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Truck-involved crashes cause serious social and economic losses, and the crash severity is higher compared to ordinary vehicles. Driver fatigue is a major crash causation, especially have a larger impact on truck drivers. Therefore, mandating a truck rest-break is one of the road safety management strategies for reducing both truck-involved crash frequency and severity. This paper analyses the change in safety performance according to the revision of the truck rest-break time on highways. Because spatial heterogeneity and homogeneity should be considered to estimate safety effects precisely after executing crash countermeasures, this study estimates the safety effect after the revision of the Trucking Transport Business Act, by developing a model based on the Multilevel Full-Bayes before and after the study. The safety performance function was developed in different section units and distributions, and the crash modification factor was calculated for the most suitable model. As a result of the analysis, the performance of the Multilevel Bayesian Poisson-gamma model was the highest, and it was found that there was a crash reduction effect after the revision of the truck break time. The results of this study can be referred to when preparing measures for road safety regulations. [ABSTRACT FROM AUTHOR]

Contact hypothesis and threat hypothesis are among the most influential theories of xenophobia. The former proposes that intergroup contact may reduce prejudice. The latter suggests that a large outgroup may increase xenophobic attitudes. Using data of a 2018 German representative sample (N = 2,016), we employed multilevel analyses. As predictors, we looked at outgroup size, gross domestic product, and unemployment rate on a county level. On the individual level, we included authoritarianism and a wide range of sociodemographic variables. Individual authoritarianism was identified as the strongest predictor of xenophobic attitudes. On the county level, a higher proportion of migrants was associated with lower values of xenophobia. This serves as an indicator for contact hypothesis. Our results suggest that contextualizing social psychological and micro-sociological theories and employing multilevel analyses are valuable tools to detangle the interplay of individual and contextual influences on xenophobic attitudes. [ABSTRACT FROM AUTHOR]

Multilevel models are often used to account for the hierarchical structure of social data and the inherent dependencies to produce estimates of regression coefficients, variance components associated with each level, and accurate standard errors. Social network analysis is another important approach to analysing complex data that incoproate the social relationships between a number of individuals. Extended linear regression models, such as network autoregressive models, have been proposed that include the social network information to account for the dependencies between persons. In this article, we propose three types of models that account for both the multilevel structure and the social network structure together, leading to network autoregressive multilevel models. We investigate theoretically and empirically, using simulated data and a data set from the Dutch Social Behavior study, the effect of omitting the levels and the social network on the estimates of the regression coefficients, variance components, network autocorrelation parameter, and standard errors. [ABSTRACT FROM AUTHOR]

Considerable interest has been shown in decreasing car use through planning and policy-making efforts. However, little is known about the interactive effects of built environment (BE) and parking policy on car use, and it is unclear whether and how these effects differ across trip purposes. We conducted a web-based survey in Beijing and collected data from 1036 respondents, including 517 male and 519 female respondents. This study estimates the interactive effects of BE and parking policy on car use for home-based work and non-work trips by employing multilevel logit models. The results show that BE variables at trip origins and destinations are important for shaping car use for both home-based work and non-work trips. Specifically, land use mixture (Coeff. = −0.121), bus stop density (Coeff. = −0.006), and population density (Coeff. = −0.009) at residential locations are negative factors affecting car use for work trips, whereas distance to local center (Coeff. = 0.012) and distance to the city center (Coeff. = 0.019) at residential locations are positive factors. Land use mixture (Coeff. = −0.323), bus stop density (Coeff. = −0.008), road density (Coeff. = −0.002), and population density (Coeff. = −0.007) at residential locations are negative factors of car use for non-work trips. Among BE factors at destinations, land use mixture (Coeff. = −0.319), bus stop density (Coeff. = −0.015), road density (Coeff. = −0.008), distance to the local center (Coeff. = −0.018), and population density (Coeff. = −0.012) are negative factors for car use for work trips, whereas the negative factors for non-work trips are land use mix (Coeff. = −0. 218), bus stop density (Coeff. = −0.038), road density (Coeff. = −0.003), distance to the city center (Coeff. = −0.121), and population density (Coeff. = −0.009). The effects of BE variables can be strengthened or weakened by free parking and parking convenience. Moreover, the results identify significant differences in the effects between work and non-work trips. These findings inform planners and policymakers of how to coordinate the BE and parking policies to decrease car dependence. [ABSTRACT FROM AUTHOR]

This article proposes the multilevel model to draw how corporate social responsibility (CSR) can increase pro-environmental behaviors and employs green identity as the mediator based on cognitive consistency theory. This article employs the multilevel model to test the theoretical framework using 400 employees from 100 different workgroups in the clean energy technology businesses of Greater China. The findings revealed that when an employee perceived more individual-level CSR at the initial time (Time 1) would increase more individual-level green self-categorization (GSC), green affective commitment (GAC), and green self-esteem (GSE), which consequently increased pro-environmental behaviors (PBs) at the individual level and work-unit level. This finding suggests that managers not only must build individual-level perceived CSR of employees but must also foster work-unit-level (atmosphere) CSR within a group to increase work-unit-level GI, which consequently can increase PBs. [ABSTRACT FROM AUTHOR]

A variety of factors are associated with the likelihood of reporting guns at school; however, mixed empirical findings hinder our ability to inform policies to reduce school violence. Additionally, many of the established factors are difficult to change over time, and limited attention has been devoted to more malleable factors such as anonymous reporting. To better understand how to improve the likelihood of gun reporting at school, we drew from three waves of survey data from 3,633 students in St. Louis, Missouri. Using a multilevel model, we find that perceived risk of victimization and the availability of anonymous reporting increase the likelihood of gun reporting, while negative peer commitment, self-reported delinquency, and victimization decrease the likelihood of reporting. Additional analyses suggest that independent of known risk factors that inhibit reporting, increases in school climate and improvements in availability of anonymous reporting can increase the likelihood of reporting guns at school. [ABSTRACT FROM AUTHOR]

Despite widespread awareness of risks, significant investments in cybersecurity protection, and substantial economic incentives to avoid security breaches, organizations remain vulnerable to phishing attacks. Phishing research has informed effective practical interventions to address phishing susceptibility that emphasize the importance of broadly applicable IT security knowledge. Yet employees still frequently fall victim to phishing attempts. To help understand why, we conceptualize phishing susceptibility as the failure to differentiate between deceptive and legitimate information processing requests that occur within the context of an employee's typical job responsibilities. We apply this contextual lens to identify characteristics of knowledge workers' organizational task and social context that may enhance or diminish performance in detecting deception in phishing email attempts. To test our hypotheses, we conducted a study in which employees of the finance division of a large university encountered simulated email-based phishing attempts as part of their normal work routine. We found evidence supporting our hypotheses that an individual's susceptibility to phishing attacks is influenced by their position in the knowledge flows of the organization and by the impact of workgroup responsibilities on their cognitive processing. We contend that phishing susceptibility is not merely a matter of IT security knowledge but is also influenced by contextualized, multilevel influences on information processing. As phishing attacks are increasingly targeted to specific organizational settings, it is even more important to incorporate this contextualized information processing view of phishing susceptibility. [ABSTRACT FROM AUTHOR]

Abstract Background Tuberculosis (TB) remains a serious global public health problem in China. The right knowledge, attitude, and practice (KAP) towards TB are indispensable to appropriate healthcare-seeking behaviors and treatment services timely. However, there are few studies that addressed the KAP towards TB in high-risk and under-developing regions in China. This study aims to evaluate the KAP towards TB in Ningxia Northwest, China, and identify factors that influence it. The findings can guide future health education and promotion interventions. Methods A stratified multistage random sampling method was used to conduct a face-to-face questionnaire survey with 33 items for selected residents. The composite score of Knowledge, Attitudes, and Practices (KAP) was divided into two groups, which are poor (scores below the average) and good (scores above the average). A two-level logistic model with a random intercept equation accounted for the similarity of residents within communities to examine the association between individual-level KAP and demographic and socioeconomic factors. Results A total of 2,341 residents were recruited, the mean age was 50, and 41.2% were female. The percentages of residents who were total awareness of TB knowledge and had positive attitudes and behavior toward TB were 51.9%, 75.3%, and 76.2%, respectively. The two-level logistic model demonstrated that residents with a high annual family income, urban living, primary school education or higher, occupation of teacher or doctor, a very good self-perceived status, medical insurance, knowing DOTS, and family members or friends with TB history had better knowledge of TB (P

Abstract The purpose of this study was to investigate the effect of feeding patterns during the first 6 months on weight development of infants ages 0–12 months. Using monitoring data from the Maternal and Child Health Project conducted by the National Center for Women and Children’s Health of the Chinese Center for Disease Control and Prevention from September 2015 to June 2019, we categorized feeding patterns during the first 6 months as exclusive breastfeeding, formula feeding, or mixed feeding. We calculated weight-for-age Z scores (WAZ) according to the World Health Organization’s (WHO) 2006 Child Growth Standard using WHO Anthro version 3.2.2. A multilevel model was used to analyze the effect of feeding patterns during the first 6 months on the WAZ of infants ages 0–12 months in monitoring regions. Length of follow-up (age of infants) was assigned to level 1, and infants was assigned to level 2. Characteristics of infants, mothers, and families and region of the country were adjusted for in the model. The average weight of infants ages 0–12 months in our study (except the birth weights of boys who were formula fed or mixed fed) was greater than the WHO growth standard. After we adjusted for confounding factors, the multilevel model showed that the WAZ of exclusively breastfed and mixed-fed infants were statistically significantly higher than those of formula-fed infants (coefficients = 0.329 and 0.159, respectively; P

Abstract Background HIV Self-Testing (HIVST) holds great significance in the fight against the HIV epidemic in Sub-Saharan Africa (SSA). It offers a convenient and confidential option for individuals to know their HIV status and seek appropriate care and support. For women in this region, where stigma, discrimination, and lack of access to healthcare services are prevalent, HIVST can empower them to take control of their health and make informed decisions. However, no study in the region has been conducted on this topic. Hence, this study aimed to fill the evidence, and population gaps by identifying women’s HIVST knowledge, and utilization, and its associated factors in SSA. Methods The data used were gathered from the most recent demographic and health surveys conducted in SSA nations between 2015 and 2022. We incorporated DHS data from 21 countries into our investigation. For our analysis, we used a weighted sample of 270,241 women overall was utilized. To handle both individual and community level factors, a multilevel logistic regression was used for the analysis. The adjusted odds ratio and its 95% confidence interval were then presented, and variables with univariate multilevel regression p-values of ≤ 0.25 and in multivariable multilevel logistic regression

[Display omitted] • First ecological momentary assessment study to examine emotion dysregulation in OCD. • More avoidance-oriented strategies in OCD vs. healthy controls. • Less positive affect and regulatory effectiveness in OCD vs. healthy controls. • Results remain significant controlling for symptoms, negative affect or depression. • Negative affect is related to more avoidance, less effectiveness, and acceptance. Emotion dysregulation is a central process implicated in the genesis and maintenance of obsessive-compulsive disorder (OCD). However, past research on OCD has examined emotion regulation with a trait-level approach, thereby neglecting important situational and temporal dynamics. The present study is the first one to examine moment-to-moment emotion regulation in individuals with OCD. A 6-day ecological momentary assessment was used to assess affect, emotion regulation strategies, perceived effectiveness of emotion regulation strategies, and acceptance of emotional experiences in n = 72 individuals with OCD and n = 54 psychologically healthy controls. As expected, individuals with OCD reported more negative and less positive affect. Group differences in positive (but not negative) affect did remain significant when controlling for baseline depression. Furthermore, the OCD group reported to use a higher momentary number of avoidance-oriented regulation strategies and less perceived effectiveness of emotion regulation, even when controlling for current symptoms and negative affect or baseline depression scores. Further, irrespective of group, more momentary negative affect amplified use of avoidance-oriented strategies and diminished perceived effectiveness and emotional acceptance. Contrary to expectations, these effects were not more pronounced in the OCD group. Possible explanations for unexpected findings and implications for future research, particularly regarding more holistic emotion regulation treatments, are discussed. [ABSTRACT FROM AUTHOR]

Maintaining order is very important for correctional authorities, as inmate misbehavior threatens the welling-being of correctional officers and other inmates. Therefore, the study aims to explore a more comprehensive model to explain inmate infractions in Taiwan and to enhance our understanding of the nature of inmate misconduct in different contexts. This study uses 1241 male inmates survey data to develop a multilevel model for inmate infraction in Taiwan. This model includes 7 inmate level variables and four prison level variables. It is found that compared to an individual inmate level model, the full model integrating both inmate- and prison-level variables raised the explanatory power from 10.2 to 24.8%. Our findings show that not only the demographic and prisonization effects are important, the relationships among inmates, interactions between inmates and prison staff and between inmates and the outside world also play a role in encouraging conformity behaviors. [ABSTRACT FROM AUTHOR]

Background: Tuberculosis (TB) remains a serious global public health problem in China. The right knowledge, attitude, and practice (KAP) towards TB are indispensable to appropriate healthcare-seeking behaviors and treatment services timely. However, there are few studies that addressed the KAP towards TB in high-risk and under-developing regions in China. This study aims to evaluate the KAP towards TB in Ningxia Northwest, China, and identify factors that influence it. The findings can guide future health education and promotion interventions. Methods: A stratified multistage random sampling method was used to conduct a face-to-face questionnaire survey with 33 items for selected residents. The composite score of Knowledge, Attitudes, and Practices (KAP) was divided into two groups, which are poor (scores below the average) and good (scores above the average). A two-level logistic model with a random intercept equation accounted for the similarity of residents within communities to examine the association between individual-level KAP and demographic and socioeconomic factors. Results: A total of 2,341 residents were recruited, the mean age was 50, and 41.2% were female. The percentages of residents who were total awareness of TB knowledge and had positive attitudes and behavior toward TB were 51.9%, 75.3%, and 76.2%, respectively. The two-level logistic model demonstrated that residents with a high annual family income, urban living, primary school education or higher, occupation of teacher or doctor, a very good self-perceived status, medical insurance, knowing DOTS, and family members or friends with TB history had better knowledge of TB (P < 0.05). Residents living in urban areas, with junior and senior high school education, a very good self-perceived status, health insurance, knowing DOTS, and family members or friends with TB history had positive attitude of TB (P < 0.05). Residents living in urban areas, a primary school education or higher, occupation of teacher, doctor and workers, a very good self-perceived status, medical insurance, knowing DOTS, and family members or friends with TB history had positive practice of TB (P < 0.05). Conclusions: Favorable demographic (higher education levels, teachers or doctors) and socioeconomic (high income, living in urban area) factors are associated to better knowledge, attitudes and practices toward TB in Northwest China. Interventions to improve KAP at the community level are required to speed up the TB reduction rate, which may benefit to ensure the End TB Strategy will be achieved. [ABSTRACT FROM AUTHOR]

The role of street networks in shaping the spatial distribution of crime has become a foundational component within environmental criminology. Most studies, however, have focused on opportunistic crime types, such as property offenses. In this study, we instead research a theoretically distinct phenomenon by examining the placement of venues that host criminal activity. In particular, we study the relationship between network structure and the placement of illicit massage businesses, which operate on the intersections of illicit and legitimate activity by hosting illicit commercial sex under the guise of legitimate massage. We model their placement as a function of two network metrics: betweenness, which measures a street's usage potential, and a variant called "local betweenness," which measures the potential of nearby streets. Multilevel models are used to examine the importance of these street‐level metrics while accounting for tract‐level covariates. Our findings demonstrate that, unlike property crimes, illicit massage businesses tend to be located on streets that are themselves quiet but that are close to areas of high activity. Such locations seem to combine accessibility and discretion, and therefore, represent ideal conditions for such businesses to thrive. Our findings can inform problem‐oriented approaches to prevent the harms associated with illegitimately operating businesses. [ABSTRACT FROM AUTHOR]

Introduction: Income inequality, a pivotal determinant of general and mental health, operates through intricate mechanisms at various geographical scales. While established at country or region levels, the impact of lower-level (municipal or neighborhood) inequality remains inconsistent. This study explores the influence of regional- and municipal-level income inequality on individual psychological distress during the COVID-19 pandemic in Italy, employing a multilevel data analysis. Materials and methods: In a post hoc analysis of data from the first wave of the pandemic (March to April 2020), three hierarchical levels were considered: individual participants, municipalities, and regions. Depressive and anxiety symptoms were measured using the PHQ-9 and GAD-7 scales, while the Gini coefficient gauged income inequality at municipal and regional levels. The analysis incorporated demographic variables as potential confounders. Results: The study encompassed 21 regions, 3,900 municipalities, and 21,477 subjects. Income inequality at both regional and municipal levels exhibited associations with distress scores, suggesting independent effects. Notably, higher distress scores were identified in southern regions with elevated inequality, despite a more substantial COVID-19 impact in the north. Discussion: Findings contribute to existing literature by emphasizing the independent impact of lower-level (municipal) and higher-level (regional) income inequality on population psychopathology. The study supports theories suggesting diverse pathways through which inequality at different levels influences health, such as potential associations with healthcare system dysfunction at the regional level and welfare dysfunction at the municipal level. The observed north-south gradient in distress scores highlights the need for psychosocial interventions to alleviate income inequality, especially in historically disadvantaged southern regions. Future research should explore the nuanced interplay between income inequality and various ecological variables to provide a comprehensive understanding of its health impact. [ABSTRACT FROM AUTHOR]

Research often finds that immigrants tend to have a different profile from locals regarding confidence in the government. Both the origin's and destination's institutional features can influence immigrants' confidence. Scholars have relied on three major models—the cultural‐persistence model, the performance model, and the dual‐reference model—to explain the possible mechanisms behind this difference. Our research builds on previous studies by expanding the country coverage to explore the heterogeneity in immigrants' confidence. Specifically, we focus on how the level of democracy as an institutional factor is associated with immigrants' confidence. Using integrated datasets from the World Value Survey (WVS, 2017–21) and the European Value Study (EVS, 2017–20) and employing a multilevel model, we confirm that immigrants, on average, tend to have a higher level of confidence in the government. However, their confidence is contingent on institutional performance. In countries with high levels of democracy, the disparity in confidence between immigrants and locals becomes more pronounced. Moreover, the institutional performance in the origin country also influences immigrants' confidence in the government of the destination country. Immigrants constantly compare the institutional performance between the two places. Compared to immigrants from countries with a high level of democracy, immigrants from countries with a lower level of democracy tend to have higher confidence in the destination government. Our results provide support for all three major theoretical models. [ABSTRACT FROM AUTHOR]

As an important part of market-based reforms, the issue of "risk" has always been a part of the public–private partnership (PPP) debate, and the way in which risks are managed determines the sustainability of market-based reforms. This study systematically examines how the institutional environment and institutional arrangements affect the effectiveness of PPP risk identification and allocation. The study aims to establish a multi-source database of all publicized PPP projects in 31 provinces during the period of 2017–2021 in China, and it incorporates different levels of influencing factors, such as the institutional environment and institutional arrangements, into a framework. Through the application of a multilevel model, the impact of the political–institutional structure at the provincial level and institutional arrangements at the social capital and project levels on PPP risk identification and allocation is judged hierarchically. It is found that only social capital at the institutional environment level can directly and positively contribute to the effective identification and allocation of PPP risks, while both the degree of potential market competition and the degree of integration at the project level have a positive effect on its risk profile. In addition, there are cross-level moderating effects, with social capital, government transparency, and government–business relations positively improving risk allocation and identification through the degree of market competition, with no significant coordinating effect on the degree of contractual integration. This study goes beyond the existing one-dimensional risk profile analysis and risk typology to dismantle the "black box" of risk identification and allocation, which is a process of continuous negotiation, and to provide a sustainable governance mechanism for the market-oriented reform of public services in the institutional arena. [ABSTRACT FROM AUTHOR]

The purpose of this study was to investigate the effect of feeding patterns during the first 6 months on weight development of infants ages 0–12 months. Using monitoring data from the Maternal and Child Health Project conducted by the National Center for Women and Children's Health of the Chinese Center for Disease Control and Prevention from September 2015 to June 2019, we categorized feeding patterns during the first 6 months as exclusive breastfeeding, formula feeding, or mixed feeding. We calculated weight-for-age Z scores (WAZ) according to the World Health Organization's (WHO) 2006 Child Growth Standard using WHO Anthro version 3.2.2. A multilevel model was used to analyze the effect of feeding patterns during the first 6 months on the WAZ of infants ages 0–12 months in monitoring regions. Length of follow-up (age of infants) was assigned to level 1, and infants was assigned to level 2. Characteristics of infants, mothers, and families and region of the country were adjusted for in the model. The average weight of infants ages 0–12 months in our study (except the birth weights of boys who were formula fed or mixed fed) was greater than the WHO growth standard. After we adjusted for confounding factors, the multilevel model showed that the WAZ of exclusively breastfed and mixed-fed infants were statistically significantly higher than those of formula-fed infants (coefficients = 0.329 and 0.159, respectively; P < 0.05), and there was a negative interaction between feeding patterns and age (both coefficients = − 0.020; P < 0.05). Infants who were exclusively breastfed were heavier than formula-fed infants from birth until 12 months of age. Mixed-fed infants were heavier than formula-fed infants before 8 months, after which the latter overtook the former. Infants' weight development may be influenced by feeding patterns during the first 6 months. Exclusive breastfeeding during the first 6 months may be beneficial for weight development of infants in infancy. [ABSTRACT FROM AUTHOR]

Background: HIV Self-Testing (HIVST) holds great significance in the fight against the HIV epidemic in Sub-Saharan Africa (SSA). It offers a convenient and confidential option for individuals to know their HIV status and seek appropriate care and support. For women in this region, where stigma, discrimination, and lack of access to healthcare services are prevalent, HIVST can empower them to take control of their health and make informed decisions. However, no study in the region has been conducted on this topic. Hence, this study aimed to fill the evidence, and population gaps by identifying women's HIVST knowledge, and utilization, and its associated factors in SSA. Methods: The data used were gathered from the most recent demographic and health surveys conducted in SSA nations between 2015 and 2022. We incorporated DHS data from 21 countries into our investigation. For our analysis, we used a weighted sample of 270,241 women overall was utilized. To handle both individual and community level factors, a multilevel logistic regression was used for the analysis. The adjusted odds ratio and its 95% confidence interval were then presented, and variables with univariate multilevel regression p-values of ≤ 0.25 and in multivariable multilevel logistic regression < 0.05 p value were considered significant factors of HIVST. Results: The overall prevalence of knowledge, and utilization of HIVST among women was about 2.17 (95% CI: 2.12, 2.23) only. Women aged 25–34 years old (AOR = 1.78, 95% CI: 1.65,1.92), and 35–49 years old (AOR = 1.33, 95% CI: 1.22,1.46), primary education(AOR = 1.25, 95%CI: 1.12, 1.38), and secondary/higher education (AOR = 3.08, 95% CI: 2.79, 3.41), poorer (AOR = 1.22, 95% CI: 1.08, 1.38), middle (AOR = 1.19, 95% CI: 1.06, 1.37), richer (AOR = 1.45, 95% CI 1.45, 1.64), and richest (AOR = 1.81, 95% CI: 1.59, 2.05), employed (AOR = 1.73 05% CI: 1.62, 1.85), mass media exposure (AOR = 1.39, 95% CI: 1.31, 1.49), knew modern contraception (AOR = 2.75, 95% CI: 1.84, 4.13), health facility delivery (AOR = 1.17, 95% CI: 1.02, 1.37), being from urban (AOR = 1.53, 95% CI: 1.63, 1.73), divorced or widowed (AOR = 77, 95% CI:1.13, 1.34), have more than one sexual partners (AOR =, 95% CI: 1.24, 1.41), heard about STIs (AOR 7.47 =, 95% CI: 5.16, 10.81), high community ANC coverage (AOR = 1.46, 95% CI: 1.31, 1.63), high community mass media (AOR = 1.37 95% CI: 1.21, 1.56), Central/Southern Africa (AOR = 0.66 95% CI: 0.59,0.74), and East Africa regions (AOR = 0.87 95% CI: 0.81,0.94) were associated with the knowledge and utilization of HIVST. Conclusions: The level of knowledge and utilization of HIVST among women in SSA was very low. To improve this situation, maternal health services can be enhanced. This can be achieved by facilitating institutional delivery, promoting access to modern contraception, increasing ANC coverage, empowering women's associations, creating culturally respectful mass media content, and involving rural and economically disadvantaged women. By implementing these measures, we can enhance women's knowledge and improve their use of HIVST. [ABSTRACT FROM AUTHOR]

Teacher rating scales (TRS) often play a part in service eligibility decisions for gifted services. Although schools regularly use TRS to identify gifted students either as part of an informal nomination process or through behavioral rating scales, there is little research documenting the between-teacher variance in teacher ratings and the consequences of such rater dependence. To evaluate the possible benefits or disadvantages of using TRS as part of a gifted identification process, we examined the student-, teacher-, and school-level variance in TRS, controlling for student ability and achievement to determine the unique information, consistency, and potential bias in TRS. Between 10% and 25% of a students' TRS score can be attributed to the teacher doing the rating, and between-teacher standard deviations represent an effect size of one-third to one-half standard deviation. Our results suggest that TRS are not easily comparable across teachers, making it impossible to set a cut score for admission into a program (or for further screening) that functions equitably across teachers. [ABSTRACT FROM AUTHOR]

Background: Compared to efficacy research, studies investigating the processes of change in psychological therapy are rare, especially for internet-based interventions. While many online therapies are based on face-to-face therapy protocols, it is unknown whether the processes of clinical improvement differ between these treatment formats. Objective: To examine candidate change processes in an online therapist-guided cognitive therapy intervention for social anxiety disorder (iCT-SAD), and compare the results to the corresponding face-to-face therapy (CT-SAD). Methods: Data from a randomised controlled trial (n = 99) were analysed using Multilevel Structural Equation Models, incorporating the temporal precedence of the process variable, and disaggregating the within- and between-subject components of the predictors. These examined three candidate change processes: self-focused attention, negative social cognitions, and depressed mood. Moderated mediation models provided an additional test of the moderating effect of treatment format. Results: Negative social cognitions and self-focused attention were supported as significant mediators of clinical improvement in both CT-SAD and iCT-SAD. Effects were of similar strength and moderated mediation was not observed. There was also evidence of cyclical relationships between social anxiety symptoms and these process variables. Depressed mood also emerged as a significant but weak mediator in CT-SAD, but not in iCT-SAD. Moderated mediation was not observed. Conclusion: The online format of therapy showed a similar pattern of change processes to face-to-face treatment, with self-focused attention and negative social cognitions mediating clinical improvement in both treatments. Efforts to improve the efficacy and efficiency of SAD interventions by targeting these factors may therefore be equally applicable to online and face-to-face interventions.

AbstractThis study explores the connections between aspects of the school environment and emotional problems among boys and girls. The sample comprised 2,120 adolescents aged 17 and 18 years, in 129 school classes from 13 upper secondary schools in Trøndelag county, Norway. The response rate was 79%. The girls reported more emotional problems than the boys. Variations in perceptions of emotional problems between schools and classes is an under-researched topic. Multilevel models revealed a substantial class-level effect regarding emotional problems and a smaller school-level effect. Emotional problems varied between classes because of the class composition (share of boys and girls) and the class context. Contextual factors relevant to emotional problems were peer support, teacher support, and that emotional problems could ‘spread’ in a class. Relations between emotional problems and peer support, teacher support, and parental support were stronger for girls than boys. The study emphasizes the importance of the classroom environment, and it suggests that fostering strong relationships between adolescents and teachers, as well as addressing emotional issues among adolescents, can have a positive impact on emotional well-being. An important topic for future studies is whether the inclusion of the health and life skills theme improves mental health support in schools.

Abstract Exposure and damage caused by noise have been reported in many countries around the world. However, few nationwide studies explored the association of residential environmental noise with depressive symptoms, this study aims to examine this association. The Korean Community Health Survey at the individual-level and the Korean Environmental Noise Measurement Database at the regional-level were used. A total of 30,630 individuals were eligible for the analysis. Multilevel model framework was applied to account for the clustered structure of the regional-level data in which individual-level data containing demographic characteristics and health information were nested. As a result of the analysis, Individuals living in the highest environmental noise area had a 1.55 times higher likelihood of experiencing depressive symptoms than those living in the lowest environmental noise area (95% CI, 1.04–2.31). After stratified analysis according to depressive symptom severity, individuals residing in areas with the highest environmental noise exposure had significantly higher odds of mild (aOR, 1.46; 95% CI, 1.02–2.07) and moderate symptoms (aOR, 1.70; 95% CI, 1.00–2.91). In conclusion, the higher the residential environmental noise, the higher the possibility of mild-to-moderate depressive symptoms. Our findings suggest the need for continued attention to and management of noise pollution, which has the potential to adversely affect individual’s mental health.

Abstract Aims To assess the extent of Coronavirus-related disruption to health and social care treatment and social interactions among people with lived or living experience of substance use in Scotland, and explore potential reasons for variations in disruption. Design Cross sectional mixed methods interview, incorporating a social network ‘egonet interview’ approach asking about whether participants had interactions with a range of substance use, health, social care or third sector organisations, or informal social interactions. Setting Five Alcohol and Drug Partnership Areas in Scotland. Participants 57 (42% women) participants were involved in the study, on average 42 years old. Measurements Five-point Likert scale reporting whether interactions with a range of services and people had gotten much better, better, no different (or no change), worse, or much worse since COVID19 and lockdown. Ratings were nested within participants (Individuals provided multiple ratings) and some ratings were also nested within treatment service (services received multiple ratings). The nested structure was accounted for using cross classified ordinal logistic multilevel models. Findings While the overall average suggested only a slight negative change in interactions (mean rating 2.93), there were substantial variations according to type of interaction, and between individuals. Reported change was more often negative for mental health services (Adjusted OR = 0.93 95% CI 0.17,0.90), and positive for pharmacies (3.03 95% CI 1.36, 5.93). The models found between-participant variation of around 10%, and negligible between-service variation of around 1% in ratings. Ratings didn’t vary by individual age or gender but there was variation between areas. Conclusions Substance use treatment service adaptations due to COVID19 lockdown led to both positive and negative service user experiences. Social network methods provide an effective way to describe complex system-wide interaction patterns, and to measure variations at the individual, service, and area level.

Abstract Background Unequal access to primary healthcare (PHC) has become a critical issue in global health inequalities, requiring governments to implement policies tailored to communities’ needs and abilities. However, the place-based facility dimension of PHCs is oversimplified in current healthcare literature, and formulating the equity-oriented PHC spatial planning remains challenging without understanding the multiple impacts of community socio-spatial dynamics, particularly in remote areas. This study aims to push the boundary of PHC studies one step further by presenting a nuanced and dynamic understanding of the impact of community environments on the uneven primary healthcare supply. Methods Focusing on Shuicheng, a remote rural area in southwestern China, multiple data are included in this village-based study, i.e., the facility-level healthcare statistics data (2016–2019), the statistical yearbooks, WorldPop, and Chinese GDP’s spatial distribution data. We evaluate villages’ PHC service capacity using the number of doctors and essential equipment per capita, which are the major components of China’s PHC delivery. The indicators describing community environments are selected based on extant literature and China’s planning paradigms, including town- and village-level factors. Gini coefficients and local spatial autocorrelation analysis are used to present the divergences of PHC capacity, and multilevel regression model and (heterogeneous) difference in difference model are used to examine the driving role of community environments and the dynamics under the policy intervention. Results Despite the general improvement, PHC inequalities remain significant in remote rural areas. The village’s location, aging, topography, ethnic autonomy, and economic conditions significantly influence village-level PHC capacity, while demographic characteristics and healthcare delivery at the town level are also important. Although it may improve the hardware setting in village clinics (coef. = 0.350), the recent equity-oriented policy attempts may accelerate the loss of rural doctors (coef. = − 0.517). Notably, the associations between PHC and community environments are affected inconsistently by this round of policy intervention. The town healthcare centers with higher inpatient service capacity (coef. = − 0.514) and more licensed doctors (coef. = − 0.587) and nurses (coef. = − 0.344) may indicate more detrimental policy effects that reduced the number of rural doctors, while the centers with more professional equipment (coef. = 0.504) and nurses (coef. = 0.184) are beneficial for the improvement of hardware setting in clinics. Conclusions The findings suggest that the PHC inequalities are increasingly a result of joint social, economic, and institutional forces in recent years, underlining the increased complexity of the PHC resource allocation mechanism. Therefore, we claim the necessity to incorporate a broader understanding of community orientation in PHC delivery, particularly the interdisciplinary knowledge of the spatial lens of community, to support its sustainable development. Our findings also provide timely policy insights for ongoing primary healthcare reform in China.

Abstract Background HIV-tuberculosis (HIV-TB) co-infection is a significant public health concern worldwide. TB delay, consisting of patient delay, diagnostic delay, treatment delay, increases the risk of adverse anti-TB treatment (ATT) outcomes. Except for individual level variables, differences in regional levels have been shown to impact the ATT outcomes. However, few studies appropriately considered possible individual and regional level confounding variables. In this study, we aimed to assess the association of TB delay on treatment outcomes in HIV-TB co-infected patients in Liangshan Yi Autonomous Prefecture (Liangshan Prefecture) of China, using a causal inference framework while taking into account individual and regional level factors. Methods We conducted a study to analyze data from 2068 patients with HIV-TB co-infection in Liangshan Prefecture from 2019 to 2022. To address potential confounding bias, we used a causal directed acyclic graph (DAG) to select appropriate confounding variables. Further, we controlled for these confounders through multilevel propensity score and inverse probability weighting (IPW). Results The successful rate of ATT for patients with HIV-TB co-infection in Liangshan Prefecture was 91.2%. Total delay (OR = 1.411, 95% CI: 1.015, 1.962), diagnostic delay (OR = 1.778, 95% CI: 1.261, 2.508), treatment delay (OR = 1.749, 95% CI: 1.146, 2.668) and health system delay (OR = 1.480 95% CI: (1.035, 2.118) were identified as risk factors for successful ATT outcome. Sensitivity analysis demonstrated the robustness of these findings. Conclusions HIV-TB co-infection prevention and control policy in Liangshan Prefecture should prioritize early treatment for diagnosed HIV-TB co-infected patients. It is urgent to improve the health system in Liangshan Prefecture to reduce delays in diagnosis and treatment.

Exposure and damage caused by noise have been reported in many countries around the world. However, few nationwide studies explored the association of residential environmental noise with depressive symptoms, this study aims to examine this association. The Korean Community Health Survey at the individual-level and the Korean Environmental Noise Measurement Database at the regional-level were used. A total of 30,630 individuals were eligible for the analysis. Multilevel model framework was applied to account for the clustered structure of the regional-level data in which individual-level data containing demographic characteristics and health information were nested. As a result of the analysis, Individuals living in the highest environmental noise area had a 1.55 times higher likelihood of experiencing depressive symptoms than those living in the lowest environmental noise area (95% CI, 1.04–2.31). After stratified analysis according to depressive symptom severity, individuals residing in areas with the highest environmental noise exposure had significantly higher odds of mild (aOR, 1.46; 95% CI, 1.02–2.07) and moderate symptoms (aOR, 1.70; 95% CI, 1.00–2.91). In conclusion, the higher the residential environmental noise, the higher the possibility of mild-to-moderate depressive symptoms. Our findings suggest the need for continued attention to and management of noise pollution, which has the potential to adversely affect individual's mental health. [ABSTRACT FROM AUTHOR]

China has been experiencing below-replacement fertility rates for decades prompting concerns about the rapid aging of the population and a dwindling labour supply. This paper examines the effects of micro-level and macro-level factors on fertility intentions in China from 2010 to 2021. The analyses utilize repeated cross-sectional data from the nationally representative Chinese General Social Survey, focusing on adults of childbearing age. A multilevel logistic regression approach is employed. The findings indicate that economic status, at both the individual and provincial levels, significantly shapes individuals' intentions regarding having two or more children. Those with higher individual economic status are more inclined to have multiple children, while individuals residing in provinces with higher mean incomes are less likely to have two or more children compared to those in provinces with lower mean incomes. Notably, the long-term impact of the one-child policy on intentions to have two or more children is particularly pronounced for urban residents and individuals from provinces that rigorously implemented the one-child policy. Additionally, the study identifies spatial differentiation in fertility intentions. [ABSTRACT FROM AUTHOR]

Aims: To assess the extent of Coronavirus-related disruption to health and social care treatment and social interactions among people with lived or living experience of substance use in Scotland, and explore potential reasons for variations in disruption. Design: Cross sectional mixed methods interview, incorporating a social network 'egonet interview' approach asking about whether participants had interactions with a range of substance use, health, social care or third sector organisations, or informal social interactions. Setting: Five Alcohol and Drug Partnership Areas in Scotland. Participants: 57 (42% women) participants were involved in the study, on average 42 years old. Measurements: Five-point Likert scale reporting whether interactions with a range of services and people had gotten much better, better, no different (or no change), worse, or much worse since COVID19 and lockdown. Ratings were nested within participants (Individuals provided multiple ratings) and some ratings were also nested within treatment service (services received multiple ratings). The nested structure was accounted for using cross classified ordinal logistic multilevel models. Findings: While the overall average suggested only a slight negative change in interactions (mean rating 2.93), there were substantial variations according to type of interaction, and between individuals. Reported change was more often negative for mental health services (Adjusted OR = 0.93 95% CI 0.17,0.90), and positive for pharmacies (3.03 95% CI 1.36, 5.93). The models found between-participant variation of around 10%, and negligible between-service variation of around 1% in ratings. Ratings didn't vary by individual age or gender but there was variation between areas. Conclusions: Substance use treatment service adaptations due to COVID19 lockdown led to both positive and negative service user experiences. Social network methods provide an effective way to describe complex system-wide interaction patterns, and to measure variations at the individual, service, and area level. [ABSTRACT FROM AUTHOR]

This study analyzes factors influencing public support for hosting the Summer Olympics in the Rhine-Ruhr (RR) region in 2036 or 2040. Analyzing data from 14 municipalities, a multilevel model is used to account for individual and contextual factors. Despite a high overall endorsement rate of 67%, the study shows that consumer capital, pride, perception of sustainability, and historical significance significantly influence voting behavior. Surprisingly, structural factors at the municipal level do not show a significant influence. This research provides valuable insights for policymakers and organizers considering future Olympic bids in the RR region. The results emphasize the importance of effective communication to gain public support. This communication should highlight the environmental and economic sustainability of the host community, historical significance, and intangible benefits such as pride. [ABSTRACT FROM AUTHOR]

Objectives: The objective of this study was to model multiple sclerosis (MS) disease progression and compare disease trajectories by sex, age of onset, and year of diagnosis. Study Design and Setting: Longitudinal EDSS scores (20,854 observations) were collected for 1,787 relapse-onset MS patients at MS clinics in South Wales and modelled using a multilevel model (MLM). The MLM adjusted for covariates (sex, age of onset, year of diagnosis, and disease-modifying treatments), and included interactions between baseline covariates and time variables. Results: The optimal model was truncated at 30 years after disease onset and excluded EDSS recorded within 3 months of relapse. As expected, older age of onset was associated with faster disease progression at 15 years (effect size (ES): 0.75; CI: 0.63, 0.86; p: <0.001) and female-sex progressed more slowly at 15 years (ES: −0.43; CI: −0.68, −0.18; p: <0.001). Patients diagnosed more recently (defined as 2007–2011 and >2011) progressed more slowly than those diagnosed historically (<2006); (ES: −0.46; CI: −0.75, −0.16; p: 0.006) and (ES: −0.95; CI: −1.20, −0.70; p: <0.001), respectively. Conclusion: We present a novel model of MS outcomes, accounting for the non-linear trajectory of MS and effects of baseline covariates, validating well-known risk factors (sex and age of onset) associated with disease progression. Also, patients diagnosed more recently progressed more slowly than those diagnosed historically. What Is New: We developed a contemporary multilevel model for multiple sclerosis disease progression with longer follow-up using an ongoing cohort established in 1985 from the same geographical region. We assessed differences in disease trajectory by sex, age of onset, and year of diagnosis; showing that patients diagnosed in earlier years (before 2006) were found to have faster disability progression, while validating results that male-sex and older age of onset progressed faster than female-sex and younger age of onset, respectively. [ABSTRACT FROM AUTHOR]

In American football, a pass rush is an attempt by the defensive team to disrupt the offense and prevent the quarterback (QB) from completing a pass. Existing metrics for assessing pass rush performance are either discrete-time quantities or based on subjective judgment. Using player tracking data, we propose STRAIN, a novel metric for evaluating pass rushers in the National Football League (NFL) at the continuous-time within-play level. Inspired by the concept of strain rate in materials science, STRAIN is a simple and interpretable means for measuring defensive pressure in football. It is a directly observed statistic as a function of two features: the distance between the pass rusher and QB, and the rate at which this distance is being reduced. Our metric possesses great predictability of pressure and stability over time. We also fit a multilevel model for STRAIN to understand the defensive pressure contribution of every pass rusher at the play-level. We apply our approach to NFL data and present results for the first eight weeks of the 2021 regular season. In particular, we provide comparisons of STRAIN for different defensive positions and play outcomes, and rankings of the NFL's best pass rushers according to our metric. [ABSTRACT FROM AUTHOR]

Background: HIV-tuberculosis (HIV-TB) co-infection is a significant public health concern worldwide. TB delay, consisting of patient delay, diagnostic delay, treatment delay, increases the risk of adverse anti-TB treatment (ATT) outcomes. Except for individual level variables, differences in regional levels have been shown to impact the ATT outcomes. However, few studies appropriately considered possible individual and regional level confounding variables. In this study, we aimed to assess the association of TB delay on treatment outcomes in HIV-TB co-infected patients in Liangshan Yi Autonomous Prefecture (Liangshan Prefecture) of China, using a causal inference framework while taking into account individual and regional level factors. Methods: We conducted a study to analyze data from 2068 patients with HIV-TB co-infection in Liangshan Prefecture from 2019 to 2022. To address potential confounding bias, we used a causal directed acyclic graph (DAG) to select appropriate confounding variables. Further, we controlled for these confounders through multilevel propensity score and inverse probability weighting (IPW). Results: The successful rate of ATT for patients with HIV-TB co-infection in Liangshan Prefecture was 91.2%. Total delay (OR = 1.411, 95% CI: 1.015, 1.962), diagnostic delay (OR = 1.778, 95% CI: 1.261, 2.508), treatment delay (OR = 1.749, 95% CI: 1.146, 2.668) and health system delay (OR = 1.480 95% CI: (1.035, 2.118) were identified as risk factors for successful ATT outcome. Sensitivity analysis demonstrated the robustness of these findings. Conclusions: HIV-TB co-infection prevention and control policy in Liangshan Prefecture should prioritize early treatment for diagnosed HIV-TB co-infected patients. It is urgent to improve the health system in Liangshan Prefecture to reduce delays in diagnosis and treatment. [ABSTRACT FROM AUTHOR]

The paper is devoted to the problem of identification of hardening parameters of the developed two-level statistical model of polycrystal inelastic deformation taking into account dynamic recrystallization. First, the approximate values of the hardening parameters are obtained, and then they are refined as a result of formulating and solving the optimization problem using the Nelder–Mead method. The result is the set of the parameters that provides high accuracy of the empirical and calculated data on the stress-strain curves during inelastic deformation of a copper polycrystal. [ABSTRACT FROM AUTHOR]

In this study, a longitudinal regression model for covariance matrix outcomes is introduced. The proposal considers a multilevel generalized linear model for regressing covariance matrices on (time-varying) predictors. This model simultaneously identifies covariate-associated components from covariance matrices, estimates regression coefficients, and captures the within-subject variation in the covariance matrices. Optimal estimators are proposed for both low-dimensional and high-dimensional cases by maximizing the (approximated) hierarchical-likelihood function. These estimators are proved to be asymptotically consistent, where the proposed covariance matrix estimator is the most efficient under the low-dimensional case and achieves the uniformly minimum quadratic loss among all linear combinations of the identity matrix and the sample covariance matrix under the high-dimensional case. Through extensive simulation studies, the proposed approach achieves good performance in identifying the covariate-related components and estimating the model parameters. Applying to a longitudinal resting-state functional magnetic resonance imaging data set from the Alzheimer's Disease (AD) Neuroimaging Initiative, the proposed approach identifies brain networks that demonstrate the difference between males and females at different disease stages. The findings are in line with existing knowledge of AD and the method improves the statistical power over the analysis of cross-sectional data. [ABSTRACT FROM AUTHOR]

Multilevel models with nested errors are widely used in poverty estimation. An important application in this context is estimating the distribution of poverty as defined by the distribution of income within a set of domains that cover the population of interest. Since unit-level values of income are usually heteroskedastic, the standard homoskedasticity assumptions implicit in popular multilevel models may not be appropriate and can lead to bias, particularly when used to estimate domain-specific income distributions. This article addresses this problem when the income values in the population of interest can be characterized by a two-level mixed linear model with independent and identically distributed domain effects and with independent but not identically distributed individual effects. Estimation of poverty indicators that are functionals of domain-level income distributions is also addressed, and a nonparametric bootstrap procedure is used to estimate mean squared errors and confidence intervals. The proposed methodology is compared with the well-known World Bank poverty mapping methodology for this situation, using model-based simulation experiments as well as an empirical study based on Bangladesh poverty data. [ABSTRACT FROM AUTHOR]

Abstract In both clinical and observational studies, sleep quality is usually assessed by subjective self-report. The literature is mixed about how accurately these self-reports track objectively (e.g. via polysomnography) assessed sleep quality, with frequent reports of little to no association. However, previous research on this question focused on between-subject designs, which may be confounded by trait-level variables. In the current study, we used the novel Budapest Sleep, Experiences and Traits Study (BSETS) dataset to investigate if within-subject differences in subjectively reported sleep quality are related to sleep macrostructure and quantitative EEG variables assessed using a mobile EEG headband. We found clear evidence that self-reported sleep quality in the morning is influenced by within-subject variations in sleep onset latency, wake after sleep onset, total sleep time, and sleep efficiency. These effects were replicated if detailed sleep composition metrics (percentage and latency of specific vigilance states) or two alternative measures of subjective sleep quality were used instead. We found no effect of the number of awakenings or relative EEG delta and sigma power. Between-subject effects (relationships between individual mean values of sleep metrics and subjective sleep quality) were also found, highlighting that analyses focusing only on these may be erroneous. Our findings show that while previous investigations of this issue may have been confounded by between-subject effects, objective sleep quality is indeed reflected in subjective sleep ratings.

Abstract In the present study, we recorded the eye movements of 20 criterion-based selected trainee teachers in economics while they responded to 25 single choice (SC) items in an economic content knowledge (CK) test and rated their confidence for each response in a digital assessment. By using a multilevel modeling approach with crossed random effects, we confirmed prior findings from eye-tracking research on SC tests, which showed longer dwell time on the correct response options (attractor) and shorter dwell time on the distractors are positively linked to correct options. Furthermore, we identified an additional effect on dwell time on the attractor in a moderator model with participants who highly rated their confidence for correct response options. Thus, we identified a specific role of students’ confidence in their CK on the gaze bias effect. We interpret these results in terms of students’ actual understanding of test contents from assessments of their professional knowledge and draw implications for further research and teacher education.

Considerable interest has been shown in decreasing car use through planning and policy-making efforts. However, little is known about the interactive effects of built environment (BE) and parking policy on car use, and it is unclear whether and how these effects differ across trip purposes. We conducted a web-based survey in Beijing and collected data from 1036 respondents, including 517 male and 519 female respondents. This study estimates the interactive effects of BE and parking policy on car use for home-based work and non-work trips by employing multilevel logit models. The results show that BE variables at trip origins and destinations are important for shaping car use for both home-based work and non-work trips. Specifically, land use mixture (Coeff. = −0.121), bus stop density (Coeff. = −0.006), and population density (Coeff. = −0.009) at residential locations are negative factors affecting car use for work trips, whereas distance to local center (Coeff. = 0.012) and distance to the city center (Coeff. = 0.019) at residential locations are positive factors. Land use mixture (Coeff. = −0.323), bus stop density (Coeff. = −0.008), road density (Coeff. = −0.002), and population density (Coeff. = −0.007) at residential locations are negative factors of car use for non-work trips. Among BE factors at destinations, land use mixture (Coeff. = −0.319), bus stop density (Coeff. = −0.015), road density (Coeff. = −0.008), distance to the local center (Coeff. = −0.018), and population density (Coeff. = −0.012) are negative factors for car use for work trips, whereas the negative factors for non-work trips are land use mix (Coeff. = −0. 218), bus stop density (Coeff. = −0.038), road density (Coeff. = −0.003), distance to the city center (Coeff. = −0.121), and population density (Coeff. = −0.009). The effects of BE variables can be strengthened or weakened by free parking and parking convenience. Moreover, the results identify significant differences in the effects between work and non-work trips. These findings inform planners and policymakers of how to coordinate the BE and parking policies to decrease car dependence.

AbstractBayesian methods have been said to solve small sample problems in frequentist methods by reflecting prior knowledge in the prior distribution. However, there are dangers in strongly reflecting prior knowledge or situations where much prior knowledge cannot be used. In order to address the issue, in this article, we considered to apply two Bayesian methods, one with weakly informative prior for random effect parameters (BayesW) and another with non-informative prior (BayesN) and compared their performance of parameter recovery with restricted maximum likelihood (REML) method, a frequentist-based estimation method commonly used in multilevel analysis. Specifically, we conducted two simulation studies using a two-level linear multilevel model and compared the performance of the BayesW, the BayesN, and the REML in various conditions that include scenarios of small sample data with a combination of small sample size both at level-1 and level-2. The results showed that the REML performed better than the BayesW, which showed overall better performance than the BayesN, in terms of convergence, bias, and coverage in some small sample scenarios. Therefore, based on the results of the present study, it is recommended to use the REML when adapting the two-level linear multilevel model and analyzing real-world data with small samples. [ABSTRACT FROM AUTHOR]

Virtual consultation has been implemented as a tool to improve the cooperation and coordination between primary care and other specialties. However, in its use in dermatology, inequities have been described. The aim of this study was to identify individual and geographical factors affecting the likelihood of accessing this resource. We conducted a cross-sectional study. The study population was individuals living in Aragón, a region in the north-east of Spain, who were users of the Aragon Health Service in 2021. To explore the differences in individual and area characteristics, between patients with virtual and non-virtual dermatology consultation, we performed bivariate analyses. To analyse the use of virtual consultation in dermatology, a multilevel methodology stratified by sex was developed. We analysed 39,174 dermatology visits, with 16,910 being virtual (43.17%). The rates of virtual consultation were higher in urban areas and the most affluent areas, for older persons, chronic complex patients and people with more advantageous socioeconomic positions. The best multilevel model conducted showed inequalities by socioeconomic position and area of residence. There are individual and area inequalities in the use of teledermatology. As this tool should improve equity of access, teledermatology interventions must address and adapt to the needs of the local patient population. [ABSTRACT FROM AUTHOR]

Tolerance of others on grounds of race, ethnicity, nationality, religion and sexuality is an important component of social capital but has received scant attention in the social capital well-being literature. We examine the components of social capital and their relationship with life satisfaction using data from the Life in Transition Survey in European Union transition countries. A principal component factor analysis identifies three distinct and independent social capital components: tolerance, ties, and trust. Using a multilevel modelling approach, we estimate the relation between these components and life satisfaction, whilst controlling for individual and area effects. Tolerance, ties (networks) and trust are positively associated with life satisfaction. [ABSTRACT FROM AUTHOR]

The privacy calculus assumes that people weigh perceived privacy risks and benefits before disclosing personal information. So far, empirical studies investigated the privacy calculus on a between-person level and, therefore, were not able to make statements about the intrapersonal psychological processes. In the present preregistered online within-person experiment, participants (N = 485) were asked to imagine three different disclosure situations in which privacy risks were indicated by a privacy score. As personality variables, rational and intuitive privacy decision-making styles and privacy resignation were assessed. Results of a within-between random effects model showed that benefit perceptions were positively associated with self-disclosure intentions on between- and within-person levels. The privacy score was found to be effective in supporting users to make more privacy aware choices (within-person level). Finally, the rational decision-making style was positively related to privacy risk perception, while especially intuitive decision-makers can benefit from decision-making aids like the privacy score. [ABSTRACT FROM AUTHOR]

This study examines inequality based on family structure within the school environment, focusing on South Korea's standardized education system. Previous research has pointed to potential challenges associated with a high concentration of students from single-parent families in schools. However, in the context of a standardized education system that aims to minimize variation across schools, these dynamics may manifest in different patterns. Using a nationwide administrative data set, the National Assessment of Educational Achievement, this study finds a significant interaction effect between the proportion of students from single-parent families within schools and the academic achievement, which is particularly pronounced for students from single-parent families. The results suggest that institutional contexts may play a significant role in reducing educational disparities associated with family structure, thereby providing schools pathways to mitigate the academic challenges prevalent among students from diverse family backgrounds. [ABSTRACT FROM AUTHOR]

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Although vacancies in the real estate market have always been of key interest to both private and public stakeholders, measuring the impact of vacancy rates on property prices is challenging. This study attempts to quantify the extent of the influence of vacancy rates on the price decline of commercial properties. The dataset used in this study was collected and collated by valuation experts. We attempt to alleviate the bias inherent in the price estimates provided by the surveyors. A Bayesian multilevel estimation model was employed, and the results revealed that while some experts do not show deviations from the standard tendency of a peer group, others do diverge from this norm. Based on these findings, a bias-controlling price decline rate was derived. As many real estate statistics are produced based on survey data compiled by experts, the approach adopted in this study is expected to be applied to various real estate practices to mitigate the inherent and inevitable surveyor bias. [ABSTRACT FROM AUTHOR]