Search Results (28)

Diversion programs are increasingly used as alternatives to criminal penalties for women involved in commercial sex, yet limited research has examined how such programs support behavior change across diverse subgroups, particularly between sex-trafficked and non-trafficked participants. This study evaluates changes in readiness for change among 131 women who participated in a court-ordered diversion program led by survivors of sex trafficking. Participants were classified as sex-trafficked or non-trafficked based on self-reported age of entry and experiences of third-party control. The program offered a range of trauma-informed services aimed at fostering holistic well-being and facilitating a pathway out of sex trafficking and prostitution. Participants engaged in group classes focused on job interview skills, emotion regulation, substance use awareness, and psychoeducation related to trauma. Life skills workshops addressed financial literacy, relationship dynamics, and conflict resolution. In addition, participants received referrals to GED programs, career training, mental health services, and emergency housing as needed. Program duration typically ranged from 12 to 16 weeks, adjusted for individual needs. Results from a repeated-measures Analysis of Variance (ANOVA) revealed a significant increase in readiness for change (p < 0.05) from program entry to completion. However, women with trafficking histories demonstrated smaller gains than their non-trafficked peers, suggesting that trauma-related and systemic barriers may limit the impact of short-term interventions. These findings underscore the importance of tailoring diversion programs to address the complex needs of sex-trafficked individuals and support the development of differentiated trauma-responsive strategies within diversion frameworks. Full article

This study analyzed citizens’ subjective perceptions and attitudes toward housing development in Norwalk, Connecticut, employing structural equation modeling (SEM) and machine learning techniques. A survey of 580 residents was conducted to study the relationship between the willingness to buy or rent from housing projects in Norwalk and perceptions of risks, benefits, and sustainability beliefs. SEM identified latent variables influencing attitudes, including perceived risks (e.g., overcrowding and the loss of historical character), benefits (e.g., enhanced infrastructure, and job creation), and sustainability beliefs. The results revealed that perceived benefits have a stronger positive impact on citizens’ attitudes than risks, mediated by sustainability beliefs in this city. Machine learning via random forest highlighted key predictors of willingness to buy or rent, such as affordability, walkability, and public infrastructure improvements, with affordability being the most influential factor. These findings emphasize the importance of framing housing projects to align with citizens’ priorities, especially through campaigns emphasizing economic and environmental benefits. The integration of SEM and machine learning offers a robust approach to understanding citizen preferences, ensuring greater support and citizens’ acceptance for sustainable housing initiatives. These findings provide actionable insights for urban planners to understand the interrelations between concerns, perceived benefits, and beliefs to foster the social acceptance of sustainable urban policies. Full article

Adolescents today face significant exposure to social inequalities and environmental crises, including the impacts of climate change, such as heatwaves, floods, and droughts. In addition, they encounter various forms of inequality, such as job insecurity, lack of affordable housing, and growing mental health challenges. Future perception is an essential variable in understanding how adolescents address these social and environmental challenges. Thus, this study adapted the Future Time Orientation Scale (FTOS) to the Italian context, assessing its validity and reliability for measuring psychological future orientation among Italian-speaking adolescents. Two studies were conducted: the first validated the FTOS through exploratory and confirmatory factor analyses, revealing two factors, “Impact” and “Distance”. The second study examined the relationship between future time orientation, future orientation in the professional field, and adolescents’ propensity to consider global challenges related to sustainable development. The results indicated that future orientation fully mediates the relationship between future time orientation and the tendency to consider global challenges in career decision-making. These findings underscore the importance of future orientation in shaping adolescents’ sustainable career choices and suggest that career interventions promoting future time orientation may enhance their engagement with global challenges. Full article

Long commuting distances pose a significant challenge for many large cities, undermining the principles of sustainable urban development. The factors influencing urban commuting distances among residents are complex and necessitate hierarchical analysis. This study uses Tianjin, one of China’s four municipalities, as a case study, employing transportation analysis zones (TAZ) as research units. We classify these units based on resident and working populations, extracting multiple built environment and personal attribute factors to establish a model that examines the influence of the job–housing balance. The analysis identifies 12 sub-items across two categories of influencing factors, with correlations tested through spatial analysis and linear regression. We found 28 positive associations and 35 negative associations. Notably, the job–housing relationship for the working population was generally more sensitive to changes than that of the resident population. At the TAZ level, personal attributes exerted a more significant influence on the job–housing balance than built environment factors, with commuting mode, life stage, age, and income level notably affecting commuting distances. Full article

A large number of studies have provided evidence regarding the factors that influence commuting time. However, few studies have explored such effects in the context of considering spatial heterogeneity across cities, which limits the generalizability of the findings. This study addresses this gap by utilizing a dataset of 113 cities in China across the years 2014, 2016, 2018, and 2020. A two-level hierarchical linear model (HLM) was developed to explore the combined effects of city-level and individual-level factors on commuting time by constructing a nested “city-individual” relationship. The results show that (1) built environments at the city level significantly impact commuting time; (2) a non-linear association between population density and commuting time (U-shaped relationship) was identified, as well as between the number of buses and commuting time (inverted U-shaped relationship); (3) the urban construction land area and road area per capita exert negative effects on commuting time; (4) the impacts of individuals’ jobs–housing balance, travel allowances, and education on commuting time vary across cities. These findings might contribute to optimizing the design of a built environment, addressing the challenge posed by longer commuting times, and providing a better understanding of the effects of individuals’ characteristics on commuting time while considering the inherent differences across cities. Full article

This research investigates the views of the resettled people regarding the practice of resettlement and compensation (RCP) to assess the developmental progress of the Tha Htay hydropower (THH) project and establish a resettlement relationship from various perspectives. In this paper, a convergent mixed research method was used for interpretations and analyses of the whole resettlement and compensation practice. Descriptive statistics were utilized to analyze the collected data on the resettlement practices of those participants who presented it by frequency and percentage of quantitative findings. The study revealed that educational facilities and development received the highest average rating from the participants, indicating a higher level of satisfaction. On the other hand, the current living situation and job opportunities received the lowest rating, indicating lower satisfaction in this aspect. Overall, the respondents expressed satisfaction with other indicators of the resettlement process, such as site selection, housing, compensation, and fundamental infrastructure services. Despite receiving foreign technical advisory assistance for resettlement and sustainable livelihoods for the resettled communities, the project fell short in providing agricultural or cultivation land as a replacement for those who relied on land-based livelihoods. It was verified that most of the resettled people seemed poorer than in the previous condition, and they were facing higher living standards without adequate income. It is therefore crucial for the project proponent to take active measures in supporting the three resettled Villages by providing agricultural land and assisting them in their livelihoods and overall living conditions, so as to ensure that the resettled households do not face long-term challenges in sustaining their livelihoods after the resettlement project. Full article

The implementation of lean manufacturing to increase productivity often neglects the impact on the environment and the well-being of employees. This can result in negative consequences such as environmental harm and poor employee satisfaction. To address this issue, an integrated ergo-green-lean conceptual model was developed in the literature. However, no case study has been conducted to support this model. Therefore, this research aims to investigate the practical outcomes of implementing the integrated framework in an automobile parts industry. Key performance indicators (KPIs) were identified, including ergonomic risk score, job satisfaction, carbon footprint emission both from direct energy consumption and material wastage, cycle time, lead time, die setup time, and rejection rate. Various assessment techniques were employed, such as the rapid entire body assessment (REBA) with the Standard Nordic Questionnaire (SNQ), job stress survey, carbon footprint analysis (CFA), and value stream mapping (VSM) to evaluate the KPIs at the pre- and post-intervention phases. The results demonstrate significant improvements in job satisfaction (49%), improved REBA score of 10 postures with very high risk numbers by 100%, a 30.3% and 19.2% decrease in carbon emissions from energy consumption and material wastage, respectively, a 45% decrease in rejection rate at the customer end, a 32.5% decrease in in-house rejection rate, a 15.5% decrease in cycle time, a 34.9% decrease in lead time, and a 21% decrease in die setup time. A Python regression model utilizing sklearn, pandas, and numpy was created to assess the relationship between process improvement and the chosen KPIs. Full article

The serious mismatch between industrialization and urbanization has led to the emergence of ghost cities. Industry-and-city integration aims to agglomerate industries and the population simultaneously by coordinating the planning and construction, and by mixing different functional areas including industry, office, living, and commercial functions. Based on the population spatial vector database of Jimei District in Xiamen in 2020, this paper empirically analyzes the effects of spatial patterns between industry and city, in terms of residential location and job accessibility, on the housing occupancy rate in new towns and cities. The findings demonstrate that: (1) The attraction of residential location to population varies among three different urban expansion models. The housing occupancy rate of residential areas that meet the concentric circle model is the highest, followed by the sector model, and the multiple nuclei model is the lowest; (2) The jobs–housing relationship has a stable and positive impact on the occupancy rate of commercial housing in the new town, which verifies that job accessibility is the basic demand for families’ residential location choice; (3) There is a significant pattern difference in the influence of job accessibility on the occupancy rate. The occupancy rate of the sector model residential area is highly dependent on job accessibility: the higher the job accessibility, the lower the occupancy rate of the concentric residential area, while job accessibility has a weak impact on the occupancy rate of the multiple nuclei residential area. The conclusions suggest that the spatial planning of new towns should include a clear population absorbing strategy, and the residential location should follow the expansion law of the urban residential functional area, balance the relationship between industrial agglomeration and the job–housing relationship, and allocate life factors in a targeted manner according to the actual impact of job accessibility. Full article

The jobs-housing imbalance and long commuting distances for residents in many megacities in China are promoting the increase in mode share with rail transit. The emergence of free-floating bike sharing (FFBS) provides an attractive and cost-effective multi-modal solution to the first/last mile problem. This study identifies the mobility patterns of free-floating bikes as a feeder mode to 277 rail transit stations in Beijing using detailed GPS data, and the relationships between these patterns, culture and spatial layout of the city are examined. The results show that the distribution of free-floating bikes, as a feeder mode to rail transit, exhibits an aggregating feature in the spatial-temporal pattern on weekdays. According to the results of the Clusters method and ANOVA analysis, the operation characteristics of free-floating bikes are related to the location of the transit station and the job-to-housing ratio around that area, and imbalanced usage of shared bikes across the city may result from the extreme values of job-to-housing ratios. Based on the fitted distance decay curve, accessing distance is greatly influenced by urban morphology and location. Based on these findings, recommendations for planning, management, and rebalancing of the FFBS system as a feeder mode to rail transit are proposed to promote the integration of FFBS and the rail transit system. Full article

Analyzing commuting-time satisfaction could help to improve the subjective well-being of society. This study aimed to explore the nonlinear relationship between commuting satisfaction and commuting times in different groups and its influencing factors. An empirical study was conducted in Kunming, China. Firstly, applying a random forest algorithm revealed that there was a nonlinear relationship between commuting satisfaction and commuting time. Secondly, the k-means clustering algorithm was used to divide the respondents into three types of commuter: short-duration-tolerant (group 1), medium-duration-tolerant (group 2), and long-duration-tolerant (group 3). It was found that the commuting-time satisfaction of these three clustered groups had different threshold effects. Specifically, the commuting satisfaction of group 1 showed a nonlinear downward trend, which decreased significantly at 12 and 28 min, respectively; the commuting satisfaction of group 2 rapidly decreased at 35 min; the commuting satisfaction of group 3 first increased in the range of 20–30 min, decreased significantly after 45 min, and decreased sharply above 70 min. These time thresholds were consistent with the ideal commuting times (ICTs) and tolerance thresholds of the commuting times (TTCTs) of the three clustered groups, which indicates that the ICT and TTCT had significant effects on commuting satisfaction. Lastly, the results of the multinominal logistic model showed that variables such as the commuting mode, job–housing distance, income, and educational background had significant effects on the three clustered groups. The policy implications of the study are that commuting circles should be planned with the TTCT as a constraint boundary and ICT as the optimal goal; in addition, different strategies should be adopted for different commuting groups to improve commuting satisfaction. Full article

Dwelling and working are two of the most fundamental urban functions. The jobs–housing relationship is pertinent to a city’s spatial and social structure. By using macro-level statistical data and micro-level mobile phone data, this paper innovatively adapts a way to explore the jobs–housing characteristics of public housing tenants in Chongqing, China. It finds that both external and internal factors matter. This study might provide some useful implications for further policy-making on public housing planning, and the research method could be used to examine urban spatial relationships further. Full article

Shale energy development activity may benefit some aspects of a regional economy (such as increased jobs or tax revenue); however, there may also be negative impacts to the local environment, such as noise and underground water contamination. We study the impact of unconventional drilling activity on housing price in an area of the country with a long history of crude oil production. A prospective home buyer may want to avoid a place near sites that have been drilled using unconventional drill technologies such as horizontal fracturing. Adopting a hedonic price model, we estimate the impact of distance to and density of unconventional drilling on housing prices in two central counties in Oklahoma during the period 2001–2016. We also apply a semiparametric approach to deal with the possibility that the relationship between an environmental pollutant source and housing price is nonlinear. The empirical results are consistent in terms of physical housing characteristics and locational aspects in all cases, with drilling activity having only a minimal effect in benchmark models. Further, the semiparametric estimation results support the findings that drilling activity has only limited impacts on local housing prices. Full article

The object of this research was to determine the subjective recognized social threats in the context of contemporary society. Given the growing number of people who feel threatened by certain social threats, there is a presumption that the risk is real, and the identified groups are affected by social risks. The recognition of social threats in the population has a broader social context, and may be influenced by key socio-demographic factors. This influence is significant for many risks, and helps to better understand the nature of the specific groups at risk. It also allows us to recognize that the socio-demographic and family context creates specific conditions for the occurrence of social threats. The aim of the paper is to find the relationships between different types of social threats and gender, age groups, personal situation (occupation), educational attainment, and family situation. A similar study was carried out by the OECD in 2018 (the Czech Republic was not included). The research was designed as cross-sectional ex-post-facto, and the statistical significance was determined using χ2 test of independence. The survey was carried out in 2018–2019 nationwide across the Czech Republic. The processed data of 5425 respondents has shown that, in the Czech Republic, the subjectively perceived significant threats seem to be the loss of job and unemployment, insufficient skills, and an unwillingness to educate oneself or to be trained, social pressure, and unsatisfactory housing conditions. The research reveals that the recognition of social threats depends on social and family conditions, and there exist specific groups feeling threats more intensively than exist in others. The groups that are at the most risk are individuals with primary education and an apprenticeship. In the population, women are more at risk, as well as the 25–34 and 45+ age groups. Full article

Background: Emerging research suggests that the novel coronavirus disease (COVID-19) pandemic and associated public health restrictions have caused psychological distress in many contexts. In order for public health authorities and policy makers to effectively address the psychological distress associated with the pandemic, it is important to determine the prevalence and correlates of mental disorders, including depression. Objectives: We aimed to determine the prevalence, and demographic, social, clinical and other COVID-19 related correlates of major depressive disorder symptoms among the general population in Ghana during the COVID-19 pandemic. Method: The study was a cross-sectional survey using online data collection methods. The survey assessed demographic, social and clinical variables as well as COVID-19 related variables. Major depressive disorder symptoms were assessed using the Patient Health Questionnaire-9. The survey link was distributed primarily through WhatsApp-based platforms. Data were analyzed using descriptive and inferential statistics. Results: The overall prevalence of likely MDD symptoms among the sample population was 12.3%. Variables such as employment, loss of jobs during the pandemic and rate of exposure to COVID-related news were independently and significantly associated with the likelihood that respondents had likely MDD. Variables such as gender, relationship, housing status and having a family member or friend who was sick from COVID-19 were not independently significantly associated with the likelihood that respondents had likely MDD, when all other factors in the model were controlled. Conclusion: This study has identified the prevalence and correlates of depression symptoms in Ghana during the COVID-19 pandemic. There is the urgent need for mental health policy makers and the government of Ghana to have policies in place to alleviate the potential threat to the mental health of the population. Full article

Within the existing relationship among urban environment, health, and poverty, it is necessary to clarify and characterize the influence that the physical environment has on community socioeconomic outcomes. Given that Detroit has one of the highest poverty rates among large metropolitan areas in the United States, this study aims to identify environmental and urban features that have influenced poverty in this city by assessing whether changes in household income are associated with characteristics of the built environment. The difference of median household income (DMHI) between 2017 and 2013 and 27 environmental and urban variables were investigated using both geographic distribution mapping and statistical correlation analysis. Results suggest that proximity of housing to job opportunity areas, as well as to certain educational and health-related facilities, were positively related to increasing household incomes. These findings outline a healthy urban design that may benefit community socioeconomic outcomes—specifically a design with dense and mixed-use areas, good accessibility, high presence of urban facilities, and features that promote a healthy lifestyle (involving physical activity and a healthy diet). In this sense, urban planning and public health may be important allies for poverty resilience. Full article