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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. [ABSTRACT FROM AUTHOR]

With clustered data, such as where students are nested within schools or employees are nested within organizations, it is often of interest to estimate and compare associations among variables separately for each level. While researchers routinely estimate between-cluster effects using the sample cluster means of a predictor, previous research has shown that such practice leads to biased estimates of coefficients at the between level, and recent research has recommended the use of latent cluster means with the multilevel structural equation modeling framework. However, the latent cluster mean approach may not always be the best choice as it (a) relies on the assumption that the population cluster sizes are close to infinite, (b) requires a relatively large number of clusters, and (c) is currently only implemented in specialized software such as Mplus. In this paper, we show how using empirical Bayes estimates of the cluster means can also lead to consistent estimates of between-level coefficients, and illustrate how the empirical Bayes estimate can incorporate finite population corrections when information on population cluster sizes is available. Through a series of Monte Carlo simulation studies, we show that the empirical Bayes cluster-mean approach performs similarly to the latent cluster mean approach for estimating the between-cluster coefficients in most conditions when the infinite-population assumption holds, and applying the finite population correction provides reasonable point and interval estimates when the population is finite. The performance of EBM can be further improved with restricted maximum likelihood estimation and likelihood-based confidence intervals. We also provide an R function that implements the empirical Bayes cluster-mean approach, and illustrate it using data from the classic High School and Beyond Study. [ABSTRACT FROM AUTHOR]

Measurement invariance (MI) of a psychometric scale is a prerequisite for valid group comparisons of the measured construct. While the invariance of loadings and intercepts (i.e., scalar invariance) supports comparisons of factor means and observed means with continuous items, a general belief is that the same holds with ordered-categorical (i.e., ordered-polytomous and dichotomous) items. However, as this paper shows, this belief is only partially true—factor mean comparison is permissible in the correctly specified scalar invariance model with ordered-polytomous items but not with dichotomous items. Furthermore, rather than scalar invariance, full strict invariance—invariance of loadings, thresholds, intercepts, and unique factor variances in all items—is needed when comparing observed means with both ordered-polytomous and dichotomous items. In a Monte Carlo simulation study, we found that unique factor noninvariance led to biased estimations and inferences (e.g., with inflated type I error rates of 19.52%) of (a) the observed mean difference for both ordered-polytomous and dichotomous items and (b) the factor mean difference for dichotomous items in the scalar invariance model. We provide a tutorial on invariance testing with ordered-categorical items as well as suggestions on mean comparisons when strict invariance is violated. In general, we recommend testing strict invariance prior to comparing observed means with ordered-categorical items and adjusting for partial invariance to compare factor means if strict invariance fails. [ABSTRACT FROM AUTHOR]

Measurement invariance holds when a latent construct is measured in the same way across different levels of background variables (continuous or categorical) while controlling for the true value of that construct. Using Monte Carlo simulation, this paper compares the multiple indicators, multiple causes (MIMIC) model and MIMIC-interaction to a novel use of alignment optimization (AO) for detecting measurement noninvariance when the violator is a continuous variable. Results showed that MIMIC and MIMIC-interaction in sequential likelihood ratio tests and Wald tests with a Bonferroni correction provided a good balance between identifying invariant and noninvariant (linear violations) items when n ≥ 500 in terms of classification accuracy (CA). AO (CA ≥ .86) was as competitive as MIMIC and MIMIC-interaction to linear invariance violations but was far better under nonlinear quadratic violations when n ≥ 1,000 (i.e., 100 per group for 10 groups). [ABSTRACT FROM AUTHOR]

We have developed, manufactured, and tested a new feed design for interferometric radio telescopes with "large-N, small-D" designs. Such arrays require low-cost and low-complexity feeds for mass production on reasonable timescales and budgets, and also require those feeds to be compact to minimize obstruction of the dishes, along with having ultra-wide frequency bands of operation for most current and future science goals. The feed presented in this paper modifies the exponentially tapered slot antenna (Vivaldi) and quad-ridged flared horn antenna designs by having an oversized backshort, a novel method of maintaining a small size that is well-suited for deeper dishes (f ∕ D ≤ 0. 2 5). It is made of laser cut aluminum and printed circuit boards, such that it is inexpensive (≲ 7 5 USD per feed in large-scale production) and quick to build; it has a 5:1 frequency ratio, and its size is approximately a third of its longest operating wavelength. We present the science and engineering constraints that went into design decisions, the development and optimization process, and the simulated performance. A version of this feed design was optimized and fabricated for the Canadian Hydrogen Observatory and Radio-transient Detector (CHORD) prototypes. When simulated on CHORD's very deep dishes (f ∕ D = 0. 2 1) and with CHORD's custom first-stage amplifiers, the on-sky system temperature T sys of the complete receiving system from dish to digitizer remains below 30 K over most of the 0.3–1.5 GHz band, and maintains an aperture efficiency η A between 0.4 and 0.6. The entire receiving chain operates at ambient temperature. The feed is designed to slightly under-illuminate the CHORD dishes, in order to minimize coupling between array elements and spillover. [ABSTRACT FROM AUTHOR]

In path analysis, using composite scores without adjustment for measurement unreliability and violations of factorial invariance across groups lead to biased estimates of path coefficients. Although joint modeling of measurement and structural models can theoretically yield consistent structural association estimates, estimating a model with many variables is often impractical in small samples. A viable alternative is two-stage path analysis (2S-PA), where researchers first obtain factor scores and the corresponding individual-specific reliability coefficients, and then use those factor scores to analyze structural associations while accounting for their unreliability. The current paper extends 2S-PA to also account for partial invariance. Two simulation studies show that 2S-PA outperforms joint modeling in terms of model convergence, the efficiency of structural parameter estimation, and confidence interval coverage, especially in small samples and with categorical indicators. We illustrate 2S-PA by reanalyzing data from a multiethnic study that predicts drinking problems using college-related alcohol beliefs. [ABSTRACT FROM AUTHOR]

Eosinophilic granulomatosis with polyangiitis (EGPA) is a rare systemic vasculitis of small to medium vessels. Gastrointestinal involvement is uncommon and is associated with higher mortality. Treatment is based on empiric evidence. In this article, we report a case of EGPA-related pancolitis and stricturing small bowel disease managed with a combination of mepolizumab and surgical resection. [ABSTRACT FROM AUTHOR]

Longitudinal measurement invariance—the consistency of measurement in data collected over time—is a prerequisite for any meaningful inferences of growth patterns. When one or more items measuring the construct of interest show noninvariant measurement properties over time, it leads to biased parameter estimates and inferences on the growth parameters. In this paper, I extend the recently developed alignment-within-confirmatory factor analysis (AwC) technique to adjust for measurement biases for growth models. The proposed AwC method does not require a priori knowledge of noninvariant items and the iterative searching of noninvariant items in typical longitudinal measurement invariance research. Results of a Monte Carlo simulation study comparing AwC with the partial invariance modeling method show that AwC largely reduces biases in growth parameter estimates and gives good control of Type I error rates, especially when the sample size is at least 1,000. It also outperforms the partial invariance method in conditions when all items are noninvariant. However, all methods give biased growth parameter estimates when the proportion of noninvariant parameters is over 25%. Based on the simulation results, I conclude that AO is a viable alternative to the partial invariance method in growth modeling when it is not clear whether longitudinal measurement invariance holds. The current paper also demonstrates AwC in an example modeling neuroticism over three time points using a public data set, which shows how researchers can compute effect size indices for noninvariance in AwC to assess to what degree invariance holds and whether AwC results are trustworthy. [ABSTRACT FROM AUTHOR]

There has been tremendous growth in research on measurement invariance over the past two decades. However, given that psychological tests are commonly used for making classification decisions such as personnel selections or diagnoses, surprisingly, there has been little research on how noninvariance impacts classification accuracy. Millsap and Kwok previously proposed a selection accuracy framework for that purpose, which has been recently extended to categorical data. Their framework, however, only deals with classification using a unidimensional test. In contrast, classification in practice usually involves multidimensional tests (e.g., personality) or multiple tests, with different weights assigned to each dimension. In the current paper, we extend Millsap and Kwok's framework for examining the impact of noninvariance to a multidimensional test on classification. We also provide an R script for the proposed method and illustrate it with a personnel selection example using data from a published report featuring a five-factor personality inventory. [ABSTRACT FROM AUTHOR]

Measurement invariance is the condition that an instrument measures a target construct in the same way across subgroups, settings, and time. In psychological measurement, usually only partial, but not full, invariance is achieved, which potentially biases subsequent parameter estimations and statistical inferences. Although existing literature shows that a correctly specified partial invariance model can remove such biases, it ignores the model uncertainty in the specification search step: flagging the wrong items may lead to additional bias and variability in subsequent inferences. On the other hand, several new approaches, including Bayesian approximate invariance and alignment optimization methods, have been proposed; these methods use an approximate invariance model to adjust for partial measurement invariance without the need to directly identify noninvariant items. However, there has been limited research on these methods in situations with a small number of groups. In this paper, we conducted three systematic simulation studies to compare five methods for adjusting partial invariance. While specification search performed reasonably well when the proportion of noninvariant parameters was no more than one-third, alignment optimization overall performed best across conditions in terms of efficiency of parameter estimates, confidence interval coverage, and type I error rates. In addition, the Bayesian version of alignment optimization performed best for estimating latent means and variances in small-sample and low-reliability conditions. We thus recommend the use of the alignment optimization methods for adjusting partial invariance when comparing latent constructs across a few groups. [ABSTRACT FROM AUTHOR]

Although many methodologists and professional organizations have urged applied researchers to compute and report effect size measures accompanying tests of statistical significance, discussions on obtaining confidence intervals (CIs) for effect size with clustered/multilevel data have been scarce. In this paper, I explore the bootstrap as a viable and accessible alternative for obtaining CIs for multilevel standardized mean difference effect size for cluster-randomized trials. A simulation was carried out to compare 17 analytic and bootstrap procedures for constructing CIs for multilevel effect size, in terms of empirical coverage rate and width, for both normal and nonnormal data. Results showed that, overall, the residual bootstrap with studentized CI had the best coverage rates (94.75% on average), whereas the residual bootstrap with basic CI had better coverage in small samples. These two procedures for constructing CIs showed better coverage than using analytic methods for both normal and nonnormal data. In addition, I provide an illustrative example showing how bootstrap CIs for multilevel effect size can be easily obtained using the statistical software R and the R package bootmlm. I strongly encourage applied researchers to report CIs to adequately convey the uncertainty of their effect size estimates. [ABSTRACT FROM AUTHOR]

This 12-month longitudinal study investigated the incidence of probable depression (i.e., changes in Center for Epidemiological Studies Depression Scale [CES-D] scores from < 16 at the baseline to ≥ 16 at the follow-up) and its psychosocial predictors among secondary 1–4 students (N = 9666) in Hong Kong, China. Of the 4100 non-probable depression participants (CES-D < 16) at baseline, data obtained from the baseline and longitudinal surveys of 3584 (87.4%) participants could be matched and were analyzed. The incidence of probable depression was 46.60 per 100 person-years. Adjusted for all background factors, negative life events, loneliness, and social anxiety were significant risk factors, while self-esteem, self-efficacy, positive affect, and family support were protective predictors of incident depression. Female sex was a risk factor but the interactions between sex and the psychosocial factors in determining incident probable depression were statistically non-significant, except for loneliness. The high incidence of probable depression calls for effective interventions on both sexes. [ABSTRACT FROM AUTHOR]

This study evaluated measurement invariance across males and females on the Neurobehavioral Symptom Inventory (NSI) in U.S. military veterans enrolled in the VA Million Veteran Program. Participants (N = 17,059; males: n = 15,450; females: n = 1,609) included Veterans who took part in the VA Traumatic Brain Injury (TBI) Screening and Evaluation Program and completed the NSI. Multiple-group confirmatory factor analyses investigated measurement invariance of the NSI 4-factor model. The configural (comparative fit index [CFI] = 0.948, root mean square error of approximation [RMSEA] = 0.060) and metric (CFI = 0.948, RMSEA = 0.058) invariance models showed acceptable fit. There was a minor violation of scalar invariance (Δχ2 = 232.50, p <.001); however, the degree of noninvariance was mild (ΔCFI = −0.002, Δ RMSEA = 0. 000). Our results demonstrate measurement invariance across sex, suggesting that the NSI 4-factor model can be used to accurately assess symptoms in males and females following TBI. Findings highlight the importance of considering validity of measurement across study groups to increase confidence that a measure is interpreted similarly by respondents from different subgroups. [ABSTRACT FROM AUTHOR]

Most of the empirical research on sex differences and cultural variations in morality has relied on within-culture analyses or small-scale cross-cultural data. To further broaden the scientific understanding of sex differences in morality, the current research relies on two international samples to provide the first large-scale examination of sex differences in moral judgements nested within cultures. Using a sample from 67 countries (Study 1; n = 336 691), we found culturally variable sex differences in moral judgements, as conceptualized by Moral Foundations Theory. Women consistently scored higher than men on Care, Fairness, and Purity. By contrast, sex differences in Loyalty and Authority were negligible and highly variable across cultures. Country-level sex differences in moral judgements were also examined in relation to cultural, socioeconomic, and gender-equality indicators revealing that sex differences in moral judgements are larger in individualist, Western, and gender-equal societies. In Study 2 (19 countries; n = 11 969), these results were largely replicated using Bayesian multi-level modelling in a distinct sample. The findings were robust when incorporating cultural non-independence of countries into the models. Specifically, women consistently showed higher concerns for Care, Fairness, and Purity in their moral judgements than did men. Sex differences in moral judgements were larger in individualist and gender-equal societies with more flexible social norms. We discuss the implications of these findings for the ongoing debate about the origin of sex differences and cultural variations in moral judgements as well as theoretical and pragmatic implications for moral and evolutionary psychology. [ABSTRACT FROM AUTHOR]

Establishing measurement invariance, or that an instrument measures the same construct(s) in the same way across subgroups of respondents, is crucial in efforts to validate social and behavioral instruments. Although substantial previous research has focused on detecting the presence of noninvariance, less attention has been devoted to its practical significance and even less has been paid to its possible impact on diagnostic accuracy. In this article, we draw additional attention to the importance of measurement invariance and advance diagnostic research by introducing a novel approach for quantifying the impact of noninvariance with binary items (e.g., the presence or absence of symptoms). We illustrate this approach by testing measurement invariance and evaluating diagnostic accuracy across age groups using DSM alcohol use disorder items from a public national data set. By providing researchers with an easy-to-implement R program for examining diagnostic accuracy with binary items, this article sets the stage for future evaluations of the practical significance of partial invariance. Future work can extend our framework to include ordinal and categorical indicators, other measurement models in item response theory, settings with three or more groups, and via comparison to an external, "gold-standard" validator. [ABSTRACT FROM AUTHOR]

In testing the factorial invariance of a measure across groups, the groups are often of different sizes. Large imbalances in group size might affect the results of factorial invariance studies and lead to incorrect conclusions of invariance because the fit function in multiple-group factor analysis includes a weighting by group sample size. The implication is that violations of invariance might not be detected if the sample sizes of the 2 groups are severely unbalanced. In this study, we examined the effects of group size differences on results of factorial invariance tests, proposed a subsampling method to address unbalanced sample size issue in factorial invariance studies, and evaluated the proposed approach in various simulation conditions. Our findings confirm that violations of invariance might be masked in the case of severely unbalanced group size conditions and support the use of the proposed subsampling method to obtain accurate results for invariance studies. [ABSTRACT FROM PUBLISHER]

Much of the previous literature on partial measurement invariance has focused on (a) statistically detecting noninvariance, and (b) modeling partial invariance to obtain correct inferences for latent mean comparisons across groups in a single research study. However, very little guidance is provided on the practical implications of partial invariance on the instrument itself in the context of selection. In a frequently cited paper, Millsap and Kwok (2004) provided a framework for evaluating the impact of partial invariance by quantifying the magnitude of noninvariance on the efficacy of the test for selection purposes, yet our literature review found that only a few of the citations have fully captured the essence of Millsap and Kwok's method. In this article, we briefly review the selection accuracy analysis for partial invariance and provide a user-friendly R script (also available as a Web application) that takes parameter estimates as input, automatically produces summary statistics for evaluating selection accuracy, and generates a graph for visualizing the results. Hypothetical and real data examples are provided to illustrate the use of the R script. The goal of this article is to help readers understand Millsap and Kwok's framework of evaluating the impact of partial invariance through an accessible computer program and step-by-step demonstrations of the selection accuracy analysis. [ABSTRACT FROM AUTHOR]

Although letter naming fluency (LNF) and letter sound fluency (LSF) measures are widely available to educators for assessing early literacy skills of kindergarten children, better understanding of the contributions of these skills to reading development can help improve the interpretation of LNF and LSF data for instructional decisions. This study investigated the interrelations of growth in LNF and LSF across the kindergarten year and their unique roles in predicting later reading fluency. Piecewise parallel-process growth models indicated that although LNF and LSF were highly correlated at kindergarten entry, fall LNF status was positively predictive of LSF growth across the fall. Bidirectional effects were present, as initial LSF was also a positive predictor of LNF growth across the fall; however, its effects were not as strong as those of initial LNF on LSF growth. More importantly, both initial status and growth in LNF and LSF were uniquely predictive of first-grade reading fluency, indicating the independent effects of each on subsequent text reading skills. Indirect effects were also observed for kindergarten LNF and LSF growth on reading fluency in second and third grades. Implications for kindergarten assessment and instruction are discussed. [ABSTRACT FROM AUTHOR]

Background and aims: Internet gaming disorder (IGD) imposes a potential public health threat worldwide. Gaming motives are potentially salient factors of IGD, but research on Chinese gaming motives is scarce. This study empirically evaluated the psychometric properties of the Chinese version of the Motives for Online Gaming Questionnaire (C-MOGQ), the first inventory that measures seven different gaming motives applicable to all type of online games. We also investigated the associations between various gaming motives and IGD symptoms among Chinese gamers. Methods: Three hundred and eighty-three Chinese adult online gamers (Mean age = 23.7 years) voluntarily completed our online, anonymous survey in December 2015. Results: The confirmatory factor analysis results supported a bi-factor model with a general factor subsuming all C-MOGQ items (General Motivation) and seven uncorrelated domainspecific factors (Escape, Coping, Fantasy, Skill Development, Recreation, Competition, and Social). High internal consistencies of the overall scale and subscales were observed. The criterion-related validity of this Chinese version was also supported by the positive correlations of C-MOGQ scale scores with psychological need satisfaction and time spent gaming. Furthermore, we found that high General Motivation (coupled with high Escape motive and low Skill Development motive) was associated with more IGD symptoms reported by our Chinese participants. Discussion and conclusions: Our findings demonstrated the utility of C-MOGQ in measuring gaming motives of Chinese online gamers, and we recommend the consideration of both its total score and subscale scores in future studies. [ABSTRACT FROM AUTHOR]

Although previous research has discussed an effect size estimator for partially nested cluster randomized designs, the existing estimator (a) is not efficient when used with primary data, (b) can be biased when the homogeneity of variance assumption is violated, and (c) has not yet been empirically evaluated for its finite sample properties. The present paper addresses these limitations by proposing an alternative maximum likelihood estimator for obtaining standardized mean difference effect size and the corresponding sampling variance for partially nested data, as well as the variants that do not make an assumption of homogeneity of variance. The typical estimator, denoted asd(dWwith pooledSDanddCwith control armSD), requires input of summary statistics such as observed means, variances, and the intraclass correlation, and is useful for meta-analyses and secondary data analyses; the newly proposed estimator(and) takes parameter estimates from a correctly specified multilevel model as input and is mainly of interest to researchers doing primary research. The simulation results showed that the two methods (dand) produced unbiased point and variance estimates for effect size. As expected, in general,was more efficient thandwith unequal cluster sizes, especially with large average cluster size and large intraclass correlation. Furthermore, under heterogeneous variances,demonstrated a greater relative efficiency with small sample size for the unclustered control arm. Real data examples, one from a youth preventive program and one from an eating disorder intervention, were used to demonstrate the methods presented. In addition, we extend the discussion to a scenario with a three-level treatment arm and an unclustered control arm, and illustrate the procedures for effect size estimation using a hypothetical example of multiple therapy groups of clients clustered within therapists. [ABSTRACT FROM AUTHOR]

Young people are vulnerable to disordered gambling in Chinese societies, such as Macao. This study aimed to assess the extent to which psychological factors (i.e., self-esteem, negative attitudes, subjective norms, and refusal self-efficacy) are associated with disordered gambling relative to two different youth populations. We recruited 809 high school students and 427 undergraduate students in a survey with anonymous, structured questionnaires. As expected, student gamblers reported significantly fewer negative attitudes, more positive subjective norms, and lower refusal self-efficacy than nongamblers. The undergraduate sample reported more positive subjective norms but higher refusal self-efficacy and self-esteem than the high school sample. Refusal self-efficacy was a negative correlate of disordered gambling symptoms in both samples, after gender was controlled for. Moreover, the indirect protective effect of self-esteem on disordered gambling via increasing refusal self-efficacy was also found. The findings suggest that global self-esteem and gambling refusal self-efficacy should be particularly emphasized in preventive interventions for disordered gambling among young gamblers. [ABSTRACT FROM AUTHOR]

Despite the high availability of offline gambling in Macao, China, Internet gambling may remain attractive to many gamblers due to its anonymity and convenience. Given the scarcity of relevant research, this study aims to not only investigate the public attitude and prevalence of Internet gambling but also identify the demographic and psychological characteristics of Internet gamblers in Macao. We recruited 952 community adults with the random residential number dialing method and 427 university students through convenience sampling. Only 5.4 % of the community adult respondents preferred online gambling compared to offline gambling, and the past-year prevalence of online gambling was about 1 %. As hypothesized, Internet gambling was found to be positively associated with pathological gambling in both community and student samples. It was also associated with casino employment across samples. Moreover, we found that male gender, casino employment, materialism, and life dissatisfaction were significant risk factors of pathological gambling among Chinese gamblers. The findings provide insights on future designs of preventive measures and research direction for Internet gambling and pathological gambling in Chinese communities. [ABSTRACT FROM AUTHOR]

Educational researchers commonly use the rule of thumb of “design effect smaller than 2” as the justification of not accounting for the multilevel or clustered structure in their data. The rule, however, has not yet been systematically studied in previous research. In the present study, we generated data from three different models (which differ in the location of the clustering effect). With a 3 (design effect) × 5 (cluster size) × 4 (number of clusters) Monte Carlo simulation study we found that the rule should not be applied when researchers: (a) are interested in the effects of higher-level predictors, or (b) have a cluster size less than 10. Implications of the findings and limitations of the study are discussed. [ABSTRACT FROM PUBLISHER]

As a prerequisite for meaningful comparison of latent variables across multiple populations, measurement invariance or specifically factorial invariance has often been evaluated in social science research. Alongside with the changes in the model chi-square values, the comparative fit index (CFI; Bentler, 1990) is a widely used fit index for evaluating different stages of factorial invariance, including metric invariance (equal factor loadings), scalar invariance (equal intercepts), and strict invariance (equal unique factor variances). Although previous literature generally showed that the CFI performed well for single-group structural equation modeling analyses, its applicability to multiple group analyses such as factorial invariance studies has not been examined. In this study we argue that the commonly used default baseline model for the CFI might not be suitable for factorial invariance studies because (a) it is not nested within the scalar invariance model, and thus (b) the resulting CFI values might not be sensitive to the group differences in the measurement model. We therefore proposed a modified version of the CFI with an alternative (and less restrictive) baseline model that allows observed variables to be correlated. Monte Carlo simulation studies were conducted to evaluate the utility of this modified CFI across various conditions including varying degree of noninvariance and different factorial invariance models. Results showed that the modified CFI outperformed both the conventional CFI and the ΔCFI (Cheung & Rensvold, 2002) in terms of sensitivity to small and medium noninvariance. [ABSTRACT FROM AUTHOR]

Although research on self-efficacy in the gambling literature took place more than 25 years ago, only in the recent decade did researchers attempt to develop valid and reliable measures of gambling-related self-efficacy. Recently Casey et al. (J Gambl Stud 24:229-246, ) developed the Gambling Refusal Self-Efficacy Questionnaire (GRSEQ) in an Australian sample, which is a valuable tool for gambling research. The first objective of this study is to validate the measure in a new sample. Given that previous research on Chinese's gamblers' self-efficacy is lacking, and that related research often used ad-hoc measures of the construct, a second objective of this study is to evaluate whether the GRSEQ is suitable for Chinese people. A sample of 427 university students (56.4 % females, 50.7 % gamblers) answered a questionnaire with measures including the GRSEQ, subjective norms, intentions toward gambling, general self-efficacy, impulsiveness, and pathological gambling symptoms. Evidence was found for the four-factor structure, internal consistency, criterion-related validity, and discriminant validity of the Chinese version of the GRSEQ among this young Chinese group. [ABSTRACT FROM AUTHOR]

This cross-sectional study applied self-determination theory to understand the relationship between coaching behaviors, psychological need satisfaction, and intrinsic motivation among young Chinese athletes from 2 universities in Macao, China (N= 208). In the path model with the demographics adjusted, coaching behaviors (training instruction, democratic behaviors, autocratic behaviors, social support, and positive feedback) and need satisfaction (perceived autonomy, competence, and relatedness) explained 44% of the variance in intrinsic motivation. We also found indirect effects of some coaching behaviors on intrinsic motivation through satisfying the psychological needs. Furthermore, independent self-construal significantly moderated the relationship between perceived relatedness and intrinsic motivation. [ABSTRACT FROM AUTHOR]

This study tested the applicability of the theory of planned behavior (TPB) on gambling intention and involvement in a representative Chinese sample in Macao, recruited by a random residential number dialing method. We successfully interviewed 685 respondents, with about one-third of them reporting that they had participated in gambling activities during the 12 months prior to the interview. The results of structural equation modeling suggested that favorable attitudes toward superstition and techniques, poor sense of perceived behavioral control over gambling refusal, and high gambling intention increased vulnerability to excessive gambling involvement. These findings generally support the efficacy of the TPB in explaining gambling intention and involvement among both Chinese gamblers and non-gamblers. Some practical implications of the findings are discussed within the Chinese context. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of current study was to evaluate change in hours of Applied Behavior Analysis (ABA) therapy utilization for autistic children during the year prior to the COVID-19 pandemic, the first three months of the pandemic (crisis phase), and the following 9 months of the pandemic (mitigation phase). Additionally, this study aimed to evaluate if change in therapy utilization differed based on child race, ethnicity, and primary payer of services. Finally, we aimed to identify potential mechanisms of ABA therapy disruption by interpreting findings using an extended version of Donabedian's structure-process-outcome model. Methods: Retrospective clinical data on client demographics and therapy utilization (n = 283) were collected from ABA clinics in California and analyzed with four piecewise growth multi-level models. Results: We found that therapy utilization dropped during the first three months of the pandemic (-10.65 h/month; p <.001) and increased during the following 9 months (2.39 h/month; p <.001). Moderator analyses revelated that Asian, Non-Latinx and school-district funded children had significantly different trajectories of change in therapy utilization compared to white, non-Latinx participants and private insurance funded participants, respectively. Conclusion: Findings suggest that utilization of ABA therapy was disrupted for a full year following the onset of the COVID-19 pandemic and that child race/ethnicity and primary payer influenced the degree to which autistic children were impacted by service disruption. These findings have implications for autistic children who lost therapy access during key developmental periods and for the ABA care delivery system. [ABSTRACT FROM AUTHOR]

ABSTRACT Although there is a large volume of research on the relationship between social identity and volunteerism, little attention was given to national identity in volunteerism research. This study examined the role of national identity in motivating people to volunteer in the Chinese culture and its role in differentiating those who showed no interest in voluntary work (i.e. non-volunteers) from those who wanted to volunteer but did not (i.e. potential volunteers). Two hundred ninety-nine participants (age, M = 34.14 years) filled out a questionnaire on their demographics, experience of volunteering, intention to volunteer, volunteer motivations, and national identity. Results showed that a stronger national identity was associated with greater volunteer motivations. Mediation analyses further supported the positive indirect effect of national identity on intention to volunteer through strengthening volunteer motivations. Marital status was the only significant factor that differentiated current volunteers from potential volunteers. We concluded that citizens' volunteer motivation increases with national identity, yet concrete measures to bring potential volunteers to actual volunteering need to be further explored. Copyright © 2012 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

The rising economic strength of China over the past decade has aroused concern over the imbalance of global power. Research on Chinese foreign policy has again become of critical importance to the study of international relations and comparative politics. This article will begin with an overview of pertinent studies, categorizing them into cultural and non-cultural approaches, then it will re-examine the methodological problems associated with studying Chinese foreign policy making. Essentially, this article argues that that any research approach can generate methodological mistakes if undertaken without due care and attention. Rather, a multi-approach with emphasis on cultural factors will be a good model for future study. In other words, we have advocated an improved synergy of rational choice, structural, and cultural approaches. In the case study of Chinese foreign policy making between 2010 and 2011, the multi-approach provided a comprehensive picture of the Chinese thinking process behind seemingly irrational or illogical policy choices. It was the rising sense of frustration, the combination of over-confidence and self-doubt, which made foreign policy choices reflect the national interests at certain times and not at other times. [ABSTRACT FROM AUTHOR]

Abstract: The SCO protein from the aerobic bacterium Bacillus subtilis (BsSCO) is involved in the assembly of the cytochrome c oxidase complex, and specifically with the CuA center. BsSCO has been proposed to play various roles in CuA assembly including, the direct delivery of copper ions to the CuA site, and/or maintaining the appropriate redox state of the cysteine ligands during formation of CuA. BsSCO binds copper in both Cu(II) and Cu(I) redox states, but has a million-fold higher affinity for Cu(II). As a prerequisite to kinetic studies, we measured equilibrium stability of oxidized, reduced and Cu(II)-bound BsSCO by chemical and thermal induced denaturation. Oxidized and reduced apo-BsSCO exhibit two-state behavior in both chemical- and thermal-induced unfolding. However, the Cu(II) complex of BsSCO is stable in up to nine molar urea. Thermal or guanidinium-induced unfolding of BsSCO-Cu(II) ensues only as the Cu(II) species is lost. The effect of copper (II) on the folding of BsSCO is complicated by a rapid redox reaction between copper and reduced, denatured BsSCO. When denatured apo-BsSCO is refolded in the presence of copper (II) some of the population is recovered as the BsSCO-Cu(II) complex and some is oxidized indicating that refolding and oxidation are competing processes. The proposed functional roles for BsSCO in vivo require that its cysteine residues are reduced and the presence of copper during folding may be detrimental to BsSCO attaining its functional state. [Copyright &y& Elsevier]

The efforts to promote healthy eating remain ineffective. The inability of these campaigns to counter the marketing resources of the mainstream fast-food chains is among the primary explanations for such failures. However, from the information processing perspective, the message's features may also play a significant role. Cue reactivity research has shown the importance of evaluating visual and verbal cues to avoid undesirable addictive behavioral outcomes. Bridging the evaluative space model (ESM) and the limited capacity model of motivated mediated message processing (LC4MP), the goal of this experiment is to further explore how food-related visual and verbal cues elicit psychophysiological reactivity and how this reactivity in turn affects attitudes toward the promotion. Multilevel modeling results showed that healthy food images paired with encouragement words elicited an uncoupled pattern of the appetitive system activation and received a predominantly positive attitude from audiences (N = 180). Results suggested that thematic congruent messages are preferred in health communication settings. Junk food images, regardless of being paired with encouragement or discouragement verbal cues, should be avoided due to their automatic activation of the appetitive motivational system. [ABSTRACT FROM AUTHOR]

This study examined the accuracy of commonly used model fit indexes in identifying number of factors in multilevel exploratory factor analysis using Monte Carlo simulations. Multilevel data were generated according to different scenarios of factor structures: cluster numbers, cluster sizes, and intraclass correlation coefficient (ICC) conditions. The results showed that when using the model-based approach, most of the commonly used fit indexes could identify the correct number of factors at the lower level, except for the within-level SRMR, AIC, CFI, and the within-level CFI. However, most of the fit indexes extracted fewer factors at the higher level when ICC and sample size were small. When using the design-based approach (assuming the same factor structure across levels), most of the fit indexes were able to identify the correct number of factors, except for SRMR, AIC, and ∆AIC, and CFI. [ABSTRACT FROM AUTHOR]

We investigated the performance of two single indicator methods: latent moderated structural equation (LMS) and reliability-adjusted product indicator (RAPI) methods, on testing interaction effects with congeneric measures, which vary in factor loadings and error variances under a common factor. Additionally, in the simulation study, we compared the performance of four reliability estimates (Cronbach's alpha, omega composite, Coefficient H, and greatest lower bound [GLB]) to adjust for the exogenous composites' measurement errors. Results from the study showed that: while estimating interaction effects with exogenous composites from congeneric measures, the four reliability estimates performed comparably well. Recommendations on the choice of reliability estimates between the LMS and the RAPI methods under different sample sizes and population reliability conditions are further discussed. [ABSTRACT FROM AUTHOR]

• A child specific assessment of teacher self-efficacy was used. • Teachers felt less self-efficacious in relation to children with disabilities. • Child-specific teacher self-efficacy predicted children's print knowledge outcomes. Using data from 73 early childhood special education (ECSE) teachers and 837 preschool children, this study examined whether teachers experienced differences in self-efficacy in teaching children with and without disabilities, as well as whether they experienced differences in self-efficacy when teaching children with different types of disabilities. Additionally, we investigated the relations between ECSE teachers' self-efficacy toward individual children and children's print knowledge, as well as the extent to which children's disability status moderated these relations. Our results showed that ECSE teachers felt less self-efficacious with children with disabilities versus children who are typically developing and experienced the lowest efficacy for teaching children with autism spectrum disorder among children with disabilities. ECSE teachers' self-efficacy in relation to individual children served as a significant predictor of children's print knowledge. Results did not support a moderation role for children's disability status. These findings illustrate the importance of examining teacher self-efficacy at the child level and indicate that higher teacher self-efficacy is beneficial to early literacy development for all children in ECSE classrooms, including those with disabilities. [ABSTRACT FROM AUTHOR]

Key Points: Question: Is there an association between sedentary behavior and risk of all-cause dementia in older adults? Findings: In this retrospective study of prospectively collected data of 49 841 adults participating in the UK Biobank, more time spent in sedentary behaviors (determined through a machine learning–based analysis of wrist-worn accelerometer data) was significantly associated with higher risk of incident dementia. Meaning: Among older adults, more time spent in sedentary behaviors was associated with higher risk of incident all-cause dementia. Importance: Sedentary behavior is associated with cardiometabolic disease and mortality, but its association with dementia is unclear. Objective: To investigate whether accelerometer-assessed sedentary behavior is associated with incident dementia. Design, Setting, and Participants: A retrospective study of prospectively collected data from the UK Biobank including 49 841 adults aged 60 years or older without a diagnosis of dementia at the time of wearing the wrist accelerometer and living in England, Scotland, or Wales. Follow-up began at the time of wearing the accelerometer (February 2013 to December 2015) and continued until September 2021 in England, July 2021 in Scotland, and February 2018 in Wales. Exposures: Mean daily sedentary behavior time (included in the primary analysis) and mean daily sedentary bout length, maximum daily sedentary bout length, and mean number of daily sedentary bouts (included in the secondary analyses) were derived from a machine learning–based analysis of 1 week of wrist-worn accelerometer data. Main Outcome and Measures: Incident all-cause dementia diagnosis from inpatient hospital records and death registry data. Cox proportional hazard models with linear and cubic spline terms were used to assess associations. Results: A total of 49 841 older adults (mean age, 67.19 [SD, 4.29] years; 54.7% were female) were followed up for a mean of 6.72 years (SD, 0.95 years). During this time, 414 individuals were diagnosed with incident all-cause dementia. In the fully adjusted models, there was a significant nonlinear association between time spent in sedentary behavior and incident dementia. Relative to a median of 9.27 hours/d for sedentary behavior, the hazard ratios (HRs) for dementia were 1.08 (95% CI, 1.04-1.12, P <.001) for 10 hours/d, 1.63 (95% CI, 1.35-1.97, P <.001) for 12 hours/d, and 3.21 (95% CI, 2.05-5.04, P <.001) for 15 hours/d. The adjusted incidence rate of dementia per 1000 person-years was 7.49 (95% CI, 7.48-7.49) for 9.27 hours/d of sedentary behavior, 8.06 (95% CI, 7.76-8.36) for 10 hours/d, 12.00 (95% CI, 10.00-14.36) for 12 hours/d, and 22.74 (95% CI, 14.92-34.11) for 15 hours/d. Mean daily sedentary bout length (HR, 1.53 [95% CI, 1.03-2.27], P =.04 and 0.65 [95% CI, 0.04-1.57] more dementia cases per 1000 person-years for a 1-hour increase from the mean of 0.48 hours) and maximum daily sedentary bout length (HR, 1.15 [95% CI, 1.02-1.31], P =.02 and 0.19 [95% CI, 0.02-0.38] more dementia cases per 1000 person-years for a 1-hour increase from the mean of 1.95 hours) were significantly associated with higher risk of incident dementia. The number of sedentary bouts per day was not associated with higher risk of incident dementia (HR, 1.00 [95% CI, 0.99-1.01], P =.89). In the sensitivity analyses, after adjustment for time spent in sedentary behavior, the mean daily sedentary bout length and the maximum daily sedentary bout length were no longer significantly associated with incident dementia. Conclusions and Relevance: Among older adults, more time spent in sedentary behaviors was significantly associated with higher incidence of all-cause dementia. Future research is needed to determine whether the association between sedentary behavior and risk of dementia is causal. This study of prospectively collected data from the UK Biobank investigates whether accelerometer-assessed sedentary behavior is associated with incident dementia in adults aged 60 years or older without a diagnosis of dementia at the time of wearing the wrist accelerometer. [ABSTRACT FROM AUTHOR]

Objective The purpose of this study was to explore racial/ethnic differences in neurobehavioral symptom reporting and symptom validity testing among military veterans with a history of traumatic brain injury (TBI). Method Participants of this observational cross-sectional study (N  = 9,646) were post-deployed Iraq-/Afghanistan-era veterans enrolled in the VA's Million Veteran Program with a clinician-confirmed history of TBI on the Comprehensive TBI Evaluation (CTBIE). Racial/ethnic groups included White, Black, Hispanic, Asian, Multiracial, Another Race, American Indian or Alaska Native, and Native Hawaiian or Other Pacific Islander. Dependent variables included neurobehavioral symptom domains and symptom validity assessed via the Neurobehavioral Symptom Inventory (NSI) and Validity-10, respectively. Results Chi-square analyses showed significant racial/ethnic group differences for vestibular, somatic/sensory, and affective symptoms as well as for all Validity-10 cutoff scores examined (≥33, ≥27, ≥26, >22, ≥22, ≥13, and ≥7). Follow-up analyses compared all racial/ethnic groups to one another, adjusting for sociodemographic- and injury-related characteristics. These analyses revealed that the affective symptom domain and the Validity-10 cutoff of ≥13 revealed the greatest number of racial/ethnic differences. Conclusions Results showed significant racial/ethnic group differences on neurobehavioral symptom domains and symptom validity testing among veterans who completed the CTBIE. An enhanced understanding of how symptoms vary by race/ethnicity is vital so that clinical care can be appropriately tailored to the unique needs of all veterans. Results highlight the importance of establishing measurement invariance of the NSI across race/ethnicity and underscore the need for ongoing research to determine the most appropriate Validity-10 cutoff score(s) to use across racially/ethnically diverse veterans. [ABSTRACT FROM AUTHOR]

Path models with observed composites based on multiple items (e.g., mean or sum score of the items) are commonly used to test interaction effects. Under this practice, researchers generally assume that the observed composites are measured without errors. In this study, we reviewed and evaluated two alternative methods within the structural equation modeling (SEM) framework, namely, the reliability-adjusted product indicator (RAPI) method and the latent moderated structural equations (LMS) method, which can both flexibly take into account measurement errors. Results showed that both these methods generally produced unbiased estimates of the interaction effects. On the other hand, the path model—without considering measurement errors—led to substantial bias and a low confidence interval coverage rate of nonzero interaction effects. Other findings and implications for future studies are discussed. [ABSTRACT FROM AUTHOR]

Recent research suggests human life history strategy (LHS) may be subsumed by multiple dimensions, including mating competition and Super-K, rather than one. In this study, we test whether a two-dimensional structure best fit data from a predominantly urban sample of young adults ages 18–24. We also test whether latent life history dimensions are associated with environmental harshness and unpredictability as predicted by life history theory. Results provide evidence that a two-dimensional model best fit the data. Furthermore, a moderate inverse residual correlation between mating competition and Super-K was found, consistent with a life history trade-off. Our findings suggest that parental socioeconomic status may enhance investment in mating competition, that harshness might persist into young adulthood as an important correlate of LHS, and that unpredictability may not have significant effects in young adulthood. These findings further support the contention that human LHS is multidimensional and environmental effects on LHS are more complex than previously suggested. The model presented provides a parsimonious explanation of an array of human behaviors and traits and can be used to inform public health initiatives, particularly with respect to the potential impact of environmental interventions. [ABSTRACT FROM AUTHOR]

This article attends to recent discussions of validity in psychometric research on human life history strategy (LHS), provides a constructive critique of the extant literature, and describes strategies for improving construct validity. To place the psychometric study of human LHS on more solid ground, our review indicates that researchers should (a) use approaches to psychometric modeling that are consistent with their philosophies of measurement, (b) confirm the dimensionality of life history indicators, and (c) establish measurement invariance for at least a subset of indicators. Because we see confirming the dimensionality of life history indicators as the next step toward placing the psychometrics of human LHS on more solid ground, we use nationally representative data and structural equation modeling to test the structure of middle adult life history indicators. We found statistically independent mating competition and Super-K dimensions and the effects of parental harshness and childhood unpredictability on Super-K were consistent with past research. However, childhood socioeconomic status had a moderate positive effect on mating competition and no effect on Super-K, while unpredictability did not predict mating competition. We conclude that human LHS is more complex than previously suggested—there does not seem to be a single dimension of human LHS among Western adults and the effects of environmental components seem to vary between mating competition and Super-K. [ABSTRACT FROM AUTHOR]

Daily emotion dynamics provide valuable information about individuals' emotion processes as they go about their lives. Emotion dynamics such as emotion levels (mean), emotion variability (degree of fluctuation), and emotion network density (strength of temporal connections among emotions) are associated with risks for various psychopathology in youth and adults. Prior work has shown that caregivers and friends play crucial socializing roles in adolescent emotional well‐being, but less is known about their roles in daily emotion dynamics. This study examined whether caregiver emotion coaching, caregiver‐adolescent closeness, and friendship quality were associated with adolescents' emotion levels, emotion variability, and emotion network density. Further, we examined whether caregiver‐adolescent closeness moderated the associations between coaching and emotion dynamics. Participants were 150 adolescents (61% girls; Mage = 14.75) and one of their caregivers (95% female; Mage = 43.35) who completed a baseline survey and 21 daily surveys. Results showed that caregiver emotion coaching interacted with caregiver‐adolescent closeness in predicting emotion levels and variability. Specifically, when closeness was higher, emotion coaching was significantly associated with lower sadness and anger levels, higher happiness levels, and lower happiness variability. Caregiver emotion coaching, independent of closeness, was also associated with lower anxiety levels, lower sadness variability, and lower emotion network density. Friendship quality was significantly associated with lower levels of sadness, anxiety, and anger, higher levels of happiness, and lower variability in anxiety and anger. These findings suggest that caregivers and friends are central to everyday emotion levels and variability and a more flexible emotion system in adolescents. [ABSTRACT FROM AUTHOR]

The present study examined the association between help-seeking public stigma and help-seeking self-stigma (i.e., internalization of stigma) and the relative association of both types of stigma with help-seeking attitude and intention using a full-information meta-analytic structural equation modeling approach. We also investigated the moderating effect of gender, age, collectivism, and social group in the internalization process. Results from 115 independent samples containing data from 54,793 individuals showed that public stigma of help-seeking was strongly and positively associated with self-stigma of help-seeking. Moreover, after controlling for the effect of each other, self-stigma, but not public stigma, remained significantly associated with help-seeking attitude and help-seeking intention. Gender, age, collectivism, and social group did not significantly moderate the association between public and self-stigma. The findings highlight that people who perceive more stigma of help-seeking from others tend to have higher levels of self-stigma. Compared with help-seeking public stigma, help-seeking self-stigma might have a larger impact on one's help-seeking attitude and intention. Help-seeking promotion campaigns should be devised to tackle both types of stigma to foster positive help-seeking attitude and intention. [ABSTRACT FROM AUTHOR]

Sedentary behavior (SB) is associated with cardiometabolic disease and mortality, but its association with dementia is currently unclear. This study investigates whether SB is associated with incident dementia regardless of engagement in physical activity (PA). A total of 146,651 participants from the UK Biobank who were 60 years or older and did not have a diagnosis of dementia (mean [SD] age: 64.59 [2.84] years) were included. Selfreported leisure-time SBs were divided into two domains: time spent watching television (TV) or time spent using a computer. A total of 3,507 individuals were diagnosed with all-cause dementia over a mean follow-up of 11.87 (±1.17) years. In models adjusted for a wide range of covariates, including time spent in PA, time spent watching TV was associated with increased risk of incident dementia (HR [95% CI] = 1.24 [1.15 to 1.32]) and time spent using a computer was associated with decreased risk of incident dementia (HR [95% CI] = 0.85 [0.81 to 0.90]). In joint associations with PA, TV time and computer time remained significantly associated with dementia risk at all PA levels. Reducing time spent in cognitively passive SB (i.e., TV time) and increasing time spent in cognitively active SB (i.e., computer time) may be effective behavioral modification targets for reducing risk of dementia regardless of engagement in PA. [ABSTRACT FROM AUTHOR]

Highlights: [•] Intracellular ROS formation is an event upstream of the lipid peroxidation which results in cell membrane instability. [•] Cell membrane instability leads to an innate autoimmune response by natural IgM and complement. [•] Trehalose protects against I/R injury by blocking IgM-mediated complement activation. [Copyright &y& Elsevier]

This meta‐analysis synthesizes the empirical data on problem behaviors among foreign‐ (G1) and U.S‐born (G2+) youth and explores the effects of immigrant status on youth internalizing and externalizing problems. A random effects meta‐regression with robust variance estimates summarized effect sizes for internalizing and externalizing problems across 91 studies (N = 179,315, Mage = 13.98). Results indicated that G1 youth reported significantly more internalizing problems (g =.06), and fewer externalizing problems than G2+ youth (g = −.06). Gender and sample type moderated the effects. The findings provide a first‐step toward reconciling mixed support for the immigrant paradox by identifying for whom and under what conditions the immigrant experience serves as a risk or protective factor for youth. [ABSTRACT FROM AUTHOR]

Objective: We investigated whether men's social confidence in an initial, opposite‐sex chatting context can be improved through a video tutorial and the extent to which being perceived as socially confident results in being seen as more romantically desirable and worthy of future contact. Method: Women chatted with men who had received or not received a tutorial on how to handle speed‐dating chats (Study 1: N = 129; Study 2: N = 60) or with male targets selected for having high versus moderate confidence in handling initial, opposite‐sex encounters (Study 3: N = 46). Results: Tutorial‐trained men felt more confident going into the chats and they, as well as male targets selected for their confidence, were perceived by female chat partners to be higher in social confidence, status, and dominance. However, only perceptions of social confidence were further associated with being perceived as more romantically desirable (as a short‐term mate) and worthy of future contact. Conclusions: Findings indicate that social confidence is trainable and that other‐perceived social confidence can impact the outcomes of social interactions. [ABSTRACT FROM AUTHOR]

Background and aims: Prison-based HCV treatment rates remain low due to multiple barriers, including accessing transient elastography for cirrhosis determination. The AST-to-platelet ratio index (APRI) and FIB-4 scores have excellent negative predictive value (NPV) in hospital cohorts to exclude cirrhosis. We investigated their performance in a large cohort of prisoners with HCV infection. Methods: This was a retrospective cohort study of participants assessed by a prison-based hepatitis program. The sensitivity, specificity, NPV and positive predictive value (PPV) of APRI and FIB-4 for cirrhosis were then analysed, with transient elastography as the reference standard. The utility of age thresholds as a trigger for transient elastography was also explored. Results: Data from 1007 prisoners were included. The median age was 41, 89% were male, and 12% had cirrhosis. An APRI cut-off of 1.0 and FIB-4 cut-off of 1.45 had NPVs for cirrhosis of 96.1% and 96.6%, respectively, and if used to triage prisoners for transient elastography, could reduce the need for this investigation by 71%. The PPVs of APRI and FIB-4 for cirrhosis at these cut-offs were low. Age ≤35 years alone had a NPV for cirrhosis of 96.5%. In those >35 years, the APRI cut-off of 1.0 alone had a high NPV >95%. Conclusion: APRI and FIB-4 scores can reliably exclude cirrhosis in prisoners and reduce requirement for transient elastography. This finding will simplify the cascade of care for prisoners living with hepatitis C. [ABSTRACT FROM AUTHOR]

BACKGROUND: Family involvement during the transition process is crucial. However, culturally and linguistically diverse (CLD) families report barriers to effective transition planning related to cultural misunderstandings with educators. Professionals need to be culturally competent when interacting with CLD families and youth. OBJECTIVE: The objective was to revise a CLD Transition Knowledge and Skills (CLDTKS) Evaluation Instrument and have special educators use the instrument to evaluate the levels of CLD transition knowledge and skills of their colleagues. METHODS: The CLDTKS Evaluation Instrument was revised following expert review. Participants included 206 special educators. Exploratory factor analysis was used to explore the factor structure of the instrument. Structural equation modeling was used to test construct validity, and confirmatory factor analyses were performed. Means were computed for all factors. RESULTS: The CLDTKS Evaluation Instrument consisted of four scales: Cultural Characteristics Related to Active Family Involvement, Family Norms and Communication Styles, Individualized Education Program (IEP) Meetings and Transition Policies, and Family Legal Status and Associated Prejudice. For all factors, there was a lower mean on skills than on knowledge. CONCLUSIONS: The CLDTKS Evaluation Instrument is a valid and reliable measure for evaluating transition knowledge and skills related to working with CLD youth and families, and it can be used for research and professional development needs. [ABSTRACT FROM AUTHOR]

Background: A clinical diagnosis of cognitive impairment is traditionally based on a single cognitive exam, but serial cognitive testing can be sensitive to subtle cognitive changes in asymptomatic individuals and inform cognitive trajectory.Objective: We evaluated the prognostic utility of identifying longitudinal neuropsychological decline along with single cognitive exam and Alzheimer's disease (AD) cerebrospinal fluid (CSF) biomarkers in predicting dementia. We also examined brain volumetric differences based on decline trajectories.Method: Regression models quantified 12-month neuropsychological decline relative to normative expectations among non-demented older adults (N = 1,074). Progression to dementia over follow-up (18-120 months) was diagnosed using independent modes of assessment.Results: In Cox regression models controlling for age, sex, education, apolipoprotein E4, and baseline cognitive diagnosis, neuropsychological decline predicted increased dementia risk, χ2 = 69.861, p < 0.001, odds ratio = 2.841, even after correction for CSF biomarkers (amyloid-β, phosphorylated tau, total tau), χ2 = 26.365, p < 0.001, odds ratio = 2.283. Voxel-based morphometry analysis indicated smaller hippocampal and medial temporal volume in participants with neuropsychological decline.Conclusions: Longitudinal diagnosis of neuropsychological decline improved prognostic accuracy beyond single cognitive exam diagnoses and AD CSF biomarkers, even in asymptomatic older adults. Older adults with a trajectory of neuropsychological decline exhibit smaller medial temporal and hippocampal brain volume. Longitudinal diagnostic approaches may benefit selection and randomization procedures for AD clinical trials in asymptomatic individuals. [ABSTRACT FROM AUTHOR]

There is evidence that men's testosterone levels decline across the transition to fatherhood and that this decline may reflect fathers' investment in the new family. There is also emerging evidence that cohabiting couples show synchrony or within-couple associations in testosterone levels during the perinatal period. Hormonal synchrony may act as a mechanism that supports fathers' biological preparation for parenthood, perhaps by facilitating perinatal declines in paternal testosterone. However, few studies have examined testosterone synchrony and change within couples. A sample of 97 U.S. couples expecting their first child provided testosterone samples during pregnancy, and of those couples, 78 couples also provided testosterone at seven months postpartum. Couples reported on relationship satisfaction both at prenatal and postpartum visits. Bayesian multilevel modeling revealed within-couple testosterone synchrony both during pregnancy and postpartum. Testosterone synchrony during pregnancy predicted a greater drop in fathers' testosterone levels from prenatal to postpartum and higher paternal postpartum relationship quality. Fathers' lower prenatal testosterone levels also subsequently predicted higher self-reported postpartum relationship quality for both parents. In sum, this study finds that couples' testosterone levels show synchrony across the transition to parenthood in ways that are associated with couple relationship quality and men's neuroendocrine preparation for fatherhood. • Higher prenatal testosterone synchrony predicted a greater drop in fathers' testosterone from prenatal to postpartum • Higher prenatal testosterone synchrony predicted fathers' higher postpartum relationship quality [ABSTRACT FROM AUTHOR]