Multi-informant universal screening: Evaluation of rater, item, and construct variance using a trifactor model

Dealing with missing data in multi-informant studies: A comparison of approaches

Multi-informant studies are popular in social and behavioral science. However, their data analyses are challenging because data from different informants carry both shared and unique information and are often incomplete. Using Monte Carlo Simulation, the current study compares three approaches that can be used to analyze incomplete multi-informant data when there is a distinction between reference and nonreference informants. These approaches include a two-method measurement model for planned missing data (2MM-PMD), treating nonreference informants' reports as auxiliary variables with the full-information maximum likelihood method or multiple imputation, and listwise deletion. The result suggests that 2MM-PMD, when correctly specified and data are missing at random, has the best overall performance among the examined approaches regarding point estimates, type I error rates, and statistical power. In addition, it is also more robust to data that are not missing at random.

Gender, racial-ethnic, and socioeconomic disparities in the development of social-emotional competence among elementary school students

Social-emotional competence (SEC) has been demonstrated to be a crucial factor for student mental health and is malleable through the high-quality implementation of effective school-based social and emotional learning (SEL) programs. SEL is now widely practiced in the United States as a Tier 1 strategy for the entire student body, yet it remains unclear whether disparities exist in the development of SEC across socio-culturally classified subgroups of students. Also, despite the field's widespread concern about teacher bias in assessing SEC within diverse student bodies, little evidence is available on the measurement invariance of the SEC assessment tools used to explore and facilitate SEC development. Based on a sociocultural view of student SEC development, this study aimed to measure and examine the extent to which gender, racial-ethnic, and socioeconomic disparities exist in SEC developmental trajectories during elementary school years. Specifically, using 3 years of SEC assessment data collected from a districtwide SEL initiative (N = 5452; Grades K-2 at baseline; nine measurement occasions), this study (a) tested the measurement invariance of a widely-used, teacher-rated SEC assessment tool (DESSA-Mini) across student gender, race and ethnicity, and socioeconomic status (SES); and (b) examined the extent to which multiyear SEC growth trajectories differed across these subgroups under a routine SEL practice condition. The invariance testing results supported strict factorial invariance of the DESSA-Mini across all the examined subgroups, thereby providing a foundation for valid cross-group comparisons of student SEC growth. The piecewise latent growth modeling results indicated that boys (vs. girls), Black students (vs. White students), Hispanic students (vs. White students), and low-income students (vs. middle-to-high-income students) started with a lower level of SEC, with these gaps being sustained or slightly widened throughout 3 elementary school years. Based on these findings, this study calls for future research that can inform practice efforts to ensure equitable SEC assessments and produce more equitable SEL outcomes, thereby promoting equity in school mental health.

Advancing equity in access to school mental health through multiple informant decision-making

There has been a substantial increase in the number of students with mental health needs, yet significant discrepancies exist in access to timely intervention. Traditional gatekeeping to intervention has been the provenance of single information sources. Multi-informant decision-making is a promising mechanism to improve equitable access. However, critical advancements are necessary to improve decision-making relating to (a) who is identified, (b) what type of need is determined, (c) the type of intervention necessary, and (d) where or under what circumstances to implement the intervention. We review critical components of effective mental health decision-making, contributors to inequities in school mental health services, and offer future directions for research and practice to increase equitable student outcomes.

Social, Emotional and Behavioral Screening Profiles Among Students in a Large Urban School District

Social, emotional, and behavioral (SEB) screening frequently employs a variable-based approach wherein individual scale scores indicate risk. However, a person-centered approach wherein risk is indicated by profiles, or constellations of scores across all scales, could help schools prioritize students based on the pervasiveness of SEB needs and match students to appropriate interventions. This study used latent profile analysis (LPA) to identify profiles within two diverse student samples ( n = 16,270 in year one; n = 4019 in year two) based on teacher ratings on the Behavior Intervention Monitoring Assessment System, Second Edition (BIMAS-2). Results suggested four profiles including one profile with elevated risk across all scales, one profile with low behavioral risk and above average social functioning, one profile with borderline risk across all scales, and one profile with typical scores across most scales. Implications for linking universal screening to intervention are discussed. Impact and Implications: Many school districts employ universal screening to prevent and address wide-ranging student needs. Grouping students based on shared sets of needs has the potential to efficiently identify and prioritize students with pervasive risk in order to match them to comprehensive services. Results from this study capture the first attempt to identify student need profiles using BIMAS-2 scores. Future research should refine this process to derive more usable and consistent student profiles allowing direct links to comprehensive student services.

A roadmap to equitable school mental health screening

Youth in the United States are experiencing mental health concerns at alarming rates. Considering the nation's legacy of racism and growing recognition of the impact of social determinants of health on educational and mental health inequities, it is imperative to re-envision how we approach mental health screening in schools to center equity. A focus on mental health screening for the sole purpose of identifying individual at-risk students ignores key contextual considerations, is ineffective in addressing health and educational inequities, and has the potential to perpetuate oppressive practices in schools. Equity-focused mental health screening requires a shift from individual- and deficit-focused approaches to systems- and holistic-focused approaches that (a) identify strengths and stressors among individuals, groups, and communities; (b) dismantle structural forms of oppression; and (c) promote positive mental health outcomes for minoritized youth. Integrating recommendations from the educational equity literature and critical school mental health frameworks, this paper identifies core considerations for equitable school mental health screening and provides guiding principles for each phase of the screening process, from screening readiness to execution to follow up. To implement these recommendations and transform school-based mental health care, schools should (a) incorporate multiple perspectives; (b) prioritize student, family, and community voices; and (c) build collaborative partnerships to co-construct a vision for equitable school mental health.

Multi-informant Assessment of Internalizing Concerns: Rater Concordance and Implications for Decision-Making

Rising rates of mental health challenges among youths have become a significant concern following the COVID 19 pandemic. Although strong evidence supports the implementation of universal screening as a preventative approach to address unmet mental health concerns, the research is less clear surrounding the use of such data in decision-making processes when significant discrepancies between informants (e.g., students and teachers) exist. The purpose of the study was twofold. First, the study aimed to determine the degree of rater concordance between teachers and students on students' internalizing concerns. The second objective was to determine whether concordance on internalizing behaviors differs across ages/grades and if this differentially impacts distal (i.e., academic) outcomes. Results indicated that teachers and students demonstrated limited agreement on ratings of internalizing behaviors. However, when students and teachers agreed, higher and more positive emotional behaviors were linked to higher reading/math performance. Furthermore, patterns of informant dis/agreement and relationships between internalizing concerns and academic outcomes were similar across grade levels. Implications and areas for future research are discussed.

Combined Approach to Multi-Informant Data Using Latent Factors and Latent Classes: Trifactor Mixture Model

Although collecting data from multiple informants is highly recommended, methods to model the congruence and incongruence between informants are limited. Bauer and colleagues suggested the trifactor model that decomposes the variances into common factor, informant perspective factors, and item-specific factors. This study extends their work to the trifactor mixture model that combines the trifactor model and the mixture model. This combined approach allows researchers to investigate the common and unique perspectives of multiple informants on targets using latent factors and simultaneously take into account potential heterogeneity of targets using latent classes. We demonstrate this model using student self-rated and teacher-rated academic behaviors (N = 24,094). Model specification and testing procedures are explicated in detail. Methodological and practical issues in conducting the trifactor mixture analysis are discussed.

Catching sight of children with internalizing symptoms in upper elementary classrooms

Teachers play a crucial role in the assessment of children's internalizing symptoms but may not always succeed in accurately identifying such symptoms in class. Using a multilevel structural equation modeling (MSEM) approach, this study aimed to explore teacher and child characteristics that may explain measurement bias in teachers' ratings of internalizing symptoms at the between- and within-teacher level. Upper elementary school teachers (N = 92, 74.9% female) filled out the Strengths and Difficulties Questionnaire, Student-Teacher Relationship Scale, and Student-Specific Teacher Self-Efficacy Scale for randomly selected children (N = 690, 50.5% girls, Grades 3-6) from their classrooms. Participating teachers and children also responded to several background questions. Multilevel SEMs suggested that teachers' self-efficacy beliefs toward, relationship experiences with, and externalizing symptom ratings of individual children affected their ratings of these children's internalizing symptoms at the within-teacher level. Specifically, given equal levels of internalizing behavior, teachers were likely to systematically under-identify symptoms of anxiety and over-identify bullying for children with more externalizing behavior and conflictual relationships, or in circumstances where teachers had lower self-efficacy. Children with high levels of closeness received systematically higher ratings on somatic complaints and lower ratings on solitary behavior and peer problems. At the between-teacher level, less experienced teachers were more likely to over-identify symptoms of worries than were more experienced teachers, given equal levels of internalizing symptoms. As such, these findings extend the limited body of evidence on children's internalizing symptoms in upper elementary school.

Evaluating the Cost of Prevention Programming and Universal Screening with Discrete Event Simulation

Discrete Event Simulation (DES) is a novel system modeling technique that allows for the evaluation of the potential costs and personnel needed for mental health services in school. A case study is presented to illustrate how DES could be used by a school's decision makers to help plan for implementation of an integrated mental health service model. Discrete Event Simulation was used to model the personnel, time, and costs of an integrated mental health service model within a school setting. In addition, costs are calculated and then compared to a business as usual model. Data from the present investigation indicate substantial cost savings of implementing a prevention oriented mental health intervention model within a school setting. In a school of 1000 students, the prevention model could result in an annual cost savings of approximately $30,000 as well as a 50% reduction in disciplinary referrals and 22% reduction in suspensions. Results from the present investigation indicate substantial savings in financial resources and overall numbers of disciplinary infractions when implementing a prevention model. The DES allows for customization of personnel and time to modify the model and resulting output to local conditions. These data may allow school administrators to modify resources to meet student needs. In addition, cost data can help address some of the common implementation barriers associated with adoption of universal screening and preventative mental health services.