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Article

Exploring Safety Perceptions Among Women Using Factor and Cluster Analysis: A Case Study of Neighborhood Parks in Jordan

by
Haneen Ahmad
1,
Yuxin Cao
1,2,
Ayat Almomani
3,
Lama Akmeel
1 and
Lijun Wang
1,2,*
1
School of Architecture, Tianjin University, Tianjin 300072, China
2
Tianjin Key Laboratory of Healthy Habitat and Smart Technology, No. 92, Weijin Road, Nankai District, Tianjin 300072, China
3
Department of Statistics, Yarmouk University, Irbid 21163, Jordan
*
Author to whom correspondence should be addressed.
Land 2025, 14(4), 725; https://doi.org/10.3390/land14040725
Submission received: 19 February 2025 / Revised: 13 March 2025 / Accepted: 27 March 2025 / Published: 28 March 2025
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Abstract

:
Most of the time, urban planning tends to exclude the specific needs and perceptions of women, resulting in spaces that fail to meet their safety needs. This study explores the impact of physical environment factors on women’s safety perceptions in neighborhood parks in Jordan. While a few studies on this topic have been conducted in Jordan, this research makes a unique contribution by focusing on the interaction between physical design factors and demographic characteristics, examining how these factors influence women’s safety perceptions. Focusing on women’s safety in neighborhood parks, a survey was conducted and involved a sample of 380 women, using a random sampling method. confirmatory factor analysis (CFA) was employed to identify underlying relationships between safety-related factors, while cluster analysis was used to group women based on their shared safety perceptions. The results revealed statistically significant differences and identified five distinct clusters, demonstrating varied perceptions of safety among women. This study emphasizes the importance of tailoring park designs to meet women’s specific safety needs, recognizing the diversity of priorities across demographic groups. The findings offer actionable insights for urban planners and policymakers, guiding the development of safer public spaces that respond to the varied needs of women.

1. Introduction

Parks are important components of green infrastructure within cities [1,2] as they provide numerous advantages to residents; they play a vital role in enhancing the quality of life and the overall well-being of urban populations by fulfilling ecological, economic, aesthetic, social, and health-related functions [3,4,5,6]. Parks act as primary venues for recreation and physical activity for various user groups, as they are essential for enhancing their physical well-being [3,7,8,9,10]. They contribute to better mental health [11,12] outcomes for individuals by facilitating a connection with nature in densely populated areas. Their role in shaping safety perceptions has been widely recognized in urban planning and environmental psychology [13,14].
Safety is considered a fundamental human need, ranking just below basic physiological needs; therefore, feelings of safety serve as a foundation for fulfilling higher emotional needs, contributing to overall well-being [15]. Furthermore, a lot of studies have indicated that a positive view of safety, particularly within neighborhoods, enhances health outcomes [16,17,18]. If residents consider a neighborhood unsafe, then it tends to have negative effects on them; it leads to an increase in anxiety and reduces life satisfaction [19], which can result in poor and negative health consequences [20]. Despite its significance, a lack of safety is becoming more recognized as a serious social issue [21,22]. In this case, one of the most urgent issues faced by urban planners is identifying the ways in which they can contribute to increasing safety.
The concept of safety perception is a complex and multidimensional issue [23,24,25], arising from the interplay between a person’s traits and the environments they encounter. The way individuals perceive safety is also affected by their previous personal experiences and backgrounds, as well as by social interactions, cultural influences, and individual traits. Consequently, the perception of safety is closely connected to a person’s social identity and its various dimensions, such as age, gender, and status.
The theory of Crime Prevention Through Environmental Design (CPTED) focuses on preventing crime and reducing fear through environmental design. It was initially brought up by Clarence Ray Jeffery in 1971. Related environmental concepts were refined by academics into four key techniques: (1) monitoring; (2) access control; (3) territoriality; and (4) maintenance [26,27]. Parks that incorporate CPTED principles are considered safe. These principles include natural inspection and access control [28,29]. Safety in urban green areas has emerged as a significant topic in recent years for modern societies; it is urging many local governments to explore management strategies that can help alleviate fears of crime and criminal activity in public parks [30,31]. Prior studies have indicated that an increase in green spaces within cities positively influences feelings of safety; nevertheless, to ensure that these green areas are comfortable for use, it is essential to cultivate safety among their users [32].
However, the design and physical attributes of parks greatly influence the safety perception of individuals, especially women. Physical elements of the environment, such as lighting, visibility, accessibility, and maintenance, play an important role in the development of safety perceptions. Parks are perceived as unsafe when these elements are inadequate, discouraging their use and diminishing their social and health benefits [33].
Studies have explored general perceptions of park safety. It is essential to consider the contribution of specific physical environmental factors to these perceptions. The physical environment of a park influences the safety perception of visitors. One of the most important factors is lighting conditions [34,35]; parks that have poor lighting cannot create feelings of safety. Lighting is especially required at night because darkness can increase the fear of potential threats. Studies have shown that well-lit parks enhance perceived safety because they reduce opportunities for crime [36,37]. Adequate lighting also promotes park use; it ensures the presence of more people and discourages criminal activities [38,39].
Another important environmental factor of parks is maintenance. Dense treetops and overgrown grass can obstruct visibility, creating hiding spots for potential criminals [40]. Research indicates that poorly maintained parks with excessive vegetation contribute to a fear of crime, and this is particularly seen among women and elderly visitors [41]. In contrast, well-managed parks with clear visibility and open spaces foster a sense of safety and encourage social interaction [42]. Park infrastructure and design also play an important role in safety perceptions. The presence of security features, such as CCTV cameras and security patrols, reduces the fear of crime [43]. Also, clear signage and designated activity zones improve navigation. Thus, they reduce the risk of crimes [44].
Gender is a commonly examined demographic factor that influences the perception of crime in urban public areas [45,46,47]. Women and men have distinct perceptions of safety [48,49]. Studies on both genders indicate that the factors affecting individuals’ safety are tied to various attributes of parks. These factors include both psychological and physical elements [47,49,50,51,52,53,54]. Programmed and effectively designed urban parks can help lower crime rates [55]. Also, positive physical attributes and appealing public areas can promote interaction among residents and aid the development of a sense of community to enhance feelings of safety [56,57].
Although a lot of research has been conducted on safety perception in parks, gaps remain in understanding how specific physical factors interact with demographic characteristics to influence safety perceptions. This study will bridge this gap by examining the effect of lighting, visibility, isolation, accessibility, maintenance, and signage on the safety perception of women.
Most studies on safety perceptions rely on qualitative assessments or crime statistics. They do not explore the role of factor analysis and clustering techniques in identifying patterns in women’s perceptions of safety [40,58,59]. Existing research focuses on urban safety concerns. But it does not distinguish the unique experiences of women in parks. Some researchers have quantitatively examined the effect of different variables on perceptions of safety among women. Most studies have focused on crime rates and social factors influencing urban safety. But there are only a few studies that have systematically analyzed the direct impact of design elements such as lighting, isolation, and visibility on safety perceptions [60,61,62].
This study addresses a significant gap in the literature by employing advanced statistical techniques, including confirmatory factor analysis (CFA) and cluster analysis, to develop a data-driven understanding of the design factors influencing women’s perceptions of safety in neighborhood parks. By integrating both factor analysis and cluster analysis, the research offers a more systematic and nuanced examination of women’s safety concerns, moving beyond the limitations of traditional qualitative assessments.
A key contribution of this study lies in its emphasis on demographic variations in safety perceptions, considering factors such as age, marital status, education, income level, and disability. This approach diverges from prior research that often treats women as a homogeneous group. The use of cluster analysis facilitates the identification of distinct subgroups of women with varying safety concerns, thereby enabling a more targeted and inclusive approach to park design. The findings aim to offer actionable insights for urban planners and policymakers, guiding the development of safer public spaces that are responsive to the diverse needs of women.
The context of Jordan is particularly significant for studying women’s perceptions of safety in public spaces, given the unique cultural, social, and urban planning challenges faced by women in this region. In recent years, there has been growing recognition of the need to address gender-specific concerns in urban design, particularly in public spaces like neighborhood parks. Understanding how women perceive and interact with their environment is critical to creating inclusive and safe urban spaces. This study is critical for Jordanian urban planning, as it seeks to identify the factors influencing women’s safety in neighborhood parks. In the context of Jordan, where urban spaces often reflect conservative views on gender roles, understanding the specific environmental factors that affect safety perceptions can provide valuable insights for policy development.

2. Materials and Methods

Survey research, as a quantitative research approach, was employed in this study to investigate how physical environment factors differentiate perceptions of safety among women in neighborhood parks. A structured questionnaire was distributed randomly online via social media platforms during September and October 2024. The questionnaire was initially drafted in English and later translated into Arabic to align with the language preferences of the target audience. A dataset of size n = 380 was analyzed using the statistical language R (version 4.2.2) after checking the data for missing data and outliers.
The questionnaire comprised 35 items. It consisted of two primary sections: The first section included six items capturing the demographic characteristics of respondents. These items included age, marital status, educational level, occupation, income level, and disability status. The second section contained 29 items focused on six key factors identified in the literature as associated with perceived safety in parks, including lighting, visibility, isolation, signage systems, accessibility, and maintenance.

2.1. Research Design

The factors were classified into the above-mentioned six groups according to the scheme presented in Table 1. Participants were asked to rate each factor in terms of safety on a 5-point Likert scale (1 = Strongly Disagree, 2 = Disagree, 3 = Neutral, 4 = Agree, 5 = Strongly Agree).

2.2. Sample Size and Characteristics

2.2.1. Sample Size

Since the total number of women visiting parks in Jordan is unknown, Cochran’s formula was applied to determine an appropriate sample size for this unknown population, assuming a 95% confidence level and a 5% margin of error:
n = Z 2 × p × q   d 2
where
  • n = required sample size;
  • Z = z-score for 95% confidence level (1.96);
  • p = estimated proportion of the population (0.5, as a conservative assumption);
  • q = 1 − p;
  • d = margin of error (0.05).
n = 1.96 2 × ( 0.5 ) × ( 0.5 ) ( 0.05 ) 2 = 380
Thus, 380 valid responses were collected to ensure statistical reliability and enhance the generalizability of findings.

2.2.2. Sample Characteristics

As previously mentioned, a total of 380 woman participants from Jordan took part in the survey. Participants’ privacy was maintained throughout the data collection process, as no personally identifiable information was collected. Only demographic details were collected, as listed in Table 2. Of the participants, 41% were aged 25–34 years old, and 47.89% identified as single. Additionally, 54.74% of respondents were employed, with the largest proportion (31.05%) earning a monthly salary of JOD 250–400. Most respondents (98%) reported no disabilities. Three women reported physical disabilities. One had vision impairment, one had hearing impairment, and one had speech impairment. These details offer a record of the diverse sample used in this study.

2.3. Validity and Reliability

Cronbach’s alpha was calculated for all dimensions of this study to test the reliability of the tool. This ensured that the questions were clear, objective, and suitable for statistical analysis [63]. The overall value of Cronbach’s alpha indicated a high level of internal consistency. It is well above the acceptable level for reliability. Each item had an alpha value well above the threshold, indicating that no items needed to be removed. The results confirm that the research tool is reliable and appropriate for measuring the intended objectives [64].

2.4. Confirmatory Factor Analysis (CFA)

Confirmatory factor analysis (CFA) is a statistical technique used to validate the factor structure of observed variables and confirm whether they accurately represent underlying theoretical constructs. In this research, CFA was applied to assess reliability, internal consistency, and model fit while refining the measurement scale. The Kaiser–Meyer–Olkin (KMO) test was used to evaluate sample adequacy and assess the factorability of the correlation matrix. Composite reliability was calculated to evaluate internal consistency, and items that did not meet the reliability threshold were excluded to enhance model stability [65]. A path diagram of the proposed factor model was developed, and fit indices such as the normed x2, comparative fit index (CFI), and Tucker–Lewis Index (TLI) were examined to determine the overall model fit. The refined model was validated as an appropriate tool for measuring the intended objectives [66].

2.5. Cluster Analysis

Cluster analysis is a statistical technique used to group similar objects or individuals into clusters based on their characteristics. The five factors (lighting, visibility, isolation, signage system, and accessibility), along with demographic variables such as age, marital status, educational level, occupation, income, and disability, were used as inputs for the cluster analysis. This was carried out to determine the number of clusters and group participants with similar characteristics. Participants were grouped into clusters based on similar responses to the five factors. Their demographic data were analyzed at the group level to identify patterns and differences. Hierarchical cluster analysis (HCA) was performed using the Ward method, which helps determine the optimal number of clusters by evaluating correlations and similarities among participants [67].

3. Results

3.1. Validation Process

Cronbach’s alpha was calculated for all study axes. It verifies the tool’s validity, as well as the clarity and objectivity of the questions. The overall Cronbach’s alpha value is 0.84, which is good and exceeds the threshold of 0.7. The Cronbach’s alpha for each item also exceeds the threshold. So, there is no need to drop any of the items. This confirms that the study tool is reliable and suitable for measuring the intended objectives.

3.2. Confirmatory Factor Analysis

Confirmatory factor analysis was performed to test the factor structure using the collected data. The Kaiser–Meyer–Olkin (KMO) test of sample adequacy was conducted to assess the factorability of the correlation matrix. As shown in Table 3, the overall measure of sample adequacy (MSA) is 0.91, which is excellent, and so are the MSA coefficients for each item. The normed x2 = 905.8, the comparative fit index (CFI) is 0.9, the Tucker–Lewis index (TLI) is 0.9, and the RMSEA value is 0.078, which is below 0.80. This indicates that the model fits the data.
Composite reliability was analyzed for each factor after dropping certain items (Table 4) to evaluate the internal consistency of the model derived from the final CFA (Figure 1). To reach the threshold of 0.7, one item was dropped in the lighting factor, one item was dropped in the isolation factor, and all maintenance items were dropped. This confirms that the study tool is appropriate and can be used to measure the required objectives.
Figure 1 shows that the factor loadings, where lighting shows moderate-to-strong contributions to the latent factor. Visibility has varying loadings, where V1 exhibits the weakest contribution, which indicates a weaker relationship with the construct. Isolation demonstrates moderate loadings, supporting its relevance to the latent construct. The signage system shows strong loadings, indicating the active measurement of this factor. Accessibility displays varied but substantial loadings; this reflects its importance in accurately measuring the latent construct.
The figure also shows the inter-factor relationships, revealing various correlations between latent factors; they can be classified as follows:
  • A strong positive correlation between the signage system and lighting shows an active connection;
  • A strong positive correlation between isolation and the signage system highlights their interconnectedness;
  • A positive correlation between the signage system and accessibility emphasizes the mutual influence of clear signage in the development of safety;
  • A notable positive correlation exists between accessibility and isolation;
  • A moderate positive correlation between accessibility and lighting shows a supportive relationship;
  • A weak positive correlation between the signage system and visibility indicates limited mutual influence;
  • A weak negative correlation between visibility and isolation reflects an inverse relationship;
  • A weak negative correlation between accessibility and visibility indicates limited inverse interaction;
  • A negative correlation between lighting and visibility shows that more lighting cannot directly improve visibility.

3.3. Cluster Analysis: Five Typologies of Women’s Groups

The performance of different hierarchical clustering methods was compared. The Ward method shows the best clustering structure. It achieves the highest ARI value of 0.94 as compared to the average (0.83), single (0.80), and complete (0.89) methods. This shows that the Ward method provides the most reliable clusters among the evaluated methods. Figure 2 illustrates the use of the Elbow method for determining the optimal number of clusters. The plot clearly indicates that five clusters should be selected, as the within-cluster sum of squares (WCSS) shows a significant decrease at this point, followed by a flattening of the curve. This signifies that additional clusters do not improve the clustering solution. These results support the choice of the Ward method as the ideal solution for this dataset. The dataset can be effectively divided into five distinct subgroups using the Ward method. The study identified five clusters with varying numbers of members, as shown in Figure 3. Cluster 1 consisted of 86 members, while Cluster 2 included 88 members. Cluster 3 was the largest with 95 members. Cluster 4 had 52 members, and Cluster 5 had 59 members.
Table 5 describes the typology of women in each of the five clusters, where the data show each cluster’s demographic profile. Moreover, Table 6 shows how women in clusters interact with the safety-related physical environment factors (lighting, visibility, isolation, signage, and accessibility) along with their variability, reflecting agreement or a diversity of opinions. The table employs a color-coded system to represent different rating levels and their variability. Green, ranging from dark to light, corresponds to high ratings, with variability decreasing from high to low. Orange encompasses a broader range, transitioning from moderate ratings with moderate variability to high ratings with low variability and further to moderate ratings with high variability. Lastly, yellow is used to denote low ratings with moderate variability.
The five clusters identified in the study can be described by combining their demographic characteristics (Table 5) with their interactions with safety-related physical environment factors (Table 6) as follows:
  • Cluster 1: Younger, educated women with moderate incomes
This cluster comprises women aged 25–34, with the majority being single. Most hold at least a bachelor’s degree and have an income between JOD 250 and 400. Employment is common in this cluster, with the majority being employed. This cluster shows high ratings with low variability for lighting and isolation, high ratings with low variability for signage and accessibility, and low ratings with moderate variability for visibility.
  • Cluster 2: Older, family-oriented women with moderate incomes
This cluster primarily includes women aged 45–54, where married women with children dominate. Most have a bachelor’s degree, earn between JOD 250 and 400, and are employed, with a notable presence of housewives and retirees. This cluster shows high ratings with low variability for lighting, moderate ratings with moderate variability for isolation, high ratings with moderate variability for signage, and high ratings with moderate variability for accessibility, while visibility is scored as moderate with moderate variability.
  • Cluster 3: Diverse ages, higher income, and balanced perceptions
This cluster mainly consists of women aged 25–34, with single women being the majority. It includes the highest-income group, earning more than JOD 800, with most participants being employed. This cluster includes moderate ratings with moderate variability for lighting and isolation, moderate ratings with high variability for signage, and moderate ratings with moderate variability for accessibility. Visibility is scored as moderate with moderate variability.
  • Cluster 4: Young, diverse group
This cluster features a majority aged 25–34, with single women and married women with children being the most common marital statuses. Most earn between JOD 250 and 400, and this cluster uniquely includes women with disabilities. It also has a mix of employed, student, and unemployed respondents. Scores for this cluster include high ratings with low variability for lighting, moderate ratings with moderate variability for isolation, high ratings with moderate variability for signage, and high ratings with moderate variability for accessibility. Visibility is scored as moderate with moderate variability.
  • Cluster 5: Young, low-income, single women
This cluster primarily consists of younger women aged 18–24. They were nearly all single. Most earn between JOD 250 and 400 or less than JOD 250. The second-largest group was students. This cluster includes high ratings with low variability for lighting, moderate ratings with moderate variability for isolation, high ratings with moderate variability for signage, and high ratings with moderate variability for accessibility, while visibility has moderate ratings with moderate variability.

4. Discussion

This study analyzed safety perceptions among women in neighborhood parks and was conducted in Jordan by measuring important physical environment factors. These factors include lighting, visibility, isolation, signage, and accessibility. This research identified the most significant factors influencing safety perceptions through factor and cluster analysis (Figure 4). In this section, we evaluate the results, compare them with previous studies, and discuss their implications for urban planning in Jordan.

4.1. Physical Environment Factors

4.1.1. Lighting

Lighting is an important factor affecting the safety perceptions of women in parks. The results indicate that well-lit areas significantly enhance safety, particularly at night. These findings align with previous studies, and they emphasize the role of adequate light in reducing the fear of crime [35]. In the urban parks of Jordan, poor lighting is an issue in some areas that have limited municipal regulation. Women in Amman have reported that they feel unsafe in parks with dim lighting [68], highlighting the need for proper lighting infrastructure.
This study also found that walking paths with proper signage and visibility significantly enhance perceived safety. This supports the argument that lighting enhances direct visibility. Research from other Middle Eastern countries has shown that insufficient lighting in public spaces is the primary hindrance to the participation of women in outdoor activities [69,70]. Thus, policymakers in Jordan should prioritize proper and high-intensity lighting systems.
Another important point of this study is the moderate correlation between lighting and accessibility. This shows that well-lit parks are not considered safe when their access points are poorly maintained [71,72]. This highlights the need for general safety interventions that incorporate light improvements with accessibility.

4.1.2. Visibility

Visibility plays an important role in determining safety in outdoor spaces. The results revealed that clear visibility increases safety perceptions. Obstructions in visibility contribute to fear and discomfort, and such hindrance may be due to walls and blind spots. These findings align with Crime Prevention Through Environmental Design (CPTED) principles. These principles emphasize maintaining open visibility to reduce crime and enhance the confidence of users in public spaces [73].
Old parks in Jordan contain design elements that obstruct visibility, such as poorly placed benches and high boundary walls. Research conducted in Amman found that women often avoid parks with hidden corners [74], supporting our finding that visibility is a key requirement for safe and inclusive park design.
This study shows correlations between visibility and isolation. Women show more concern about areas where visual obstructions result in segregated spaces. This aligns with global studies that indicate that isolation intensifies a sense of fear [75]. Park planners in Jordan should adopt open-space designs that minimize hidden areas. This will ensure that all sections of the park remain visible from multiple points.

4.1.3. Isolation

Isolation is considered one of the greater hinderances to park use among women. The results indicate that secluded areas do not offer feelings of safety and have minimal human activity. These findings are consistent with earlier studies which suggest that social isolation in public spaces creates a sense of crime-related fear [76].
Several neighborhood parks have poor maintenance in Jordan, so people rarely visit them, which makes them abandoned. Research in [77] highlights that many women avoid using parks that lack security and social presence. This aligns with the finding of this study that isolation strongly correlates with negative safety perceptions. The absence of nearby residences and commercial areas makes certain parks less safe for women because isolation affects the lack of safety perception of women.
Community gatherings in parks play a vital role in reducing isolation. For example, organizing fitness activities and social gatherings can help increase the presence of park users. This will thereby reduce the perception of seclusion. In Amman, some parks have implemented community-led initiatives to maintain an occupied atmosphere. This has improved the willingness of women to visit parks [78]. These interventions show that more traffic is an effective strategy for reducing the negative effects of isolation.

4.1.4. Signage System

Signage is also an essential factor that influences the safety perceptions of women. This study found that clear signage systems reduce anxiety by improving orientation. The presence of directional signs, emergency contact information, and park maps has a positive effect on safety [79].
The importance of signage in parks has already been discussed in previous studies. Poor signage increases stress and fear, as individuals feel disoriented in the absence of proper signs [80]. In Jordan, inconsistent signage is a common issue in some public parks. Many parks lack sufficient directional signs, and sometimes, signs are improper and difficult to read.
This study shows a strong positive correlation between signage and accessibility. This suggests that signage has dual significance. It enhances safety perceptions and guides proper orientation. Safety among users improves when they can easily locate entry points and other facilities [81]. Public authorities should invest in standardized, easy-to-understand signage to ensure that all park users can navigate the space safely.

4.1.5. Accessibility

Accessibility is one of the most vital components of park safety. The results indicate that parks with multiple entry points and easy accessibility generally enhance women’s perceptions of safety. This study also found that features such as ramps and emergency exits contribute to overall safety. Accessibility barriers are a significant issue in many parks, disproportionately affecting women. Research in [82,83] found that many public spaces in Amman lack basic accessibility features. It is difficult for individuals to overcome fears for their safety. This aligns with a finding from another study that poorly designed pathways negatively impact safety perceptions.
In this study, another correlation is identified between accessibility and isolation. Parks that were difficult to access typically had fewer visitors, making them feel more secluded, which heightened feelings of fear. This shows that overall feelings of safety can be increased by improving access points to main roads or public transportation. The best international practices show that inclusive design principles can help to fill the accessibility gap. Such rules include barrier-free pathways and well-maintained entry points [84,85]. Urban planners should incorporate these features into park development projects to create safer and more inclusive public spaces.

4.2. Cluster Analysis

In addition to factor analysis, cluster analysis was conducted to investigate safety perception in different groups of women. This analysis identified five distinct clusters. Each cluster had unique safety perceptions (Figure 5). These perceptions are based on various physical environment factors. The influence of demographic factors such as age and income on women’s safety in public spaces can be depicted easily by results from cluster analysis [86].
The first cluster consists of younger and educated women with moderate incomes. This cluster showed that lighting, isolation, and accessibility make a major contribution to safety perceptions. This group showed the highest satisfaction level with parks that had proper lighting, clear signage, and accessibility. Previous research in [87,88] found that well-lit and easily accessible parks increase the participation of women in outdoor activities. However, similar studies [89,90] revealed that women feel unsafe in less visible areas within parks, so they are also concerned about visibility. This highlights the need for open-air park designs without obstructed areas.
The second cluster represents older and family-oriented women. This cluster also showed that lighting and signage play an important role in safety perceptions. This group also showed high concern about isolation. This result aligns with a previous study [91,92,93], which highlighted that women feel insecure in isolated areas of public spaces. Women in this cluster mostly have children, so they preferred parks with clear visibility and more access points. This shows the importance of family park designs. Such designs provide safety features that consider the changing social aspects of the park. Previous studies also show the same results as this study [94,95,96]. They emphasized the importance of inclusive designs. Inclusive designs are suitable for various users, especially families with young children.
The third cluster consists of women from various age groups with higher incomes. This group evaluated all factors moderately. This group shows a preference for high-quality parks. This cluster showed less concern about safety features as compared to other clusters. A previous study [97] also revealed similar findings. According to the study, women with higher incomes have more expectations for parks. These women focus more on overall park design than on safety features. A park design with a balanced approach (having both safety and comfort) is the most effective strategy for this group [98].
Cluster four is composed of young women and some with disabilities. This cluster focuses on the importance of accessibility and lighting in safety perception. Studies highlighted that women with disabilities experience more problems due to poor accessibility in public spaces [99,100,101]. This also aligns with findings in [102]. The authors suggested that the unique needs of individuals with disabilities necessitate inclusive design in public spaces.
Cluster five comprises young, low-income, and single women. This cluster exhibits concern for lighting and accessibility. These women focus on accessibility. This accessibility concern was also seen in previous studies [103,104]. This group shows less concern for visibility. Previous studies identified that women with lower-income backgrounds have limited access to high-quality public spaces. This may be due to a lack of resources. According to their preferences, it is necessary to improve the accessibility of parks through public transportation. This would reduce their concerns about safety.
The cluster analysis in this study supports the idea that complex interactions of environmental factors and individual demographic characteristics affect safety perceptions in neighborhood parks. The findings of this study also align with global trends and those observed in past studies [105]. Recent research related to this issue identified that signage and visibility are important in improving safety perceptions. These global trends highlight the importance of clear signage and visibility for improving safety perception in public spaces.

4.3. Summary

This research provides quantitative data that address the safety concerns of women in parks. It shows that safety perception in women can be enhanced by incorporating proper lighting, visibility, clear signage, and accessible infrastructure. Authorities should invest in high-quality lighting systems to ensure that parks remain well lit throughout the night, with solar-powered lighting offering a sustainable and energy-efficient solution.
In the future, park planning should prioritize open layouts that have fewer hidden corners. Visibility can be improved by regular vegetation trimming and the proper placement of park features. Overall safety can be improved by proper lighting, visibility, and accessibility. Public spaces should feature clear and multilingual signs. Government agencies should enforce accessibility standards; this will ensure that parks are inclusive for all individuals. Regular maintenance of pathways and parking areas should be prioritized. Jordanian urban planners can create safer and more public spaces for women by implementing these recommendations. Social participation and community well-being can be improved by ensuring that neighborhood parks cater to diverse safety needs.
Enhancing safety perceptions in parks is linked to environmental sustainability as it promotes increased park use, which fosters a sense of community and encourages the preservation of public green spaces. Using these spaces can lead to increased community advocacy for maintaining and enhancing them; this will support the long-term sustainability of these spaces. This process contributes to sustainable urban development by ensuring that parks are valued, maintained, and incorporated into urban planning strategies.

5. Conclusions

The current research aims to examine the relationship between physical environmental factors and women’s safety perceptions in neighborhood parks. Individual factors that influence perceptions of safety in parks and the physical attributes of parks that contribute to women’s safety were examined. This was achieved through factor and cluster analysis. The results obtained from data analysis and the correlation relationships between study variables revealed that environmental factors such as lighting and visibility play an important role in shaping safety perception in women. The availability of proper lighting, clear signage, and accessibility had the highest positive correlation with perceived safety. Conversely, poor lighting and isolated areas were associated with a lack of safety.
These findings have significant implications for sustainable development. This research is expected to contribute to urban planning discussions on designing safer and more inclusive neighborhood parks for women, informing urban planners and policymakers working toward SDG 11, which aims to make cities inclusive, safe, and sustainable by addressing how safety perceptions influence park use. The research highlights the importance of creating safe spaces to enhance population well-being, which aligns with global efforts to improve urban environmental quality and support the sustainability of cities.
This research faced some limitations: The study involved 380 women from Jordan, which may limit the generalizability of the findings to women in other countries or cultures with different perceptions of safety. While this study included several physical environment factors, it may not have accounted for other potential influences on safety perceptions. Based on the results and methodology of this study, several recommendations for future research are made:
  • Comparative analysis of safety perceptions among women should be conducted in different geographic and cultural contexts to identify region-specific concerns;
  • The role of community engagement and urban design in developing safer public spaces for women should be investigated;
  • The psychological impact of a fear of crime and its implications for urban planning should be studied;
  • It is necessary to develop policy guidelines and urban planning strategies that incorporate gender-based approaches to improve park safety;
  • The impact of park design elements, such as designated female-friendly zones, on increasing women’s participation in parks should be examined.

Author Contributions

Conceptualization, H.A.; methodology, H.A.; software, A.A.; formal analysis, H.A. and A.A.; project administration: L.W.; investigation, H.A. and L.A.; writing—original draft preparation, H.A.; writing—review and editing, H.A., Y.C. and L.A.; visualization, H.A. and A.A.; supervision, L.W. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the National Key Research and Development Program of China, grant number 2023YFC3807404-3.

Institutional Review Board Statement

According to Article 32 of the “Measures for Ethical Review of Life Science and Medical Research Involving Human” issued by the Ministry of Science and Technology of China (https://www.gov.cn/zhengce/zhengceku/2023-02/28/content_5743658.htm, accessed on 4 February 2025), ethical review and approval were waived for this study.

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

The data presented in this study are available in the article itself.

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

The following abbreviations are used in this manuscript:
CFAConfirmatory Factor Analysis
SDGsSustainable Development Goals
JODJordanian Dinar

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Figure 1. Model of the confirmatory factor analysis.
Figure 1. Model of the confirmatory factor analysis.
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Figure 2. Elbow method plot.
Figure 2. Elbow method plot.
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Figure 3. Cluster analysis: (a): cluster dendrogram; (b): scatter plot of clustering.
Figure 3. Cluster analysis: (a): cluster dendrogram; (b): scatter plot of clustering.
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Figure 4. Factor analysis results: dark green—strong contributions to the latent factor; light green—weak contributions to the latent factor.
Figure 4. Factor analysis results: dark green—strong contributions to the latent factor; light green—weak contributions to the latent factor.
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Figure 5. Factor ratings among clusters.
Figure 5. Factor ratings among clusters.
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Table 1. Factors indicated in the questionnaire.
Table 1. Factors indicated in the questionnaire.
Group FactorSub-IndicatorsSymbol
LightingGood lightingL1
Seeing someone from a distance during the nightL2
Seeing the walking paths clearlyL3
All the lights are working in the parkL4
Existence of lighting signage systemL5
Signage systemExistence of enough signs identifying the parkS1
The ease of finding the signs and mapsS2
The ease of understanding the signs and mapsS3
VisibilitySeeing everything clearly (in front of/surrounded by me)V1
Sharp edges and blind spots that block my viewV2
Walls or fences that block my viewV3
Trees and bushes that block my viewV4
Vehicles that block my viewV5
IsolationFeeling isolated in the parkI1
Existence of people during the dayI2
Existence of people during the nightI3
Being able to hear me if I’m screamingI4
AccessibilityThe park is close to the main roadA1
The park is in residential or commercial areasA2
Having more than one entrance to the parkA3
Ease of movement in the park if I use a wheelchair or strollerA4
Having parking spaces for people with disabilitiesA5
Easy access to emergency exitsA6
Sound crossing deviceA7
Tactile pavement paths (for visually impaired women)A8
MaintenanceHave a lot of trash and litterM1
Have a lot of vandalism or graffitiM2
Signs indicating who to contact for maintenanceM3
Having enough green spaces in the parkM4
Table 2. Sample characteristics (n = 380).
Table 2. Sample characteristics (n = 380).
CategorySubcategoryFrequencyPercentage (%)
Age GroupUnder 1210.26
12–1741.05
18–248121.32
25–3415741.32
35–445815.26
45–546015.79
55–64164.21
65 or older30.79
Marital StatusSingle18247.89
Married with children14738.68
Married without children348.95
Divorced82.11
Widowed92.37
Education LevelNo degree10.26
Primary school20.53
High school246.32
Bachelor’s degree25466.84
Master’s degree7419.47
Doctorate degree256.58
OccupationOut of work4612.11
Student7620
Employees20854.74
Retired215.53
Homemakers4411.58
Unable to work10.26
Income Level (JOD)Less than 2506617.37
250–40011831.05
400–6007118.68
600–8006316.58
More than 8006116.05
DisabilityNo disability37498.42
Physical disability30.79
Vision impairment20.53
Stuttering10.26
Table 3. Fit model data.
Table 3. Fit model data.
ModelNormed x2Comparative Fit Index (CFI)Tucker–Lewis Index (TLI)Root Mean Square Error of Approximation (RMSEA)
1. 905.8 0.90.90.078
Table 4. Composite reliability of the five factors.
Table 4. Composite reliability of the five factors.
FactorLightingVisibilityIsolationSignageAccessibility
alpha0.70.820.730.90.88
Table 5. The five clusters based on demographic data.
Table 5. The five clusters based on demographic data.
CategoryCluster 1Cluster 2Cluster 3Cluster 4Cluster 5
Most Frequent Age group25–34 (64%)45–54 (34%),
25–34 (28%)		25–34 (40%), 35–44 (20%)25–34 (46%), 18–24 (21%)18–24 (69%), 25–34 (25%)
Marital StatusSingle (52%), Married with children (36%)Married with children (65%)Single (52%), Married with children (43%)Single (56%), Married with children (33%)Single (98%)
EducationBachelor’s (57%), Master’s (34.9%)Bachelor’s (80%)Bachelor’s (53%)Bachelor’s (67%)Bachelor’s (85%)
Most Frequent Income Level250–400 (37%), 450–600 (26%)250–400 (31%), 450–600 (26%)More than 800 (34%), 650–800 (26%)250–400 (27%), More than 800 (21%)250–400 (49%), Less than 250 (44%)
OccupationEmployed (67%)Employed (50%), Housewives (31%), Retired (13%)Employed (62%), Students (24%)Employed (44%), Students (25%)Students (47%), Employed (41%)
Other Notes---Includes women with disabilities-
Table 6. Clusters and cluster scores (mean and standard deviation of factors).
Table 6. Clusters and cluster scores (mean and standard deviation of factors).
VariableCluster 1Cluster 2Cluster 3Cluster 4Cluster 5
Lighting4.18 (0.302)
High (Low Variability)		3.98 (0.360)
High (Low Variability)		3.32 (0.567)
Moderate (Moderate Variability)		4.00 (0.403)
High (Low Variability)		3.68 (0.304)
High (Low Variability)
Isolation3.94 (0.390)
High (Low Variability)		3.36 (0.552)
Moderate (Moderate Variability)		3.32 (0.635)
Moderate (Moderate Variability)		4.11 (0.659)
High (Moderate Variability)		3.44 (0.481)
Moderate (Moderate Variability)
Signage4.80 (0.377)
High (Low Variability)		4.43 (0.592)
High (Moderate Variability)		3.35 (0.847)
Moderate (High Variability)		4.54 (0.572)
High (Moderate Variability)		4.31 (0.557)
High (Moderate Variability)
Accessibility4.70 (0.372)
High (Low Variability)		4.19 (0.503)
High (Moderate Variability)		3.63 (0.692)
Moderate (Moderate Variability)		4.35 (0.607)
High (Moderate Variability)		High 4.17 (0.557)
(Moderate Variability)
Visibility2.13 (0.443)
Low (Moderate Variability)		2.51 (0.708)
Moderate (Moderate Variability)		2.56 (0.680)
Moderate (Moderate Variability)		3.56 (0.904)
High (High Variability)		2.43 (0.537)
Moderate (Moderate Variability)
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MDPI and ACS Style

Ahmad, H.; Cao, Y.; Almomani, A.; Akmeel, L.; Wang, L. Exploring Safety Perceptions Among Women Using Factor and Cluster Analysis: A Case Study of Neighborhood Parks in Jordan. Land 2025, 14, 725. https://doi.org/10.3390/land14040725

AMA Style

Ahmad H, Cao Y, Almomani A, Akmeel L, Wang L. Exploring Safety Perceptions Among Women Using Factor and Cluster Analysis: A Case Study of Neighborhood Parks in Jordan. Land. 2025; 14(4):725. https://doi.org/10.3390/land14040725

Chicago/Turabian Style

Ahmad, Haneen, Yuxin Cao, Ayat Almomani, Lama Akmeel, and Lijun Wang. 2025. "Exploring Safety Perceptions Among Women Using Factor and Cluster Analysis: A Case Study of Neighborhood Parks in Jordan" Land 14, no. 4: 725. https://doi.org/10.3390/land14040725

APA Style

Ahmad, H., Cao, Y., Almomani, A., Akmeel, L., & Wang, L. (2025). Exploring Safety Perceptions Among Women Using Factor and Cluster Analysis: A Case Study of Neighborhood Parks in Jordan. Land, 14(4), 725. https://doi.org/10.3390/land14040725

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