance of a number of factors influencing the frequency of use and the perception of the benefits of urban green spaces for the physical and mental health of residents. While environmental awareness and social interaction significantly predicted usage frequency, accessibility and quality were not found to have a significant impact on usage frequency. The results confirmed the hypotheses about the positive effect of accessibility, quality of green spaces, social interactions, and environmental awareness on the frequency of their use. In addition, the important role of the frequency of visiting green spaces in the perception of the physical and mental health of the population was revealed.

The results of the analysis also revealed significant direct effects of green space accessibility and environmental awareness on the perception of their benefits for physical and mental health. At the same time, the quality of green spaces did not have a significant effect on either the frequency of their use or the perception of their health benefits. In addition, an unexpected negative effect of social interactions on perceived mental benefits was found, which may indicate the need for a more in-depth study of the nature of social activities in these areas. The practical significance of the obtained results is that city authorities and urban planners can use them when developing strategies to improve the quality of the urban environment.