Search Results (1,290)

Background: Concerns over women’s mental health have intensified globally, especially among mothers managing dual careers and family responsibilities. Positive Psychology Interventions (PPIs), such as gratitude journaling and well-being workshops, have demonstrated promise in enhancing mental health; however, their applicability in Arab contexts remains underexplored. This study aims to investigate the effectiveness of PPIs on mothers’ well-being, gratitude, depression, anxiety, and stress in Saudi Arabia. Methods: This quasi-experimental, one-group pretest–posttest study assessed the effects of a four-week PPI on 37 Saudi working mothers (aged 21–50 years) employed at a private school in Riyadh. The intervention included guided gratitude journaling thrice weekly and two workshops on positive psychology and gratitude. Pre- and post-intervention assessments used validated Arabic versions of the Depression Anxiety Stress Scale (DASS-21), WHO-5 Well-being Index, and Gratitude Questionnaire (GQ-6). Results: Significant improvements were found post-intervention: depression, anxiety, and stress scores decreased (p < 0.001), while well-being and gratitude increased (p = 0.001). However, participants with lower household income (<50,000 SAR) showed less improvement, indicating a potential moderating effect of socioeconomic status. Conclusions: The intervention demonstrated promising short-term improvements in mental health and well-being among Saudi mothers. The findings underscore the importance of culturally appropriate PPIs and highlight the need for further research using controlled, long-term designs. Limitations include the small, non-random sample, absence of a control group, and restriction to a single geographic region. Full article

Background: Health equity can only be achieved when every individual has access to quality healthcare without fear of being discriminated against. This study analyzed the sociodemographic characteristics associated with self-reported racial discrimination when receiving medical care in the United States. Methods: This quantitative cross-sectional study utilized the 2022 National Trends Survey 6. We performed a logistic regression analysis using 6102 survey responses from study participants who answered the question about perceived discrimination. Results: Older adults aged 75 years and above had significantly lower odds of reporting perceived discrimination when receiving medical care compared to those aged 18–34 years (AOR = 0.24; 95% CI: 0.10–0.58). The odds of reporting perceived discrimination were significantly higher among non-Hispanic Blacks (AOR = 7.30; 95% CI: 4.48–11.88), Hispanics (AOR = 3.56; 95% CI: 2.45–5.17), non-Hispanic Asians (AOR = 5.95; 95% CI: 2.25–15.73), and individuals identifying as non-Hispanic Other (AOR = 10.91; 95% CI: 5.42–21.98), compared to non-Hispanic Whites. Compared to individuals from households earning less than USD 20,000, the odds of reporting perceived discrimination when receiving medical care were significantly lower among individuals from households earning between USD 50,000 and <USD 75,000 (AOR = 0.42; 95% CI: 0.23–0.78) and those earning USD 75,000 or more (AOR = 0.43; 95% CI: 0.22–0.83). Conclusions: Despite having a multicultural and ethnically diverse population, racial discrimination persists in the United States and has become a barrier to achieving health equity. Health organizations should implement policies that ensure health workers attend mandatory anti-racism training. Full article

Urban flooding has significantly impacted the livelihoods of households and communities worldwide. It highlights the urgency of focusing on both flood preparedness and adaptation strategies to understand the community’s perception and adaptive capacity. This study investigates the levels of risk perception, flood preparedness, and adaptive capacity, while also exploring the inter-relationships among these factors within the context of urban flooding in Malaysia. A quantitative approach was employed, involving a structured questionnaire administered to residents in flood-prone urban areas across Greater Kuala Lumpur, Malaysia. A total of 212 responses were analysed using descriptive statistics, categorical index classification, and Spearman correlation analysis. The findings indicate that residents generally reported high levels of risk perception and preparedness, although adaptive capacity exhibited greater variability, with a mean score of 3.97 (SD = 0.64). Positive associations were found among risk perception, flood preparedness, and adaptive capacity. This study contributes to the existing knowledge by providing evidence on community resilience and highlighting key factors that can guide flood management policies and encourage adaptive planning at the community level. Full article

Dams play a vital role in securing water and electricity supplies for households and industry, and they contribute significantly to flood protection. Regular monitoring of dam deformations holds fundamental socio-economic and ecological importance. Traditionally, this has relied on time-consuming in situ techniques that offer either high spatial or temporal resolution. Persistent Scatterer Interferometry (PSI) addresses these limitations, enabling high-resolution monitoring in both domains. Sensors such as TerraSAR-X (TSX) and Sentinel-1 (S-1) have proven effective for deformation analysis with millimeter accuracy. Combining TSX and S-1 datasets enhances monitoring capabilities by leveraging the high spatial resolution of TSX with the broad coverage of S-1. This improves monitoring by increasing PS point density, reducing revisit intervals, and facilitating the detection of environmental deformation drivers. This study aims to investigate two objectives: first, we evaluate the benefits of a spatially and temporally densified PS time series derived from TSX and S-1 data for detecting radial deformations in individual dam segments. To support this, we developed the TSX2StaMPS toolbox, integrated into the updated snap2stamps workflow for generating single-master interferogram stacks using TSX data. Second, we identify deformation drivers using water level and temperature as exogenous variables. The five-year study period (2017–2022) was conducted on a gravity dam in North Rhine-Westphalia, Germany, which was divided into logically connected segments. The results were compared to in situ data obtained from pendulum measurements. Linear models demonstrated a fair agreement between the combined time series and the pendulum data ($R^2$ = 0.5; MAE = 2.3 mm). Temperature was identified as the primary long-term driver of periodic deformations of the gravity dam. Following the filling of the reservoir, the variance in the PS data increased from 0.9 mm to 3.9 mm in RMSE, suggesting that water level changes are more responsible for short-term variations in the SAR signal. Upon full impoundment, the mean deformation amplitude decreased by approximately 1.7 mm toward the downstream side of the dam, which was attributed to the higher water pressure. The last five meters of water level rise resulted in higher feature importance due to interaction effects with temperature. The study concludes that integrating multiple PS datasets for dam monitoring is beneficial particularly for dams where few PS points can be identified using one sensor or where pendulum systems are not installed. Identifying the drivers of deformation is feasible and can be incorporated into existing monitoring frameworks. Full article

As part of the post-conflict reconstruction and recovery, the development of Kabul New City aims to bring relief to the existing capital city, Kabul, which has experienced exponential population growth, putting heavy pressure on its existing resources. Kabul New City is divided into four subsectors, and each of them is being developed and is expected to reach a target population by 2025, as defined by the master plan. The study’s objective is to determine which of the four zones are in demand and need to be prioritized for development, as per the model results. The data collection involves an online questionnaire, and the responses are collected from residents of Kabul and Herat. Agent-based modeling (ABM) is an emerging method of simulating urban dynamics. Cities are evolving continuously and are forming unique spatial patterns that result from the movement of residents in search of new locations that accommodate their needs and preferences. An agent-based model is developed using the weighted random selection process based on household size and income levels. The agents are the residents of Kabul and Herat, and the environment is the land use classification image using the Sentinel 2 image of Kabul New City. The barren class is treated as the developable area and is divided into four sub-sectors. The model simulates three alternative growth rate scenarios, i.e., ambitious, moderate, and steady. The results of the simulation reveal that the sub-sector Dehsabz South, being closer to Kabul city, is in higher demand. Barikab is another sub-sector high in demand, which has connectivity through the highway and is an upcoming industrial hub. Full article

As shared micromobility grows quickly in metropolitan settings, e-scooter safety issues have become more urgent. This paper uses a Bayesian hierarchical model applied to census block groups in several Texas metropolitan areas to construct a spatial risk assessment methodology for e-scooter crashes. Based on crash statistics from 2018 to 2024, we develop a severity-weighted crash risk index and combine it with variables related to land use, transportation, demographics, economics, and other factors. The model comprises a geographically structured random effect based on a Conditional Autoregressive (CAR) model, which accounts for residual spatial clustering after capture. It also includes fixed effects for covariates such as car ownership and nightlife density, as well as regional random intercepts to account for city-level heterogeneity. Markov Chain Monte Carlo is used for model fitting; evaluation reveals robust spatial calibration and predictive ability. The following key predictors are statistically significant: a higher share of working-age residents shows a positive association with crash frequency (incidence rate ratio (IRR): ≈1.55 per +10% population aged 18–64), as does a greater proportion of car-free households (IRR ≈ 1.20). In the built environment, entertainment-related employment density is strongly linked to elevated risk (IRR ≈ 1.37), and high intersection density similarly increases crash risk (IRR ≈ 1.32). In contrast, higher residential housing density has a protective effect (IRR ≈ 0.78), correlating with fewer crashes. Additionally, a sensitivity study reveals that the risk index is responsive to policy scenarios, including reducing car ownership or increasing employment density, and is sensitive to varying crash intensity weights. Results show notable collision hotspots near entertainment venues and central areas, as well as increased baseline risk in car-oriented urban environments. The results provide practical information for targeted initiatives to lower e-scooter collision risk and safety planning. Full article

Numerous rural residential buildings exhibit inadequate seismic performance when subjected to blast-induced vibrations, which poses potential threats to their overall stability and structural integrity when in proximity to blasting project sites. The investigation conducted in conjunction with the Qianshi Mountain blasting operations along the Wenzhou segment of the Hangzhou–Wenzhou High-Speed Railway integrates household field surveys and empirical measurements to perform modal analysis of rural residential buildings through finite element simulation. Adhering to the principle of stratified arrangement and composite measurement point configuration, an effective and reasonable experimental observation framework was established. In this investigation, the seven-story rural residential building in adjacent villages was selected as the research object. Strong-motion seismographs were strategically positioned adjacent to frame columns on critical stories (ground, fourth, seventh, and top floors) within the observational system to acquire test data. Methodical signal processing techniques, including effective signal extraction, baseline correction, and schedule conversion, were employed to derive temporal dynamic characteristics for each story. Combined with the Fourier transform, the frequency–domain distribution patterns of different floors are subsequently obtained. Leveraging the structural dynamic theory, time–domain records were mathematically converted to establish the structure’s maximum response spectra under blast-induced loading conditions. Through the analysis of characteristic curves, including floor acceleration response spectra, dynamic amplification coefficients, and spectral ratios, the dynamic response patterns of rural residential buildings subjected to blast-induced vibrations have been elucidated. Following the normalization of peak acceleration and velocity parameters, the mechanisms underlying differential floor-specific dynamic responses were examined, and the layout principles of measurement points were subsequently formulated and summarized. These findings offer valuable insights for enhancing the seismic resilience and structural safety of rural residential buildings exposed to blast-induced vibrations, with implications for both theoretical advancements and practical engineering applications. Full article

Amid the rapid expansion of the digital economy, online shopping has become increasingly common among rural households in China, yet the social interaction mechanisms driving such behavior remain insufficiently explored. This study examines the impact of peer effects on farmers’ online shopping behavior using data from the China Family Panel Studies (CFPS) covering the years 2014 to 2022. A Logit model is applied to estimate peer influence, and interaction terms are introduced to assess the moderating roles of land assets and social expenditures. The results reveal that peer behavior significantly increases the likelihood of rural households participating in online shopping, with the effect being particularly strong among low-income, less-educated households and those in western regions. Additionally, both land-rich households and those with higher social expenditures demonstrate greater responsiveness to peer influence. These findings highlight the importance of local social interaction in shaping rural online shopping behavior and provide theoretical and practical implications for digital inclusion and rural e-commerce strategies. Full article

This study investigates the impact of remittances on income inequality in Lebanon using annual time-series data for the years 2000–2023. Applying Johansen’s cointegration test, with financial development (FD), GDP, and household consumption expenditure (HCE) as the control variables, the study examines the long-run and short-run relationship between remittances and inequality. The study also considers the moderating impacts of FD and HCE to account for their indirect role in the remittance–inequality relationship. Dynamic relations are also examined by using impulse response functions (IRFs) and Forecast Error Variance Decomposition (FEVD) analyses. The long-run model estimates validate that remittances and income inequality are significantly and negatively related, i.e., increased remittance receipts serve to reduce income inequality in Lebanon. Remittance effects, however, are statistically insignificant in the short run. Interestingly, the results reveal that financial development weakens the remittances’ inequality-reducing effect, dampening their impact. Contrarily, a higher household consumption expenditure slightly strengthens the inequality-reducing effect of remittances. A comparison between the pre- and post-2019 periods reveals that the explanatory strength of remittances weakened during times of economic crisis, since the function of remittances was different during times of economic distress. Based on these findings, this study recommends that Lebanon not only promote financial development but also focus on financial inclusion, improve social safety nets, and provide inclusive economic growth to maximize remittance inflow benefits and efficiently reduce inequality. Full article

This paper examines how demographic characteristics, institutional structures, and livelihood strategies shape household resilience to climate variability and drought in West Pokot County, one of Kenya’s most climate-vulnerable arid and semi-arid lands (ASALs). Using a mixed-methods approach, it combines household survey data with three statistical techniques: Multinomial Logistic Regression (MLR) assesses the influence of gender, age, and education on livestock ownership and livelihood choices; Multiple Correspondence Analysis (MCA) reveals patterns in institutional access and adaptive practices; and Stepwise Linear Regression (SLR) quantifies the relationship between resilience strategies and agricultural productivity. Findings show that demographic factors, particularly gender and education, along with access to veterinary services, drought-tolerant inputs, and community-based organizations, significantly shape resilience. However, trade-offs exist: strategies improving livestock productivity may reduce crop yields due to resource and labor competition. This study recommends targeted interventions, including gender-responsive extension services, integration of indigenous and scientific knowledge, improved infrastructure, and participatory governance. These measures are vital for strengthening resilience not only in West Pokot but also in other drought-prone ASAL regions across sub-Saharan Africa. Full article

Background: While some evidence supports the benefits of food-related tasks, research examining their association with psychosocial health in adolescents remains scarce. The aim of this study was to examine the association between Spanish adolescents’ involvement in food-related household tasks and their psychosocial health. Methods: This cross-sectional study used secondary data from the original Eating Healthy and Daily Life Activities (EHDLA) study. The final sample comprised 273 boys (43.0%) and 361 girls (57.0%). Adolescents self-reported their weekly frequency of involvement in two food-related tasks: meal preparation and grocery shopping, with responses ranging from ‘never’ to ‘seven times’. Psychosocial health was assessed using the 25-item self-report version of the Strengths and Difficulties Questionnaire (SDQ), comprising five subscales: emotional problems, conduct problems, hyperactivity, peer problems, and prosocial behavior. A total difficulties score was calculated by summing the first four subscales. Generalized linear models were used to evaluate associations between the frequency of food task involvement (categorized into five levels) and SDQ outcomes. All models were adjusted for age, sex, socioeconomic status, body mass index, sleep duration, physical activity, sedentary behavior, and energy intake. Results: Concerning to the frequency of helping to prepare food for dinner, an inverse association was observed between food preparation involvement and several psychosocial problems. Adolescents who helped seven times per week reported significantly lower scores in conduct problems (B = −2.00; 95% CI −3.30 to −0.69; p = 0.003), peer problems (B = −2.83; 95% CI −4.29 to −1.38; p < 0.001), internalizing problems (B = −3.90; 95% CI −7.03 to −0.77; p = 0.015), and total psychosocial difficulties (B = −5.74; 95% CI −10.68 to −0.80; p = 0.023), compared to those who never helped. Conversely, those who helped seven times per week had higher prosocial behavior than their counterparts who never helped (B = 1.69; 95% CI: 0.14 to 3.24; p = 0.033). Regarding the frequency of helping to shop for food, similar patterns were found, with lower conduct problems (B = −2.11; 95% CI −3.42 to −0.81; p = 0.002), peer problems (B = −2.88; 95% CI −4.34 to −1.42; p < 0.001), internalizing problems (B = −4.16; 95% CI −7.28 to −1.04; p = 0.009), and total psychosocial difficulties (B = −6.31; 95% CI −11.24 to −1.39; p = 0.012) associated with more frequent involvement, especially among those who helped five or more times per week. Conversely, adolescents who helped seven times per week had higher prosocial behavior than their peers who never helped (B = 1.56; 95% CI: 0.01 to 3.11; p = 0.049). Conclusions: Although adolescent psychosocial health is influenced by multiple factors, our findings suggest that regular involvement in food-related household tasks may serve as a protective factor against conduct problems, peer problems, internalizing problems, and total difficulties, while also enhancing prosocial behavior. However, given the cross-sectional design, conclusions regarding causality should be made cautiously, and further longitudinal research is needed to confirm these associations and assess their long-term impact. These results highlight the relevance of daily structured routines, such as meal preparation and grocery shopping, as potential support for mental well-being during adolescence. Full article

The growing mismanagement of energy resources is a pressing issue that poses significant risks to both individuals and the environment. As energy consumption continues to rise, the ramifications become increasingly severe, necessitating urgent action. In response, the rapid expansion of Internet of Things (IoT) devices offers a promising and innovative solution due to their adaptability, low power consumption, and transformative potential in energy management. This study describes a novel, integrative strategy that integrates IoT and Artificial Neural Networks (ANNs) in a smart monitoring mobile application intended to optimize energy usage and promote sustainability in residential settings. While both IoT and ANN technologies have been investigated separately in previous research, the uniqueness of this work is the actual integration of both technologies into a real-time, user-adaptive framework. The application allows for continuous energy monitoring via modern IoT devices and wireless sensor networks, while ANN-based prediction models evaluate consumption data to dynamically optimize energy use and reduce environmental effect. The system’s key features include simulated consumption scenarios and adaptive user profiles, which account for differences in household behaviors and occupancy patterns, allowing for tailored recommendations and energy control techniques. The architecture allows for remote device control, real-time feedback, and scenario-based simulations, making the system suitable for a wide range of home contexts. The suggested system’s feasibility and effectiveness are proved through detailed simulations, highlighting its potential to increase energy efficiency and encourage sustainable habits. This study contributes to the rapidly evolving field of intelligent energy management by providing a scalable, integrated, and user-centric solution that bridges the gap between theoretical models and actual implementation. Full article

Natural and man-made disasters are occurring more frequently, making household emergency preparedness essential for an effective response. Enrollees of the World Trade Center Health Registry have been found to be less prepared than the US national average despite their prior disaster exposure. The purpose of this study was to evaluate and compare the effectiveness of two interventions—a mailed brochure and a structured phone call—for increasing emergency preparedness knowledge among this population. We conducted a two-arm parallel group trial between February 2019 and August 2020. Participants were Registry enrollees who completed the Wave 4 Registry (2015–2016) survey, whose primary language was English or Spanish, who lived in New York City, and who did not report being a rescue and recovery worker affiliated with FDNY or NYPD. Enrollees were randomized to receive either a brochure by mail summarizing the components of emergency preparedness or a 15 min phone call describing the same. The primary outcome measure was the number of “yes” responses to the ten-item CDC CASPER emergency preparedness questionnaire, measured at baseline and post-intervention. Enrollees were sequentially alternatively assigned to either the brochure or phone call groups. In total, 705 enrollees were assigned to the brochure (n = 353) or phone call (n = 352) groups, and a total of 702 enrollees were analyzed. The Incident Rate Ratio (IRR) for the effect of time was 1.17 (95% CI = (1.14, 1.20)) and for intervention was 1.00 (95% CI = (0.95, 1.05)) Both the brochure and phone call interventions improved knowledge of emergency preparedness from baseline to post-intervention assessment, and to the same extent. Full article

Dengue virus infection (DVI), a mosquito-borne arboviral infection, is prevalent in tropical and subtropical regions, including Bangladesh, where incidence has surged over the past three decades—particularly in urban and peri-urban areas. This study investigates the factors influencing DVI seropositivity among clinically suspected patients admitted to the selected hospitals of Savar, Dhaka, and Chattogram. Data were collected from 850 clinically suspected patients admitted to two hospitals in Savar, Dhaka, and two in Chattogram during 2019. Questionnaire responses and laboratory test results (NS1, IgM, and IgG) were analyzed using descriptive statistics, chi-square tests, and logistic regression. Out of 450 admissions in Savar, 330 tested positive, while Chattogram reported 145 positives from 400 cases. No significant differences were observed between regions in relation to hospital type, season, gender, or household preventive measures. In Savar, DVI status was significantly associated with season, mosquito net use, and patient contact. In Chattogram, household repellent use and patient contact were key factors. Diagnostic tests varied in detection capability. These findings can inform targeted intervention strategies and public health messaging, such as promoting personal protection measures and community awareness campaigns, particularly in high-incidence urban settings. However, further research across diverse geographic and socio-ecological contexts is needed to enhance the generalizability and policy relevance of these results. Full article

Agricultural green production (AGP) is a key strategy for ensuring stable and sustainable grain production in developing countries. However, from the perspective of technology acquisition, research on farmers’ willingness to adopt AGP remains limited. Based on this, a survey was conducted on 862 households in major grain-producing counties in the Huang Huai Hai Plain of China with a reliable and effective response rate of 97.44%. The aim was to employ Probit and mediation models to empirically analyze the direct impacts of green perception benefits and environmental regulation intensity on farmers’ AGP willingness, and further examine the intrinsic mechanisms of technology acquisition. The results demonstrated that both green perception benefits and environmental regulation intensity significantly enhanced farmers’ willingness to engage in AGP, with green perception benefits having a greater influence. Among the two-dimensional variables, economic benefits had a stronger promoting effect than identity benefits, with a difference of 0.044 units, while subjective regulation intensity outperformed objective regulation intensity by 0.173 units. This suggested the need to strengthen the subjective impact of AGP policies in practice. Further analysis revealed that technology acquisition mediated 5.87% of the effect of green perception benefits on farmers’ AGP willingness, with acquisition evaluation having the greatest mediating effect, followed by acquisition quality and acquisition channels. However, although the overall environmental regulation intensity did not significantly impact farmers’ willingness to engage in AGP, its two-dimensional indicators played a mediating role to varying degrees. The findings in this study provide valuable empirical evidence for promoting AGP among grain producers, contributing to grain production security and the sustainable development of developing countries. Thus, implementing environmental regulatory policies tailored to local conditions, enhancing farmers’ economic awareness and sense of responsibility, and expanding farmers’ channels for technology acquisition are reasonable policy choices. Full article