Testing for intersectional measurement invariance with the alignment method: Evaluation of the 8-item patient health questionnaire.

OBJECTIVE: To demonstrate the use of the alignment method to evaluate whether surveys function similarly (i.e., have evidence of measurement invariance) across culturally diverse intersectional groups. Intersectionality theory recognizes the interconnected nature of social categories such as race, gender, ethnicity, and socioeconomic status. DATA SOURCES: A total of 30,215 American adult's responses to the eight-item Patient Health Questionnaire depression assessment scale (PHQ-8) from the 2019 National Health Interview Survey (NHIS). STUDY DESIGN: Using the alignment method, we examined the measurement invariance (equivalence) of the PHQ-8 depression assessment scale across 16 intersectional subgroups defined at the intersection of age (under 52, 52 and older), gender (male, female), race (Black, non-Black), and education (no bachelor's degree, bachelor's degree). PRINCIPAL FINDINGS: Overall, 24% of the factor loadings and 5% of the item intercepts showed evidence of differential functioning across one or more of the intersectional groups. These levels fall beneath the benchmark of 25% suggested for determining measurement invariance with the alignment method. CONCLUSIONS: The results of the alignment study suggest that the PHQ-8 functions similarly across the intersectional groups examined, despite some evidence of different factor loadings and item intercepts in some groups (i.e., noninvariance). By examining measurement invariance through an intersectional lens, researchers can investigate how a person's multiple identities and social positions possibly contribute to their response behavior on an assessment scale.

Bidirectional effects of parental and adolescent symptom change in trauma-focused cognitive behavioral therapy.

OBJECTIVE: The current study examines dynamic, bidirectional associations between parent and adolescent symptom improvement in response to children's therapy for posttraumatic stress disorder (PTSD). METHOD: Data were collected from a racially and ethnically heterogeneous sample of 1,807 adolescents (age 13-18 years old; 69% female) and a parent participating in Trauma-Focused Cognitive Behavioral Therapy (TF-CBT) at a community outpatient behavioral health clinic. Parents self-reported their depressive symptoms and youth self-reported their PTSD and depressive symptoms at the onset of treatment and every three months for up to nine months. Using a bivariate dual change score model (BDCSM) we examine: (a) individual dyad members' change in symptoms and (b) the bidirectional associations between changes in the parent's and youth's symptoms across treatment. RESULTS: Parents' and adolescents' symptoms at the start of treatment were correlated and both parents' and adolescents' symptoms decreased over the course of treatment. Parents' elevated depressive symptoms at each time point contributed to smaller decreases in their children's PTSD and depressive symptoms at the subsequent time point. Adolescents' elevated symptoms at each time point contributed to greater decreases in their parents' symptoms at the subsequent time point. CONCLUSIONS: These findings highlight the impact that parents and children have on each other's response to children's trauma-focused psychotherapy. Notably, parents' depressive symptoms appeared to slow their children's progress in treatment, suggesting that attending to parents' symptoms and providing them with supportive services may be an important adjunct to children's interventions. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Relationships between native and non-native speech perception.

Individuals differ in their ability to perceive and learn unfamiliar speech sounds, but we lack a comprehensive theoretical account that predicts individual differences in this skill. Predominant theories largely attribute difficulties of non-native speech perception to the relationships between non-native speech sounds/contrasts and native-language categories. The goal of the current study was to test whether the predictions made by these theories can be extended to predict individual differences in naive perception of non-native speech sounds or learning of these sounds. Specifically, we hypothesized that the internal structure of native-language speech categories is the cause of difficulty in perception of unfamiliar sounds such that learners who show more graded (i.e., less categorical) perception of sounds in their native language would have an advantage for perceiving non-native speech sounds because they would be less likely to assimilate unfamiliar speech tokens to their native-language categories. We tested this prediction in two experiments in which listeners categorized speech continua in their native language and performed tasks of discrimination or identification of difficult non-native speech sound contrasts. Overall, results did not support the hypothesis that individual differences in categorical perception of native-language speech sounds is responsible for variability in sensitivity to non-native speech sounds. However, participants who responded more consistently on a speech categorization task showed more accurate perception of non-native speech sounds. This suggests that individual differences in non-native speech perception are more related to the stability of phonetic processing abilities than to individual differences in phonetic category structure. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

A Cautionary Note about Having the Right Mixture Model but Classifying the Wrong People.

Mixture models can be used for explanation or individual prediction and classification. In practice, researchers are often tempted to make the class membership manifest by classifying cases according to their class of maximum posterior probability and using the "observed" class membership directly or as a variable in follow-up analyses to predict distal outcomes. This study revisits the issue of correct class assignment in latent profile analysis by providing an example where the number of classes is known (3-classes), sampling variability is eliminated, and precise estimates of classification indices are provided. This pseudo-population study design assumes the data-generating mechanism is known and provides a "best-case" scenario for evaluating correct class assignment. We use a variety of classification indices and graphical displays to show that correct classification may be poor despite relatively high entropy and overall correct class assignment metrics (e.g., percent correct). Our study serves as a reminder of the risks associated with trying to make latent class memberships manifest.

Timing and frequency of screening in schools: A latent variable analysis of behavioral stability over time.

The growth of school-based initiatives incorporating multitiered systems of support (MTSS) for social, emotional, and behavioral domains has fueled interest in behavioral assessment. These assessments are foundational to determining risk for behavioral difficulties, yet research to date has been limited with regard to when and how often to administer them. The present study evaluated these questions within the framework of behavioral stability and examined the extent to which behavior is stable when measured by two school-based behavioral assessments: the Direct Behavior Rating-Single-Item Scales (DBR-SIS), and the Behavioral and Emotional Screening System (BESS). Participants included 451 students rated three times per year across 4 years, with the primary teacher from each year providing the within-year ratings. Latent variable models were employed to measure the constructs underlying the observed assessment scores. Models demonstrated that the DBR-SIS best captured changes within the year, whereas the BESS scores remained stable across time points within a year. Across years, scores from both assessments captured changes. The unique contributions of each assessment in the data-based decision-making process are discussed, and recommendations are given for their combined use within and across school years. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Associations among childhood threat and deprivation experiences, emotion dysregulation, and mental health in pregnant women.

OBJECTIVE: Women who have experienced childhood maltreatment are at increased risk for experiencing mental health problems. When these occur during pregnancy, they are associated with birth complications and worse developmental outcomes for children. Emotion dysregulation (ED) may be an important, and potentially modifiable, mechanism that links women's maltreatment experiences with their mental health. However, there is limited information about the emotion regulation skills of pregnant women to guide treatment. The current study examines the unique effects of childhood threat (physical, sexual, and emotional abuse and exposure to violence) and deprivation (physical and emotional neglect and separation from primary caregivers) experiences on pregnant women's ED, posttraumatic stress and negative emotional symptoms, and social support. METHOD: Two hundred forty-three women were recruited from an urban prenatal care clinic, the majority of whom identified as Latinx (80%) and low-income (90%). The mean age of the women was 27 years (SD = 5.5). RESULTS: Structural equation modeling revealed significant indirect pathways from childhood threat experiences to posttraumatic stress and negative emotional symptoms via women's ED. In contrast, childhood deprivation experiences were associated with inattention to one's emotions and low perceived social support. CONCLUSIONS: These results underscore the importance of identifying women during pregnancy who may be at risk for ED or emotional inattentiveness due to childhood maltreatment experiences and providing prevention and intervention efforts aimed at enhancing their emotional awareness and regulation. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Factorial invariance of the Usage Rating Profile for Supporting Students' Behavioral Needs (URP-NEEDS).

[Correction Notice: An Erratum for this article was reported online in School Psychology on Dec 30 2019 (see record 2019-80953-001). In the fourth paragraph of the "Understanding the Factors That Influence Usage" section and in the "Usage Rating Profile for Supporting Students' Behavioral Needs (URP-NEEDS)" section, the URP-NEEDS was incorrectly reported to have 23 items. This measure consists of 24 items. This item was also missing in the Appendix under the "Understanding" factor: "School personnel understand how goals for social, emotional, and behavioral screening fit with a system of student supports." All versions of this article have been corrected.] Previous research has suggested that multiple factors beyond acceptability alone (e.g., feasibility, external supports) may interact to determine whether consumers will use an intervention or assessment in practice. The Usage Rating Profile for Supporting Students' Behavioral Needs (URP-NEEDS) was developed in order to provide a simultaneous assessment of those factors influencing use of a particular approach to identifying and supporting the social, emotional, and behavioral needs of students. As the measure was intended for use with a range of school-based stakeholders, a first necessary step involved establishing the measurement invariance of the instrument. Participants in the current study included 1,112 district administrators, 431 building administrators, and 1,355 teachers who were asked to identify the approach used within their school district to identify and support the social, emotional, and behavioral needs of students, and then to complete the URP-NEEDS in reference to this identified approach. Results supported the measurement invariance of the URP-NEEDS across stakeholder groups. In addition, measurement invariance was found across self-identified approaches to social, emotional, and behavioral risk identification within the district administrator and teacher groups. (PsycINFO Database Record (c) 2020 APA, all rights reserved).

Methods matter: A multi-trait multi-method analysis of student behavior.

Reliable and valid data form the foundation for evidence-based practices, yet surprisingly few studies on school-based behavioral assessments have been conducted which implemented one of the most fundamental approaches to construct validation, the multitrait-multimethod matrix (MTMM). To this end, the current study examined the reliability and validity of data derived from three commonly utilized school-based behavioral assessment methods: Direct Behavior Rating - Single Item Scales, systematic direct observations, and behavior rating scales on three common constructs of interest: academically engaged, disruptive, and respectful behavior. Further, this study included data from different sources including student self-report, teacher report, and external observers. A total of 831 students in grades 3-8 and 129 teachers served as participants. Data were analyzed using bivariate correlations of the MTMM, as well as single and multi-level structural equation modeling. Results suggested the presence of strong methods effects for all the assessment methods utilized, as well as significant relations between constructs of interest. Implications for practice and future research are discussed.

Test order in teacher-rated behavior assessments: Is counterbalancing necessary?

Counterbalancing treatment order in experimental research design is well established as an option to reduce threats to internal validity, but in educational and psychological research, the effect of varying the order of multiple tests to a single rater has not been examined and is rarely adhered to in practice. The current study examines the effect of test order on measures of student behavior by teachers as raters utilizing data from a behavior measure validation study. Using multilevel modeling to control for students nested within teachers, the effect of rating an earlier measure on the intercept or slope of a later behavior assessment was statistically significant in 22% of predictor main effects for the spring test period. Test order effects had potential for high stakes consequences with differences large enough to change risk classification. Results suggest that researchers and practitioners in classroom settings using multiple measures evaluate the potential impact of test order. Where possible, they should counterbalance when the risk of an order effect exists and report justification for the decision to not counterbalance. (PsycINFO Database Record

Using time-varying covariates in multilevel growth models.

This article provides an illustration of growth curve modeling within a multilevel framework. Specifically, we demonstrate coding schemes that allow the researcher to model discontinuous longitudinal data using a linear growth model in conjunction with time-varying covariates. Our focus is on developing a level-1 model that accurately reflects the shape of the growth trajectory. We demonstrate the importance of adequately modeling the shape of the level-1 growth trajectory in order to make inferences about the importance of both level-1 and level-2 predictors.

Educators' Implicit theories of intelligence and beliefs about the identification of gifted students / Teorías implícitas de los educadores sobre la inteligencia y creencias sobre la identificación de los estudiantes talentosos

This research study analyzed the structure of educators’ implicit theoriesof intelligence (ITI) and explored the relationship between ITI and beliefsabout the identification of gifted students. This study included a sampleof 372 educators. School Teachers and professors from colleges of educationfavor practical, analytical, and creative attributes in their prototypes of an intelligence person. However, participants were fairly neutral aboutwhether interpersonal and intrapersonal attributes characterized intelligentpeople. Educators that rated creativity as an important attribute ofintelligence tend to favor multiple methods to identify gifted students. Incontrast, educators who supported the use of IQ test as the primary basis of gifted identification tended to agree that analytical abilities were part of the structure of intelligence.

Este estudio analizó la estructura de las teorías implícitas de los educadores sobre la inteligencia (ITI, por sus siglas en inglés) y exploró la relación entre las mismas y las creencias sobre la identificación de los estudiantes talentosos. El estudio incluyó una muestra de 372 educadores. Los profesores de colegio y universidad favorecen atributos prácticos, analíticos y creativos en sus prototipos de una persona inteligente. Sin embargo, los participantes mostraron bastante neutralidad a la hora de determinar si los atributos interpersonales o intrapersonales caracterizan a la gente inteligente. Los educadores que puntuaron la creatividad como atributo importante de la inteligencia tienden a favorecer múltiples métodos para identificar a los estudiantes talentosos. En contraste, los educadores que apoyaban el uso de pruebas de coeficiente intelectual como la base para la identificación del talento generalmente estuvieron de acuerdo con que las habilidades analíticas eran parte de la estructura de la inteligencia.

Applications of hierarchical linear models for evaluations of health interventions: demystifying the methods and interpretations of multilevel models.

Despite the wide availability of statistical programs designed to deal with longitudinal data from a multilevel perspective, many applied researchers remain unfamiliar with the benefits of this methodology, particularly for the evaluation of interventions. The authors present an example of multilevel modeling as part of the analysis of evaluation data from an HIV intervention study. Strategies for understanding multilevel models using longitudinal (panel) data are demonstrated and discussed. The authors illustrate how multiple linear regression models provide a convenient conceptual background to understanding how hierarchical linear models can be developed and interpreted. Multilevel analysis results are compared and contrasted with typical approaches through general linear models for repeated-measures data. Analyses are presented using the SPSS and HLM 5 software.

The differential impact of academic self-regulatory methods on academic achievement among university students with and without learning disabilities.

Although research on academic self-regulation has proliferated in recent years, no studies have investigated the question of whether the perceived usefulness and the use of standard self-regulated learning strategies and compensation strategies provide a differential prediction of academic achievement for university students with and without learning disabilities (LD). We developed and tested a model explaining interrelationships among self-regulatory variables and grade point average (GPA) using structural equation modeling and multiple group analysis for students with LD (n = 53) and without LD (n = 421). Data were gathered using a new instrument, the Learning Strategies and Study Skills survey. The results of this study indicate that students with LD differed significantly from students without LD in the relationships between their motivation for and use of standard self-regulated learning strategies and compensation strategies, which in turn provided a differential explanation of academic achievement for students with and without LD. These paths of influence and idiosyncrasies of academic self-regulation among students with LD were interpreted in terms of social cognitive theory, metacognitive theory, and research conducted in the LD field.