Phonological working memory and central executive function differ in children with typical development and dyslexia.

The primary purpose of this study was to compare the working memory performance of monolingual English-speaking second- grade children with dyslexia (N = 82) to second-grade children with typical development (N = 167). Prior to making group comparisons, it is important to demonstrate invariance between working memory models in both groups or between-group comparisons would not be valid. Thus, we completed invariance testing using a model of working memory that had been validated for children with typical development (Gray et al., 2017) to see if it was valid for children with dyslexia. We tested three types of invariance: configural (does the model test the same constructs?), metric (are the factor loadings equivalent?), and scalar (are the item intercepts the same?). Group comparisons favoured the children with typical development across all three working memory factors. However, differences in the Focus-of-Attention/Visuospatial factor could be explained by group differences in non-verbal intelligence and language skills. In contrast, differences in the Phonological and Central Executive working memory factors remained, even after accounting for non-verbal intelligence and language. Results highlight the need for researchers and educators to attend not only to the phonological aspects of working memory in children with dyslexia, but also to central executive function.

Different Roles of Prior Distributions in the Single Mediator Model with Latent Variables.

In manifest variable models, Bayesian methods for mediation analysis can have better statistical properties than commonly used frequentist methods. However, with latent variables, Bayesian mediation analysis with diffuse priors can yield worse statistical properties than frequentist methods, and no study to date has evaluated the impact of informative priors on statistical properties of point and interval summaries of the mediated effect. This article describes the first examination of using fully conjugate and informative (accurate and inaccurate) priors in Bayesian mediation analysis with latent variables. Results suggest that fully conjugate priors and informative priors with the same relative prior sample sizes have notably different effects at N = 200 and 400, than at N = 50 and 100. Consequences of a small amount of inaccuracy in priors for loadings can be alleviated by making the prior less informative, whereas the same is not always true of inaccuracy in priors for structural paths. Finally, the consequences of using informative priors depend on the inferential goals of the analysis: inaccurate priors are more detrimental for accurately estimating the mediated effect than for evaluating whether the mediated effect is nonzero. Recommendations are provided about when to gainfully employ Bayesian mediation analysis with latent variables.

Most chilblains observed during the COVID-19 outbreak occur in patients who are negative for COVID-19 on polymerase chain reaction and serology testing.

BACKGROUND: Acral lesions, mainly chilblains, are the most frequently reported cutaneous lesions associated with COVID-19. In more than 80% of patients tested, nasopharyngeal swabs were negative on reverse transcription polymerase chain reaction (RT-PCR) for SARS-CoV-2 when performed, and serology was generally not performed. METHODS: A national survey was launched on 30 March 2020 by the French Society of Dermatology asking physicians to report cases of skin manifestations in patients with suspected or confirmed COVID-19 by using a standardized questionnaire. We report the results for acral manifestations. RESULTS: We collected 311 cases of acral manifestations [58.5% women, median age 25.7 years (range 18-39)]. The most frequent clinical presentation (65%) was typical chilblains. In total, 93 cases (30%) showed clinical suspicion of COVID-19, 67 (22%) had only less specific infectious symptoms and 151 (49%) had no clinical signs preceding or during the course of acral lesions. Histology of skin biopsies was consistent with chilblains. Overall, 12 patients showed significant immunological abnormalities. Of the 150 (48%) patients who were tested, 10 patients were positive. Seven of 121 (6%) RT-PCR-tested patients were positive for SARS-CoV-2, and five of 75 (7%) serology-tested patients had IgG anti-SARS-CoV-2. Tested/untested patients or those with/without confirmed COVID-19 did not differ in age, sex, history or acral lesion clinical characteristics. CONCLUSIONS: The results of this survey do not rule out that SARS-CoV-2 could be directly responsible for some cases of chilblains, but we found no evidence of SARS-CoV-2 infection in the large majority of patients with acral lesions during the COVID-19 lockdown period in France. What is already known about this topic? About 1000 cases of acral lesions, mainly chilblains, were reported during the COVID-19 outbreak. Chilblains were reported to occur in young people within 2 weeks of infectious signs, which were mild when present. Most cases did not have COVID-19 confirmed by reverse transcription polymerase chain reaction (RT-PCR), and few serology results were available. What does this study add? Among 311 patients with acral lesions, mainly chilblains, during the COVID-19 lockdown period in France, the majority of patients tested had no evidence of SARS-CoV-2 infection. Overall, 70 of 75 patients were seronegative for SARS-Cov-2 serology and 114 of 121 patients were negative for SARS-CoV-2 RT-PCR.

Dynamic Bayesian Network Modeling of Game-Based Diagnostic Assessments.

Digital games offer an appealing environment for assessing student proficiencies, including skills and misconceptions in a diagnostic setting. This paper proposes a dynamic Bayesian network modeling approach for observations of student performance from an educational video game. Drawing from and advancing methods in dynamic Bayesian networks, cognitive diagnostic modeling, and analysis of process data, a Bayesian approach to model construction, calibration, and use in facilitating inferences about students on the fly is described, and implemented in the context of an educational video game.

Tests of Simple Slopes in Multiple Regression Models with an Interaction: Comparison of Four Approaches.

In multiple regression researchers often follow up significant tests of the interaction between continuous predictors X and Z with tests of the simple slope of Y on X at different sample-estimated values of the moderator Z (e.g., ±1 SD from the mean of Z). We show analytically that when X and Z are randomly sampled from the population, the variance expression of the simple slope at sample-estimated values of Z differs from the traditional variance expression obtained when the values of X and Z are fixed. A simulation study using randomly sampled predictors compared four approaches: (a) the Aiken and West ( 1991 ) test of simple slopes at fixed population values of Z, (b) the Aiken and West test at sample-estimated values of Z, (c) a 95% percentile bootstrap confidence interval approach, and (d) a fully Bayesian approach with diffuse priors. The results showed that approach (b) led to inflated Type 1 error rates and 95% confidence intervals with inadequate coverage rates, whereas other approaches maintained acceptable Type 1 error rates and adequate coverage of confidence intervals. Approach (c) had asymmetric rejection rates at small sample sizes. We used an empirical data set to illustrate these approaches.

Parenting of siblings in Latinx families during middle childhood.

Parents' management of their children's sibling relationships, or sibling-focused parenting, has substantial theoretical and practical importance but is rarely studied. This study's goals were to describe dimensions of sibling-focused parenting and to examine sociocultural resources and challenges as potential correlates among Latinx mothers and fathers in 262 families with two children in middle childhood. Families were recruited from 11 public elementary schools, and caregivers (248 mother figures; 118 father figures) participated in a home visit and phone interviews at the onset of the study. Sibling-focused parenting included three dimensions: positive guidance (10 items), nonintervention (four items), and authoritarian control (five items). Parents rated positive guidance as their most frequent strategy, and comparisons of mothers and fathers from the same families revealed that mothers engaged in more sibling-focused parenting overall than fathers. Regarding correlates, mothers' familism values and mothers' and fathers' family cohesion reports were associated with more positive guidance and mothers' cohesion was negatively related to nonintervention in sibling conflicts. For mothers only, parenting stress was linked to all three dimensions of sibling-focused parenting-negatively to guidance and positively to authoritarian control and nonintervention; maternal depressive symptoms were positively linked to authoritarian control. Economic hardship was not a significant correlate of any dimension. Findings suggest that sibling-focused parenting is a key domain of parenting in need of further research. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Perspectives on Bayesian inference and their implications for data analysis.

Use of Bayesian methods has proliferated in recent years as technological and software developments have made Bayesian methods more approachable for researchers working with empirical data. Connected with the increased usage of Bayesian methods in empirical studies is a corresponding increase in recommendations and best practices for Bayesian methods. However, given the extensive scope of Bayes, theorem, there are various compelling perspectives one could adopt for its application. This paper first describes five different perspectives, including examples of different methodologies that are aligned within these perspectives. We then discuss how the different perspectives can have implications for modeling and reporting practices, such that approaches and recommendations that are perfectly reasonable under one perspective might be unreasonable when viewed from another perspective. The ultimate goal is to show the heterogeneity of defensible practices in Bayesian methods and to foster a greater appreciation for the variety of orientations that exist. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

"More is better" or "better near the middle"? A U.S.-based individual participant data meta-analysis of socioeconomic status and depressive symptoms.

Socioeconomic status (SES) is a widely researched construct in developmental science, yet less is known concerning relations between SES and adaptive behavior. Specifically, is the relation linear, with higher SES associated with better outcomes, or does the direction of association change at different levels of SES? Our aim was to examine linear ("more is better") and quadratic ("better near the middle") associations between components of SES (i.e., income, years of education, occupational status/prestige) and depressive symptoms (Center for Epidemiologic Studies-Depression Scale), and to explore moderation by developmental period (adolescence, young, middle, and older adulthood), gender/sex (female, male), and race/ethnicity (Asian American, Black, Latinx, multiracial, Native American, White). We hypothesized that there would be more support for a model containing quadratic associations. We conducted a two-stage meta-analytic structural equation model of 60 data sets (27,242 correlations, 498,179 participants) within the United States, accounting for dependencies between correlations, which were identified via the Interuniversity Consortium for Political and Social Research and handled using a two-step approach. Income was quadratically associated with depressive symptoms, but the quadratic model did not explain more variance in depressive symptoms than the linear model. Developmental period and race/ethnicity moderated the associations: Income was quadratically associated with depressive symptoms among middle-aged adults, and years of education were quadratically associated with depressive symptoms among White samples. Our findings suggest that researchers and clinical practitioners should consider the elevated risk of depressive symptoms for individuals from low and high-income backgrounds in the United States. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Considerations for Fitting Dynamic Bayesian Networks With Latent Variables: A Monte Carlo Study.

Dynamic Bayesian networks (DBNs; Reye, 2004) are a promising tool for modeling student proficiency under rich measurement scenarios (Reichenberg, 2018). These scenarios often present assessment conditions far more complex than what is seen with more traditional assessments and require assessment arguments and psychometric models capable of integrating those complexities. Unfortunately, DBNs remain understudied and their psychometric properties relatively unknown. The current work aimed at exploring the properties of DBNs under a variety of realistic psychometric conditions. A Monte Carlo simulation study was conducted in order to evaluate parameter recovery for DBNs using maximum likelihood estimation. Manipulated factors included sample size, measurement quality, test length, the number of measurement occasions. Results suggested that measurement quality has the most prominent impact on estimation quality with more distinct performance categories yielding better estimation. From a practical perspective, parameter recovery appeared to be sufficient with samples as low as N = 400 as long as measurement quality was not poor and at least three items were present at each measurement occasion. Tests consisting of only a single item required exceptional measurement quality in order to adequately recover model parameters.

Working Memory Predicts New Word Learning Over and Above Existing Vocabulary and Nonverbal IQ.

PURPOSE: The purpose of this study was to use an established model of working memory in children to predict an established model of word learning to determine whether working memory explained word learning variance over and above the contributions of expressive vocabulary and nonverbal IQ. METHOD: One hundred sixty-seven English-speaking second graders (7- to 8-year-olds) with typical development from two states participated. They completed a comprehensive battery of working memory assessments and six word learning tasks that assessed the creation, storage, retrieval, and production of phonological and semantic representations of novel nouns and verbs and the ability to link those representations. RESULTS: A structural equation model with expressive vocabulary, nonverbal IQ, and three working memory factors predicting two word learning factors fit the data well. When working memory factors were entered as predictors after expressive vocabulary and nonverbal IQ, they explained 45% of the variance in the phonological word learning factor and 17% of the variance in the semantic word learning factor. Thus, working memory explained a significant amount of word learning variance over and above expressive vocabulary and nonverbal IQ. CONCLUSION: Results show that working memory is a significant predictor of dynamic word learning over and above the contributions of expressive vocabulary and nonverbal IQ, suggesting that a comprehensive working memory assessment has the potential to identify sources of word learning difficulties and to tailor word learning interventions to a child's working memory strengths and weaknesses. SUPPLEMENTAL MATERIAL: https://doi.org/10.23641/asha.19125911.

A Systematic Overview of Meta-Analyses on Socioeconomic Status, Cognitive Ability, and Achievement: The Need to Focus on Specific Pathways.

Meta-analyses on the relation between socioeconomic status (SES) and performance on measures of cognitive ability and achievement arrive at the same general conclusion of a small to medium association. Advancements in methods make possible for meta-analyses to examine specific pathways linking SES to cognitive ability and achievement, as well as the moderators of these pathways. In this study, we conducted a systematic overview of meta-analyses on SES to address three research questions: 1) what is the direction and overall strength of association between SES and performance on measures of cognitive ability and achievement, and how precise are the effect sizes reported? 2) to what extent have meta-analyses examined moderation by components of SES, age, sex, and race/ethnicity? and 3) to what extent have meta-analyses examined mechanisms linking SES to cognitive ability and achievement? We conducted a systematic search using online archives (i.e., PsycINFO, ERIC, PubMed, Sociological Abstracts, and Web of Science), searching issues in Psychological Bulletin and Review of Educational Research, and examining references and citations. We identified 14 meta-analyses published between 1982 and 2019. These meta-analyses consistently reported positive associations of small to medium magnitude, indicating that SES is a meaningful contributor to the development of cognitive ability and achievement. Fewer meta-analyses reported evidence of moderation by age, sex, and race/ethnicity. None of the meta-analyses directly examined mechanisms, but provided evidence of possible mechanisms for future research. We suggest that meta-analyses can increase their contribution to future research, interventions, and policy by narrowing their focus on specific pathways.

Socioeconomic status and depressive symptoms: An individual-participant data meta-analysis on range restriction and measurement in the United States.

INTRODUCTION: The association between socioeconomic status (SES) and depressive symptoms is well documented, yet less attention has been paid to the methodological factors contributing to between-study variability. We examined the moderating role of range restriction and the depressive-symptom measurement instrument used in estimating the correlation between components of SES and depressive symptoms. METHODS: We conducted an individual participant data meta-analysis of nationally-representative, public-access datasets in the United States. We identified 123 individual datasets with a total of 1,655,991 participants (56.8 % female, mean age = 40.33). RESULTS: The presence of range restriction was associated with larger correlations between income and depressive symptoms and with smaller correlations between years of education and depressive symptoms. The measurement instrument of depressive symptoms moderated the association for income, years of education, and occupational status/prestige. The Center for Epidemiological Studies-Depression scale consistently produced larger correlations. Higher measurement reliability was also associated with larger correlations. LIMITATIONS: This study was not a comprehensive review of all measurement instruments of depressive symptoms, focused on datasets from the United States, and did not examine the moderating role of sample characteristics. DISCUSSION: Methodological characteristics, including range restriction of SES and instrument of depressive symptoms, meaningfully influence the observed magnitude of association between SES and depressive symptoms. Clinicians and researchers designing future studies should consider which instrument of depressive symptoms is suitable for their purpose and population.

Knowledge about epilepsy and confidence in instructing students with epilepsy: teachers' responses to a new scale.

Knowledgeable and confident teachers are crucial for students with epilepsy. In this study, 91 current teachers of a student with epilepsy (CTs) and 203 teachers in general (TiGs) were surveyed using a new scale. CTs knew more school-relevant epilepsy facts than TiGs, even after controlling for special education background, F(1, 293)=5.75, P=0.017, η(2)=0.02. Both groups of teachers, however, knew less than one-half of the facts (means=10.6 [CTs] 8.7 [TiGs] of 25 items). CTs also expressed greater confidence than TiGs in their ability to meet an array of instructional, safety, and psychosocial requirements, even when between-group differences in teachers' background in special education were controlled, F(1, 293)=34.97, P<0.001, η(2)=0.11. Still, neither group communicated a high absolute level of confidence. As expected, more knowledgeable teachers expressed greater confidence (r=0.43, P<0.001). Results suggest that some facts about epilepsy require additional dissemination to educators.

A generalized dimensionality discrepancy measure for dimensionality assessment in multidimensional item response theory.

A generalized dimensionality discrepancy measure is introduced to facilitate a critique of dimensionality assumptions in multidimensional item response models. Connections between dimensionality and local independence motivate the development of the discrepancy measure from a conditional covariance theory perspective. A simulation study and a real-data analysis demonstrate the utility of the discrepancy measure's application at multiple levels of analysis in a posterior predictive model checking framework.

Incorporating Uncertainty Into Parallel Analysis for Choosing the Number of Factors via Bayesian Methods.

A number of psychometricians have suggested that parallel analysis (PA) tends to yield more accurate results in determining the number of factors in comparison with other statistical methods. Nevertheless, all too often PA can suggest an incorrect number of factors, particularly in statistically unfavorable conditions (e.g., small sample sizes and low factor loadings). Because of this, researchers have recommended using multiple methods to make judgments about the number of factors to extract. Implicit in this recommendation is that, when the number of factors is chosen based on PA, uncertainty nevertheless exists. We propose a Bayesian parallel analysis (B-PA) method to incorporate the uncertainty with decisions about the number of factors. B-PA yields a probability distribution for the various possible numbers of factors. We implement and compare B-PA with a frequentist approach, revised parallel analysis (R-PA), in the contexts of real and simulated data. Results show that B-PA provides relevant information regarding the uncertainty in determining the number of factors, particularly under conditions with small sample sizes, low factor loadings, and less distinguishable factors. Even if the indicated number of factors with the highest probability is incorrect, B-PA can show a sizable probability of retaining the correct number of factors. Interestingly, when the mode of the distribution of the probabilities associated with different numbers of factors was treated as the number of factors to retain, B-PA was somewhat more accurate than R-PA in a majority of the conditions.

The Structure of Word Learning in Young School-Age Children.

Purpose We investigated four theoretically based latent variable models of word learning in young school-age children. Method One hundred sixty-seven English-speaking second graders with typical development from three U.S. states participated. They completed five different tasks designed to assess children's creation, storage, retrieval, and production of the phonological and semantic representations of novel words and their ability to link those representations. The tasks encompassed the triggering and configuration stages of word learning. Results Results showed that a latent variable model with separate phonological and semantic factors and linking indicators constrained to load on the phonological factor best fit the data. Discussion The structure of word learning during triggering and configuration reflects separate but related phonological and semantic factors. We did not find evidence for a unidimensional latent variable model of word learning or for separate receptive and expressive word learning factors. In future studies, it will be interesting to determine whether the structure of word learning differs during the engagement stage of word learning when phonological and semantic representations, as well as the links between them, are sufficiently strong to affect other words in the lexicon.

[Efficacy of TNF-alpha antagonists for plaque-type psoriasis: a systematic review and graphical presentation]. / Efficacité des anti-TNF-alpha dans le psoriasis: revue systématique et représentation graphique.

BACKGROUND: Numerous studies investigating the efficacy of TNF-alpha antagonists in moderate-to-severe plaque-type psoriasis have been published. We present a graphic synthesis of efficacy data based on a systematic review of the published studies. METHODS: The Medline, Embase and Cochrane Library bibliographic databases were searched for studies based on the following selection criteria: 1. Original studies, 2. Using infliximab, etanercept or adalimumab as the sole systemic treatment for plaque-type cutaneous psoriasis, 3. Minimum follow-up of 10 weeks, 4. Use of the PASI75 index (improvement of at least 75% from baseline PASI score) as an endpoint. Twenty-one articles were selected and PASI75 scores and corresponding 95% confidence intervals were calculated at three, six and 12 months. RESULTS: At M3, success rates were about 80% with infliximab and adalimumab once-weekly, around 50% with etanercept 50mg twice-weekly and adalimumab fortnightly; and 30% with etanercept 25mg twice-weekly. Maintenance regimens after three months ensured success rates above 50% with all three treatments, although the long-term results were based on fewer studies. CONCLUSION: Our graphic synthesis and tolerance data for the three drugs should guide clinicians in their therapeutic choices in moderate-to-severe plaque-type psoriasis. Additional studies with better reporting of loss to follow-up are needed to better assess the long-term efficacy of these drugs.

A fully conditional specification approach to multilevel imputation of categorical and continuous variables.

Specialized imputation routines for multilevel data are widely available in software packages, but these methods are generally not equipped to handle a wide range of complexities that are typical of behavioral science data. In particular, existing imputation schemes differ in their ability to handle random slopes, categorical variables, differential relations at Level-1 and Level-2, and incomplete Level-2 variables. Given the limitations of existing imputation tools, the purpose of this manuscript is to describe a flexible imputation approach that can accommodate a diverse set of 2-level analysis problems that includes any of the aforementioned features. The procedure employs a fully conditional specification (also known as chained equations) approach with a latent variable formulation for handling incomplete categorical variables. Computer simulations suggest that the proposed procedure works quite well, with trivial biases in most cases. We provide a software program that implements the imputation strategy, and we use an artificial data set to illustrate its use. (PsycINFO Database Record