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A growing number of sport-for-development (SFD) organizations have emerged in the nonprofit sector to leverage sport for social change, yet many organizations struggle with chronic resource deficiencies that inhibit their long-term viability and highlight a pressing need to examine the sustainability of SFD organizations through resource-based perspectives. This study analyzed secondary financial and administrative data from SFD organizations in the United States to examine changes in key resources during early organizational life stages. Latent profile analysis was utilized to classify organizations based on their level of resources, and multilevel growth modeling revealed significant changes in key resources over the first 5 years of operation, as well as significant differences based on initial resource levels and rates of change. The results provide theoretical insight into the key resources associated with organizational sustainability in the SFD field and offer practical implications for resource procurement, prioritization, and management. [ABSTRACT FROM AUTHOR]

The bidirectional relationship between physical health (PH) and depressive symptoms (DS) remains unclear. Data were extracted from the Health and Retirement Study in the United States. PH was measured with a composite of chronic diseases, functional limitations and difficulties in basic and instrumental activities of daily living, and DS with a modified Center for Epidemiological Studies of Depression. Latent growth curve models (LGCM) were employed to examine how the change in PH or DS affected their mutual trajectories in later life. In addition, multilevel models were utilized. There were 6144 participants included, with an average age of 69.82 ± 6.85 years at baseline, of whom 3686 (59.99 %) were women. PH scores increased from 5.65 in 2010 to 7.72 in 2018, while depression scores increased from 1.14 to 1.31. LGCM results showed that the initial levels of PH and DS were associated (β = 0.558, P <.001), and the initial level of PH could predict the trajectory of DS (β = 0.089, P <.001). Likewise, the initial level of DS was also related to initial PH (β = −0.563, P <.001) but couldn't predict the trajectory of PH. Furthermore, the slopes of PH and DS were predicted bidirectionally by each other. Two-level logistic models further demonstrated the bidirectional association between PH and DS. There was a bidirectional association between physical health and depressive symptoms, which highlights the necessity of comprehensive health management for older adults with poor physical health or depression symptoms. • The study examineed the reciprocal association between physical health and depressive symptoms among older adults. • There is a bidirectional relationship between physical health and depressive symptoms. • Highlighting the importance of health management for older adults with poor physical health or depression symptoms. [ABSTRACT FROM AUTHOR]

Objective: Rates of adolescent mood disorders and adolescent smartphone use have risen in parallel, leading some to suggest that smartphone use might have detrimental effects on adolescents' moods. Alternatively, it is possible that adolescents turn to smartphone use when experiencing negative mood. The purpose of this study was to explore the relationship between adolescent smartphone use and mood using a longitudinal methodology that measured both in real-time. Method: This study used an Ecological Momentary Assessment (EMA) procedure completed by 253 12-17-year old participants from across the United States. Participants received short surveys delivered to their smartphones at random points throughout the day. Measures included real-time, in-situ assessments of smartphone use, current mood, and mood before smartphone use. Results: Based on tests of a multilevel regression model, adolescent moods were positively associated with smartphone use (β = 0.261, F(1,259.49) = 19.120, p < 0.001), and that mood was positively associated with the length of phone use sessions (length of phone use β = 0.100, F(1, 112.88) = 5.616, p = 0.020). Participants also reported significant changes in mood during phone use, such that moods before phone use were significantly lower than moods during phone use (MChange= 0.539, t(2491) = 23.174, p < 0.001). Change in mood (mood before minus mood during phone use) was positively associated with the length of smartphone use sessions (β = 0.097, F(1,122.20) = 4.178, p = 0.043), such that participants who had a higher change in mood were more likely to report a longer length of smartphone use. Conclusions: Findings suggest that adolescent smartphone use is positively associated with mood. This finding may suggest that adolescents use smartphones for mood modification, which aligns with an understanding of smartphone use as potentially addictive behavior. [ABSTRACT FROM AUTHOR]

Preventive health care use can reduce the risk of disease, disability, and death. Thus, it is critical to understand factors that shape preventive care use. A growing body of research identifies structural sexism as a driver of population health, but it remains unknown if structural sexism is linked to preventive care use and, if so, whether the relationship differs for women and men. Gender performance and gendered power and resource allocation perspectives lead to competing hypotheses regarding these questions. This study explores the relationship between structural sexism and preventive care in gender-stratified, multilevel models that combine data from the Behavioral Risk Factor Surveillance System with state-level data (N = 425,454). We find that in states with more structural sexism, both men and women were less likely to seek preventive care. These findings support the gender performance hypothesis for men and the gendered power and resource allocation hypothesis for men and women. [ABSTRACT FROM AUTHOR]

Background: With a growing emphasis on value of care, understanding factors associated with rising healthcare costs is increasingly important. In this national study, we evaluated the degree of center-level variation in the cost of spinal fusion. Methods: All adults undergoing elective spinal fusion were identified in the 2016 to 2020 National Inpatient Sample. Multilevel mixed-effect models were used to rank hospitals based on risk-adjusted costs. The interclass coefficient (ICC) was utilized to tabulate the amount of variation attributable to hospital-level characteristics. The association of high cost-hospital (HCH) status with in-hospital mortality, perioperative complications, and overall resource utilization was analyzed. Predictors of increased costs were secondarily explored. Results: An estimated 1,541,740 patients underwent spinal fusion, and HCH performed an average of 9.5% of annual cases. HCH were more likely to be small (36.8 vs 30.5%, p<0.001), rural (10.1 vs 8.8%, p<0.001), and located in the Western geographic region (49.9 vs 16.7%, p<0.001). The ICC demonstrated 32% of variation in cost was attributable to the hospital, independent of patient-level characteristics. Patients who received a spinal fusion at a HCH faced similar odds of mortality (0.74 [0.48–1.15], p = 0.18) and perioperative complications (1.04 [0.93–1.16], p = 0.52), but increased odds of non-home discharge (1.30 [1.17–1.45], p<0.001) and prolonged length of stay (β 0.34 [0.26–0.42] days, p = 0.18). Patient factors such as gender, race, and income quartile significantly impacted costs. Conclusion: The present analysis identified 32% of the observed variation to be attributable to hospital-level characteristics. HCH status was not associated with increased mortality or perioperative complications. [ABSTRACT FROM AUTHOR]

Background and Aims: The two most common interventions used to treat painless jaundice from pancreatic cancer are endoscopic retrograde cholangiopancreatography (ERCP) and percutaneous transhepatic biliary drainage (PTBD). Our study aimed to characterize the geographic distribution of ERCP‐performing hospitals among patients with pancreatic cancer in the United States and the association between geographic accessibility to ERCP‐performing hospitals and biliary interventions patients receive. Methods: This is a retrospective cohort study using the Surveillance, Epidemiology, and End Results (SEER)‐Medicare database for pancreatic cancer from 2005 to 2013. Multilevel models were used to examine the association between accessibility to ERCP hospitals within a 30‐ and 45‐min drive from the patient's residential ZIP Code and the receipt of ERCP treatment. A two‐step floating catchment area model was used to calculate the measure of accessibility based on the distribution across SEER regions. Results: 7464 and 782 patients underwent ERCP and PTBD, respectively, over the study period. There were 808 hospitals in which 8246 patients diagnosed with pancreatic cancer in SEER regions from 2005 to 2013 received a procedure. Patients with high accessibility within both 30‐ and 45‐min drive to an ERCP‐performing hospital were more likely to receive an ERCP (30‐min adjusted odds ratio [aOR]: 1.53, 95% confidence interval [CI]: 1.17–2.01; 45‐min aOR: 1.31, 95% CI: 1.01–1.70). Furthermore, in the adjusted model, Black patients (vs. White) and patients with stage IV disease were less likely to receive ERCP than PTBD. Conclusions: Patients with pancreatic cancer and high accessibility to an ERCP‐performing hospital were more likely to receive ERCP. Disparities in the receipt of ERCP persisted for Black patients regardless of their access to ERCP‐performing hospitals. [ABSTRACT FROM AUTHOR]

In the United States, 21 million adults are diagnosed with depression. Couple therapy effectively treats depression, however, couples encounter access barriers. The Relationship Checkup is an assessment and feedback intervention delivered in participants' homes. The current study examines changes in relationship satisfaction and depressive symptoms, and moderators and mechanisms of change in a community sample (N = 85 couples). Changes in depressive symptoms and satisfaction, and the association between changes in satisfaction and depressive symptoms were examined with multilevel modeling. Depressive symptoms (Cohen's d = 0.36) and satisfaction (d = 1.43) improved from baseline to 1‐month follow‐up, with greater declines in depression (d = 0.44) for those with more severe symptoms. Increases in satisfaction were associated with decreases in depressive symptoms (d = 0.23), and decreases in depressive symptoms were associated with increases in satisfaction (d = 0.33). Individuals with depression and relationship distress may be well served by this intervention. [ABSTRACT FROM AUTHOR]

In the United States, megaregions, which are networks of urban centres and their hinterlands, have a greater prevalence of COVID-19, but have been overlooked as a geographical unit for multi-jurisdictional governance for pandemic response. Existing multi-metropolitan planning organization (MPO) collaborations and state-level COVID-19 coalitions in the United States demonstrate the utility of the megaregion as an effective framework for regional collaboration and operations. Using multilevel modelling, we explore the significance of megaregions in explaining disease occurrence. The results suggest that the megaregion can be an appropriate geographical scale for multi-jurisdictional operations, governance and pandemic response. [ABSTRACT FROM AUTHOR]

Computational thinking (CT) is an essential problem-solving skill that students need to successfully live and work with developing technologies. There is an increasing call in the literature by researchers and policy leaders to integrate CT at the elementary level into core subjects to provide early and equitable access for all students. While some critics may claim the concepts and skills of CT are developmentally advanced for elementary age students, subjects such as science can provide real-world and relevant problems to which foundational CT components can be applied. By assessing how CT concepts and approaches integrate authentically into current science lessons, policymakers, and district leaders can be more intentional in supporting implementation efforts. This research used an exploratory survey design to examine the frequencies of CT concepts (decomposition, algorithms, abstraction, and pattern recognition) and approaches (tinkering, creating, debugging, perseverance, and collaboration) that exist in science in K–5 schools in a northeast state in the United States as reported by elementary science teachers (n = 259). Hierarchical linear modeling was used to analyze the influence of teacher and district factors on the amount of time CT concepts and approaches were integrated in the science lessons. Experience, grade level, confidence, and participation in a research–practice partnership were found to be significant predictors of CT. This study contributes to a better understanding of variables affecting CT teaching frequency that can be leveraged to impact reform efforts supporting CT integration in science. [ABSTRACT FROM AUTHOR]

Recovery housing is an important resource for those in recovery from substance use disorders. Unfortunately, we know little about its relationship to key community health risk and protective factors, potentially limiting the role it could play as a broader health resource. Leveraging county-level data on recovery residences from the National Study of Treatment and Addiction Recovery Residences (NSTARR), this study used multilevel modeling to examine Community COVID Vulnerability Index (CCVI) scores as well as availability of COVID testing and vaccination sites in relation to recovery housing. CCVI composite scores were positively associated with recovery housing availability. Analyses using CCVI thematic sub-scores found that population density and number of churches were positively associated with recovery housing availability, while epidemiological factors and healthcare system factors were negatively associated with recovery housing availability. In counties with recovery housing, there also was a positive association between CCVI and both COVID testing and vaccination availability. Recovery residences tend to be located in areas of high COVID vulnerability, reflecting effective targeting in areas with higher population density, more housing risk factors, and other high-risk environments and signaling a key point of contact to address broader health issues among those in recovery from substance use disorders. [ABSTRACT FROM AUTHOR]

Science achievements of individuals play a crucial role when students aim to pursue highly demanded occupations and advanced academic degrees. Enhancing science attainment is crucial in improving the effectiveness of science education. This study investigates the impact of home educational resources, students' attitudes toward learning, instructional practices and strategies, and school factors on science achievement. This investigation utilizes Trends in International Mathematics and Science Study 2019 eighth‐grade science data from the United States. The technique of hierarchal linear models is employed to find the effects of the multilevel factors on science achievements. Results of fixed effects show that science achievement is primarily affected by home educational resources, attitude toward learning, and school composition by student background. Of the four attitudinal predictors, students' confidence in science is most correlated to their achievements. Home educational resources, students like learning science, and self‐efficacy for computer use predictors, have significant random effects on science achievement. This study finds that ensuring adequate resources and employing appropriate instructional methodologies to reinforce students' motivation in learning are two major priorities in improving science achievement. The limitations of this research and suggestions for future work are also discussed. [ABSTRACT FROM AUTHOR]

Research has shown that students in the United States have been developing negative perceptions of science as a field of study, which is associated with low science identity. The science identity can be influenced by a variety of personal demographic predictors, non-cognitive science-related variables (e.g. science self-efficacy and science interest), and contextual predictors (e.g. school locale and geographical location). The current study explored the variability in the effect of student-level factors (i.e. gender, SES, ethnicity, science self-efficacy, science utility, and science interest) and school-level factors (i.e. school type, locale, and geographical location) on ninth-grade students' science identity. Data on 16,216 ninth-grade students in the United States were obtained from a large-scale national database, the High School Longitudinal Study of 2009. Three models were tested using Hierarchical Linear Modeling. The findings showed that student-level factors accounted for a significant amount (36%) of the variability in students' science identity and a much smaller amount (< 5%) of the variability in identity was due to the variation between schools. Students' science identity was bolstered by a higher level of science self-efficacy, utility, interest, and socioeconomic status. Females, African Americans, and Hispanics had lower levels of science identity. Science identity was lower among students in rural schools and town schools compared with students in city schools and higher among students in private schools compared with students in public schools. Students in the Northeast and South had higher science identity compared to students in the West. Establishing valuable contributions in the STEM field is strengthened when students hold constructive science identities. The current study found that various individual and contextual variables formulate students' science identities. These influences are salient in rural and town public schools with poor SES status. [ABSTRACT FROM AUTHOR]

We applied a structural intersectionality approach to cross-sectionally examine the relationships between macro-level systems of oppression, their intersections, and access to oral care in the United States. Whether and the extent to which the provision of government-funded dental services attenuates the emerging patterns of associations was also assessed in the study. To accomplish these objectives, individual-level information from over 300,000 respondents of the 2010 US Behavioral Risk Factor Surveillance System was linked with state-level data for 2000 and 2010 on structural racism, structural sexism, and income inequality, as provided by Homan et al. Using multilevel models, we investigated the relationships between systems of oppression and restricted access to oral health services among respondents at the intersections of race, gender, and poverty. The degree to which extended provision of government-funded dental services weakens the observed associations was determined in models stratified by state-level coverage of oral care. Our analyses bring to the fore intersectional groups (e.g., non-Hispanic Black women and men below the poverty line) with the highest odds of not seeing a dentist in the previous year. We also show that residing in states where high levels of structural sexism and income inequality intersect was associated with 1.3 greater odds (95% confidence interval, 1.1–1.5) of not accessing dental services in the 12 mo preceding the survey. Stratified analyses demonstrated that a more extensive provision of government-funded dental services attenuates associations between structural oppressions and restricted access to oral health care. On the basis of these and other findings, we urge researchers and health care planners to increase access to dental services in more effective and inclusive ways. Most important, we show that counteracting structural drivers of inequities in dental services access entails providing dental care for all. [ABSTRACT FROM AUTHOR]

According to the parasite-stress theory, collectivism serves as a trait of ingroup assortative sociality, providing defense against infectious diseases. This study investigated the association between cultural collectivism and COVID-19 severity at the state (Study 1: N = 51), county (Study 2: N = 3,133), and daily (Study 3: N = 52,806) levels from the beginning of 2020 to the end of 2022. State-level collectivism was assessed using two distinct measures: the U.S. collectivism index, focusing on social interconnectedness and interdependence, and the subjective-culture individualism-collectivism index (reversed), capturing attitudes and beliefs related to religion, abortion, and same-sex marriage. By employing random-intercept multilevel models, the results demonstrated significant and negative effects of state-level collectivism, as measured by the U.S collectivism index, on COVID-19 cases per million, COVID-19 deaths per million, and composite COVID-19 severity index, after controlling for confounding factors, such as socioeconomic development, ecological threats, disease protective behaviors, cultural norms, and political influences. A mini meta-analysis (Study 4: N = 9) confirmed the significance of these effects across studies. These findings supported the proactive role of collectivism in defending against the novel coronavirus in the United States, aligning with the parasite-stress theory of sociality. However, the subjective-culture individualism-collectivism index (reversed) did not exhibit a significant relationship with COVID-19 severity when confounding factors were considered. The high correlation between the subjective-culture individualism-collectivism index (reversed) and the controlled variables suggested shared variance that could diminish its impact on COVID-19 outcomes. Accordingly, the present findings underscore the significance of accounting for confounding factors when examining the association between collectivism and COVID-19 severity at population level. By considering relevant confounding factors, researchers could gain a comprehensive understanding of the complex interplay between cultural collectivism and its influence on COVID-19 severity. Overall, this research contributes to our understanding of how cultural collectivism shapes the COVID-19 pandemic in the United States, emphasizing the importance of adjusting for confounding effects in population level studies. [ABSTRACT FROM AUTHOR]

The United States combine high rates of firearm homicides with high gun prevalence. In the past, a significant positive association was found between the two. This study revisits the gun prevalence-gun homicide debate using more elaborate estimates of gun ownership for the 50 States. Longitudinal data (1999–2016) were analysed with Bayesian multilevel Gamma-Poisson models. The results demonstrated a very small positive association that diminished after adjusting for crime rates. Findings suggest that the association either attenuated in more recent years, or previous studies had overestimated this association. [ABSTRACT FROM AUTHOR]

Although police decision making and behavior always face intense public scrutiny, officers' criminal lifestyles have largely been ignored in national debates and discussions. The primary focus of this study was to understand factors that predicted police criminality. To achieve this objective, we analyzed a nationally representative dataset on officers who were arrested from 2005 to 2011 using advanced statistical approaches. Results obtained using multilevel modeling demonstrate the predictive effects of officer and agency characteristics in explaining police criminality. Specifically, findings reveal differences in types of crimes committed by the officers. For example, male officers engage in crimes that are entirely different from those committed by their female counterparts. Likewise, on-duty officers tend to criminally behave differently from their off-duty counterparts. Furthermore, agency-level factors such as type of agency, number of sworn officers, and location of the agency predict police crime. Current findings highlight the importance of policies that would directly address criminality in law enforcement. [ABSTRACT FROM AUTHOR]

Negative perceptions of aging and older adulthood, including the idealization of youth, are common in the United States. Past work has found that holding negative perceptions of aging is closely associated with poor mental and physical health consequences, yet few studies have examined how these perceptions impact day-to-day experiences. The current study had two objectives: (1) investigate whether age discrepancy (specifically desiring to be younger than one's chronological age) was related to daily negative affect and (2) examine whether this relationship changed as participants aged over time. We utilized the Midlife in the United States (MIDUS) diary study, a longitudinal measurement burst study with three waves of 8-day daily diaries indexing approximately 20 years. Participants (N = 2398; Mage [baseline] = 46.85, SD = 12.24; 54.7% women; 92.4% White) reported their desired age as well as daily negative affect at each wave. Using multilevel modeling, we examined whether age discrepancy predicted daily negative affect across 3 waves of observation. Results supported a significant relationship between age discrepancy and daily negative affect. However, no interactions among age discrepancy and baseline age or time across study were found. This suggests that the relationship between age discrepancy and daily negative affect was consistent across waves and participants over a 20-year period and provides evidence for the pernicious effect of deidentifying with one's real age on daily life. Daily experiences can act as potential risk or protective factors and shape developmental trajectories. Reducing ageism through societal interventions or increasing personal acceptance of aging through targeted interventions are two potential pathways of promoting health and well-being across the lifespan. [ABSTRACT FROM AUTHOR]

Small businesses have suffered disproportionately from the COVID-19 pandemic. We use near-real-time weekly data from the Small Business Pulse Survey (April 26, 2020 - June 17, 2021) to examine the constantly changing impact of COVID-19 on small businesses across the United States. A set of multilevel models for change are adopted to model the trajectories of the various kinds of impact as perceived by business owners (subjective) and those recorded for business operations (objective), providing insights into regional resilience from a small business perspective. The findings reveal spatially uneven and varied trajectories in both the subjectively and the objectively assessed impact of COVID-19 across the U.S., and the different responses to the pandemic shock can be explained by evolving health situations and public policies, as well as by the economic structure and degree of socioeconomic vulnerability in different areas. This study contributes to scholarship on small businesses and regional resilience, as well as identifying policies and practices that build economic resilience and regional development under conditions of global pandemic disruption. [ABSTRACT FROM AUTHOR]

Introduction: It is assumed that age-related increases in loss (e.g., health decline) motivate behavioral changes (e.g., prevention of health decline) across adulthood. This assumption has rarely been directly tested in empirical research, and the current study seeks to fill this gap. Methods: By performing random intercept cross-lagged panel model and multilevel modeling analyses on a three-wave longitudinal dataset from the Midlife in the United States survey (N = 7,108; 51.6% female; between 20 and 75 years at T1), we examined the between-person and the within-person associations between subjective health and engagement in physical activity. Chronic conditions, difficulty in performing daily activities, and demographic variables were controlled for. Results: At the between-person level, subjective (i.e., self-rated) health was positively associated with physical activity in the whole sample and the older subgroup (T1 age >55 years), but not in the younger subgroup (T1 age <35 years). At the within-person level, the association between subjective health and subsequent physical activity was negative in the whole sample and the older subgroup, but nonsignificant (between T1 and T2) or positive (between T2 and T3) in the younger subgroup. Discussion: This study revealed various associations between subjective health and engagement in physical activity across levels (the within- vs. between-person level) and across age groups (younger vs. older group). The finding contributes to a better understanding of people's health behavior in reaction to health decline at different ages. It also supports the proposition that age-related intraindividual increases in losses (e.g., health decline) motivate behaviors that counteract such losses (e.g., physical activity that protects health). [ABSTRACT FROM AUTHOR]

Understanding science allows students with and without developmental and behavioral‐based (DB) disabilities to better appreciate the world around them as well as prepare them for the growing science‐related job market. However, students in the United States consistently underperform on science achievement tests compared to students from other nations. This underperformance could be attributed, in part to science having many specialized vocabulary terms that are not often taught explicitly, leaving students with incomplete or inaccurate understandings of word meanings. Improving science vocabulary instructional practices may support students with and without DB disabilities in enhancing their science achievement. To address this need, researchers implemented multicomponent multimedia professional development (PD) to support middle‐school science teachers in delivering high‐quality vocabulary instruction in inclusive settings. In this paper, data collected from a study evaluating the efficacy of the PD were analyzed to determine the influence on student outcomes using ANOVA and multilevel modeling methodologies. Though initial results indicate a promising impact on teacher instructional practices, little is known whether teacher participation in the PD affected student science vocabulary and content knowledge growth. Using multilevel modeling, student science knowledge growth was evaluated following their teachers' exposure to the PD. The findings from this study indicate having indirect exposure to PD had a positive effect on science content knowledge for students with and without DB disabilities (N = 980). In addition, the authors found students with DB disabilities whose teachers had access to PD showed a larger gain in science knowledge than general education students whose teachers did not have access to the PD. [ABSTRACT FROM AUTHOR]

This study examines how teachers' unions differently affect teacher attrition by gender, relying on nationally representative, district–teacher matched data from the United States. To identify union effects, the article employs a multilevel linear model and exploits natural experiments. Results find that teachers' unions reduce teacher attrition and that the union effects greatly differ by teacher gender and teaching subject. The study also finds that the changes in legal institutions restricting the collective bargaining of teachers significantly raise teacher attrition, especially in science, technology, engineering, and mathematics (STEM) subjects. HIGHLIGHTS Teachers' unions help districts deal with teacher shortage problems by reducing attrition of their teachers. Union effects are greater for men STEM teachers than for non-STEM men teachers; the pattern is the opposite for women teachers. Because teaching is dominated by women, districts with higher union membership may imply more room for women's voices. Legal changes that undermine teachers' unions are likely to result in deteriorating employment conditions and, ultimately, poor educational outcomes. [ABSTRACT FROM AUTHOR]

National data on bronchoscopy for the evaluation of acute respiratory failure are lacking, and the limited available data suggest wide variation in use. How commonly is bronchoscopy performed among hospitalizations with acute respiratory failure? How has use changed over time and across hospitals? This was an observational cohort study of adult hospitalizations (2012-2018) treated with invasive mechanical ventilation (IMV) using the National Inpatient Sample, which represents 97% of all hospitalizations in the United States. We measured the proportion of hospitalizations treated with IMV who underwent bronchoscopy and assessed trends in bronchoscopy use over time. Multilevel linear regression models were used to quantify hospital-level variation, adjusting for differences in patient and hospital characteristics. We identified 6,101,070 IMV-treated hospitalizations (2012-2018), of whom 609,405 underwent bronchoscopy; among hospitalizations receiving bronchoscopy, mean age was 61 years, 41.8% were women, and in-hospital mortality was 30.8%. The percentage of IMV-treated hospitalizations receiving bronchoscopy increased from 9.5% (95% CI, 9.1%-9.9%) in 2012 to 10.8% (95% CI, 10.4%-11.2%) in 2018 (P <.001 for difference). In 2018, bronchoscopy use varied from 0% to 57.1% among 1,787 hospitals, and in multilevel models adjusted for patient and hospital characteristics, 16.0% of the variation was explained at the hospital level. The median OR was 2.13 (95% CI, 2.05-2.21), indicating 113% increased odds of receiving bronchoscopy if moving from a lower-use to a higher-use hospital. Bronchoscopy use among hospitalizations treated with IMV has increased over time. The large variation in use of bronchoscopy across hospitals suggests potentially unwarranted practice variation and need for further studies to clarify which patients benefit from bronchoscopy. [ABSTRACT FROM AUTHOR]

Workforces are aging rapidly and older workers are typically assumed to take more sickness absence. However, the relationship between age and sickness absence is not well understood, as research has yielded mixed findings and has neglected broader societal factors that cascade to shape the age‐sickness absence relationship. To advance the literature, we adopted a resource‐based perspective and investigated the relationship between employee age and sickness absence as mediated by two countervailing mechanisms: physical health issues and work engagement. We also highlighted two country‐level boundary conditions (health expenditure per capita and labor force participation rate) for these mechanisms. We tested our hypotheses with two archival datasets. In Study 1, using a sample of 28,553 employees from 35 European countries, we tested a multilevel model and found that age was positively related to the number of physical health issues, which in turn was positively associated with sickness absence. Country‐level health expenditure per capita was found to mitigate this relationship. We also found that age was positively related to work engagement, which was negatively related to sickness absence, and country‐level labor force participation rate strengthened this relationship. In Study 2, using a multi‐wave dataset (N = 304) from the Health and Retirement Study (HRS) in the United States, we found further support for the two hypothesized mechanisms (physical health issues and work engagement) between age and sickness absence. Our findings have cross‐national implications for understanding and managing sickness absence by helping workers stay healthier and be more engaged in the context of population aging. [ABSTRACT FROM AUTHOR]

There are at least two sources of health insurance coverage estimates in the United States: the Behavioral Risk Factor Surveillance System (BRFSS) and the Small Area Health Insurance Estimates (SAHIE) program. This paper addresses the integration of BRFSS and SAHIE data using multilevel models that account for the different levels of aggregation at which data are available and for the different errors to which data are subject to. The uncertainty in the initial state-level estimates available from BRFSS and SAHIE is improved by borrowing information from both sources and across geographies. County-level model estimates are produced on both BRFSS and SAHIE scales, improving the usability of the BRFSS public-use data and inspiring possible extensions to estimation of BRFSS quantities other than health insurance coverage. The application uses 2018 public-use data. Parallels to small area estimation models and measurement error models are briefly discussed. [ABSTRACT FROM AUTHOR]

Background: Comparison between cross‐national job‐exposure matrices (JEMs) may provide indications of their reliability, particularly if created using the same items. This study evaluated concordance between two JEMs created from United States (US) and Italian O*NET data, using job codes linked through international job codes. Methods: Twenty‐one physical exposures were obtained from the US and Italian O*NET databases. Italian O*NET items were direct translations of US O*NET items. Six hundred and eighty‐four US and 586 Italian job codes were linked via crosswalks to 281 ISCO‐08 job codes. A sensitivity study also assessed concordance on 258 jobs matched one‐to‐one across the two national job classifications. Concordance of US and Italian O*NET exposures was estimated by intraclass correlation coefficients (ICC) in multilevel models adjusted and not adjusted for country. Results: ICCs showed moderate to poor agreement for all physical exposures in jobs linked through ISCO‐08 codes. There was good to moderate agreement for 14 out of 21 exposures in models with one‐to‐one matched jobs between countries; greater agreement was found in all models adjusted for country. Exposure to whole‐body vibration, time standing, and working outdoor exposed to weather showed the highest agreement. Conclusions: These results showed moderate to good agreement for most physical exposures across the two JEMs when US and Italian jobs were matched one‐to‐one and the analysis was adjusted for country. Job code assignments through crosswalks and differences in exposure levels between countries might greatly influence the observed cross‐country agreement. Future multinational epidemiological studies should consider the quality of the cross‐national job matching, and potential cross‐national differences in exposure levels. [ABSTRACT FROM AUTHOR]

Background: We tested if fatigue in incident Peritoneal Dialysis associated with an increased risk for mortality, independently from main confounders. Methods: We conducted a side-by-side study from two of incident PD patients in Brazil and the United States. We used the same code to independently analyze data in both countries during 2004 to 2011. We included data from adults who completed KDQOL-SF vitality subscale within 90 days after starting PD. Vitality score was categorized in four groups: >50 (high vitality), ≥40 to ≤50 (moderate vitality), >35 to <40 (moderate fatigue), ≤35 (high fatigue; reference group). In each country's cohort, we built four distinct models to estimate the associations between vitality (exposure) and all-cause mortality (outcome): (i) Cox regression model; (ii) competing risk model accounting for technique failure events; (iii) multilevel survival model of clinic-level clusters; (iv) multivariate regression model with smoothing splines treating vitality as a continuous measure. Analyses were adjusted for age, comorbidities, PD modality, hemoglobin, and albumin. A mixed-effects meta-analysis was used to pool hazard ratios (HRs) from both cohorts to model mortality risk for each 10-unit increase in vitality. Results: We used data from 4,285 PD patients (Brazil n = 1,388 and United States n = 2,897). Model estimates showed lower vitality levels within 90 days of starting PD were associated with a higher risk of mortality, which was consistent in Brazil and the United States cohorts. In the multivariate survival model, each 10-unit increase in vitality score was associated with lower risk of all-cause mortality in both cohorts (Brazil HR = 0.79 [95%CI 0.70 to 0.90] and United States HR = 0.90 [95%CI 0.88 to 0.93], pooled HR = 0.86 [95%CI 0.75 to 0.98]). Results for all models provided consistent effect estimates. Conclusions: Among patients in Brazil and the United States, lower vitality score in the initial months of PD was independently associated with all-cause mortality. [ABSTRACT FROM AUTHOR]

Scholars interested in understanding the unequal exposure to environmental harms by race and class have often relied on urban sociological theory. Specifically, the argument that the outmigration of middle-class Whites and African Americans from America's industrial areas, and the decline in manufacturing employment in these communities, concentrated minority poverty around industrial sites. These nested, community-level, processes have not yet been measured as such in the environmental inequality literature. This article addresses this limitation by using spatial measures of poverty segregation between and within racial groups. Multilevel models are presented that examine how the density of industrial facilities is related to the economic health of a host tract, the broader economic context of the county, and the level of poverty segregation (both within and between racial/ethnic groups). Results demonstrate a spatial separation of the economic benefits and environmental harms across the United States, a pattern that has remained consistent over time. [ABSTRACT FROM AUTHOR]

For decades, the governance regimes of the United States and many other nations have increasingly devolved authority from central federal governments to substantially weaker state and local governments and even private industry. This trend produces uneven results for affected spaces and modes of governance. At the same time, industries have been re‐regulated under neoliberalization to maximize corporate profitability. Conterminous to the trend of neoliberal deregulation is the global energy transition. The U.S. energy system has shifted away from coal toward natural gas and has become the world's top producer of hydrocarbons due to the widespread deployment of drilling techniques that allow access to unconventional resources. We evaluate the ways that neoliberal governance structures can create uneven socio‐economic impacts from oil and gas development across U.S. states using a multi‐level modeling framework with random slopes and cross‐level interactions. We utilize a multi‐level state and county data set that covers 2000–2016 to examine different outcomes across scales and places. We find evidence that state political economies—reflected in the ideological composition of state legislatures as well as the political spending of the energy sector—condition the effects of oil and gas development on well‐being. These findings are discussed in reference to theories of neoliberalism, growth machine politics, energy boomtowns, and natural resource‐dependent communities. [ABSTRACT FROM AUTHOR]

Protest is the result of complex multilevel processes. It is triggered by contextual factors such as political opportunities or events, it depends on organizations' mobilizing capacity as well as on the type of people who protest, and it is shaped by the characteristics of the populations they come from. To effectively study the antecedents that operate at various levels, social movement research needs to integrate data from multiple analytical levels and systematically examine the relationships across the various levels. While large N statistical techniques of multilevel modelling are well understood, less is known about applying multilevel analysis research examining small number of cases. The article develops conceptual and methodological tools for multilevel analysis of protests in studies with a small number of cases. First, it demonstrates the empirical requirements associated with analyzing three types of multilevel effects: contextual effects, composition effects, and cross-level interactions. Next, specific multilevel small N designs that can be used to examine the three multilevel effects are presented. The last section uses the multilevel approach to examine the demobilization of anti-Iraq War protests in the United States. [ABSTRACT FROM AUTHOR]

Background: Active learning used in science, technology, engineering, and mathematics (STEM) courses has been shown to improve student outcomes. Nevertheless, traditional lecture-orientated approaches endure in these courses. The implementation of teaching practices is a result of many interrelated factors including disciplinary norms, classroom context, and beliefs about learning. Although factors influencing uptake of active learning are known, no study to date has had the statistical power to empirically test the relative association of these factors with active learning when considered collectively. Prior studies have been limited to a single or small number of evaluated factors; in addition, such studies did not capture the nested nature of institutional contexts. We present the results of a multi-institution, large-scale (N = 2382 instructors; N = 1405 departments; N = 749 institutions) survey-based study in the United States to evaluate 17 malleable factors (i.e., influenceable and changeable) that are associated with the amount of time an instructor spends lecturing, a proxy for implementation of active learning strategies, in introductory postsecondary chemistry, mathematics, and physics courses. Results: Regression analyses, using multilevel modeling to account for the nested nature of the data, indicate several evaluated contextual factors, personal factors, and teacher thinking factors were significantly associated with percent of class time lecturing when controlling for other factors used in this study. Quantitative results corroborate prior research in indicating that large class sizes are associated with increased percent time lecturing. Other contextual factors (e.g., classroom setup for small group work) and personal contexts (e.g., participation in scholarship of teaching and learning activities) are associated with a decrease in percent time lecturing. Conclusions: Given the malleable nature of the factors, we offer tangible implications for instructors and administrators to influence the adoption of more active learning strategies in introductory STEM courses. [ABSTRACT FROM AUTHOR]

• Used eight U.S. national travel surveys to construct a panel data that covers a continuous range of ages. • Analyzed the trend of daily vehicle miles traveled (VMT) by an average person from each generation and its subgroups. • Baby Boomers, Generation X, and Millennials shared a three-phased trending pattern of VMT over the life course. • Millennials have kept their daily VMT consistently lower than that of Generation X during adulthood. • Estimated generation-specific VMT elasticities WRT person age, driving licensure, car ownership, household size, and income. Millennials' automobility preferences and choices have attracted widespread attention from academia, policy makers, and business industries. Existing studies, however, have reported mixed findings on whether Millennials differ from their predecessor generations, leading to contradictory conclusions drawn for transportation planning and policy recommendations. This study utilized eight U.S. national travel surveys to construct a panel data that covers a continuous range of ages for persons five years and older for Baby Boomers, Generation X, and Millennials. With this unique dataset, the study performed analyses on the trend of daily vehicle miles traveled (VMT) by an average person from each generation and its subgroups. The study found that Baby Boomers, Generation X, and Millennials shared a three-phased trending pattern of VMT over the life course but exhibited varying levels of daily VMT in different life stages. During adulthood, Millennials have kept their daily VMT consistently lower than that of Generation X by about 3 VMT, or 8%, whereas the younger group of Baby Boomers outdrove the older Millennials at age 28 and after by about 3.5 VMT, or 9% daily. When each generation is considered over its life course, peak-level daily VMT tends to occur at earlier ages for each successive generation. From the multi-level modeling of daily VMT, the study identified generation-related group effects and estimated VMT elasticities with respect to person age, driving licensure, vehicle ownership, household size, and gasoline price-adjusted income. The study's findings on the direction and size of VMT influences associated with the five planning or policy variables did not support the speculation that Millennials would match or surpass Baby Boomers and Generation X in their future daily VMT trajectory. Public policies should be designed to nurture the shifting trend of reduced automobility from the older to the younger generations. [ABSTRACT FROM AUTHOR]

We examine the extent to which income inequality is associated with materialistic values and behavior in Europe and the United States (US). In the US, existing research on materialistic behavior is largely focused on the study of shopping behavior and shows that, when income inequality is higher, individuals search for and buy products that are more luxury. In Europe, the evidence for this phenomenon is mainly based on survey questions on people's values, and results are mixed. To determine whether these conflicting findings are rooted in methodology or reflect structural differences between the situation of Americans and Europeans, we measure materialistic behavior and values in both the US and Europe. Different types of data are used to test our arguments. In study 1, we use information on materialistic values from the European Social Survey (ESS) and the World Values Survey (WVS) to study the relationship between income inequality and materialistic values, examining the same research question in the contexts of Europe and the United States. In study 2, we use information from Google Trends to examine the relationship between income inequality and internet searching behavior both in Europe and in the United States. Hybrid multilevel models analyzing the variation in these relationships both over time and across regions show that in Europe as well as in the US, income inequality is not associated with materialistic values. However, in the US, materialistic behavior is greatly enhanced when income inequality is high. In contrast, in Europe, increasing income inequality is associated with decreasing materialistic behavior. [ABSTRACT FROM AUTHOR]

Background: Severe acute pain is still commonly treated with opioid analgesics in the United States, but this practice could prolong the duration of pain.Objectives: Estimate the risk of experiencing persistent pain after opioid analgesic use after emergency department (ED) discharge among patients with suspected urolithiasis.Methods: We analyzed data collected for a longitudinal, multicenter clinical trial of ED patients with suspected urolithiasis. We constructed multilevel models to estimate the odds ratios (ORs) of reporting pain at 3, 7, 30, or 90 days after ED discharge, using multiple imputation to account for missing outcome data. We controlled for clinical, demographic, and institutional factors and used weighting to account for the propensity to be prescribed an opioid analgesic at ED discharge.Results: Among 2413 adult ED patients with suspected urolithiasis, 62% reported persistent pain 3 days after discharge. Participants prescribed an opioid analgesic at discharge were OR 2.51 (95% confidence interval [CI] 1.82-3.46) more likely to report persistent pain than those without a prescription. Those who reported using opioid analgesics 3 days after discharge were OR 2.24 (95% CI 1.77-2.84) more likely to report pain at day 7 than those not using opioid analgesics at day 3, and those using opioid analgesics at day 30 had OR 3.25 (95% CI 1.96-5.40) greater odds of pain at day 90.Conclusions: Opioid analgesic prescription doubled the odds of persistent pain among ED patients with suspected urolithiasis. Limiting opioid analgesic prescribing at ED discharge for these patients might prevent persistent pain in addition to limiting access to these medications. [ABSTRACT FROM AUTHOR]

The objective of this study was to examine changes in American recruits' perceptions of the seriousness of behaviors related to police integrity from the beginning to the end of their academy training. Using a sample of 655 recruits from multiple academies in the United States, multilevel growth models were used. The results showed that the recruits rated scales related to misconduct, code of silence, and a noble cause less seriously at the end than at the beginning of their training. The results also showed that ethics training mitigated the effects of socialization, while organizational injustice intensified the effects of socialization. Female recruits rated the behaviors more seriously at the beginning and the end of training compared to male recruits. The results confirm the role of the academy in socializing officers into the negative aspects of the traditional police culture and highlight important avenues for police reform. [ABSTRACT FROM AUTHOR]

More than 720,000 patients with end‐stage renal disease in the United States require life‐sustaining dialysis treatment. In this population of typically older patients with a high morbidity burden, hospitalization is frequent at a rate of about twice per patient‐year. Aside from frequent hospitalizations, which is a major source of death risk, overall mortality in dialysis patients is higher than other comparable populations, including Medicare patients with cancer. Thus, understanding patient‐ and facility‐level risk factors that jointly contribute to longitudinal hospitalizations and mortality is of interest. Towards this objective, we propose a novel methodology to jointly model hospitalization, a binary longitudinal outcome, and survival, based on multilevel data from the United States Renal Data System (USRDS), with repeated observations over time nested in patients and patients nested in dialysis facilities. In our approach, the outcomes are modeled through a common set of multilevel random effects. In order to accommodate the USRDS data structure, we depart from the literature on joint modeling of longitudinal and survival data by including multilevel random effects and multilevel covariates, at both the patient and facility levels. An approximate Expectation‐Maximization algorithm is developed for estimation and inference where fully exponential Laplace approximations are utilized to address computational challenges. [ABSTRACT FROM AUTHOR]

This study investigates whether the September 11 terrorist attacks had any impacts on the labor market outcomes of refugees resettled in the United States, who should be distinguished from economic migrants or usual nonnatives. Furthermore, this paper sheds unprecedented light on whether those impacts were heterogeneous depending on a refugee's ethnicity or religion. In terms of econometric methods, this research attempts to allow for the violation of the conventional condition of independently and identically distributed (i.i.d.) observations and control for cluster-specific unobservables by using nonlinear multi-level models, considering that refugees form unique networks in their resettlement regions and actively interact with one another within their clusters. Due to the binary dependent variable of this study, the incidental parameters problem is also taken into account. The multi-level estimates of this paper suggest that the September 11 attacks did not uniformly shock all sub-populations of refugees: rather, they presented a unique, substantial opportunity for Asian refugees and a serious threat to African and Arab refugees. One unanticipated finding is that the employment probability of European refugees remained stable, whereas that of Asian refugees markedly increased after the attacks. However, in terms of employment quality, measured by real wages, European refugees were the only ones who benefited from the attacks. Possible explanations for such heterogeneous impacts and different patterns of benefits are discussed, including positive versus negative selection into employment. [ABSTRACT FROM AUTHOR]

Objectives: To measure disparities in experience of police use of force and injury among persons with serious mental illnesses. Methods: We gathered novel police use of force and suspect injury data from 2011 to 2017 from a nonrandom sample of nine police departments in the United States and used synthetic methods to estimate the share of the local population with serious mental illness. We estimate disparities using multi-level models estimated in a Bayesian framework. Results: Persons with serious mental illness constitute 17.0% of use of force cases (SD = 5.8) and 20.2% of suspects injured in police interaction (SD = 9.0) in sample cities. The risk that persons with serious mental illness will experience police use of force is 11.6 times higher (95% CI, 10.7–12.6) than persons without serious mental illness. Persons with serious mental illness are also at a higher risk of experiencing injury, 10.7 times (95% CI, 9.6–11.8), relative to persons without serious mental illness. These relative risk ratios are several times larger than racial and ethnic disparities estimated in the same cities. Conclusion: Persons with serious mental are at a significantly elevated risk of experiencing police use of force and injury in police encounters than the general public. The disparities we estimate are several times higher than racial/ethnic disparities in force and injury. Efforts to reform police practices and reimagine public safety in the United States should address significant disparities in police use of force against those with serious mental illness. [ABSTRACT FROM AUTHOR]

Although masks (face coverings) are a prime tool in fighting airborne pathogens, during the COVID-19 pandemic in the United States the use of masks encountered resistance based on existing patterns of cultural division. We argue that mask wearing must be understood basis on existing cultural frames assessed at both the individual level and the state level. We relied on prominent frameworks in cultural psychology: individualism-collectivism as well as independent and interdependent self-construals, the tightness-looseness framework, U.S. honor cultures, and political orientation as predictors. Using multilevel modeling, in a sample of 633 respondents from 45 U.S. states we investigated mask-wearing behavior, masks' perceived utility, implications for well-being, and the social meaning attributed to masks. Conservatism was linked to lower mask wearing, and consistently unfavorable perceptions of mask wearing. Collective interdependence predicted favorable perceptions of masks, as did state-level differences in collectivism; both constructs were linked with viewing mask wearing to be normative. Independent self-construal predicted a greater intent to wear masks, even though masks were also evaluated less favorably. Mediation analyses revealed that a single mediator, the perceived utility of mask wearing, was implicated in translating the effects of different cultural predictors into behavior. Additional findings highlighted that in tightener (vs. looser) states masks wearing was conceived of as a civic duty, whereas in U.S. honor states mask were seen as spoiling one's public image. Our discussion focuses on the cultural and political context of mask wearing, argues that different communities in the U.S. respond to its symbolic and social meaning, and suggest strategies to increase mask wearing among those who are otherwise reluctant to do so. [ABSTRACT FROM AUTHOR]

Since 2000, the National Cancer Institute's Cancer Intervention and Surveillance Modeling Network (CISNET) modeling teams have developed and applied microsimulation and statistical models of breast cancer. Here, we illustrate the use of collaborative breast cancer multilevel systems modeling in CISNET to demonstrate the flexibility of systems modeling to address important clinical and policy-relevant questions. Challenges and opportunities of future systems modeling are also summarized. The 6 CISNET breast cancer models embody the key features of systems modeling by incorporating numerous data sources and reflecting tumor, person, and health system factors that change over time and interact to affect the burden of breast cancer. Multidisciplinary modeling teams have explored alternative representations of breast cancer to reveal insights into breast cancer natural history, including the role of overdiagnosis and race differences in tumor characteristics. The models have been used to compare strategies for improving the balance of benefits and harms of breast cancer screening based on personal risk factors, including age, breast density, polygenic risk, and history of Down syndrome or a history of childhood cancer. The models have also provided evidence to support the delivery of care by simulating outcomes following clinical decisions about breast cancer treatment and estimating the relative impact of screening and treatment on the United States population. The insights provided by the CISNET breast cancer multilevel modeling efforts have informed policy and clinical guidelines. The 20 years of CISNET modeling experience has highlighted opportunities and challenges to expanding the impact of systems modeling. Moving forward, CISNET research will continue to use systems modeling to address cancer control issues, including modeling structural inequities affecting racial disparities in the burden of breast cancer. Future work will also leverage the lessons from team science, expand resource sharing, and foster the careers of early stage modeling scientists to ensure the sustainability of these efforts. Author summary: Since 2000, our research teams have used computer models of breast cancer to address important clinical and policy-relevant questions as part of the National Cancer Institute's Cancer Intervention and Surveillance Modeling Network (CISNET). Our 6 CISNET breast cancer models embody the key features of systems modeling by incorporating numerous data sources and reflecting tumor, person, and health system factors that change over time and interact to represent the burden of breast cancer. We have used our models to investigate questions related to breast cancer biology, compare strategies to improve the balance of benefits and harms of screening mammography, and support insights into the delivery of care by modeling outcomes following clinical decisions about breast cancer treatment. Moving forward, our research will continue to use systems modeling to address issues related to reducing the burden of breast cancer including modeling structural inequities affecting racial disparities. Our future work will also leverage lessons from engaging multidisciplinary scientific teams, expand efforts to share modeling resources with other researchers, and foster the careers of early stage modeling scientists to ensure the sustainability of these efforts. [ABSTRACT FROM AUTHOR]

In early 2020, the COVID-19 pandemic forced a large portion of the world into quarantine, leading to an extensive period of stress making it necessary to explore regulatory techniques that are effective at stimulating long-lasting positive emotion. Previous research has demonstrated that anticipating positive events produces increases in positive emotion during discrete stressors. We hypothesized that state and trait positive anticipation during the COVID-19 pandemic would be associated with increased positive emotions. We assessed how often participants thought about a future positive/negative/neutral event, activity, or goal through a daily reconstruction method that represented a "day in the life" of people in the United States during the early stages of the COVID-19 pandemic. The results of multi-level modeling and mediational analyses demonstrated that higher optimism, one form of trait positive anticipation, was related to higher state positive anticipation, which was in turn related to higher positive emotions during the current episode, which persisted to the next episode. In addition, both optimism and state positive anticipation were related to adaptive responses to the pandemic. These findings suggest that anticipation of future emotional experiences and hopefulness for the future can be a powerful predictor of positive emotions during global pandemics and perhaps other similar chronic stressors. [ABSTRACT FROM AUTHOR]

This paper examines the treatment and processing of immigration court decisions for unaccompanied alien children (UAC) in the United States from 2013 to 2017. We focus on two primary questions in our research: (1) whether asylum cases involving UAC are substantially different in outcome than non‐UAC cases, and (2) whether there have been significant differences in the immigration courts' asylum decisions involving unaccompanied minors before and after the Trump administration came to power. We utilize various multilevel models to test individual applicant‐, immigration judge‐, county‐, and state‐level variables on the likelihood of UAC receiving a positive outcome in immigration court. We find strong support for the second hypothesis and mixed support for the first. Overall, our findings suggest that multiple political, economic, social, and geographical factors influence immigration hearings for UAC beyond the individual strength of any one child's case. [ABSTRACT FROM AUTHOR]

The aim of this article is to assess the role of early childhood education and care (ECEC) program access and generosity on child maltreatment as measured by Child Protective Services (CPS) reports. Using administrative data capturing CPS reports in the United States, I estimate the role of Child Care and Development Fund (CCDF) child-care subsidies, Head Start, Early Head Start, state prekindergarten, and universal prekindergarten programs on CPS reports using ordinary least squares and multilevel models. I exploit exogenous variation in state prekindergarten enrollment shocks to compare the CPS reports across children's age-based eligibility using difference-in-difference-in-difference and event-history frameworks. Results suggest that the largest welfare gains in program access may occur among the youngest children (under age 3), the group for whom program access is most constrained. However, findings from state-level models provide weak overall evidence of a lower-bound benefit. [ABSTRACT FROM AUTHOR]

Informed by the Core and Balance Model of Family Leisure Functioning, we investigated the contribution of one type of family leisure—couple vacations—in enhancing couples' cohesion and flexibility (i.e., functioning). Studying dyadic data from 112 couples (224 individuals) from across the United States of America, results of multilevel models showed that the variable "shared experiences during vacations" was positively associated with couples' day-to-day functioning at home. Couples who engaged in higher levels of shared experiences during their vacations, such as effective communication, showing affection, or experiencing new things together, reported higher levels of couple flexibility and cohesion following their vacations, regardless of the number of vacations. We discuss the implications of these results for couples who spend quality time together away from home, as well as future use of our study model when examining benefits of vacationing for families. [ABSTRACT FROM AUTHOR]

We introduced a multilevel model of value shift to describe the changing social context of wildlife conservation. Our model depicts how cultural‐level processes driven by modernization (e.g., increased wealth, education, and urbanization) affect changes in individual‐level cognition that prompt a shift from domination to mutualism wildlife values. Domination values promote beliefs that wildlife should be used primarily to benefit humans, whereas mutualism values adopt a view that wildlife are part of one's social network and worthy of care and compassion. Such shifts create emergent effects (e.g., new interest groups) and challenges to wildlife management organizations (e.g., increased conflict) and dramatically alter the sociopolitical context of conservation decisions. Although this model is likely applicable to many modernized countries, we tested it with data from a 2017–2018 nationwide survey (mail and email panel) of 43,949 residents in the United States. We conducted hierarchical linear modeling and correlational analysis to examine relationships. Modernization variables had strong state‐level effects on domination and mutualism. Higher levels of education, income, and urbanization were associated with higher percentages of mutualists and lower percentages of traditionalists, who have strong domination values. Values affected attitudes toward wildlife management challenges; for example, states with higher proportions of mutualists were less supportive of lethal control of wolves (Canis lupus) and had lower percentages of active hunters, who represent the traditional clientele of state wildlife agencies in the United States. We contend that agencies will need to embrace new strategies to engage and represent a growing segment of the public with mutualism values. Our model merits testing for application in other countries. Article impact statement: Application of a multilevel model of social change reveals implications of a shift in public values for wildlife conservation in the United States. [ABSTRACT FROM AUTHOR]

Accumulating evidence suggests that lifetime trauma exposure is associated with adulthood cognitive functioning. However, the nature and extent of this relation have yet to be fully explored. We used multilevel modeling to examine trauma exposure and age at first trauma exposure as predictors of the level of and change in cognitive functioning over a 9-year period. Data were from the Midlife in the United States study, a national survey that began in 1995. Data regarding trauma exposure and age at first exposure were obtained from the 2004 wave, whereas cognitive data were obtained from the 2004 and 2013 waves. The analyses were conducted using data from the 2,471 participants (age range: 28-84 years) who had complete data on all variables from the 2004 wave. Lifetime trauma exposure predicted change in executive functioning (EF), B = -0.03, SE = 0.01, p = .015, 95% CI [-0.05, -0.01]; and episodic memory, B = -0.05, SE = 0.02, p = .023, 95% CI [-0.10, -0.01], such that individuals with more trauma exposure had more decline over 9 years. Age at first exposure also predicted change in EF, B = -0.002, SE = 0.00, p = .009, 95% CI [-0.004, -0.001], such that individuals who were first exposed to trauma later in life had greater EF decline than individuals whose first traumatic event occurred earlier in life. Delta pseudo- R2 values were moderate, ΔpseudoR2 = .17-.39. These findings identify trauma exposure as a risk factor for cognitive decline in adulthood and highlight the elevated risk associated with adulthood trauma exposure. [ABSTRACT FROM AUTHOR]

Objective: To develop fetal growth standards for twin gestations by placental chorionicity in a Spanish population and compare them with European and American standards to estimate the suitability of their use in clinical practice.Study Design: This was a retrospective cohort study of 518 twin pregnancies, 435 dichorionic-diamniotic and 83 monochorionic-diamniotic, performed between January 2012 and December 2017. A total of 4,783 and 1,455 estimated fetal weights were considered from the 17th to the 37th week of gestation, using multilevel models, to build dichorionic-diamniotic and monochorionic-diamniotic standards, respectively. The percentages of small and large for gestational age were calculated as a model adjustment measure and adjustment to the studied data and the values provided by our model were compared against those of six European and American twin standards and three singleton standards. Correlation analyses between percentile predictions were performed using Cohen kappa coefficient. The predictive ability to detect small for gestational age was also provided by the sensitivity and positive predictive value.Results: We found slight differences between standards by chorionicity, being dichorionic-diamniotic percentiles slightly higher than monochorionic-diamniotic ones from the 17th to 37th weeks' gestation. For dichorionic-diamniotic cases, both our standard (9.8-8.2) and that of Grantz (8.2-10.5) showed good adjustments for the 10th and 90th percentiles while the other compared standards underestimated or overestimated them. For monochorionic-diamniotic cases, both our standard (10.2-8.5) and that of Shivkumar (11.4-6.8) had the most suitable adjustment. The correlation analysis between small and large for gestational age cases provided by standards, showed clear differences among them. Kappa's coefficient showed a substantial agreement between both Ananth (0.7) and Stirrup (0.69) dichorionic-diamniotic cases and our standard. There was also a substantial agreement between the Shivkumar (0.77) standard and our results for monochorionic-diamniotic cases. The correlation was moderate for all other comparisons.Conclusions: Our model showed a good adjustment to the studied population. There are clear differences among small and large for gestational age cases provided by twin standards in our studied population. The twin growth standards depend on the population characteristics and model structure. We found the use of singleton standards for twin pregnancies inadequate. [ABSTRACT FROM AUTHOR]

The extent to which disproportionate minority contact (DMC) in the juvenile justice system varies across states remains largely unknown. Using a multijurisdictional sample of 146 counties across four states, the present study utilizes multilevel modeling with cross-level interactions to explore whether there is variation in the influence of race and ethnicity among states across four major juvenile justice processing decisions—preadjudication detention, petition of delinquency, adjudication of delinquency, and judicial disposition. The results highlight the existence of some variation in DMC across the four states, with the variation most pronounced at detention and least pronounced at disposition. The possibility of state variation in DMC underscores the need for state-specific analysis of DMC, what contributes to it, and what can be done to reduce it. [ABSTRACT FROM AUTHOR]

Objective: Suicide remains a leading cause of death in the United States, and recent reports have suggested the suicide rate is increasing. One of the most robust predictors of future suicidal behavior is a history of attempting suicide. Despite this, little is known about the factors that reduce the likelihood of reattempting suicide. This study compares theoretically derived suicide risk indicators to determine which factors are most predictive of future suicide attempts. Method: We used data from a randomized, controlled trial comparing 3 forms of dialectical behavior therapy (DBT; Linehan et al., 2015). Participants (N = 97, mean age = 30.3 years, 100% female, 71% White) met criteria for borderline personality disorder and had repeated and recent self-injurious behavior. Assessments occurred at 4-month intervals throughout 1 year of treatment and 1 year of follow-up. Time-lagged generalized linear mixed models (GLMMs) were used to evaluate relationship satisfaction, emotion dysregulation, and coping styles as predictors of suicide attempts. Results: Both univariate and multivariate models suggested that higher between-person variance in problem-focused coping and lack of access to emotion regulation strategies were weakly associated with additional suicide attempts over the 2-year study. Within-person variance in the time-lagged predictors was not associated with subsequent suicide attempts. Conclusions: Among individuals with a recent suicide attempt, problem-focused coping and specific deficits in emotion regulation may differentiate those likely to reattempt from those who stop suicidal behavior during and after psychotherapy. These results suggest that treatments for recent suicide attempters should target increasing problem-focused coping and decreasing maladaptive emotion regulation skills. What is the public health significance of this article?: Suicide is a complex public health problem, and researchers are unable to reliably predict when suicide attempts are likely to occur. Results from this study suggest that some of the risk factors studied to date explain differences between people who continue to be at high-risk for suicide, but individual deviations in these risk factors do not prospectively predict suicide attempts. [ABSTRACT FROM AUTHOR]

Objective: To assess the accuracy of nursing home self-report of major injury falls on the Minimum Data Set (MDS).Data Sources: MDS assessments and Medicare claims, 2011-2015.Study Design/methods: We linked inpatient claims for major injury falls with MDS assessments. The proportion of claims-identified falls reported for each fall-related MDS item was calculated. Using multilevel modeling, we assessed patient and nursing home characteristics that may be predictive of poor reporting. We created a claims-based major injury fall rate for each nursing home and estimated its correlation with Nursing Home Compare (NHC) measures.Principal Findings: We identified 150,828 major injury falls in claims that occurred during nursing home residency. For the MDS item used by NHC, only 57.5 percent were reported. Reporting was higher for long-stay (62.9 percent) than short-stay (47.2 percent), and for white (59.0 percent) than nonwhite residents (46.4 percent). Adjusting for facility-level race differences, reporting was lower for nonwhite people than white people; holding constant patient race, having larger proportions of nonwhite people in a nursing home was associated with lower reporting. The correlation between fall rates based on claims vs the MDS was 0.22.Conclusions: The nursing home-reported data used for the NHC falls measure may be highly inaccurate. [ABSTRACT FROM AUTHOR]