Residential Choice Research Articles

Assessment of forensic medicine education impact on medical students' knowledge and specialisation attitudes: a multicenter analysis from Italian universities.

This study aimed to assess students' knowledge, awareness, and attitudes regarding forensic-medicine concepts taught during a Medicine and Surgery degree program at eight Italian universities. Additionally, the study aimed to evaluate the impact of the course on students' knowledge and attitudes toward choosing medical residency. A cross-sectional study was conducted through an anonymous web-based survey of medical students at eight italian universities. Descriptive, univariate, and logistic regression analyses were performed for the selected questions. The survey was completed by 1022 students. Forensic medicine appears to be important for providing training in the fundamental concepts of forensic medicine, especially professional liability, defensive medicine, and forensic pathology. The descriptive and univariate analyses demonstrate that the course can assist students in choosing their specialisation school. The multivariate analysis highlighted the impact of the forensic medicine course on orienting students' choice of medical residency, increasing it by nine times after attending the course. In the logistic regression analysis of the influence of medical liability on the choice of medical residency, students recognised a doubled effect after attending the course. Finally, the perceived usefulness of the course was significantly higher after attendance. Forensic medicine courses have the task of defining the duties and responsibilities of forensic physicians, providing indispensable tools for future medical practitioners regardless of their future specialisation, and limiting the increasing use of defensive medicine. In conclusion, it is imperative for governments to implement measures directed at diminishing the risk of burnout arising from the ongoing pressure associated with the fear of medicolegal litigation, encompassing both criminal and civil contexts.

Spatial overlap: trade-offs in refugees’ residential choices

ABSTRACT Social science research gives rise to what we call the ‘refugee mobility puzzle’: While restrictions on the freedom of residence limit refugees’ socio-economic integration, those who do not face such restrictions often move to areas with high unemployment that similarly hinder their labor market prospects. This study addresses a central element of this puzzle: What draws refugees to high unemployment areas? We propose the spatial overlap hypothesis arguing that refugees in comparatively generous reception systems initially prioritize or are forced to prioritize non-labor-market resources such as affordable housing and proximity to social networks. Thereby they often settle in areas with general economic disadvantage as such areas frequently overlap with said resources. Based on the IAB-BAMF-SOEP Survey of Refugees this study tracks residential histories of more than 2,400 refugee respondents across all German counties and postcodes. Discrete choice models show that preferences for cities, lack of affordable housing, the presence of small, service-oriented companies, and co-ethnic communities explain refugees’ gravitation to disadvantaged areas. These results support the spatial overlap hypothesis and suggest that recently approved refugees face trade-offs: area characteristics that are initially attractive tend to spatially overlap with such that likely inhibit longer-term integration prospects.

Exploring Factors Influencing US Medical Students’ Choice of Internal Medicine Residency

Exploring Factors Influencing US Medical Students’ Choice of Internal Medicine Residency

Analysis of microbial contamination and risk assessment model construction at critical public congregation areas of apartment buildings

In the context of rapid urbanization, apartments have become the preferred living choice for many urban residents, bringing the microbial environment of public areas and its impact on residents' health into sharp focus. This study sampled airborne and settling microbes at key congregation points within apartment public areas, analyzed microbial community composition, and systematically assessed microbial risks during both static and dynamic stages. The results reveal that in the static phase, the airborne microbial population is dominated by Staphylococcus (740 CFU/m³), Lysinibacillus (650 CFU/m³), and Micrococcus (550 CFU/m³), while the settling microbial population is led by Staphylococcus (5658.8 CFU/(m²·h)), Micrococcus (4872.9 CFU/(m²·h)), and Lysinibacillus (2672.2 CFU/(m²·h)). The highest counts of airborne microbes were found in the stairwell (270 CFU/m³) during both phases, whereas settling microbes peaked at the apartment entrance (3615.4 CFU/(m²·h)) in the static phase and in the elevator car (15,247.4 CFU/(m²·h)) during the dynamic phase. Further biodiversity analysis results showed that the elevator car had higher diversity during both the morning and evening peaks in the dynamic phase, indicating that pedestrian flow significantly impacts the composition of the microbial community. A mathematical model was also developed to evaluate microbial hazards. The model reveals the elevator car having the highest microbial risk during dynamic phase, with an 18.2% higher risk in the evening peak compared to the morning. This study provides a scientific basis for microbial risk management, environmental design optimization, and disease prevention strategies in public areas of apartment buildings, which will help improve residents' living environment.

Impact of the COVID-19 pandemic on food choices among the working-age adult residents of Lithuania

Abstract Background The COVID-19 pandemic affected the nutrition of various populations. Assuming that the majority of the population of working-age residents of Lithuania know healthy nutrition recommendations and that food selection criteria might serve as an indicator of the following them, we aimed to assess the food selection criteria during and after the COVID-19 pandemic among working-age adult residents of Lithuania. Materials and methods Three cross-sectional surveys among working-age adult residents of Lithuania were carried out: in 2019 (before the pandemic), in 2021 (during the pandemic), and in 2022 (after the pandemic). In 2019, this study included 1007 residents, 1600 residents were surveyed in 2021, also, 1600 residents were surveyed in 2022. Distribution of the respondents by food selection criteria was compared between the samples according to gender, age, marital status, education level, place of residence, employment, income. Results The COVID-19 pandemic affected the food choices of Lithuanian residents (p < 0.05). In 2019, products’ benefits for health criterion was in the third place when choosing foods. It was indicated by 22% of the respondents. In 2019, the most prevalent criterion for selecting foods was taste. It was indicated by 37% of the respondents. The second most prevalent food selection criterion was the price. It was indicated by 24% of the sample. In 2021 selection of foods because of products’ health benefits became the most prevalent and accounted for 31% of the sample. In 2022, it returned back to the prepandemic level and accounted for 19% of the sample. In all social and demographic groups changes in food selection criteria remained as well (p < 0.05). Conclusions The COVID-19 pandemic had a positive impact on the food choices of working-age adult residents of Lithuanian. Changes of food selection criteria were observed within the different groups of gender, age, marital status, education level, place of residence, employment, income. Key messages • The COVID-19 pandemic had a positive impact on the food choices of working-age adult residents of Lithuanian. • Less than a year after the pandemic food selection according to its health benefits rapidly decreased and returned back to the prepandemic level.

Mapping the interplay of work-arrangement, residential location, and activity engagement within an integrated model

Virtual activities, such as teleworking have been identified as major travel demand management strategies to tackle traffic congestion and emission. However, integrated models, which are capable of testing such strategies, have not yet been properly extended to capture emerging activity patterns. This study fills-up the literature gap by implementing individuals’ work-arrangement and introducing in-home (IH) virtual activities within an integrated Transport, Land-use, and Emission (iTLE) modeling framework. First, it conducts a household travel survey, which collected socio-economic, activity-travel, and work-related information through a questionnaire survey in the Halifax Regional Municipality (HRM), Nova Scotia, Canada. Next, it develops a work-arrangement choice model based on the mixed-logit modelling (MXL) approach and implements it within iTLE. After that, individuals’ daily activity programs are generated in a sequential manner utilizing a Markov Chain Monte Carlo (MCMC) modelling approach considering their work-arrangement, employment, and vehicle ownership. To demonstrate the application of the developed tool, individuals’ socio-demographics, residential-location, work-location, and activity-participation are longitudinally simulated up to 2031. The analysis of teleworking parameters revealed distinct clusters and individual preferences, emphasizing the significance of personalized approaches in formulating teleworking strategies. Most non-teleworkers stay closer to downtown than full-teleworkers while clustered behavior is observed among hybrid workers for residential location choice. Increase is observed for shopping, dining-out, and IH maintenance/discretionary activities while decrease is observed for out-of-home work. The outcomes of this paper will be helpful for policymakers and transport researchers to understand the evolution of work-arrangement and examine subsequent impacts on transportation and land-use systems.

Exploring gaps in residential and parking location choice models for autonomous vehicles: a proposed evaluation framework

ABSTRACT The advent of autonomous vehicles (AVs) is poised to transform urban landscapes, notably by altering perceptions of travel time value, reshaping parking structures, and introducing additional travel demand through empty-cruising and self-parking capabilities. These changes are anticipated to influence both residential and parking location choices. This study delves into the complexities of these decisions by integrating insights from 28 modelling studies on residential and/or parking location choices in the context of AVs and by proposing an evaluation framework for future modelling efforts. A critical gap identified is the oversight of empty-cruising and parking costs in the context of residential relocation choice for owners of privately-owned AVs. Furthermore, no study has adopted a joint-choice modelling approach for residential and parking location choices. By offering guidelines for the incorporation of these elements, this study contributes to the development of a holistic residential and parking location choice model with AVs, thus providing a valuable roadmap for future research in urban planning and transportation economics.

Rational cuts? The local impact of closing undersized schools

The availability of public education services can influence residential choices. Therefore, policies aimed at ‘rationalising’ service provision by reducing the number of undersized nodes in the public school network can lead to population decline, especially in spatially isolated areas lacking valid alternatives to the removed services. This paper examines the demographic and income effects of primary school closures by exploiting an Italian education reform that resulted in the contraction of the school network. We assess whether school closures impact households’ residential choices, over and above preexisting negative population trends that motivate school closures. Our findings indicate that municipalities affected by school closures experience significant reductions in population and income. The effect is primarily driven by peripheral municipalities located far away from economic centres and distant from the next available primary school. This evidence indicates that school ‘rationalisation policies’, by fostering depopulation of peripheral areas, have an influence on the spatial distribution of households and income, thus affecting territorial disparities.

What makes medical students choose their residencies? Association between mental health of medical students and their choices of future medical specialties

Background: Excessive cognitive demands and chronic stress contribute to the occurrence of mental health problems among medical students. It may be hypothesized that the presence of such disturbances have an influence on their choices of post-graduate training programs. Objective: The aim of the study was to evaluate the state of mental health of medical students and to assess if there is any association between the prevalence of mental health problems and their residency choices. Materials and methods: 114 medical students were surveyed in terms of their residencies' choices and their mental health with the usage of validated psychological questionnaires. Results: 74 (64,91%) of medical students needed psychiatric or psychological treatment at some stage in their lives. Intensity of risky alcohol consumption was positively correlated with the choice of surgery (p=.0000) and negatively correlated with the choice of psychiatry (p=.0000). The severity of depressive symptoms was positively correlated with emergency medicine choice (p=.0479). Anxiety symptoms, eating disorders and autism spectrum severity symptoms were not significantly correlated with the choice of any medical specialty. Conclusions: Medical students were found seriously affected by mental health problems, what to some extent seemed to impact their future career choices.

Residential water choices: Assessing the willingness to adopt alternative water sources by examining risk perceptions and personal norms in Belgium

With escalating freshwater scarcity, transformative shifts in infrastructure, technology, and societal attitudes are essential. This study applies Protection Motivation Theory to explore how perceived water scarcity impacts individuals' willingness to reduce tap water consumption and increase the use of alternative sources in households. An online survey (n = 2623) in Belgium assessed acceptance of tap water, rainwater, and recycled greywater for various household activities. Sequential regression analysis examined the influence of threat appraisal, coping appraisal, personal norms, and socio-demographics on this willingness. The results indicate that willingness to conserve tap water is strongly driven by self-efficacy rather than risk appraisal. Conversely, willingness to use rainwater and recycled greywater depends on perceived future water scarcity, perceived self-efficacy, and personal norms. Perceptions of present water scarcity negatively influenced the willingness to use rainwater and recycled greywater, suggesting a boomerang effect. However, future water scarcity perceptions encourage the use of alternative water sources, providing a nuanced perspective. These findings provide valuable insights into the acceptance of alternative water sources and underline the importance of context-specific approaches, enhancing self-efficacy and personal norms to encourage the adoption of alternative water sources for household activities, ensuring effective freshwater conservation.

Household residential energy choices in green transition: insights from a household survey in rural China.

It has been widely recognized that accelerating green residential energy transition from traditional solid fuels (biomass and coal) to clean and high-efficient energy sources is critical for rural sustainable development. However, little attention has been paid to estimate panel data discrete choice models to analyze the dynamic behavior information of individual households in the process of energy transition. Hence, this paper investigates green residential energy transition using a panel dataset from 3308 rural households in eight provinces of China in 2015 and 2018. The results show that although traditional solid biomass still plays a dominating role in rural residential energy choice, fuel switching from solid fuels to modern clean energy alternatives is taking place. Off-farm employment plays an important role in the transition towards more sustainable energy sources, as households with off-farm employed heads and higher off-farm income level are highly likely to choose superior energy alternatives other than traditional biomass. Besides, the educational level of the household head and household location are also important influencing factors of household residential energy choices. Based on these findings, this paper suggests that job creation in non-farm sectors should be given a priority in future policy design to promote rural green energy transition in residential sector. North-south differences should be taken into account, whereas more policy options for optimizing biomass energy use should be explored.

Home Country Work Experience and Immigrant Self-Employment in the United States

Immigrant entrepreneurship in the United States has grown steadily in the last four decades. In this paper, I study the occupational choices of legal permanent residents and their associated earnings in paid and self-employment. Using a unique data set with pre- and postmigration individual-level information, I analyze the role of home country work experience of immigrants in their probability of becoming entrepreneurs and their earnings after migration. To control for endogenous sector selection in the estimation of earnings distributions, I follow a novel identification strategy based on extremal quantile regressions that does not require exclusion restrictions or a large support variable. I find that foreign work experience in paid and self-employment is an important predictor of entrepreneurship after migration. In addition, it impacts earnings in the United States but differently across sectors, controlling for human capital, assimilation, time, region of origin, U.S. destination, previous migratory status, and demographic characteristics. Overall, my results highlight the role played by immigrants’ labor market history from their home countries to better understand their outcomes in the United States.

Urban–rural migration in Germany: A decision in favour of ‘the rural’ or against ‘the urban’?

For many years, the debate on internal migration in Germany focused on rural out-migration. Since the early 2000s, large cities have had positive migration balances. Almost unnoticed, however, in the early 2010s the patterns of internal migration started to shift towards rural locations. It was only the COVID-19 pandemic that drew attention to these changing tendencies and the apparent new appreciation of rural living.In this paper, we will first shed light on the changes in internal migration between 2000 and 2021. We divide this period into three phases and show that the overall pattern of population centralisation transformed into a process of decentralisation. This trend further intensified during the first two years of the COVID-19 pandemic. Secondly, based on a German-wide population survey, we present findings on the reasons why households moved from urban to rural areas between mid-2015 and mid-2020, with personal, employment-related and housing-related reasons being the most relevant. To better understand urban-rural migration (or ‘counterurbanisation’), we pay particular attention to how respondents experienced cities and urban housing markets and which residential characteristics they ascribed to the rural destination. We show that urban-rural migration is a multifaceted decision in which the structural impediments of urban housing markets lacking affordable housing play a relevant part. In conclusion, we argue that research on urban-rural migration needs to more systematically pursue the idea of a complex and contingent decision that is driven by both structural factors and personal preferences. Extending the long-standing counterurbanisation debate beyond a mere residential choice for ‘the rural’ is all the more important to adequately interpret future findings on post-pandemic patterns of internal migration.

Rural residential choices: unravelling the nexus of accessibility and preferences

ABSTRACT As rural residents increasingly migrate to urban areas to improve living conditions, employment, and education, closely examining the relationship between residential choices and accessibility becomes crucial. This study employs a Stated Preference Survey (SP) with an orthogonal experimental design and uses the Multinomial Logit Model (MNL) to explore the preferences of rural residents for accessibility in the built environment when choosing new residences, including potential disparities between residents on the urban fringe and those in suburban areas. The findings reveal a strong inclination among residents for proximity to essential services such as education, transportation, healthcare, markets, recreation, and amenities. Preferred residential locations include within a 2-kilometre radius of schools, 300 metres from bus stops, 500 metres from medical facilities, 2 kilometres from markets, between 500 metres and 1 kilometre from leisure facilities, and within 1 kilometre of supermarkets. Additionally, commuting time preferences vary, with rural residents favoring a 15-minute commute, peri-urban residents preferring 5 minutes, and distant suburban residents showing no clear preference for commute times ranging from 5 to 15 minutes. These insights carry significant implications for urban and rural planning and development.

A DPSIR-Driven Agent-Based Model for Residential Choices and Mobility in an Urban Setting

A DPSIR-Driven Agent-Based Model for Residential Choices and Mobility in an Urban Setting

Study on the Impact of Urban-Rural Education Resource Equitability and Student Endowment Differences on Promoting Educational Equity

Based on the empirical analysis of the China Education Panel Survey (CEPS), this paper explores the impact of the equitability of urban-rural education resources and student endowment differences on educational equity. The findings not only provide a new perspective and empirical support for the study of the theory of educational equity but also offer valuable references for policymaking and education reform to promote social equity and harmonious development. It is empirically found that cognitive abilities and parents' educational expectations have a positive impact on students' educational expectations, while the dropout situation of friends has a negative impact. Additionally, although health status has a positive influence on educational expectations, it does not significantly affect the choice of future residence. These factors together reveal the significant impact of the family environment, personal ability, and social relationships on students' education and life choices, emphasizing the necessity to optimize educational resources and family education support, holding significant theoretical and practical significance.

Determinants of Intra-City Residential Migration Patterns of Older Adults: A GIS and Decision Tree Analysis of Yancheng City, China

This study investigates the spatial patterns of residential migration among older adults in the city center of Yancheng and the influencing factors using data on the home purchases of individuals aged 65 and older from 2016 to 2018, along with peripheral point of interest (POI) data, analyzed with ArcGIS and a decision tree model. The results indicated that persons aged 60–65 accounted for 42.8% of the total sample and primarily chose to migrate in the early stages of retirement. The intra-city migration of older adults exhibits both centripetal and centrifugal patterns, with a greater tendency toward the city center. House prices, floor levels, and commercial facilities significantly impact their choice of migration destinations. Among these, house prices were the most critical determinant, with the majority of older adults migrating to neighborhoods with lower house prices. This study contributes by integrating residential migration and location choice research and constructing an analytical framework based on facility accessibility. The findings provide insights into the key determinants of location choice for intra-city residential migration among older adults and the construction of livable neighborhoods for them.

The role of social support in the decision to migrate for childbirth: qualitative evidence from India.

Temporary Childbirth Migration (TCM) involves women returning to their natal homes during or after pregnancy, a common but understudied practice in India and South Asia. This study examines social support practices influencing TCM decisions among Indian women. Factors such as family support, especially from husband, in-laws and parents, play a crucial role in migration decisions during the perinatal period. Understanding these factors is essential for improving maternal and child health outcomes and for developing targeted policies and interventions. Cultural influences also contribute to TCM decisions, impacting the timing, duration, and motivations behind women's choices to migrate during or after delivery. Our study was conducted at the Vadu Health and Demographic Surveillance System (HDSS) in Western Maharashtra, India. We conducted 41 in-depth interviews with triads of women, their husbands, and mothers-in-law from Vadu HDSS, focusing on perceptions, timing, reasons, decision-making, and support related to Temporary Childbirth Migration (TCM). Participants varied in age, education, occupation, marriage type, migration type, delivery method, and included women who recently delivered or had infants up to two years old. The qualitative data were analyzed using both rapid analysis and traditional analysis using coded transcripts, incorporating both predefined and emergent codes to capture a wide range of participant characteristics and experiences. We later categorized our findings in Social support domains. Social support, including emotional, financial, instrumental, and informational, is a critical factor in TCM. Emotional support from mothers is highly valued, providing a stress-free environment. Financial support from husbands, in-laws, or parents influences the decision, with financial responsibilities sometimes dictating the choice of residence. Instrumental support, such as help with household chores, is essential, with varying levels of support at different locations. Informational support from experienced family members also guides expectant mothers. Healthcare access, household status, and the role of husbands further impact TCM decisions. Women prioritize proximity to medical facilities, comfort, and freedom in their natal homes. The inclusive decision-making process often involves women, in-laws, parents, and husbands. The study's findings highlight the complex interplay of social support, cultural norms, and practical considerations in TCM decisions, underscoring the need for more research to understand and support women's choices during the perinatal period. In conclusion, social support is a key driver of TCM and women's status in their households affects their support needs. Recognizing the importance of emotional, financial, informational, and instrumental support will help healthcare providers and policymakers to better assist expectant mothers, promoting positive maternal and child health outcomes.

Small-area population forecasting in a segregated city using density-functional fluctuation theory

Policy decisions concerning housing, transportation, and resource allocation would all benefit from accurate small-area population forecasts. However, despite the success of regional-scale migration models, developing neighborhood-scale forecasts remains a challenge due to the complex nature of residential choice. Here, we introduce an innovative approach to this challenge by extending density-functional fluctuation theory (DFFT), a proven approach for modeling group spatial behavior in biological systems, to predict small-area population shifts over time. The DFFT method uses observed fluctuations in small-area populations to disentangle and extract effective social and spatial drivers of segregation, and then uses this information to forecast intra-regional migration. To demonstrate the efficacy of our approach in a controlled setting, we consider a simulated city constructed from a Schelling-type model. Our findings indicate that even without direct access to the underlying agent preferences, DFFT accurately predicts how broader demographic changes at the city scale percolate to small-area populations. In particular, our results demonstrate the ability of DFFT to incorporate the impacts of segregation into small-area population forecasting using interactions inferred solely from steady-state population count data.

Precision in decision-making: a novel Z-number DEA approach for European country rankings

PurposeConventional approaches such as Data Envelopment Analysis (DEA) and Fuzzy Data Envelopment Analysis (FDEA) cannot effectively account for uncertainty, which can lead to imprecise decision-making. Furthermore, these methods frequently rely on precise numbers, ignoring the inherent uncertainty of real-world data. To address this gap, the research question arises: How can we develop a methodology that combines Z-number theory and FDEA to provide a comprehensive assessment of residency preferences in European countries while accounting for uncertainty in information reliability? The proposed methodology aims to fill this gap by incorporating Z-number theory and FDEA.Design/methodology/approachThe proposed study assesses residency preferences across 39 European countries, focusing on key factors like environment, sustainability, technology, education, and development, which significantly influence individuals' residency choices. Unlike conventional DEA and FDEA approaches, the proposed method introduces a novel consideration: dependability. This inclusion aims to refine decision-making precision by accounting for uncertainties related to data reliability. The proposed methodology utilizes an interval approach, specifically employing the a-cut approach with interval values in the second step. Unlike using crisp values, this interval programming resolves formulations to determine the efficiencies of decision-making units (DMUs).FindingsThe comprehensive findings provide valuable insights into the distinctive factors of European nations, aiding informed decision-making for residency choices. Malta (75.6%-76.1%-75.8%), Austria (78.2%-78%-76.1%), and the United Kingdom (79.3%-78.4%-77%) stand out with distinct characteristics at levels of a = 0-a = 0.5-a = 1, assuming the independence of variables of the overall evaluation. Individual consideration of each factor reveals various countries as prominent contenders, except for the environmental factor, which remains consistent across countries.Originality/valueTraditional DEA models encounter challenges when dealing with uncertainties and inaccuracies, particularly in the evaluation of large systems. To overcome these limitations, we propose integrating Z-numbers—a powerful mathematical tool for modeling uncertainty—into the conventional DEA process. Our methodology not only assesses the effectiveness of countries across various socio-economic and environmental metrics but also explicitly addresses the inherent uncertainties associated with the data. By doing so, it aims to enhance the precision of decision-making and provide valuable insights for policymakers and stakeholders.