Cluster-robust Standard Errors Research Articles

Relationships between elementary teachers' enjoyment and students' engagement across content areas and among student groups.

We explored associations among teachers' self-reported enjoyment for teaching mathematics, science, and English language arts and their students' self-reported behavioral engagement in each content area, and how these associations varied depending on student sex and socioeconomic status. Participants included 33 fourth-grade teachers and 443 students from 14 schools in the Southwestern United States. Multiple regression models with cluster robust standard errors was used. Models regressed students' content-area engagement on teachers' content-area enjoyment, controlling for students' initial engagement in that content area and other relevant covariates. Teachers' English language arts and mathematics enjoyment were each positively associated with students' engagement in each content area, and an interaction effect was detected in mathematics whereby lower socioeconomic status students with low-mathematics-enjoyment teachers reported lower mathematics engagement. Findings extend recent research highlighting teachers' emotions, and more specifically positive emotions, as factors that can be leveraged to support student learning, as well as provide more nuanced information about the contexts and student groups for whom these processes may be most relevant. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Investigating the Black Birth Experience: A Race-Stratified Analysis of Preterm Birth Risk and Exposure to Metropolitan Statistical Area-Level Police-Related Deaths, US 2018-2019.

Police-related violence may be a source of chronic stress underlying entrenched racial inequities in reproductive health in the USA. Using publicly available data on police-related fatalities, we estimated total and victim race-specific rates of police-related fatalities (deaths per 100,000 population) in 2018-2019 for Metropolitan Statistical Areas (MSA) and counties within MSAs in the USA. Rates were linked to data on live births by maternal MSA and county of residence. We fit adjusted log-Poisson models with generalized estimating equations and cluster-robust standard errors to estimate the relative risk of preterm birth associated with the middle and highest tertiles of police-related fatalities compared to the lowest tertile. We included a test for heterogeneity by maternal race/ethnicity and additionally fit race/ethnicity-stratified models for associations with victim race/ethnicity-specific police-related fatality rates. Fully adjusted models indicated significant adverse associations between police-related fatality rates and relative risk of preterm birth for the total population, non-Hispanic Black, and non-Hispanic White groups separately. Results confirm the role of fatal police violence as a social determinant of population health outcomes and inequities, including preterm birth.

Longitudinal method comparison: modeling polygenic risk for post-traumatic stress disorder over time in individuals of African and European ancestry

Cross-sectional data allow the investigation of how genetics influence health at a single time point, but to understand how the genome impacts phenotype development, one must use repeated measures data. Ignoring the dependency inherent in repeated measures can exacerbate false positives and requires the utilization of methods other than general or generalized linear models. Many methods can accommodate longitudinal data, including the commonly used linear mixed model and generalized estimating equation, as well as the less popular fixed-effects model, cluster-robust standard error adjustment, and aggregate regression. We simulated longitudinal data and applied these five methods alongside naïve linear regression, which ignored the dependency and served as a baseline, to compare their power, false positive rate, estimation accuracy, and precision. The results showed that the naïve linear regression and fixed-effects models incurred high false positive rates when analyzing a predictor that is fixed over time, making them unviable for studying time-invariant genetic effects. The linear mixed models maintained low false positive rates and unbiased estimation. The generalized estimating equation was similar to the former in terms of power and estimation, but it had increased false positives when the sample size was low, as did cluster-robust standard error adjustment. Aggregate regression produced biased estimates when predictor effects varied over time. To show how the method choice affects downstream results, we performed longitudinal analyses in an adolescent cohort of African and European ancestry. We examined how developing post-traumatic stress symptoms were predicted by polygenic risk, traumatic events, exposure to sexual abuse, and income using four approaches—linear mixed models, generalized estimating equations, cluster-robust standard error adjustment, and aggregate regression. While the directions of effect were generally consistent, coefficient magnitudes and statistical significance differed across methods. Our in-depth comparison of longitudinal methods showed that linear mixed models and generalized estimating equations were applicable in most scenarios requiring longitudinal modeling, but no approach produced identical results even if fit to the same data. Since result discrepancies can result from methodological choices, it is crucial that researchers determine their model a priori, refrain from testing multiple approaches to obtain favorable results, and utilize as similar as possible methods when seeking to replicate results.

Drought risk and audit pricing: a mixed-methods study

PurposeClimate change has led to a rise in the frequency, intensity and scope of droughts, posing significant implications for businesses. This study examines the impact of local community drought levels on audit pricing. Additionally, it explores the moderating effects of high-tech industries, auditor busyness and the level of local community concern regarding the drought crisis.Design/methodology/approachThis study employs a mixed-methods approach to rigorously test the research hypotheses. The quantitative phase of the study utilizes a sample of 1,278 firm-year observations from Iran’s capital market. For the analysis of the quantitative data, ordinary least squares regression with clustered robust standard errors is used. Additionally, this research supplements its quantitative findings with qualitative evidence obtained through semi-structured interviews with 19 Iranian audit partners.FindingsThe results suggest that firms operating in provinces facing severe droughts experience notably higher audit fees. Furthermore, the positive relationship between drought and audit fees is weakened when auditors are busy, local community concern regarding the drought crisis is high or the firm operates within high-tech industries. These findings are supported by a range of robustness checks and qualitative evidence gathered from the field.Originality/valueThis research contributes to the growing literature on climate change by examining the influence of local community drought levels on audit pricing within an Iranian context. Additionally, our study sheds light on how high-tech industries, auditor workload and the level of local community concern regarding the drought crisis moderate the relationship between drought and audit fees. Importantly, our study pioneers in providing mixed-methods evidence of the association between drought severity and audit fees.

Syringe reuse among people who inject drugs in rural Appalachian Kentucky

BackgroundPersonal syringe reuse (i.e., reuse of one's own syringes) can place people who inject drugs at increased risk for infectious disease but has received relatively little attention in published literature. The purpose of this study is to identify factors associated with syringe reuse among people who inject drugs in rural Kentucky. MethodsParticipants (n = 238) completed interviewer-administered questionnaires on syringe reuse and demographic, behavioral, and service access characteristics. Unadjusted negative binomial regression with cluster-robust standard errors was used to model the associations with a logged offset for number of injections in the past 30 days. ResultsThe average age of the sample was 35 and 59.7 % were male. Most participants (77.7 %) reused syringes at least once in the past 30 days, using each syringe a median of three times. Reuse was higher among those who were older and reported a higher street price for syringes. Syringe reuse was lower among people who were within walking distance to a syringe service program (SSP) and who obtained most of their syringes from SSPs or pharmacies. ConclusionSyringe reuse among people who inject drugs in rural Kentucky is common. However, these data suggest that increased access to syringes from SSPs and pharmacies, as well as policy-level interventions that reduce street syringe price, might reduce syringe reuse and related harms.

Get advanced or retreat: well-informed board and bank risk-taking

Purpose This paper aims to examine the relationship between board structure and risk-taking, exploring how this association is influenced by advanced technologies in the banking sector. Design/methodology/approach This study uses a panel sample of 22 Pakistani banks from 2011 to 2018. To test the authors’ hypothesis, the authors use regression analysis with two-way cluster robust standard errors. Further, the authors also check the robustness of the authors’ findings using alternate proxies of board structure and bank risk-taking behavior. To address endogeneity concerns, the authors use the two-stage least square technique. Findings In the era of the Fourth Industrial Revolution, Pakistani banks’ digitalization is modeled by the presence of Temenos-T24/Oracle as their core banking system (software providing end-to-end operational integration). Its interactional effect with corporate governance is evaluated to implicate informed risk-taking by the board as a result of improved information access and analysis. The authors find that board size has a positive association with risk-taking, and the use of modern technology reshapes this association in the banking sector. Originality/value The contribution of this paper is twofold. First, the impact of board structure on bank risk-taking has not been extensively researched in Pakistan – a highly volatile and unpredictable economy. Second, the evaluation of the role of technology on bank risk is being researched for the very first time – a uniqueness of this paper.

Dental implant failures in Utah and US veteran cohorts.

Approximately, 5.5 million dental implants are estimated to be surgically placed in the United States yearly, with an anticipated long-term failure rate ranging from 3% to 10%. At the Salt Lake City Dental Clinic within the Department of Veterans Affairs (VHA), specific protocols have been established to mandate that clinicians present every dental implant case for review by a committee. To understand the effectiveness of this approach, a comparative data analysis was undertaken to compare local dental implant failure data against national VHA data. Leveraging electronic health records of veterans spanning from 2000 to 2021, we gathered procedural records related to dental implant placement or failure, demographic information, and medical history for individuals who received dental care at various dental clinics within the nationwide VHA network. Subsequently, statistical analyses were conducted using mixed-effects Poisson regression models with cluster-robust standard errors. Incident rate ratios (IRRs) for Utah-specific and nationwide cohorts were ascertained. The Utah VHA dental clinical data showed that there was a slightly lower prevalence of implant failure at 6.7% compared to the national cohort, which had a rate of 6.9%. The implant level failure rates were also low, with 4.20 (confidence interval [CI]: 3.68, 4.81) per 1000 implant placements per year for Utah cohorts. The adjusted IRR indicated a relative 16% reduction in risk among Utah Veterans (IRR 0.84, 95% CI [0.76-0.92]; p < 0.001). The stringent protocols in place at Salt Lake City, which integrate evidence-based practices and expert opinion for evaluating patient suitability for dental implant placement and subsequent care, contributed to the reduced risk among Utah Dental Clinic veterans pool compared to veterans of other states.

Can mutual fund characteristics predict future performance? Evidence from Portugal

Purpose This paper aims to investigate not only the performance of Portuguese mutual funds investing in domestic and international equities but also which fund characteristics, such as age, size, family size, expense ratios and flows, influence future performance. Design/methodology/approach Fund performance is evaluated over the 2005–2022 period by a robust six-factor model, while the impact of fund characteristics on performance is assessed by a set of fixed-effects panel data regressions with two-way cluster-robust standard errors. Findings The results show that, while funds investing in domestic equities predominantly exhibit neutral performance, most international equity funds have significantly negative alphas. The authors document a negative and statistically significant relationship between fund age and performance for all fund categories. Total expense ratios have an inverse relationship with domestic equity fund performance but do not impact the performance of international equity funds significantly. Though fund flows have a neutral effect on performance across the overall period, they are important determinants of both domestic and international funds’ performance in more recent years. Originality/value The authors contribute to the literature by carrying out a comprehensive analysis, based on recent and robust methodologies, of the impact of mutual fund characteristics on the future performance of Portuguese equity funds. The research findings serve as a premise for advising investors on how to choose the top-performing funds.

Sex-Specific Association of Ambient Temperature With Urine Biomarkers in Southwest Coastal Bangladesh

IntroductionMen are vulnerable to ambient heat-related kidney disease burden, but limited evidence exists on how vulnerable women are when exposed to high ambient heat. We evaluated the sex-specific association between ambient temperature and urine electrolytes (concentration and 24-hour excretion), and 24-hour urine total protein, and volume. MethodsWe pooled a longitudinal data of 1,175 participants' concentration and 24-hour excretion of urine electrolytes and other biomarkers (24-hour urine total protein and volume) (5624 person-visits) collected in southwest coastal Bangladesh (Khulna, Satkhira, and Mongla districts) during November 2016 - April 2017. We then spatiotemporally linked ambient temperature data from local weather stations to participants' health outcomes. For evaluating the relationships between average ambient temperature and urine electrolytes and other biomarkers, we plotted confounder-adjusted restricted cubic spline (RCS) plots using participant-, household-, and community-level random intercepts. We then used piece-wise linear mixed-effects models for different ambient temperature segments determined by inflection points in RCS plots and reported the maximum likelihood estimates and cluster robust standard errors. By applying interaction terms for sex and ambient temperature, we determined the overall significance using the Wald test. Bonferroni correction was used for multiple comparisons. ResultsThe RCS plots demonstrated non-linear associations between ambient heat and urine biomarkers for males and females. Piecewise linear mixed-effects models suggested sex did not modify the relationship of ambient temperature with any of the urine parameters after Bonferroni correction (p-value <0.004). ConclusionOur findings suggest that women are as susceptible to the effects of high ambient temperature exposure as men.

Adolescent Mental Health and Resilience Before and During the COVID-19 Pandemic

PurposeWe aimed to assess levels of depression, anxiety, and resilience factors before and during the COVID-19 pandemic in a school sample of adolescents. We also aimed to examine the compensatory and protective effects of individual, family, and school resilience factors on adolescent mental health. MethodsWe used fall 2019 and fall 2020 survey responses from a cluster randomized controlled trial implemented in 20 schools in a Midwestern county. The sample consisted of 3,085 responses from students in grades 5 and 6. Multilevel mixed-effects models with cluster robust standard errors were used to investigate the associations between exposure to the COVID-19 pandemic, mental health (anxiety, depression), and resilience factors (future orientation, family engagement, and having a caring school adult). ResultsAnxiety, but not depression, was higher in fall 2020 compared to fall 2019. Family engagement increased during the pandemic, while future orientation of the student body was lower during that time and the prevalence of having a caring adult at school was unchanged. A positive future orientation was associated with lower levels of anxiety and depression, while having a caring school adult was associated with lower depression. Adolescents with less positive future orientations, low family engagement, and no caring school adults experienced the greatest increases in anxiety. DiscussionPositive future orientations, family engagement, and supportive nonparental adult relationships had compensatory and protective effects on adolescent mental health during the COVID-19 pandemic. Adding these measures to the inventory of modifiable resilience factors during natural disasters may promote healthy adaptation among adolescents.

The Added Value of MRI-Based Targeted Biopsy in Biopsy-Naïve Patients: A Propensity-Score Matched Comparison.

Multiparametric Magnetic Resonance Imaging (mpMRI)-based targeted biopsy has shown to be beneficial in detecting Clinically Significant Prostate Cancer (csPCa) and avoiding diagnosis of Non-csPCa (ncsPCa); however, its role in the treatment of biopsy-naïve patients is still under discussion. After identifying predictors for the diagnosis of csPCa via Multivariate Logistic Regression Analysis (MLRA), a propensity-score (1:1 nearest neighbor) matched comparison was performed between a Systematic-Only Biopsy (SOB) cohort and a mpMRI-based Combined (systematic + targeted) Biopsy (CB) cohort from two tertiary urologic centers (SOB: Department of Urology, University General Hospital of Heraklion, University of Crete, School of Medicine, Heraklion, Crete, Greece; CB: LKH Hall in Tirol, Austria). Only biopsy-naïve patients were included in the study. The study period for the included patients was from February 2018 to July 2023 for the SOB group and from July 2017 to June 2023 for the CB group. The primary outcome was the diagnosis of csPCa (≥ISUP 2); secondary outcomes were overall cancer detection, the added value of targeted biopsy in csPCa detection, and the reduction in ncsPCa diagnosis with CB compared to SOB. To estimate the Average Treatment effect of the Treated groups (ATT), cluster-robust standard errors were used to perform g-computation in the matched sample. p-values < 0.05 with a two-sided 95% confidence interval were considered statistically significant. Matching achieved well-balanced groups (each n = 140 for CB and SOB). In the CB group, 65/140 (46.4%) patients were diagnosed with csPCa compared to 44/140 (31.4%) in the SOB group (RR 1.48, 95%-CI: 1.09-2.0, p = 0.01). In the CB group, 4.3% (6/140) and 1.4% (2/140) of csPCa cases were detected with targeted-only and systematic-only biopsy cores, respectively. In the CB group, 22/140 (15.7%) patients were diagnosed with ncsPCa compared to 33/140 (23.6%) in the SOB group (RR = 0.67, 95% CI: 0.41-1.08, p = 0.1). When comparing SOB to CB (ATT), the marginal OR was 0.56 (95% CI: 0.38-0.82, p = 0.003) for the diagnosis of csPCa and 0.75 (95% CI: 0.47-1.05, p = 0.085) for the diagnosis of overall cancer (≥ISUP 1). The CB approach was superior to the SOB approach in detecting csPCa, while no additional detection of ncsPCa was seen. Our results support the application of mpMRI for biopsy-naïve patients with suspicions of prostate cancer.

Effect of on-pump vs. off-pump coronary artery bypass grafting in patients with non-dialysis-dependent severe renal impairment: propensity-matched analysis from the UK registry dataset.

On-pump coronary artery bypass (ONCABG) grafting in patients with a pre-existing poor renal reserve is known to carry significant morbidity and mortality. There is limited controversial evidence on the benefit of off-pump coronary artery bypass (OPCABG) grafting in these high-risk groups of patients. We compared early clinical outcomes in propensity-matched cohorts of patients with non-dialysis-dependent pre-operative severe renal impairment undergoing OPCABG vs. ONCABG, captured in a large national registry dataset. All data for patients with a pre-operative creatinine clearance of less than 50 mL/min who underwent elective or urgent isolated OPCABG or ONCABG from 1996 to 2019 were extracted from the UK National Adult Cardiac Surgery Audit (NACSA) database. Propensity score matching was performed using 1:1 nearest neighbor matching without replacement using several baseline characteristics. We investigated the effect of ONCABG vs. OPCABG in the matched cohort using cluster-robust standard error regression. We identified 8,628 patients with severe renal impairment undergoing isolated CABG, of whom 1,142 (13.23%) underwent OPCABG during the study period. We compared 1,141 propensity-matched pairs of patients undergoing OPCABG vs. ONCABG. The median age of the matched population was 78 years in both groups, with no significant imbalance post-matching in the rest of the variables. There was no difference between OPCABG and ONCABG in in-hospital mortality rates, post-operative dialysis, and stroke rates. However, the return to theatre for bleeding or tamponade was higher in ONCABG vs. OPCABG (P > 0.02); however, OPCABG reduced the total length of stay in the hospital by 1 day (P = 0.008). After double adjustment in the matched population using cluster-robust standard regression, ONCABG did not increase mortality compared to OPCABG (OR, 1.05, P = 0.78), postoperative stroke (OR, 1.7, P = 0.12), and dialysis (OR, 0.7, P = 0.09); however, ONCABG was associated with an increased risk of bleeding (OR, 1.53, P = 0.03). In this propensity analysis of a large national registry dataset, we found no difference in early mortality and stroke in patients with pre-operative severe renal impairment undergoing OPCABG or ONCABG surgery; however, ONCABG was associated with an increased risk of return to theatre for bleeding and an increased length of hospital stay.

Evaluating two small-sample corrections for fixed-effects standard errors and inferences in multilevel models with heteroscedastic, unbalanced, clustered data.

Multilevel modeling (MLM) is commonly used in psychological research to model clustered data. However, data in applied research usually violate one of the essential assumptions of MLM-homogeneity of variance. While the fixed-effect estimates produced by the maximum likelihood method remain unbiased, the standard errors for the fixed effects are misestimated, resulting in inaccurate inferences and inflated or deflated type I error rates. To correct the bias in fixed effects standard errors and provide valid inferences, small-sample corrections such as the Kenward-Roger (KR) adjustment and the adjusted cluster-robust standard errors (CR-SEs) with the Satterthwaite approximation for t tests have been used. The current study compares KR with random slope (RS) models and the adjusted CR-SEs with ordinary least squares (OLS), random intercept (RI) and RS models to analyze small, heteroscedastic, clustered data using a Monte Carlo simulation. Results show the KR procedure with RS models has large biases and inflated type I error rates for between-cluster effects in the presence of level 2 heteroscedasticity. In contrast, the adjusted CR-SEs generally yield results with acceptable biases and maintain type I error rates close to the nominal level for all examined models. Thus, when the interest is only in within-cluster effect, any model with the adjusted CR-SEs could be used. However, when the interest is to make accurate inferences of the between-cluster effect, researchers should use the adjusted CR-SEs with RS to have higher power and guard against unmodeled heterogeneity. We reanalyzed an example in Snijders & Bosker (2012) to demonstrate the use of the adjusted CR-SEs with different models.

Social Disconnectedness, Perceived Loneliness, and Cognitive Functioning: The Role of Neighborhood Environment.

Social disconnectedness and loneliness pose significant challenges for older Chinese immigrants. Yet, it remains unclear whether they are associated with an increased risk of cognitive decline in this population. This study aimed to investigate the association of social disconnectedness and loneliness with cognitive functioning and examine the moderation role of neighborhood contexts. This longitudinal analysis examined a sample of individuals aged 60 years and older from the Population Study of Chinese Elderly in Chicago (N = 2,044). Global cognition was assessed using the averaged z-scores of cognitive performance tests. Social disconnectedness was constructed using 5 indicators about structural aspects of social relationships. Loneliness was assessed with the R-UCLA loneliness scale. Neighborhood socioeconomic status (NSES) and neighborhood segregation index were constructed using 2010-2014 American Community Survey data at the census tract level. Individual perceptions about neighborhood environments were used to construct neighborhood cohesion index and neighborhood disorder index (NDI). Latent growth curve models with adjusted cluster robust standard errors were estimated. More loneliness was associated with a higher level of initial cognitive functioning (B = 0.030, p < .01), but also with a faster decline rate over time (B = -0.007, p < .01) after adjusting for covariates. High NSES and less neighborhood segregation buffered the negative effects of loneliness on cognitive decline, respectively. High NDI amplified the positive relationship between loneliness and initial functioning, but accelerated the rate of cognitive decline associated with loneliness. The study revealed that perceived loneliness, but not social disconnectedness, is a risk factor for cognitive decline among older Chinese immigrants. Living in a neighborhood with low socioeconomic status, more segregation, and high disorder elevated the detrimental effect of loneliness on long-term cognitive decline. Further research needs to investigate the complex interplay between social relationships, neighborhood environment, and cognition.

Triglyceride-glucose index's link to cardiovascular outcomes post-percutaneous coronary intervention in China: a meta-analysis.

Percutaneous coronary intervention (PCI) addresses myocardial ischaemia, but a significant subset of patients encounter major adverse cardiovascular events (MACE) post-treatment. This meta-analysis investigated the relationship between the post-PCI triglyceride-glucose (TyG) index and MACE. Comprehensive searches of the Embase, PubMed, Cochrane Library, and Web of Science databases were conducted up to 3 March 2023, using relevant keywords. The effect size was determined based on I2 statistic using random-effects models. Cluster-robust standard errors crafted the dose-response curve, and the GRADE Evaluation Scale was employed to rate the quality of evidence. The group with the highest TyG index had significantly higher post-PCI MACE rates than the lowest index group, with hazard ratios (HRs) of 2.04 (95% CI 1.65-2.52; I2 =77%). Each unit increase in TyG index corresponded to HRs of 1.82 for MACE (95% CI 1.34-2.46; I2 =92%), 2.57 for non-fatal MI (95% CI 1.49-4.41; I2 =63%), and 2.06 for revascularization (95% CI 1.23-3.50; I2 =90%). A linear relationship between TyG index and MACE risk was established (R2 =0.6114). For all-cause mortality, the HR was 1.93 (95% CI 1.35-2.75; I2 =50%), indicating a higher mortality risk with elevated TyG index. The GRADE assessment yielded high certainty for non-fatal MI but low certainty for all-cause mortality, revascularization, and MACE. The TyG index may predict risks of post-PCI MACE, all-cause mortality, non-fatal MI, and revascularization, with varied levels of certainty. A potential linear association between the TyG index and MACE post-PCI was identified. Future research should validate these findings.

The power of institutional investors: empirical evidence on their role in investment in internal audit function

PurposeInstitutional investors are major shareholders in publicly traded firms and play crucial roles in the financial and governance aspects of these firms. Despite their importance, little is known about their role in internal auditing. This study aims to fill this gap by investigating the relationship between institutional investors’ ownership and investment in the internal audit function (IAF).Design/methodology/approachThe study uses ordinary least squares regressions with two-way cluster-robust standard errors (firm and year) to estimate the relationship between institutional investors’ ownership and investment in IAF for Malaysian listed firms between 2009 and 2020.FindingsThe findings show that companies with higher levels of institutional ownership invest more in IAF, suggesting that institutional investors can effectively monitor managers due to their large holdings. Moreover, both transient and dedicated institutional investors are more likely to invest in IAF.Originality/valueThe results highlight the importance of institutional investors as a significant determinant of investment in IAF, which can aid regulators and managers in understanding the institutional investors’ role in governing and optimizing the efficient use of a firm’s resources. The findings also provide insight into institutional investors’ behavior regarding monitoring systems, which may inspire regulators and policymakers to consider increasing institutional investors’ participation to enhance governance structures.

Clinical effectiveness of robotic-assisted compared to open or video-assisted lobectomy in Germany: a real-world data analysis.

Despite robotic-assisted thoracic surgery (RATS) lobectomy being on the rise in Europe, the majority of lobectomies in Germany are still performed with an open or thoracoscopic [video-assisted thoracic surgery (VATS)] approach. Empirical evidence in favour of RATS lobectomy is inconsistent. This retrospective cohort study investigates the impact of RATS lobectomy compared with open thoracic surgery (OPEN) and VATS lobectomy on short-term outcomes in Germany using multicentre real-world data. Anonymized routine data from Germany from 2018 to 2020 were retrospectively analysed. These data were provided by 61 German hospitals. Propensity score matching with subsequent generalized linear models was performed for statistical analysis. Additionally, in order to test the robustness of the results, multivariable regression analyses with cluster-robust standard errors were used. A total of 2498 patients with lobectomy were identified: in 1345 patients OPEN, in 983 VATS and 170 a RATS lobectomy was performed. RATS-compared to OPEN and VATS-reduced length of stay (LOS) by 28% or 4.2 days [confidence interval: 2.9; 5.4] and by 13% or 1.6 days [confidence interval: 0.2; 3.0], respectively. The risk of pneumonia was reduced by 5.3 percentage points in the RATS group compared to both OPEN and VATS (P = 0.07/0.01). RATS-compared to an open approach-reduces the risk of blood transfusions by 8.8 percentage points (P < 0.001) and LOS on the intensive care unit (P < 0.001). This study provides strong support that RATS lobectomy outperforms OPEN or VATS lobectomy in terms of hospital LOS, and short-term in-hospital postoperative complications in the real-world scenario in Germany.

RESIDENTIAL SEGREGATION AND DEPRESSIVE SYMPTOMS IN OLDER CHINESE IMMIGRANTS: MEDIATING ROLE OF SOCIAL PROCESSES

Abstract Older Chinese immigrants are particularly at risk for depression due to acculturative stress and language barriers. Residential segregation with respect to language use may play an important role in mental health of historically marginalized immigrant populations. Previous research provided mixed evidence about the segregation effect among older Latino and Asian immigrants. Guided by a model of social processes, we examined the direct and indirect effects of residential segregation on depressive symptoms via multiple mechanisms of acculturation, discrimination, social network, social support, social strain, and social engagement. Four waves of depressive symptoms were assessed in the Population Study of Chinese Elderly (2011-2019, N=1,970), and linked to the 2010-2014 American Community Survey estimates of neighborhood context. Residential segregation was measured by the Index of Concentrations at the Extremes that simultaneously assesses Chinese and English language use within a given census tract. Latent growth curve models with adjusted cluster robust standard errors were estimated after controlling for individual-level factors. Residents of segregated Chinese-speaking neighborhoods had fewer baseline depressive symptoms but a slower decline rate than those living in segregated toward English-only speaking neighborhoods. Racial discrimination, social strain, and social engagement partially mediated the association between segregation and initial level; social strain and social engagement also partially mediated the association with decline in depressive symptoms. This study demonstrates the importance of residential segregation and social processes in shaping mental well-being among older Chinese immigrants and suggests potential mechanisms to alleviate mental health risks.

An investigation of the influencing factors of value added tax collection effectiveness in EU Member States

AbstractTax evasion is reducing the revenues of public budgets of many European Union (EU) Member States (MS). To improve the effectiveness of tax collection, during the last decade authorities in several MS have taken measures to reduce the value added tax (VAT) gap (i.e., revenue received as a percentage of theoretical liability). In the Central and Eastern European region, VAT gap reduction measures have been implemented effectively in Hungary and Poland, whereas in Romania the effectiveness of these measures is very low: Romania has been the worst-performing EU MS in collecting VAT for more than 10 years. Our study analyses the factors influencing this VAT gap. Our analysis relied mainly on a fixed effects panel regression model, using for a balanced panel an individual and time fixed-effects with cluster-robust standard errors model, and for the unbalanced panel the fixed-effects regression with individual-specific slopes. Our results show that the size of the VAT gap is primarily influenced by five variables: the transparency index, the tax collection ratio, the law enforcement index, the VAT revenues ratio and the digitisation index.

Day care availability and awareness of gendered economic risks: How they shape work and care norms

Family policies not only provide money, time and infrastructure to families, but also convey normative assumptions about what is considered desirable or acceptable in paid work and family care. This study conceptualises and empirically investigates how priming respondents with brief media report-like information on existing day care policy entitlements and economic consequences of maternal employment interruptions may change personal normative judgements about parental work–care arrangements. Furthermore, we analyse whether these effects differ between groups of respondents assumed to vary in their degree of affectedness by the information as well as previous knowledge. The theoretical framework builds on the concept of normative policy feedback effects combined with social norm theory and human cognition theories. The study is based on a fully randomized survey experiment combined with a vignette experiment in Wave 12 of the German Family Panel (pairfam). It applies linear and ordinal logistic regressions with cluster-robust standard errors to a sample of 5,783 respondents. Our results suggest that priming respondents with information on day care policy and long-term economic risks of maternal employment interruptions increases acceptance of intensive day care use across the full sample and especially for mothers with children below school entry age. It further increases support for longer maternal hours spent in paid work among childless women and mothers with school-aged children. Norms regarding paternal working hours are largely unaffected by the information given in this survey experiment.