Pediatric Symptom Checklist-17: Factor Structure and Uniform Differential Item Functioning Across Gender and Age in HIV Orphans and Vulnerable Children in Zambia

This study aimed to investigate the psychometric properties of the Pediatric Symptom Checklist-17 (PSC-17) in a sample of children orphaned or made vulnerable (OVC) by HIV in Zambia. Caregivers of 1,076 OVC (55.1% boys; M_age = 12.91 years) completed the PSC-17. Competing models, including confirmatory factor analysis (CFA), hierarchical CFA, bifactor CFA, exploratory structural equation modeling (ESEM), and bifactor ESEM, were tested to evaluate the optimal factor structure of the PSC-17. Results showed that the bifactor ESEM provided the best approximation of the PSC-17 data with a well-defined general psychosocial problems factor explaining 72% of the reliable variance in the total score and an internalizing factor containing 63% of reliable variance unique from the general factor. The observed overall psychosocial problems score was associated with lower academic achievement and working memory (with small effect sizes), supporting the discriminant validity of score interpretation. Results of multiple indicators multiple causes (MIMIC) analyses revealed that all items functioned equivalently across child gender and age.

A preliminary investigation of psychometric properties of the youth-reported Pediatric Symptom Checklist (PSC-Y) in Chinese elementary, middle, and high schools

The current study validated the youth-reported Pediatric Symptom Checklist-Youth (PSC-Y) using a Chinese youth sample (N = 20,996). The factor structure, measurement invariance, and criterion validity were examined. First, factor analysis documented that the correlated three-factor structure, including externalizing problems, internalizing problems, and attention problems fit the data best, which aligns with the prior factor structure of the PSC-Y in other settings (e.g., teacher ratings). In addition, measurement invariance was established across gender and age groups. The latent mean differences revealed that middle and high school students and females reported more internalizing and attention problems than elementary students and males. Additionally, high school students and females were less likely to report externalizing problems than elementary students and males. Finally, the criterion validity of the PSC-Y was established using external scales assessing subjective wellbeing and prosocial behavior. Teachers, school administrators, and school psychologists can utilize the results of this study to more precisely identify youth at risk for psychosocial problems.

Assessing measurement equivalence of PSC-17 across teacher and parent respondents

The Pediatric Symptom Checklist-17 (PSC-17) is a popular screening instrument used by parents and clinicians to assess children's behavioral functioning. However, more schools are examining the potential of the PSC-17 as part of a Multi-Tier System of Support framework. To investigate the potential of the PSC-17 in the schools, a sample of 1,779 U.S. preschool and kindergarten-aged children rated by parents (n = 667) and teachers (n = 1,112) was used to assess the measurement invariance of the PSC-17 across respondent groups. Multiple-group Confirmatory Factor Analysis supported partial scalar invariance for the PSC-17, indicating functional equivalence across teacher and parent respondents. Latent mean testing revealed teachers rated children as exhibiting a lower level of Externalizing Problems relative to parents; however, no significant differences in children's Internalizing Problems and Attention Problems were found between teacher and parent ratings.

The Quality of Life for Children with Autism Spectrum Disorder Scale: Factor Analysis, MIMIC Modeling, and Cut-Off Score Analysis

Our purpose in this study was to further examine the psychometric properties of the Quality of Life for Children with Autism Spectrum Disorder (QOLASD-C) scale. We first investigated the factor structure and the internal consistency of the scale. The bifactor model showed good fit and strong reliability. Second, we used multiple-indicators multiple-causes (MIMIC) modeling to examine the associations between demographic variables and the QOLASD-C dimensions. Results showed differences on overall QOL based on age, race/ethnicity, and autism spectrum disorder severity, but no relationships with gender. All demographic variables were associated with one or all three subscales (i.e., interpersonal relationships, self-determination, emotional well-being) of the QOLASD-C. Third, an optimal cut-off score of 37 was identified. Implications for research and practice are discussed.

Comparing Informants for Mental Health Screening at the Preschool Level

Universal screening for mental health in preschools provides the opportunity for early identification and early intervention, but guidance regarding which informants to use is needed. Preschoolers' (N = 535) parent and teacher reports across two screening forms were analyzed to determine similarities and discrepancies for classification results and screener scores. The analyses also examined if an additional rater provided incrementally valid information to the prediction of longitudinal kindergarten outcomes. Parents' and teachers' screening scores were significantly correlated across forms by rater and across raters. However, categorical classification results indicated that teachers were more likely than parents to rate preschoolers in at-risk ranges across forms. Finally, hierarchical regression analyses revealed teacher ratings were predictive of kindergarten social-emotional, cognitive, and academic outcomes, and that the addition of parent ratings did not significantly improve prediction of outcomes. Implications are discussed in the context of multiple raters within multiple-gating screening procedures.

Utilizing Deep Learning and Oversampling Methods to Identify Children’s Emotional and Behavioral Risk

Deep neural network (DNN) has been widely used in various artificial intelligence applications and is, unsurprisingly, penetrating the field of school psychology. In the school environment, universal screening is used by teachers to identify children’s emotional and behavioral risk (EBR) within a screener. EBR can be used to predict possible emotional and behavioral disorders, which impact children’s educational and social outcomes. Using the BASC-2 Behavioral and Emotional Screening System Teacher Rating Scale (BASC-2 BESS TRS; Reynolds & Kamphaus (2004). Behavior Assessment System for Children (2nd ed.). Circle Pines, MN: American Guidance Service) norm data, we classified children’s EBR status from normal to at-risk using DNN. Data oversampling was used to overcome the imbalanced sample feature (i.e., few cases with emotional and behavioral disorder). Traditional machine learning methods, such as Naïve Bayes and logistic regression, were included for comparison. The results indicated that the DNN with oversampling achieved the highest performance levels with accuracy (ACC) of .957, precision (PPV) of .545, true positive rate (TPR or sensitivity) of 1.000, and true negative rate (TNR or specificity) of .942 compared with the other methods. This novel method is helpful to provide accurate screening results for early identification of children’s EBR. The current study provides a useful guide for researchers to apply the DNN and oversampling to classification in assessment-related research.

Pediatric Symptom Checklist-17

Abstract. The Pediatric Symptom Checklist-17 (PSC-17) is a screener designed to measure children’s behavioral and emotional problems. The measurement invariance of the scale’s higher-order factor structure was investigated in the current study. Gender invariance was established through a series of tests for configural invariance (baseline model), metric invariance, scalar invariance, residual variance invariance of items, higher-order factor loadings invariance, intercepts invariance of first-order factors, disturbances invariance of first-order factors, and factor variance invariance of a higher-order factor. The latent mean difference of the higher-order factor indicates that boys exhibited more problems with a strong effect size ( d = .870). As invariance holds, the PSC-17 may be an option to identify preschool children’s behavioral and emotional problems in Response to Intervention programs in school-based settings.

Validating the Pediatric Symptoms Checklist–17 in the Preschool Environment

In the Response to Intervention framework, a psychometrically sound screening tool is essential for identification of children with emotional and behavioral risk. The purpose of this study was to examine the validity of the Pediatric Symptom Checklist–17 (PSC-17) screener in school-based settings. Forty-four teachers rated 738 preschoolers using the PSC-17; children were later assessed using long forms of the Behavior Assessment System for Children (BASC-2) Preschool form or the Achenbach System of Empirically Based Assessment (ASEBA) Caregiver–Teacher Report Form to identify emotional and behavioral disorder. Validity evidence including examinations of a multilevel factor structure, internal consistency, and criterion-related validity supported the conclusion that the PSC-17 is a high-quality universal screening tool in school-based settings. Finally, to identify emotional and behavioral risk with young children, receiver operating characteristic curve analyses with the PSC-17 yielded a lower cutoff score (i.e., 7) than the original cutoff score (i.e., 15) based on a clinical sample.

Assessing Equivalency of PSC-17 Ratings: Does It Matter if Mixed or Grouped Item Format Is Used?

This study investigated the effect of item position on descriptive statistics, psychometric information, and factor structure of the Pediatric Symptoms Checklist 17-item social-emotional screening instrument (PSC-17). The goal was to determine whether item position, either grouped by factor or mixed across constructs, produced similar results. Descriptive statistics, reliability estimates, and model-data fit were similar across the two versions of the screener. Factor invariance tests supported strict invariance across the two versions, and very small differences between latent means for the three factors measured by the PSC-17. Both forms are equivalent for use with screening activities.