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Examining the stability of SAEBRS scores, classifications, and latent profiles
Abstract
We investigated the stability of the Social, Academic, and Emotional Behavior Risk Screener (SAEBRS) using a naturalistic sample of teacher-report ratings for K-5 students (N = 1253) across three universal screening occasions (i.e., fall, winter, and spring) within one school year. We analyzed the stability of SAEBRS raw scores and classifications derived from these scores between screening occasions. Results showed strong raw score stability and moderate-to-strong classification stability for the SAEBRS total scale and subscales, with the Emotional Behavior subscale demonstrating the weakest relative stability. We also explored latent profiles indicated by SAEBRS subscale scores, the stability of membership in these profiles across occasions, and the role of student sociodemographic characteristics in predicting membership within these profiles. Findings indicated that two general risk profiles (i.e., at-risk and not at-risk) were identified and that membership in these profiles had strong stability across screening occasions. Moreover, we found that students' grade level, sex, race/ethnicity, special education, and free/reduced-price lunch status significantly predicted membership in the at-risk profile. Overall, results suggest that SAEBRS raw scores, classifications, and latent profiles all demonstrate good stability across three screening occasions within one school year. We discuss implications of these findings related to using the SAEBRS for universal screening in elementary settings and highlight key directions for future research.
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The use of self-report measures evaluating social, emotional, and behavioral risk can be an important element of universal screening with older children and adolescents. Research has demonstrated discrepancies between teacher ratings and student self-report ratings of social, emotional, and behavioral risk, which commonly result in incongruent risk classifications. The present study explored classification incongruence and informant discrepancies on the teacher- and student self-report versions of the Social, Academic, and Emotional Behavior Risk Screener. Screening data from over 600 high school students and their homeroom teachers were examined. Results showed classification congruence was highest for the Social Behavior subscale and lowest for the Emotional Behavior subscale of the Social, Academic, and Emotional Behavior Risk Screener, with teachers endorsing lower levels of risk compared to students. Analysis of potential sociodemographic predictors of informant discrepancies indicated that grade, sex, free and reduced-price lunch eligibility, 504 plan status, and special education status were significant predictors of classification incongruence on at least one Social, Academic, and Emotional Behavior Risk Screener subscale. Implications for practice and limitations are discussed.
Universal screening for social, emotional, and behavioral risk is an important method for identifying students in need of additional or targeted support (Eklund and Dowdy in School Mental Health 6:40–49, 2014). Research is needed to explore how potential bias may be implicated in universal screening. We investigated student demographics as predictors of being placed at risk via a teacher-report measure: the Social, Academic, and Emotional Behavior Risk Screener as reported by Kilgus et al. (in: Theodore J. Christ et al. (eds) Social, academic, and emotional behavior risk screener (SAEBRS), 2014). Results indicated student demographics, including sex, special education status, free/reduced price lunch status, and identification as a student of color, were statistically significant predictors across multiple SAEBRS risk placements. The predictive power of student demographics was meaningful when evaluated independently (i.e., when each characteristic was considered separately with each risk placement) as well as when evaluated relatively or dependently (i.e., when all characteristics were taken together as a set to predict each risk placement). We discuss findings in the context of implications for implementation of universal behavioral screening amidst potential bias and serving students with identified levels of social, emotional, and behavioral risk.
Mental health screening is a pivotal practice for promoting the social–emotional–behavioral (SEB) health and well-being of youth in schools. However, some aspects of traditional mental health screening practices may inadvertently perpetuate structural racism and unintentionally facilitate oppression and SEB disparities. We address this issue constructively by presenting an intentional approach to guide school psychologists and related professionals in implementing more socially just mental health screening in schools. Our guidelines are grounded within the four phases of the Participatory Culture-Specific Intervention Modeling (PCSIM) framework: system entry, culture-specific model development, culture-specific program development, and program continuation or extension. We propose that conceptualizing mental health screening within PCSIM methodology promotes more socially just practices by (a) displacing the implicit power of professionals, (b) giving transparent representation to local communities, and (c) employing methods that are recursive, culturally relevant, and intended to build capacity for sustained transformative change. Within each PCSIM phase, we recommend culturally responsive practices for professionals that foster equity in screening and SEB outcomes and discuss ways to resist practices that perpetuate oppression and disparities. We aim to convey a method for mental health screening that is not done to students and schools but rather done in partnership with and for the benefit of students and schools.
Universal screening has emerged as one strategy within schools for identifying students who demonstrate social emotional and behavioral (SEB) concerns to provide appropriate support. However, research has demonstrated little evidence of equity around diagnostic accuracy; that is, how students might be differentially identified as at‐risk for SEB concerns based on race/ethnicity. The current study examined the diagnostic accuracy of the Social, Academic, and Emotional Behavior Risk Screener (SAEBRS) teacher screening measure as affected by student race/ethnicity, drawing from a sample of 730 students and 54 teachers from four urban, Midwestern elementary schools. Data were analyzed using nonparametric receiver operating characteristic (ROC) curve analyses, as well as ROC regression tests incorporating student race/ethnicity status as a covariate. Results indicated the SAEBRS (1) demonstrated borderline to optimal sensitivity and specificity across student racial/ethnic subgroups in predicting student SEB risk status, and (2) diagnostic accuracy did not vary across racial/ethnic subgroups to a statistically significant degree. Results highlight the need for further research on this topic.
Along with increased attention to universal screening for identifying social, emotional, and behavioral (SEB) concerns is the need to ensure the psychometric adequacy of tools available. Nearly all extant tests of universal SEB screening validity focus on traditional inferential forms with little to no study of the consequences of actions following those inferences, or consequential validity proposed under Messick's unified validity theory. This study examines one facet of consequential validity (i.e., utility) of results from one popular screening tool in six elementary schools in one large U.S. district. The schools identified students who were receiving SEB supports on a monthly form throughout one school year. Screening identified 991 students with SEB risk, of which 91 (9%) were receiving intervention prior to screening. After screening, schools provided intervention to an additional 66 students (7%). Unaddressed SEB risk remained after screening for 84% of screener-identified students. Latent profile analyses detected five patterns of risk with those students demonstrating the most risk and predominately externalizing concerns being most likely to receive intervention after screening. Study schools also provided intervention to students with elevated low risk after screening, but this profile was the largest group leaving 708 students with unaddressed SEB risk after screening. Results provide evidence of universal SEB screening interpretation to identify unaddressed SEB risk but insufficient use to provide intervention services at a rate that substantially reduced unaddressed SEB risk. Future research and practice directions for advancing the consequential validity of universal SEB screening are recommended and measurement limitations discussed. (PsycInfo Database Record (c) 2023 APA, all rights reserved).
Despite general agreement about the importance of test score relevance, utility, and consequences, empirical articles rarely examine or report these facets of validity. The purpose of this special issue of School Psychology was to provide empirical examples that examine the social consequences of educational test score use. The goal was to illustrate best practices in social consequence considerations and encourage future measurement articles to go beyond a basic consideration of psychometric properties. In this overview article, we provide an overview of validity frameworks and their application in education research. We also review the current state of social consequence research and offer recommendations to increase and improve this research in our field. After summarizing the articles and commentaries in the special issue, we conclude by describing a framework for guiding test development and ongoing evaluation from a social consequence perspective.
The studies in this special issue examine the social consequences of educational measures. In this commentary, I reflect on past and contemporary conceptualizations of the consequences of measurement and discuss advancing a more justice-oriented approach. To this end, it is imperative that we engage a critical lens in order to interrogate and act upon structural issues as they manifest in testing, assessment, and measurement. Importantly, we must attend to both the intended and unintended consequences of the use and interpretation of educational measures in order to advance equity and social justice.
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).
Latent transition analysis (LTA), also referred to as latent Markov modeling, is an extension of latent class/profile analysis (LCA/LPA) used to model the interrelations of multiple latent class variables. LTA methods have become increasingly accessible and in-turn are being utilized in applied research. The current article provides an introduction to LTA by answering 10 questions commonly asked by applied researchers. Topics discussed include: (1) an overview of LTA; (2) a comparison of LTA to other longitudinal models; (3) software used to run LTA; (4) sample size suggestions; (5) modeling steps in LTA; (6) measurement invariance; (7) the inclusion of auxiliary variables; (8) interpreting results of an LTA; (9) the nature of data (e.g., longitudinal, cross-sectional); and (10) extensions of LTA. An applied example of LTA is included to help understand how to build an LTA and interpret results. Finally, the article suggests future areas of research for LTA. This article provides an overview of LTA, highlighting key decisions researchers need to make to navigate and implement an LTA analysis from start to finish. (PsycInfo Database Record (c) 2022 APA, all rights reserved).
Teachers’ perceptions of high cultural responsiveness in the classroom may be related to positive behavioral outcomes (e.g., higher academic engagement, lower social risk), but little research has explored this possibility. This article addresses this research gap by building upon findings from a preliminary paper in which these relationships were evidenced. Specifically, we present two interrelated follow-up studies. Study 1 examined the relationship between teachers’ ( n = 20) ratings on a measure of cultural responsiveness, the Double Check Self-Refection Tool, and students’ observed classroom behavior. Results from multilevel modeling indicated that higher Double Check scores significantly predicted higher academic engagement and lower disruptive behavior for 454 students observed. Study 2 investigated the relationship between teachers’ ( n = 30) ratings on the Double Check Self-Refection Tool and ratings of 622 students’ risk on the Social, Academic, and Emotional Behavior Risk Screener (SAEBRS). Results indicated higher Double Check scores were associated with lower ratings of students’ social and emotional risk. Findings also indicated identification as a Black student and a student with a disability predicted teachers’ perceptions of higher risk, consistent with previous research. As results remain preliminary, implications include recommendations for additional research and high-quality professional development to promote teachers’ cultural responsiveness.
Ample evidence suggests that PK‐12 students experience racism and other forms of discrimination in school and that these experiences have a deleterious impact on their mental health. Several studies have shown a consistent and strong relationship between racism and negative mental health outcomes including increased depression and anxiety, decreased self‐worth and self‐esteem, as well as psychological maladjustment. School‐based mental health services can ensure that racial and ethnic minoritized (REM) students gain access to mental health services. Because schools are one place where REM students experience structural and individual discrimination, it is critical that school‐based mental health providers utilize strategies to promote school climates that are safe and affirming for these students. Using a multitiered system of support framework, we describe the tier 1 interventions to promote positive school racial climate and the elements of culturally responsive practices to be integrated into tier 2 and tier 3 interventions to improve mental health outcomes for REM youth.
Detecting mental health concerns in youth accurately and promptly may prevent poor school outcomes, long‐term mental illness, and adverse lifelong outcomes. Practitioners often use universal behavioral risk screeners to identify students at‐risk on indicators related to mental health concerns. However, research is needed to inform the stability of risk identification scores across the academic year. Using a sample of N = 1496 elementary and middle school‐aged students, latent class analysis and latent transition analysis were employed to identify and characterize the risk classes and the stability of latent classes of student risk longitudinally across one school year (i.e., fall, winter, and spring). The screener of interest within this study was the Social, Academic, and Emotional Behavior Risk Screener–Student Rating Scale (SAEBRS‐SRS). Results revealed three distinct risk classes (low, moderate, and high risk) that remained stable across screening periods. Future directions and implications for practice are discussed.
It is important to explore the relationship between teachers' perceptions of their cultural responsiveness as well as students' classroom behavior and risk, as these relationships may impact decisions about equitable access to school behavioral health supports. This paper includes two studies conducted with teachers in two large suburban school districts. Study 1 investigated the relationship between teachers' (n = 20) ratings on a measure of cultural responsiveness, the Assessment of Culturally and Contextually Relevant Supports (ACCReS), and students' classroom behavior. Results indicated that higher ACCReS scores significantly predicted lower classwide disruptive behavior. Study 2 investigated the relationship between teachers' (n = 30) ratings on the ACCReS and ratings of their students' risk on the Social, Academic, and Emotional Behavior Risk Screener. For social behavior, higher ACCReS scores predicted teachers perceiving lower social risk; however, identification as a Black student and a student with a disability predicted higher risk. Findings are preliminary, yet implications include recommendations for high‐quality professional development to promote teacher cultural responsiveness. Such support could guide teachers to create educational environments in which fewer discipline referrals for behavior occur, teachers perceive less social risk, and access to school behavior supports is more equitable.
Latent profile analysis (LPA) is a categorical latent variable approach that focuses on identifying latent subpopulations within a population based on a certain set of variables. LPA thus assumes that people can be typed with varying degrees of probabilities into categories that have different configural profiles of personal and/or environmental
attributes. Within this article, we (a) review the existing applications of LPA within past vocational behavior research; (b) illustrate best practice procedures in a non-technical way of how to use LPA methodology, with an illustrative example of identifying different latent profiles of heavy work investment (i.e., working compulsively, working excessively,
and work engagement); and (c) outline future research possibilities in vocational behavior research. By reviewing 46 studies stemming from central journals of the field, we identified seven distinct topics that have already been investigated by LPA (e.g., job and organizational attitudes and behaviors, work motivation, career-related attitudes and
orientations, vocational interests). Together with showing descriptive statistics about how LPA has been conducted in past vocational behavior research, we illustrate and derive best-practice recommendations for future LPA research. The review and "how to" guide can be helpful for all researchers interested in conducting LPA studies.
Background:
Similar to other health care sectors, mental health has moved towards the secondary prevention, with the effort to detect and treat mental disorders as early as possible. However, converging evidence sheds new light on the potential of primary preventive and promotion strategies for mental health of young people. We aimed to reappraise such evidence.
Methods:
We reviewed the current state of knowledge on delivering promotion and preventive interventions addressing youth mental health.
Results:
Half of all mental disorders start by 14 years and are usually preceded by non-specific psychosocial disturbances potentially evolving in any major mental disorder and accounting for 45% of the global burden of disease across the 0-25 age span. While some action has been taken to promote the implementation of services dedicated to young people, mental health needs during this critical period are still largely unmet. This urges redesigning preventive strategies in a youth-focused multidisciplinary and trans-diagnostic framework which might early modify possible psychopathological trajectories.
Conclusions:
Evidence suggests that it would be unrealistic to consider promotion and prevention in mental health responsibility of mental health professionals alone. Integrated and multidisciplinary services are needed to increase the range of possible interventions and limit the risk of poor long-term outcome, with also potential benefits in terms of healthcare system costs. However, mental health professionals have the scientific, ethical, and moral responsibility to indicate the direction to all social, political, and other health care bodies involved in the process of meeting mental health needs during youth years.
Navigating academic demands in middle and high school may be particularly challenging for youth experiencing emotional and behavioral difficulties, and screening practices are a necessary first step in identifying youth in need of services. The goal of this study was to inform efficient universal screening practices in secondary schools by comparing 3 common methods of screening, including self- and teacher report on the Strengths and Difficulties Questionnaire, and grade point average (GPA) to indicate moderate and high levels of risk. Participants were 2,350 secondary students (47% female; 94% non-Hispanic White) and their teachers in 1 socioeconomically diverse school district. Using the moderate-risk criteria, there was low agreement among methods, and almost half the sample (46%) was identified as at risk by at least 1 of the 3 methods, indicating that responding to the needs of students who cross this liberal cutoff may not be feasible given school resources. Using the high-risk criteria reduced the agreement among screening measures. Self-report identified the most students as high risk and was more sensitive to teacher-rated concerns than the converse. If students were uniquely identified by teacher report, teachers rated them at high levels of risk, and predominant concerns were related to conduct problems. GPA captured few students with self- or teacher-rated internalizing or externalizing difficulties. Implications for universal screening within secondary schools are discussed. (PsycINFO Database Record (c) 2019 APA, all rights reserved).
Attention deficit hyperactivity disorder (ADHD) is a common neurodevelopmental disorder with onset in early childhood. It is a clinically heterogenous condition with comorbidity posing a distinct challenge to diagnosing and managing these children and adolescents. This review aims to provide an overview of comorbidity with ADHD including other neurodevelopmental disorders, learning disorders, externalising and internalising disorders. Challenges in screening for, diagnosing and managing comorbidity with ADHD are summarised. Also, methodological challenges and future directions in research in this interesting field are highlighted.
Identifying youth with mental health concerns and connecting them to effective intervention is important because poor mental health is related to lower educational achievements, substance abuse, violence, compromised health, and reduced life satisfaction. This study examined the ability of teachers (n = 153) to accurately identify mental health concerns among elementary children using vignettes scenarios depicting children with severe and moderate externalizing or internalizing behavior problems. Teachers were asked to rate the seriousness of the problem, their concern for the child’s well-being, and whether they felt the student needed school-based or community mental health services. Findings indicated that teachers can accurately identify students with severe externalizing and internalizing problems. However, they were less accurate and less likely to think students with moderate or subclinical symptoms needed services. Additionally, teachers perceived externalizing problems to be more serious and more concerning, than internalizing problems. In most cases, teachers’ concern for the child’s well-being, but not their perceived seriousness of the problem, predicted endorsement of referral to school and/or community-based mental health professionals, even when controlling for the child’s gender. Implications for practice and future research areas are discussed.
The first purpose of the current study was to examine the defensibility of common recommendations for the frequency of screening administrations. The second purpose was to examine the internal consistency and criterion related validity of the Devereux Student Strengths Assessment (DESSA)-mini (Naglieri, LeBuffe, & Shapiro, 2011a), a strength-based social-emotional and behavioral (SEB) risk screening tool. Specifically, the current study examined the defensibility of the oft-recommended triannual screening schedule, while also evaluating alternative screening schedules (i.e., once and twice per year). Participants included 525 students sampled across 2 rural mid-western elementary schools. Teachers completed the DESSA-mini across 3 time periods throughout the school year. Schools provided data for outcome variables, including student attendance, reading scores, and office discipline referrals (ODRs). Analyses revealed (a) adequate internal consistency and alternate forms reliability of DESSA-mini scores, and (b) small to moderate relations between DESSA-mini scores and the various outcomes. Findings also suggested strength-based SEB risk status was relatively stable over the 3 screening periods. Furthermore, generalized linear modeling and classification accuracy analyses indicated that after accounting for fall screening scores, winter and spring screening scores contributed little to the prediction of the outcome variables. Limitations and implications for practice are discussed.
Due to early onset and rising prevalence rates, there is an established need for early identification of youth demonstrating symptoms of internalizing disorders (e.g., anxiety and depression). Accordingly, calls have been made for the use of universal screening tools to identify internalizing behavior risk. Current research has spoken to the adequacy of individual screeners, but researchers have yet to quantitatively synthesize the broader internalizing screening literature. The purpose of the current study was to systematically review the literature and conduct a reliability and validity generalization meta-analysis of available psychometric evidence. This meta-analysis identified 40 studies in which 18 distinct internalizing behavior screeners were examined. Of interest were both (a) broadband screeners, which included internalizing items along with items specific to other areas (e.g., externalizing problems), and (b) narrowband screeners, which included internalizing items alone. Across examined studies, mean coefficient alpha reliability estimates were equal to .84 for broadband screeners and .78 for narrowband screeners. For broadband screeners, mean validity correlation coefficients were equal to .66 when predicting other internalizing measures and .51 when predicting other criteria (e.g., extant academic and behavioral data). For narrowband screeners, mean validity coefficients were equal to .45 when predicting other internalizing measures and .26 when predicting other criteria. Interestingly, moderator analyses indicated neither reliability nor validity was moderated by any study or measurement characteristics. Taken together, results supported the psychometric defensibility of both broadband and narrowband internalizing screeners. Limitations of the study and implications for research are discussed, including recommendations for additional diagnostic accuracy research.
Responsive service delivery frameworks rely on the use of screening approaches to identify students in need of support and to guide subsequent assessment and intervention efforts. However, limited empirical investigations have been directed to informing how often screening should occur for social, emotional, and behavioral difficulties in school settings. The purpose of the current study was to evaluate the stability of risk status on 3 different screening instruments across 3 administrations across the course of a school year. A total of 1,594 students had complete screening data across 3 time points, corresponding to a total of 187 teachers from 22 different public schools located within the northeastern and midwestern United States. Across measures, we examined patterns of risk across time points and investigated the utility of (a) different screening schedules (fall, winter, and spring) and (b) borderline screening when conducting multiple screenings per year. Results indicated that a large proportion of students exhibited stable risk patterns across time points and suggested that borderline screening may be a viable alternative for schools with limited resources. Implications for practice and future research are discussed.
Data derived from universal screening procedures are increasingly utilized by schools to identify and provide additional support to students at risk for behavioral and emotional concerns. As screening has the potential to be resource intensive, effort has been placed on the development of efficient screening procedures, including brief behavior rating scales (BBRS). This study utilized classical test theory and generalizability theory to examine the extent to which differences among students, raters, occasions, and screening measures affect the amount of variance in data derived from universal screening procedures. Teacher pairs from three middle school classrooms completed two BBRS during fall and spring for each student in their classrooms. Correlation coefficients examining interrater reliability, test-retest reliability, and convergent validity were generally strong. Generalizability analyses indicated that the majority of variance in teacher ratings was attributable to student differences across all score comparisons, but differences between teacher ratings for particular students accounted for relatively large percentages of error variance among student behavior ratings. Although decision studies suggested that increasing the number of screening occasions resulted in more generalizable data, they also demonstrated that increasing the number of raters not only resulted in more generalizable data but also procedures that are more efficient.
Despite promising evidence that school-based health centers (SBHCs) and school mental health (SMH) services can reduce disparities in access to mental health care for underserved populations, little is known about what predicts retention of youth in SMH services. This study aimed to identify individual- and school-level factors associated with access and retention in mental health services provided in SBHCs. Existing data were analyzed for 17,348 students (2205 who received SMH services) who attended 17 middle and high schools in an urban school district. Student-level predictors included sex, race/ethnicity, and mental health need at intake. School-level predictors included grade level (middle vs. high school), student/teacher ratio, percent of white students, and percent of students receiving free or reduced lunch. Hierarchical generalized linear modeling was used to examine the association between student- and school-level variables and retention in care. White, Latino, and Asian students were less likely to access SMH services; multiracial and Native American students were more likely to access services, and African-American students were no more or less likely. Hierarchical models found that retention in services was more likely for female students, those who presented with social/educational problems, internalizing problems, and trauma/abuse/neglect, and less likely for Asian students. Retention was also more likely for students in middle schools, schools with a lower student/teacher ratio, and schools with a smaller percentage of students eligible for free or reduced lunch. While SMH services show promise in increasing access for underserved groups, ensuring equitable retention of students in care will likely require concerted effort focused on consistently engaging students and ensuring quality of care.
A growing interest has been given to examining the heterogeneity of children’s health to provide for their particular needs. This study examined subgroups of elementary school children’s social, emotional, and behavioral functioning (SEB) using teacher ratings of children with the Behavioral and Emotional Screening System. A Latent Profile Analysis (LPA) was conducted with 5,150 students aged from kindergarten to fifth grade. Subscale scores in the areas of externalizing risk, internalizing risk, and adaptive skills risk were used to identify profiles. Students’ grade level, sex, race, and status of receiving special education services were added to investigate the impact of covariates on the classification of latent profiles. Four profiles of risk were identified: Well Development (60.5%), Normal Development (25.8%), Externalizing and Adaptive Skills Risk (9.1%), and Elevated Risk (4.6%). Significant differences of covariates including sex, race, and status of receiving special education services were identified. Specifically, males and African American students were more likely to be classified into the “Elevated Risk” profile than other profiles. Students who did not receive special education services were more in the “Well Development” profile. The results may have important implications for the stakeholders to allocate intervention and treatment resources effectively and accurately.
Although several studies have focused on why school climate is important, the timing of the collection of climate measures should be considered. This is of particular interest to schools that gauge school improvement efforts within a school year and are interested in how climate changes from the beginning to the end of the academic year. We show that there is a tendency for school-level climate measures to fluctuate in a predictable, nontrivial manner (ds=0.25–0.47). Findings are
based on data from 26 secondary schools (using over 20,000 student responses) that had school climate measures taken in fall and spring over 18months. We show that in the fall, on average, students consistently had a more favorable outlook of the school based on five climate measures.
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.
Full text available open access at - https://www.sciencedirect.com/science/article/pii/S0022440522000929
ARTICLE FREE TO ACCESS AT: https://doi.org/10.1080/15374416.2022.2158842. In this editorial statement, we briefly delineated a series of observations, guidelines, and directions for future research focused on the most common outcome of multi-informant assessments of youth mental health. Discrepancies commonly occur between estimates of youth mental health and conclusions drawn from these estimates, depending on the informant’s report that led to the estimates. This editorial statement is a culmination of not only this Special Issue of JCCAP, but also 60 years of research on these informant discrepancies. We know a great deal about these discrepancies, and thus can come to some definitive conclusions about how often they occur, what they likely reflect, and, importantly, what they are unlikely to reflect. Based on these observations about informant discrepancies, we can also arrive at some preliminary guidelines for integrating multi-informant data in youth mental health research, and improve our practices for transparency in reporting the justification or evidence base for the procedures we use to integrate these data. That said, we do have a great deal more to learn about these informant
discrepancies. Thus, we articulated several directions for future research that are by no means exhaustive but nonetheless are of high priority in terms of advancing knowledge about this ubiquitous assessment phenomenon. A dozen years removed from JCCAP’s first Special Section about informant discrepancies (De Los Reyes, 2011), we remain curious about the work that lies ahead. We hope that this statement informs your thinking about this most crucial area of youth mental health research.
While there is evidence suggesting school-based transitions impact student mental health and academics (Lester et al., 2013 Lester, L., Waters, S., & Cross, D. (2013). The relationship between school connectedness and mental health during the transition to secondary school: A path analysis. Australian Journal of Guidance and Counselling, 23(2), 157–171. https://doi.org/10.1017/jgc.2013.20[Crossref] , [Google Scholar]), it is unknown how these transitions specifically impact the domains of social, academic, and emotional behavior, as measured via the Social, Academic, and Emotional Behavior Risk Screener (SAEBRS). The purpose of this study was to explore the relationship between school-based transitions and teacher ratings of student SAEBRS scores in a midsize, suburban school district. Using paired t-tests and McNemar’s test we examined changes in SAEBRS scores and benchmark risk levels across grade level changes and school-based transitions. SAEBRS scores decreased significantly from 8th to 9th grade (school-based transition) in the total, academic, and emotional subscales, although risk level did not increase significantly during this transition. In contrast, SAEBRS scores increased significantly in each subscale as students transitioned from 7th to 8th grade (no school-based transition). Implications for research and school psychology are discussed.
Impact Statement
Findings from this study confirm students transitioning to high school experience academic and emotional behavior risk, as observed by teachers. In contrast, students transitioning from the middle grade in their school to the top grade (e.g., 7th to 8th grade) experienced improvement in social, academic, and emotional behavior. Therefore, school psychologists can focus school-based mental health efforts on equipping students with the socioemotional skills and academic enablers to cope prior to the transition to high school.
Mental health encompasses a range of mental, emotional, social, and behavioral functioning and occurs along a continuum from good to poor. Previous research has documented that mental health among children and adolescents is associated with immediate and long-term physical health and chronic disease, health risk behaviors, social relationships, education, and employment. Public health surveillance of children's mental health can be used to monitor trends in prevalence across populations, increase knowledge about demographic and geographic differences, and support decision-making about prevention and intervention. Numerous federal data systems collect data on various indicators of children's mental health, particularly mental disorders. The 2013-2019 data from these data systems show that mental disorders begin in early childhood and affect children with a range of sociodemographic characteristics. During this period, the most prevalent disorders diagnosed among U.S. children and adolescents aged 3-17 years were attention-deficit/hyperactivity disorder and anxiety, each affecting approximately one in 11 (9.4%-9.8%) children. Among children and adolescents aged 12-17 years, one fifth (20.9%) had ever experienced a major depressive episode. Among high school students in 2019, 36.7% reported persistently feeling sad or hopeless in the past year, and 18.8% had seriously considered attempting suicide. Approximately seven in 100,000 persons aged 10-19 years died by suicide in 2018 and 2019. Among children and adolescents aged 3-17 years, 9.6%-10.1% had received mental health services, and 7.8% of all children and adolescents aged 3-17 years had taken medication for mental health problems during the past year, based on parent report. Approximately one in four children and adolescents aged 12-17 years reported having received mental health services during the past year. In federal data systems, data on positive indicators of mental health (e.g., resilience) are limited. Although no comprehensive surveillance system for children's mental health exists and no single indicator can be used to define the mental health of children or to identify the overall number of children with mental disorders, these data confirm that mental disorders among children continue to be a substantial public health concern. These findings can be used by public health professionals, health care providers, state health officials, policymakers, and educators to understand the prevalence of specific mental disorders and other indicators of mental health and the challenges related to mental health surveillance.
The dual-factor model of mental health emphasizes the integration of subjective well-being and psychopathology to obtain a complete conceptualization of mental health. When used in schoolwide screenings, this dual-factor approach provides a more comprehensive picture of students' mental health. In a sample of adolescents (N = 404) attending a Midwestern U.S. middle school (Grades 6–8), the current study empirically identified mental health groups through latent profile analysis (LPA) and examined how profile membership was predicted by various demographic variables, academic achievement, general grit, academic grit, and growth mindset. Three mental health profiles emerged: Complete Mental Health (above average life satisfaction and affect, below average internalizing and externalizing problems), Symptomatic but Content (average to above average life satisfaction and affect, above average internalizing and externalizing difficulties), and Troubled (below average life satisfaction and affect, above average internalizing and externalizing difficulties). These profiles partially supported the dual-factor model of mental health, although a vulnerable group was not identified. Gender, SES, racial identity, and IEP status were significant predictors of mental health profile membership. Academic achievement, general grit, academic grit, and growth mindset were also significant predictors of mental health group membership. Limitations, future directions, and implications are discussed, including how these findings inform school psychological theory and practice.
Universal screening is a proactive method for identifying student risk, yet remains under-utilized in school systems. Instead, many schools rely on teacher reports and referrals without accounting for different informant perspectives. In the current study, multi-informant universal screening in evaluated using a trifactor model. The study utilized the Social, Academic, and Emotional Behavior Risk Screener (SAEBRS), specifically the teacher (SAEBRS-TRS) and student (mySAEBRS) self-report forms, with items indicating risk for social, academic, and emotional behavior. Data from a national sample of over 24,000 K-12 teacher-student dyads were used to examine the extent and variance of discrepant reports between students and teachers of common, perspective, and item factors. Results demonstrated that informant perspective factors were a strong predictor for student and teacher emotional behavior item ratings. Whereas age had a positive effect on younger student reports of risk on the behavior items compared to older student reports, teachers showed the opposite effect. The teacherperspective of social and emotional behaviors of students was predicted by gender. Implications and directions for future research are further discussed.
Many schools attempt to identify and service students at risk for poor mental health outcomes within a multi-tiered system of support (MTSS). Universal screening within a MTSS requires technically adequate tools. The Social, Academic, and Emotional Behavior Risk Screener (SAEBRS) has been put forth as a technically adequate screener. Researchers have examined the factor structure, diagnostic accuracy, criterion validity, and internal consistency of SAEBRS data. However, previous research has not examined its temporal stability or replicated the criterion validity results with a racially/ethnically diverse urban elementary school sample. This study examined the test–retest reliability, convergent validity, and predictive validity of teacher-completed SAEBRS ratings with racially/ethnically diverse group students enrolled in first through fifth grade in an urban elementary school. Reliability analyses resulted in significant test–retest reliability coefficients across four weeks for all SAEBRS scales. Furthermore, nonsignificant paired samples t tests were observed with the exception of the third-grade Emotional subscale. Validity analyses yielded significant concurrent and predictive Pearson correlation coefficients between SAEBRS ratings, oral reading fluency, and office discipline referrals. Limitations and implications of the results are discussed.
Dual-factor models of mental health are increasingly supported but little is known about longitudinal trends in dual-factor mental health. The current study used latent profile analysis (LPA) to empirically identify dual-factor mental health classes at each of Grades 9 through 12 and latent transition analysis (LTA) to examine stability of classes over four academic years. A sample of 875 adolescents from two cohorts reported on their social-emotional strengths and psychological distress. Cross-sectional LPAs for each grade year resulted in four mental health classes: complete mental health, moderately mentally healthy, symptomatic but content, and troubled. An LTA model indicated that the complete mental health class exhibited the most stability, followed by moderately mentally healthy and symptomatic but content classes. The troubled class exhibited the least stability. Less than 24% of participants remained in the same mental health class across all years. Findings support regular monitoring of students' dual-factor mental health to accurately inform mental health promotion, prevention, and intervention efforts.
Universal screening has been proposed as a method for effectively and efficiently identifying students at risk for mental health concerns. As with traditional rating scales, screeners have historically been used in the absence of any user training. Recent research suggests, however, that systematic training can be used to enhance the psychometric defensibility of teacher rating data. Thus, the present investigation evaluated the effectiveness of a pilot teacher training intervention on improving identification of students with behavioral or emotional concerns. A total of 91 teachers (57 training, 34 control) participated in the study. Participants in the training group received information on the utility of universal screening and were provided with information regarding mental and behavioral risk in schools. Videos depicting examples of problem behaviors and student concerns were also provided, and trainees were given the opportunity to practice rating videos with performance feedback. Following training, teachers completed the Social, Academic, and Emotional Behavior Risk Screener (SAEBRS) for their 1,158 students in four urban elementary schools. Teachers also completed measures of perceived assessment usability and willingness and efficacy to engage in universal screening. Finally, schools provided extant data regarding each student's academic and behavioral functioning (e.g., benchmark assessments, suspensions, and disciplinary referrals). Structural equation modeling and moderation analyses indicated a stronger relationship between SAEBRS fall risk and end-of-year behavioral outcomes in the trained group, and this relationship was moderated by assessment acceptability. Implications for practice and future research are discussed. 2018
Preschool has been recognized as an optimal time to provide behavioral and emotional supports to children; however, there is a need to examine the stability, accuracy, and predictive validity of universal emotional and behavioral screening scores in early childhood to inform procedures for repeated screenings across time. The present study included a sample of 1,014 students assessed with the Behavioral and Emotional Screening System Teacher Preschool screening form and comprehensive, omnibus teacher rating scales in preschool through first grade. Results indicated that scores from the Behavioral and Emotional Screening System Teacher screener were relatively stable within the school year and showed evidence of predictive validity of clinical problems in early childhood. To help identify who may benefit from a repeated screening later in the academic year, receiver operating characteristic curve analyses were conducted. A cut score of 51 emerged as a useful cut point to minimize expended resources and maximize sensitivity and specificity in finding new cases of risk. Implications for practitioners are discussed, including those related to the efficiency, timing, and frequency of screening in early childhood. © 2018 National Association of School Psychologist. All rights reserved.
This brief report presents preliminary psychometrics of responses to the Youth Externalizing Problems Screener (YEPS), which is a 10-item self-report rating scale intended for use as a screening instrument. The YEPS was designed to function as a companion measure to the Youth Internalizing Problems Screener (YIPS), facilitating the screening of broad mental health problems among students in secondary school settings. Analyses presented herein were conducted with the same small, preliminary samples of urban high-school students as those reported on for the initial development and validation of the YIPS (Sample 1: n = 177, Sample 2: n = 219). Results suggest that responses to the YEPS showed a sound, unidimensional factor structure that is internally consistent, providing initial evidence for the purported internal structure of the measure. Findings also showed that YEPS scores had meaningful associations with other self-reported, theoretically relevant mental health variables, providing initial convergent evidence in favor of construct interpretation. Taken together, preliminary psychometrics support the validation argument for the interpretation and use of YEPS scores as a brief measure of adolescents’ general externalizing problems. Implications for future research and practice are discussed.
Detecting mental illness in school students may prevent poor school outcomes. Clinicians often use universal behavioral screeners to identify students at risk for mental illness. This study examined the applicability of Kane’s interpretation and use argument (IUA) to the Social, Academic, and Emotional Behavior Risk Screener–Teacher Rating Scale (SAEBRS-TRS). Using an imputed sample of N = 1,357 students, latent transition analysis was employed to understand the IUA framework on this sample and the stability of the latent classes of student risk over time. Results provide initial support for the interpretation and use of the SAEBRS-TRS, and suggest that student risk statuses remain relatively stable across time. Future directions and implications for practice are discussed.
The purpose of this study was to evaluate the internal consistency reliability, validity, and diagnostic accuracy of Social, Academic, and Emotional Behavior Risk Screener–Teacher Rating Scale (SAEBRS) scores. Teachers (n = 68) universally screened 1,242 elementary students using two measures: the SAEBRS and the Behavioral and Emotional Screening System (BESS). Multilevel analyses indicated that although SAEBRS scores were internally consistent at the overall level, reliability suffered for certain SAEBRS scores at the between-group (classroom) level. Multilevel correlational analyses revealed moderate-to-large and statistically significant relations between SAEBRS and BESS scores at the overall, between-group, and within-group levels. Follow-up Fisher’s z tests revealed a pattern of convergent and discriminant relations in accordance with theory-driven expectations. Receiver operating characteristic (ROC) curve analyses supported the diagnostic accuracy of each SAEBRS scale. Further examination of findings relative to prior research suggested SAEBRS diagnostic accuracy is moderated by the type of criterion measure under consideration.
The study of measurement invariance in latent profile analysis (LPA) indicates whether the latent profiles differ across known subgroups (e.g., gender). The purpose of the present study was to examine the impact of noninvariance on the relative bias of LPA parameter estimates and on the ability of the likelihood ratio test (LRT) and information criteria statistics to reject the hypothesis of invariance. A Monte Carlo simulation study was conducted in which noninvariance was defined as known group differences in the indicator means in each profile. Results indicated that parameter estimates were biased in conditions with medium and large noninvariance. The LRT and AIC detected noninvariance in most conditions with small sample sizes, while the BIC and adjusted BIC needed larger sample sizes to detect noninvariance. Implications of the results are discussed along with recommendations for future research.
Although teacher-student relationships (TSRs) lie at the heart of teaching and learning, measuring these relationships presents unique challenges. These challenges implicate how school leaders understand the connections between TSRs and student outcomes. This article addresses these challenges by describing a new approach to measuring TSRs centered around a new scale that measures the positive and negative aspects of the overall TSR from teachers' and students' perspectives. We describe the scale development process, document the measure's psychometric properties, and then use the scale to predict student outcomes. Drawing from a sample of middle and high school students (N= 595) and their teachers (N = 88) in four different schools, we found that a two-factor model best fits our items. Compared to a more traditional approach, our approach explains more variability in student outcomes and gives educators a sharper understanding of the patterning of associations between TSRs and student outcomes.
Some universal behavioural screening processes require classroom teachers to complete a risk assessment measure on each student
in their class, leading to a possible, but unexplored, problem: risk
assessment scores may be influenced by the teacher completing the
measure. The current study investigated whether teacher-reported
risk assessment scores systematically differ between teachers and
whether they differ across both deficit- and strengths-based risk
assessment measures. Results from this study indicated that between
7.7 and 20.5% of the variance in risk assessment scores was attributable
to between-teacher differences. These findings underscore the need
to account for and control between-teacher differences in teacher-
reported risk assessments.
This study examined the extent to which teacher ratings of student behavior via the Social, Academic, and Emotional Behavior Risk Screener (SAEBRS) predicted academic achievement in math and reading. A secondary purpose was to compare the predictive capacity of three SAEBRS subscales corresponding to social, academic, or emotional domains of behavior. Universal screening was conducted to evaluate 1,058 elementary students’ performance in both reading and math, which were then combined to form a composite estimate of overall academic performance. Results indicated that the SAEBRS composite scale and all three subscales each individually predicted academic performance. Results further indicated that the SAEBRS Academic Behavior subscale was the best predictor of academic performance. Furthermore, the SAEBRS Social Behavior scale was found to function as a net suppressor variable, enhancing the capacity of Academic Behavior to predict academic performance via the suppression of variance irrelevant relative to academic performance. Follow-up path analyses suggested Academic Behavior also served as a mediating variable, as it partially accounted for the relationship between Social Behavior and academic performance. Implications for educators and limitations of this study are discussed.