Using a person-centered analysis to examine second-grade outcomes of a universal SEL program.

Effective universal social skills programs are intended to facilitate the development of students' social competencies and enhance classroom learning. As such, the present study sought to provide additional insights and a more nuanced understanding of the impacts of one such universal program, the Social Skills Improvement System Classwide Intervention Program (SSIS-CIP; Elliott & Gresham, 2007). Using a person-centered data analytic approach, we evaluated SSIS-CIP's association with heterogeneity in patterns of change on social skills and problem behavior measures over time for second-grade students. Specifically, latent profile analysis yielded three consistent behavior profiles over time: high social competence and low problem behavior, moderate social competence and low problem behavior, and low social competence and high problem behavior. Latent transition analysis suggested that students who were exposed to the SSIS-CIP program were more likely to stay in the same profile or transfer to a more positive behavioral profile than students in the comparison condition. The SSIS-CIP also appeared to benefit those with lower levels of skills and likely in need of intervention. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Bridging Big Data: Procedures for Combining Non-equivalent Cognitive Measures from the ENIGMA Consortium.

Investigators in neuroscience have turned to Big Data to address replication and reliability issues by increasing sample sizes, statistical power, and representativeness of data. These efforts unveil new questions about integrating data arising from distinct sources and instruments. We focus on the most frequently assessed cognitive domain - memory testing - and demonstrate a process for reliable data harmonization across three common measures. We aggregated global raw data from 53 studies totaling N = 10,505 individuals. A mega-analysis was conducted using empirical bayes harmonization to remove site effects, followed by linear models adjusting for common covariates. A continuous item response theory (IRT) model estimated each individual's latent verbal learning ability while accounting for item difficulties. Harmonization significantly reduced inter-site variance while preserving covariate effects, and our conversion tool is freely available online. This demonstrates that large-scale data sharing and harmonization initiatives can address reproducibility and integration challenges across the behavioral sciences.

Multi-informant validity evidence for the SSIS SEL Brief Scales across six European countries.

The SSIS SEL Brief Scales (SSIS SELb) are multi-informant (teacher, parent, and student) measures that were developed to efficiently assess the SEL competencies of school-age youth in the United States. Recently, the SSIS SELb was translated into multiple languages for use in a multi-site study across six European countries (Croatia, Greece, Italy, Latvia, Portugal, and Romania). The purpose of the current study was to examine concurrent and predictive evidence for the SEL Composite scores from the translated versions of the SSIS SELb Scales. Results indicated that SSIS SELb Composite scores demonstrated expected positive concurrent and predictive relationships with scores from the Connor-Davidson Resilience Scale (CD-RISC) and negative relationships with scores from the problem behavior scales of the Strengths and Difficulties Questionnaire (SDQ). Although there were a few exceptions, these patterns generally were consistent across informants (parents, teachers, and students) and samples providing initial validity evidence for the Composite score from the translated versions of the SSIS SELb Scales. Limitations and future research directions are discussed.

The "Haves, Have Some, and Have Nots:" a Latent Profile Analysis of Capacity, Quality, and Implementation in Community-Based Afterschool Programs.

Implementation of evidence-based practices is a critical factor in whether afterschool programs are successful in having a positive impact upon risk reduction and positive youth development. However, important prevention research reveals that contextual and organizational factors can affect implementation (Bradshaw & Pas in School Psychology Review, 40, 530-548, 2011) (Flaspohler et al., in American Journal of Community Psychology, 50(3-4), 271-281, 2012) (Gottfredson et al., Prevention Science, 3, 43-56, 2002) (McIntosh et al., Journal of Positive Behavior Interventions, 18(4), 209-218, 2016) (Payne in Prevention Science, 10, 151-167, 2009). Using a latent profile approach (LPA), this paper examines multiple organizational and neighborhood contextual factors that might affect the degree to which afterschool programs effectively implement evidence-based practices in the context of a cluster-randomized trial of the Paxis Good Behavior Game (PaxGBG). The Interactive Systems Framework (ISF) explores dimensions of capacity that might matter for prevention efforts. As expected, we found that well-resourced and high-quality programs performed well in terms of implementation (the Haves) and, in neighborhood contexts rich in racial-ethnic diversity. Yet, we found that some programs with less physical and material capacity (the Have Nots), demonstrated greater program quality (i.e., supportive adult and peer relationships, engagement, a sense of belonging) and implementation, relative to programs with better capacity (e.g., space, material resources, staffing, and leadership, the Have Somes). While capacity matters, intentional prevention initiatives that seek to promote evidence-based practices are helpful to sites in supporting organizations that might otherwise fail to provide quality programming for youth. This paper addresses a conundrum in prevention science, namely, how to make programming accessible to those who need it with a focus on organizational processes, program quality, and implementation of evidence-based practices.

The SSIS SEL Brief Scales-Student Form: Initial development and validation.

The SSIS SEL Brief Scales-Student Form (SSIS SELb-S) was developed to create an efficient assessment of students' social and emotional learning (SEL). Using item response theory with ratings from 800 students in Grades 3-12 from the standardization sample, 20 items were selected from the full-length SSIS SEL Rating Form - Student to maximize score information and rating efficiency. After identifying items for the SSIS SELb-S, we conducted several reliability and validity analyses. These analyses provided initial support for the use of the SSIS SELb-S for low-stakes decision making contexts. As such, the SSIS SELb-S holds promise for incorporating the perspectives of students ages 8-18 into assessments of their SEL competencies. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Social validity of the Social Skills Improvement System-Classwide Intervention Program (SSIS-CIP) in the primary grades.

The purpose of this study was to examine the social validity of the Social Skills Improvement System-Classwide Intervention Program (SSIS-CIP) for teachers in the primary grades. Participants included 45 first and second grade teachers who completed a 16-item social validity questionnaire during each year of the SSIS-CIP efficacy trial. Findings indicated that teachers generally perceived the SSIS-CIP as a socially valid and feasible intervention for primary grades; however, teachers' ratings regarding ease of implementation and relevance and sequence demonstrated differences across grade levels in the second year of implementation. (PsycINFO Database Record

Metabolic control and academic achievement over time among adolescents with type 1 diabetes.

The relation between metabolic control (HbA1c) and achievement (grade point average [GPA]) was examined over a period of 2.5 years (every 6 months) employing a dynamical systems approach that allowed for the examination of whether HbA1c was associated with change in subsequent GPA and vice versa. Metabolic control tends to deteriorate (i.e., with higher HbA1c reflecting poorer metabolic control) during adolescence. It was hypothesized that these higher levels of HbA1c would limit subsequent increases in GPA. The sample included 252 adolescents (Mbaseline age = 12.49 years, SD = 1.53; 53.6% female) with Type 1 diabetes. Mothers' report and school records provided information on relevant demographics and GPA; medical records provided values of HbA1c. Two simultaneous coupled change equations (i.e., examining current values in 1 variable associated with changes in the other) controlling relevant risk indicators (i.e., age, sex, disease duration, insulin delivery method, IQ) revealed higher levels of HbA1c limited increases in GPA. Higher levels of GPA, however, were not associated with change in HbA1c except for 2 instances where moderation existed by disease duration and IQ. Higher GPA was associated with slower increases in HbA1c over time for youth with shorter disease duration and lower IQ. These results affirm the importance of maintaining good metabolic control to facilitate adequate school performance across the adolescent years. Further, the results suggest that factors related to school achievement may protect adolescents who are newly diagnosed or who have low cognitive ability from subsequent deterioration in metabolic control. (PsycINFO Database Record

Maximizing measurement efficiency of behavior rating scales using Item Response Theory: An example with the Social Skills Improvement System - Teacher Rating Scale.

Measurement efficiency is an important consideration when developing behavior rating scales for use in research and practice. Although most published scales have been developed within a Classical Test Theory (CTT) framework, Item Response Theory (IRT) offers several advantages for developing scales that maximize measurement efficiency. The current study provides an example of using IRT to maximize rating scale efficiency with the Social Skills Improvement System - Teacher Rating Scale (SSIS - TRS), a measure of student social skills frequently used in practice and research. Based on IRT analyses, 27 items from the Social Skills subscales and 14 items from the Problem Behavior subscales of the SSIS - TRS were identified as maximally efficient. In addition to maintaining similar content coverage to the published version, these sets of maximally efficient items demonstrated similar psychometric properties to the published SSIS - TRS.

Performance of Fit Indices in Choosing Correct Cognitive Diagnostic Models and Q-Matrices.

In applications of cognitive diagnostic models (CDMs), practitioners usually face the difficulty of choosing appropriate CDMs and building accurate Q-matrices. However, functions of model-fit indices that are supposed to inform model and Q-matrix choices are not well understood. This study examines the performance of several promising model-fit indices in selecting model and Q-matrix under different sample size conditions. Relative performance between Akaike information criterion and Bayesian information criterion in model and Q-matrix selection appears to depend on the complexity of data generating models, Q-matrices, and sample sizes. Among the absolute fit indices, MX2 is least sensitive to sample size under correct model and Q-matrix specifications, and performs the best in power. Sample size is found to be the most influential factor on model-fit index values. Consequences of selecting inaccurate model and Q-matrix in classification accuracy of attribute mastery are also evaluated.

Confirmatory factor analysis of the Early Arithmetic, Reading, and Learning Indicators (EARLI).

Despite growing interest in early intervention, there are few measures available to monitor the progress of early academic skills in preschoolers. The Early Arithmetic, Reading, and Learning Indicators (EARLI; DiPerna, Morgan, & Lei, 2007) were developed as brief assessments of critical early literacy and numeracy skills. The purpose of the current study was to examine the factor structure of the EARLI probes via confirmatory factor analysis (CFA) in a sample of Head Start preschoolers (N=289). A two-factor model with correlated error terms and a bifactor model provided comparable fit to the data, although there were some structural problems with the latter model. The utility of the bifactor model for explaining the structure of early academic skills as well as the utility of the EARLI probes as measures of literacy and numeracy skills in preschool are discussed.

Examining early literacy skill differences among children in Head Start via latent profile analysis.

The purpose of the present study was to determine whether there are systematic differences in literacy skills among children from less-advantaged households, using latent profile analysis. Early reading skills were measured using the Early Arithmetic, Reading, and Learning Indicators (EARLI; DiPerna, Morgan, & Lei, 2007) literacy tasks. Participants (N = 166) were 4-year-old children enrolled in Head Start. Results revealed three classifications of children: Profile 1 had the lowest overall literacy skill levels, with relative strength in expressive vocabulary and weaknesses in skills related to letter knowledge (i.e., Alphabet Recitation, Letter Naming); Profile 2 had the highest overall level of literacy skills and a relative strength on the Segmenting task; and Profile 3 showed the greatest variability across the EARLI probe scores, with a relative strength in Alphabet Recitation and weaknesses on tasks measuring phonemic and phonological awareness (i.e., Letter Sounds, Sound Deletion, and Segmenting). Repeated measures ANOVA revealed that, although students in each profile demonstrated skill growth over a 6-month period, significant skill differences still remained between profiles at the end of the preschool year.

Development of the Counseling Center Assessment of Psychological Symptoms-62 (CCAPS-62).

Few instruments have been designed specifically to address the needs of college counseling centers. This article reviews existing instruments and presents 4 studies that describe the development and psychometric properties of a new instrument, the Counseling Center Assessment of Psychological Symptoms-62 (CCAPS-62). Study 1 describes the initial item development, factor analysis, and preliminary scale development steps. Study 2 describes the results of exploratory and confirmatory factor analyses using data from more than 22,000 clients pooled via a national practice-research network of counseling centers. Studies 3 and 4 provide preliminary evidence of subscales' convergent validity and retest reliability. Results from these 4 studies provide support for the instrument's factor structure, construct validity, and subscale reliabilities for both the total sample and subgroups. Clinical and methodological issues pertaining to the future development of the CCAPS are discussed in the context of a national practice-research network of college counseling centers.

Investigating the relationship between item exposure and test overlap: item sharing and item pooling.

To date, exposure control procedures that are designed to control item exposure and test overlap simultaneously are based on the assumption of item sharing between pairs of examinees. However, examinees may obtain test information from more than one examinee in practice. This larger scope of information sharing needs to be taken into account in refining exposure control procedures. To control item exposure and test overlap among a group of examinees larger than two, the relationship between the two indices needs to be identified first. The purpose of this paper is to analytically derive the relationships between item exposure rate and each of the two forms of test overlap, item sharing and item pooling, for fixed-length computerized adaptive tests. Item sharing is defined as the number of common items shared by all examinees in a group, while item pooling is the number of overlapping items that an examinee has with a group of examinees. The accuracy of the derived relationships was verified using numerical examples. The relationships derived will lay the foundation for future development of procedures to simultaneously control item exposure and item sharing or item pooling among a group of examinees larger than two.

Controlling item exposure and test overlap on the fly in computerized adaptive testing.

This paper proposes an on-line version of the Sympson and Hetter procedure with test overlap control (SHT) that can provide item exposure control at both the item and test levels on the fly without iterative simulations. The on-line procedure is similar to the SHT procedure in that exposure parameters are used for simultaneous control of item exposure rates and test overlap rate. The exposure parameters for the on-line procedure, however, are updated sequentially on the fly, rather than through iterative simulations conducted prior to operational computerized adaptive tests (CATs). Unlike the SHT procedure, the on-line version can control item exposure rate and test overlap rate without time-consuming iterative simulations even when item pools or examinee populations have been changed. Moreover, the on-line procedure was found to perform better than the SHT procedure in controlling item exposure and test overlap for examinees who take tests earlier. Compared with two other on-line alternatives, this proposed on-line method provided the best all-around test security control. Thus, it would be an efficient procedure for controlling item exposure and test overlap in CATs.

CTTITEM: SAS macro and SPSS syntax for classical item analysis.

This article describes the functions of a SAS macro and an SPSS syntax that produce common statistics for conventional item analysis including Cronbach's alpha, item difficulty index (p-value or item mean), and item discrimination indices (D-index, point biserial and biserial correlations for dichotomous items and item-total correlation for polytomous items). These programs represent an improvement over the existing SAS and SPSS item analysis routines in terms of completeness and user-friendliness. To promote routine evaluations of item qualities in instrument development of any scale, the programs are available at no charge for interested users. The program codes along with a brief user's manual that contains instructions and examples are downloadable from suen.ed.psu.edu/-pwlei/plei.htm.

Empirical Bayes estimation of the prevalence of uninsured individuals by county in the state of Tennessee and analyses of predictive factors.

Lawmakers at the state level require good estimates of those without health insurance in the areas they serve to inform policy decisions. These estimates are often built on inadequate data from smaller geographic areas, such as counties. The Small Area Estimates Branch of the U.S. Census Bureau developed a method to generate stable estimates at the county level using data from the Annual Social and Economic Supplement to the Current Population Survey and several other sources. Using data collected in the state of Tennessee, this article presents a less complicated and arguably less expensive alternative to that method, while providing comparable results. Limitations of both methods and suggestions for future research are discussed.

A comparative evaluation of methods of adjusting GPA for differences in grade assignment practices.

Numerous methods have been proposed for constructing an adjusted grade point average (adjusted-GPA) that controls for differences in grading standards across college courses and departments. Compared to the raw GPA, adjusted-GPA measures are generally more predictable from preadmissions variables, such as standardized tests and high school achievement. Relative rankings of students on adjusted-GPA measures are also more consistent with their relative standings within courses. This study compared the performance of 4 polytomous IRT and 3 linear models for constructing adjusted-GPA measures. Unlike previous studies, the regression weights of predictor variables and the course parameter estimates used to compute adjusted-GPA were cross-validated. Adjusted-GPA retained noticeable advantages over raw GPA on cross-validation. The largest advantages were seen in the multiple correlation of adjusted-GPA with preadmission variables, when adjusted-GPA was constructed with the rating scale and partial credit IRT models. The cross-validity of adjusted-GPA was the weakest with the graded response model.