Search Results (270)

Background: Access to safe and reliable water and sanitation remains a critical public health and development challenge, with rural and low-income communities being disproportionately affected by inadequate services and heightened exposure to waterborne diseases. Despite global efforts and infrastructure-based progress indicators, significant disparities persist, and these often overlook users’ perceptions of water quality, reliability, and safety. This study explores the determinants of household satisfaction with drinking water in rural areas, comparing subjective user feedback with official access data to reveal gaps in current monitoring approaches and support more equitable, user-centered water governance. Methods: This study was conducted in Kazakhstan’s Atyrau Region, where 1361 residents from 86 rural villages participated in a structured survey assessing household access to drinking water and perceptions of its quality. Data were analyzed using descriptive statistics and multinomial logistic regression to identify key predictors of user satisfaction, with results compared against official records to evaluate discrepancies between reported experiences and administrative data. Results: The field survey results revealed substantial discrepancies between official statistics and residents’ reports, with only 58.1% of respondents having in-house tap water access despite claims of universal coverage. Multinomial logistic regression analysis identified key predictors of user satisfaction, showing that uninterrupted supply and the absence of complaints about turbidity, odor, or taste significantly increased the likelihood of higher satisfaction levels with drinking water quality. Conclusions: This study underscores the critical need to align official water access statistics with household-level experiences, revealing that user satisfaction—strongly influenced by supply reliability and sensory water quality—is essential for achieving equitable and effective rural water governance. Full article

This study defines evidence-based minimum internal floor areas required to support long-term residential use across different household types. It addresses the following question: what is the smallest viable floor area that supports sustained occupancy without persistent stress, conflict, or turnover? An integrative review method was employed, drawing from behavioural studies in environmental psychology, international regulatory standards, and real-world market data. The analysis focuses on essential domestic functions including sleep, hygiene, food preparation, storage, social interaction, and work. Quantitative findings from tenancy surveys, post-occupancy research, and market performance data indicate that residential units below 30 square metres for single occupants and 45 square metres for couples are consistently associated with reduced satisfaction and shorter tenancies. Regulatory minimums across diverse jurisdictions tend to converge near these same thresholds. The study proposes technical minimums of 30, 45, and 60 square metres for one-, two-, and three-person households, respectively. These values reflect functional lower bounds rather than ideal or aspirational sizes and are intended to inform performance-based housing standards. Full article

The growing global demand for energy has resulted in a demand for innovative strategies for residential energy management. This study explores a novel framework—MELISSA (Modern Energy LLM-IoE Smart Solution for Automation)—that integrates Internet of Things (IoT) sensor networks with Large Language Models (LLMs) to optimize household energy consumption through intelligent automation and personalized interactions. The system combines real-time monitoring, machine learning algorithms for behavioral analysis, and natural language processing to deliver personalized, actionable recommendations through a conversational interface. A 12-month randomized controlled trial was conducted with 100 households, which were stratified across four socioeconomic quintiles in metropolitan areas. The experimental design included the continuous collection of IoT data. Baseline energy consumption was measured and compared with post-intervention usage to assess system impact. Statistical analyses included k-means clustering, multiple linear regression, and paired t-tests. The system achieved its intended goal, with a statistically significant reduction of 5.66% in energy consumption (95% CI: 5.21–6.11%, $p<0.001$) relative to baseline, alongside high user satisfaction (mean = 7.81, SD = 1.24). Clustering analysis ($k=4$, silhouette = 0.68) revealed four distinct energy-consumption profiles. Multiple regression analysis ($R^2=0.68$, $p<0.001$) identified household size, ambient temperature, and frequency of user engagement as the principal determinants of consumption. This research advances the theoretical understanding of human–AI interaction in energy management and provides robust empirical evidence of the effectiveness of LLM-mediated behavioral interventions. The findings underscore the potential of conversational AI applications in smart homes and have practical implications for optimization of residential energy use. Full article

Current research on aged housing prioritizes community planning and environmental enhancement over older adults’ needs, creating a retrofit mismatch amid population aging. To investigate the relationship between indoor environmental quality and residential satisfaction among elderly occupants, this study examines 72 households in aged residential buildings, analyzing four environmental indicators (thermal, lighting, acoustic environments, and air quality). The environmental measurements reveal that 81.9% of thermal environment parameters fall below the ASHRAE-55 comfort range, with winter average temperatures reaching only 13.94 °C. Insufficient illumination exists in kitchen and bedroom areas. Lifestyle patterns including infrequent air conditioning use (87%) and window ventilation substituting range hoods (32%) may deteriorate thermal comfort and air quality. An ordered logistic regression analysis demonstrates significant correlations between all four environmental indicators and elderly satisfaction levels. Thermal comfort emerges as the priority focus for aging-adapted retrofitting. Air quality improvement shows particularly significant potential for enhancing residential satisfaction. Although prolonged window opening (73%) exacerbates low-temperature/high-humidity conditions and noise exposure, it still contributes positively to overall satisfaction. This research provides crucial insights for aligning aged residential retrofitting with home-based elderly care requirements, promoting housing development that better accommodates the lifestyle patterns of older populations, thereby improving quality of life for aging-in-place residents. Full article

Building on our prior research with a national survey sample of 5385 US participants, the Pooled Rideshare Acceptance Model (PRAM) was built upon two factor analyses. This exploratory study extends the PRAM framework using the Pooled Rideshare Acceptance Model Multigroup Analyses (PRAMMA) to examine how 16 demographic variables influence and interact with the acceptance of Pooled Rideshare (PR), filling a gap in understanding user segmentation and personalization. Using a national sample of 5385 US participants, this methodological approach allowed for the evaluation of how PRAM variables such as safety, privacy, service experience, and environmental impact vary across diverse groups, including gender, generation, driver’s license, rideshare experience, education level, employment status, household size, number of children, income, vehicle ownership, and typical commuting practices. Factors such as convenience, comfort, and passenger safety did not show significant differences across the moderators, suggesting their universal importance across all demographics. Furthermore, geographical differences did not significantly impact the relationships within the model, suggesting consistent relationships across different regions. The findings highlight the need to move beyond a “one size fits all” approach, demonstrating that tailored strategies may be crucial for enhancing the adoption and satisfaction of PR services among various demographic groups. The analyses provide valuable insight for policymakers and rideshare companies looking to optimize their services and increase user engagement in PR. Full article

Interest in the balance between work and life and improving the quality of life is expected to steadily increase the number of users of forest welfare facilities. In this study, the “2023 Forest Recreation and Welfare Activity Survey” was used to analyze how characteristics of forest visits, such as visit frequency, the number of visited areas, expenditures, and the presence of companion animals, affect life satisfaction based on three visit types: daily (less than 4 h), day (more than 4 h), and overnight (more than 1 night). A hierarchical regression of 9437 respondents revealed that age, occupation, education, spouse, children, household income, and type of residence, excluding sex, were significantly correlated with life satisfaction. A hierarchical regression analysis revealed that for daily visitors, both visit frequency and companion animals increased life satisfaction. For day visitors, visit frequency, the number of visited areas, expenditures, and companion animals enhanced life satisfaction. For overnight visitors, visit frequency and expenditures positively impacted life satisfaction. Across all visit types, the frequency of forest visits consistently increased life satisfaction. This study statistically clarified how the characteristics of each visit type affect life satisfaction. The findings provide foundational data for future policies and research on forest recreation and welfare. Full article

It is well understood that climate change is a major cause of the environmental shifts that are significantly impacting human lives. The floods caused by climate change are not only occurring more frequently each year, but they also bring up the problem of access to clean water for drinking and other daily usage for the affected communities. The Swat district of the Khyber Pakhtunkhwa province in Pakistan is one of the impacted regions and the growing concern for clean water access is yet to be resolved. This study aims to propose a sustainable solution to water access during the emergencies, particularly in flood and drought situations. While the roof water harvesting system (RWHS) is well established and functional in many developed regions, its potential remains underexplored in Pakistan. This research study analyzed the climate change projection data for the Saidu Sharif region of Swat. The regional climate data are gathered from the Shared Socio-economic Pathways (SSPs) for the period from 2015 to 2045. Five general circulation models (GCMs) were selected based on their performance in South Asian climate simulations. Analysis of the regional forecasted climate data indicates that almost all of the five climate models have predicted the periods of excessive rainfall to occur in the months of July, August, and September, while prolonged dry seasons may last between 271 and 325 days annually. Hydrological modeling was used to estimate RWHS performance, which incorporated the key parameters such as catchment area, runoff coefficient, and rainfall intensity. The findings suggest that the proposed RWHS could meet basic drinking water needs during the floods and even during the drought periods near around 100% satisfaction of water demand under certain conditions. For example, for an average drought period of 273 days, a household of seven people with a per capita daily water demand of 17 L requires a storage capacity of 33 m³. On the other hand, for a maximum drought duration of 325 days, the required storage volume increases to 39 m³. Demand satisfaction calculations are also used to evaluate the effectiveness of the proposed model. This research contributes to addressing the growing water scarcity challenge posed by climate change in the Swat region and offers a sustainable and practical solution. Full article

With the development of society, energy application and building thermal comfort in rural residences are receiving more and more attention. The rural residences in this survey mainly cover the rural areas of 21 prefectures in Guangdong province, of which 24.7% are in the Pearl River Delta, 18.9% in western Guangdong, 13.1% in eastern Guangdong, and 43.2% in northern Guangdong. Rural household energy consumption is mainly used for lighting equipment, household appliances, and cooking equipment, where lighting equipment and household appliances mainly consume electrical energy, and cooking equipment consumes different types of energy due to the diversity of types. First, there is a wide variety and variation in rural energy consumption, with electricity and liquefied petroleum gas as the main sources of cooking energy. Hot water is mainly obtained by heating with electricity and natural gas. Secondly, for rural residents, renewable energy is too expensive to build, is also affected by the environment and weather, and is often not convenient to use. Third, rural residents generally experience a warm, humid indoor environment with adequate airflow, but poor kitchen ventilation reduces air quality satisfaction. To enhance renewable energy adoption, technological advancements and cost reductions are necessary, along with increased government efforts in awareness campaigns, policy incentives, and demonstration projects. This study analyses the rural energy structure in Guangdong, proposes the direction of rural energy optimization, and analyses rural energy use and the feasibility of renewable energy promotion, considering the population and income of rural households. Full article

In the realm of housing, the concept of adaptability has emerged as a pivotal solution to address the evolving space needs of households. The hypothesis and contribution that this paper puts forward is that dwellings can be designed to accommodate society’s demographic transformation and facilitate the evolving interior space needs of their occupants. It investigates the concept of Life Cycle Homes manifested through designs of flexible living spaces that can be easily modified to align with the changing dynamics of family structures over time to achieve user satisfaction, circularity, and sustainability. The investigation begins with an exploration of contemporary demographic shifts and variations in family sizes. The discussion underscores how different types of families interact with their homes, highlighting the necessity for adaptable housing solutions. The paper then continues with the study of past theories and application in adaptable housing, most notably through the work of Habraken and Japanese housing innovation. A detailed examination of various flexible housing strategies is presented, focusing on innovative approaches like demountable partitions. These strategies are instrumental in creating versatile living spaces that can seamlessly adapt to households’ diverse and dynamic requirements. Following a research and development process, and as part of the methodology, the paper introduces the Life Cycle Home project that was conceived by the author to illustrate a practical implementation of adaptable housing strategies. The three-floors home exemplifies how flexibility and versatility can meet the changing needs of homeowners, offering a blueprint for future residential design. Full article

The results of numerous studies show that the control of power grid modes is carried out mainly using a technical criterion. The economic criterion is taken into account through the use of complex and inaccurate models that do not accurately predict the result. The emergence of market relations in the energy sector makes power systems economic entities in terms of production and satisfaction of demand for electricity by various economic entities (industry, households, businesses, etc.). Under these conditions, electricity is a commodity with a corresponding price and quality indicators. This requires the application of the risk assessment methodology as an economic category in the activities of power systems as a business entity. The methodology of risk assessment in market conditions requires business entities to search for methods to minimize risk as a possibility of adverse events. Under these conditions, it becomes possible to make the best management decisions regarding the most important criterion that reflects the interests of business entities at a given time. However, the imperfection of the relevant methodology for risk assessment in the energy sector delays their application in the industry. At the same time, when making management decisions, three possible levels can be distinguished: decision-making in conditions of certainty, when the result is presented in a deterministic form and can be determined in advance; decision-making under conditions of risk, when the outcome cannot be determined in advance, but there is information on the probability of distribution of possible consequences; decision-making in conditions where the outcome is random and there is no information about the consequences of the decision. An analysis of scientific publications shows that some authors’ works are devoted to solving the issues of applying the theory and principles of risks in the energy sector, in which the problem is solved only at the first two levels. At the same time, the operation of energy facilities is characterized by a high level of uncertainty and incomplete information about the consequences of such decisions. Therefore, the development of a methodology for making management decisions in the energy sector based on the theory and practice of risks, taking into account the high level of uncertainty and incomplete information, is an urgent scientific task. Implementation of algorithms and programs for controlling the modes of power grids based on them can meet the requirements for reliable and high-quality energy supply to the most demanding consumers and create favorable conditions for their business. This work is devoted to the development of scientific and methodological foundations for determining the voltage risk in power system networks, taking into account the uncertain nature of the loads and its impact on consumers. Based on the results of the study, a mathematical model of the risk of voltage collapses in networks, an algorithm and a methodology for its calculation were proposed. Full article

This study examines the economic activities of married women aged 20 and above after the COVID-19 pandemic, focusing on variations across income levels. Using data from the 2022 Social Survey by Statistics Korea, which includes a nationally representative sample of over 38,000 individuals from 19,000 households, this study investigates the determinants of married women’s participation in economic activities and their impact on life satisfaction. Key variables, including employment status, income level, and life satisfaction, are measured using validated survey instruments. Hierarchical and multiple regression analyses are employed to assess how income levels moderate these effects, while correlation analysis is conducted to address multicollinearity concerns and ensure the robustness of the results. Findings indicate that income level has a significant but varying influence on the relationship between economic participation and life satisfaction. Lower-income women exhibit greater sensitivity to employment status in terms of life satisfaction, whereas higher-income women’s satisfaction is more influenced by social status and cultural factors. Additionally, education and household conditions emerged as critical determinants of economic engagement across different income groups. These results underscore the need for income-specific policy interventions to support married women’s workforce participation post-pandemic. However, as this study relies on cross-sectional survey data, causality cannot be definitively established. Policymakers should consider differentiated strategies that address financial constraints, work–family balance, and cultural expectations to foster greater economic inclusion. Full article

Rapid urbanization has accelerated the transformation of community dynamics, highlighting the critical need to understand the interplay between subjective perceptions and objective built environments in shaping life satisfaction for sustainable urban development. Existing studies predominantly focus on linear relationships between isolated factors, neglecting spatial heterogeneity and nonlinear dynamics, which limits the ability to address localized urban challenges. This study addresses these gaps by utilizing multi-scale geographically weighted regression (MGWR) to assess the spatial nonstationarity of subject perceptions and built environment factors while employing gradient-boosting decision trees (GBDT) to capture their nonlinear relationships and incorporating eXtreme Gradient Boosting (XGBoost) to improve predictive accuracy. Using geospatial data (POIs, social media data) and survey responses in Suzhou, China, the findings reveal that (1) proximity to business facilities (β = 0.41) and educational resources (β = 0.32) strongly correlate with satisfaction, while landscape quality shows contradictory effects between central (β = 0.12) and peripheral zones (β = −0.09). (2) XGBoost further quantifies predictive disparities: subjective factors like property service satisfaction (R² = 0.64, MAPE = 3.72) outperform objective metrics (e.g., dining facilities, R² = 0.36), yet objective housing prices demonstrate greater stability (MAPE = 3.11 vs. subjective MAPE = 6.89). (3) Nonlinear thresholds are identified for household income and green space coverage (>15%, saturation effects). These findings expose critical mismatches—residents prioritize localized services over citywide economic metrics, while objective amenities like healthcare accessibility (threshold = 1 km) require spatial recalibration. By bridging spatial nonstationarity (MGWR) and nonlinearity (XGBoost), this study advances a dual-path framework for adaptive urban governance, the community-level prioritization of high-impact subjective factors (e.g., service quality), and data-driven spatial planning informed by nonlinear thresholds (e.g., facility density). The results offer actionable pathways to align smart urban development with socio-spatial equity, emphasizing the need for hyperlocal, perception-sensitive regeneration strategies. Full article

Background/Objectives: The outpatient healthcare experiences of patients with chronic diseases significantly impact disease management and quality of life. Patient satisfaction with healthcare services serves as a critical indicator of the responsiveness of healthcare systems and the advancement of patient-centered care. This study aimed to identify key factors influencing patient satisfaction and propose strategies for improvement. Methods: Using secondary data from the 2023 Healthcare Service Experience Survey (HSES), we analyzed patient satisfaction and its associated factors among respondents aged 15 years and older from households nationwide. Through multiple regression analysis and statistical testing, we examined the impact of the healthcare facility type, sociodemographic characteristics, and healthcare service experiences on satisfaction levels. Results: Information provided by physicians and nurses, communication with healthcare providers, and shared decision-making processes had a significant impact on patient satisfaction. Satisfaction levels were highest in hospitals and lowest in clinics. Older patients and those who discontinued treatment due to the financial burden reported lower satisfaction. Notably, information provided by nurses had the most substantial positive influence on satisfaction. Conclusions: Delivering patient-centered outpatient healthcare services is essential in improving satisfaction and health outcomes. Enhancing the service quality, reducing financial burdens, and adopting digital platforms to promote patient engagement are critical measures. These approaches will strengthen chronic disease management systems and contribute to improving the overall quality of life of the population. The entire study focused on outpatient care. Full article

Food consumption plays a fundamental role in human life, shaping not only daily nutrition but also economic and social behaviors. Household expenditures on food remain among the highest, and the time allocated to food purchasing and preparation is significant. Beyond biological necessity, food represents a cultural and social phenomenon, influencing consumer habits, market trends, and lifestyle choices. This study explores the key factors influencing purchasing decisions in the agro-food sector in the North-East Region of Romania, focusing on socio-cultural influences, product attributes, brand trust, tradition, and lifestyle. The research employs a quantitative approach, utilizing a structured questionnaire to collect data from 337 residents through a convenience sampling strategy. The collected data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) via SmartPLS 4.0 to examine the interrelationships between subjective norms, product attributes, price, consumer trust, and purchasing decisions. The findings indicate that social norms, price, product attributes, brand trust, customer satisfaction, and lifestyle have a significant and positive impact on consumer purchasing decisions. By understanding the key drivers behind sustainable food choices, businesses can optimize product offerings and enhance consumer engagement, while policymakers can design initiatives that promote sustainable consumption at both regional and national levels. Full article

In sub-Saharan Africa, protected areas are located in close proximity to communities, leading to frequent negative encounters between humans and wildlife. This is coupled with increased pressure from communities seeking park resources to support their livelihoods. To address this, land use plans have been designed around protected areas. For example, in Kenya, wildlife conservancies have been created out of private and community lands. The aim of these conservancies is to contribute to improved livelihoods, reduce human–wildlife conflicts, and increase support for conservation. However, limited research exists on how the conservancies have achieved their aims among local communities. This study focuses on the Maasai Mara region in Kenya and examines how livelihoods and human–wildlife conflicts influence support for conservation among conservancy members. Data were gathered from 411 households adjacent to the reserve through a survey conducted in June and July 2024. The findings indicate a high incidence of human–wildlife conflict and improved security in health and education only. Despite this, there is high satisfaction with the conservancy model and strong support for conservation. Although these findings highlight the significance of conservancies in mitigating human–wildlife conflict, enhancing livelihoods, and garnering conservation support, more attention is needed for food and financial security. Full article