Abstract
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.
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References
Allen, A., Kilgus, S. P., Burns, M. K., & Hodgson, C. (2019). Surveillance of internalizing behaviors: a reliability and validity generalization study of universal screening evidence. School Mental Health, 11, 194–209.
Arms, E., Bickett, J., & Graf, V. (2008). Gender bias and imbalance: girls in US special education programmes. Gender and Education, 20(4), 349–359.
Atkins, M. S., Hoagwood, K. E., Kutash, K., & Seidman, E. (2010). Toward the integration of education and mental health in schools. Administration and Policy in Mental Health and Mental Health Services Research, 37, 40–47.
Bruhn, A. L., Lane, K. L., & Hirsch, S. E. (2014a). A review of tier 2 interventions conducted within multitiered models of behavioral prevention. Journal of Emotional and Behavioral Disorders, 22(3), 171–189.
Bruhn, A. L., Woods-Groves, S., & Huddle, S. (2014b). A preliminary investigation of emotional and behavioral screening practices in K-12 schools. Education & Treatment of Children, 37(4), 611–634.
Burns, M. D., Monteith, M. J., & Parker, L. R. (2017). Training away bias: the differential effects of counterstereotype training and self-regulation on stereotype activation and application. Journal of Experimental Social Psychology, 73, 97–110.
Center on Multi-Tiered Systems of Support at the American Institutes for Research. (2019). Tips for intensifying instruction at Tier 1. American Institutes for Research.
Chen, H., Cohen, P., & Chen, S. (2010). How big is a big odds ratio? Interpreting the magnitudes of odds ratios in epidemiological studies. Communications in Statistics—Simulation and Computation, 39(4), 860–864.
Dever, B. V., Dowdy, E., Raines, T. C., & Carnazzo, K. (2015). Stability and change of behavioral and emotional screening scores. Psychology in the Schools, 52(6), 618–629.
Dever, B. V., Raines, T. C., Dowdy, E., & Hostutler, C. (2016). Addressing disproportionality in special education using a universal screening approach. The Journal of Negro Education, 85(1), 59–71.
Dineen, J. N., Chafouleas, S. M., Briesch, A. M., McCoach, D. B., Newton, S. D., & Cintron, D. W. (2022). Exploring social, emotional, and behavioral screening approaches in US public school districts. American Educational Research Journal, 59(1), 146–179.
Dowdy, E., Dever, B. V., Raines, T. C., & Moffa, K. (2016). A preliminary investigation into the added value of multiple gates and informants in universal screening for behavioral and emotional risk. Journal of Applied School Psychology, 32(2), 178–198.
Dowdy, E., & Kim, E. (2012). Choosing informants when conducting a universal screening for behavioral and emotional risk. School Psychology Forum, 6(4), 1–10.
Illuminate Education. (2022a). FastBridge SAEBRS. Retrieved from https://www.illuminateed.com/products/fastbridge/social-emotional-behavior-assessment/saebrs/.
Illuminate Education. (2022b). SAEBRS and mySAEBRS norms and benchmarks. Retrieved from https://fastbridge.illuminateed.com/hc/en-us/articles/1260802344370-SAEBRS-and-mySAEBRS-Norms-and-Benchmarks.
Eklund, K., & Dowdy, E. (2014). Screening for behavioral and emotional risk versus traditional school identification methods. School Mental Health, 6, 40–49.
Fabiano, G. A., & Evans, S. W. (2019). Introduction to the special issue of school mental health on best practices in effective multi-tiered intervention frameworks. School Mental Health, 11, 1–3.
Fallon, L. M., Veiga, M. B., Susilo, A., & Kilgus, S. P. (2023). Do teachers’ perceptions of high cultural responsiveness predict better behavioral outcomes for students? Behavioral Disorders, 48(2), 97–105.
Fallon, L. M., Veiga, M. B., Susilo, A., Robinson-Link, P., Berkman, T. S., Minami, T., & Kilgus, S. P. (2022). Exploring the relationship between teachers’ perceptions of cultural responsiveness, student risk, and classroom behavior. Psychology in the Schools, 59, 1948–1964.
Forscher, P. S., Mitamura, C., Dix, E. L., Cox, W. T. L., & Devine, P. G. (2017). Breaking the prejudice habit: Mechanisms, timecourse, and longevity. Journal of Experimental Social Psychology, 72, 133–146. https://doi.org/10.1016/j.jesp.2017.04.009
Gilliam, W. S., Maupin, A. N., Reyes, C. R., Accavitti, M., & Shic, F. (2016). Do early educators’ implicit biases regarding ex and race relate to behavior expectations and recommendations of preschool expulsions and suspensions? Yale University Child Study Center.
Girvan, E. J., Gion, C., McIntosh, K., & Smolkowski, K. (2017). The relative contribution of subjective office referrals to racial disproportionality in school discipline. School Psychology Quarterly, 32(3), 392–404.
Hart, S. R., Domitrovich, C., Embry, D. D., Becker, K., Lawson, A., & Ialongo, N. (2021). The effects of two elementary school-based universal prevention interventions on special education students’ socioemotional outcomes. Remedial and Special Education, 42(1), 31–43.
Iaccarino, S., von der Embse, N., & Kilgus, S. P. (2019). Interpretation and use of the social, academic, and emotional behavior risk screener: A latent transition approach. Journal of Psychoeducational Assessment, 37(4), 486–503.
Izumi, J. T. (2020). Detecting and explaining differential item functioning on the social, academic, and emotional behavior risk screener. (Doctoral dissertation, University of Missouri-Columbia).
Kilgus, S. P., Chafouleas, S. M., Riley-Tillman, T. C., & von der Embse, N. P. (2014). Social, Academic, and Emotional Behavior Risk Screener (SAEBRS). Theodore J. Christ & Colleagues.
Kilgus, S. P., Chafouleas, S. M., & Riley-Tillman, T. C. (2013). Development and initial validation of the social and academic behavior risk screener for elementary grades. School Psychology Quarterly, 28, 210–226.
Kilgus, S. P., & Eklund, K. (2016). Consideration of base rates within universal screening for behavioral and emotional risk: A novel procedural framework. School Psychology Forum: Research in Practice, 10(1), 120–130.
Kilgus, S. P., Taylor, C. N., & von der Embse, N. P. (2018). Screening for behavioral risk: Identification of high risk cut scores within the social, academic, and emotional behavior risk screener (SAEBRS). School Psychology Quarterly, 33(1), 155–159.
Letourneau, N. L., Duffett-Lelger, L., Levac, L., Watson, B., & Young-Morris, C. (2011). Socioeconomic status and child development: A meta-analysis. Journal of Emotional and Behavioral Disorders, 21(3), 211–224.
Mahoney, J. L., Durlak, J. A., & Weissberg, R. P. (2018). An update on social and emotional learning outcome research. Phi Delta Kappan, 100(4), 18–23.
Malone, C. M., Wycoff, K., & Turner, E. A. (2022). Applying a MTSS framework to address racism and promote mental health for racial/ethnic minoritized youth. Psychology in the Schools, 59(12), 2438–2452.
Marcucci, O. (2020). Implicit bias in the era of social desirability: Understanding antiblackness in rehabilitative and punitive school discipline. The Urban Review, 52, 47–74.
Margherio, S. M., Evans, S. W., & Owens, J. S. (2019). Universal screening in middle and high schools: Who falls through the cracks? School Psychology, 34(6), 591–602.
McCormick, M. P., Neuhaus, R., Horn, E. P., O’Connor, E. E., White, H. I., Harding, S., Cappella, E., & McClowry, S. (2019). Long-term effects of social–emotional learning on receipt of special education and grade retention: Evidence from a randomized trial of insights. AERA Open, 5(3), 1–21.
McIntosh, K., Girvan, E. J., Horner, R. H., & Smolkowski, K. (2014). Education not incarceration: A conceptual model for reducing racial and ethnic disproportionality in school discipline. The Journal of Applied Research on Children, 5, 1–22.
McLean, D., Eklund, K., Kilgus, S. P., & Burns, M. K. (2019). Influence of teacher burnout and self-efficacy on teacher-related variance in social-emotional and behavioral screening scores. School Psychology, 34(5), 503–511.
Mondi, C. F., & Reynolds, A. J. (2021). Socio-emotional learning among low-income prekindergarteners: The roles of individual factors and early intervention. Early Education and Development, 32(3), 360–384.
Moore, S., Long, A. C. J., Coyle, S., Cooper, J. M., Mayworm, A. M., Amirazizi, S., Edyburn, K. L., Pannozzo, P., Choe, D., Miller, F. G., Eklund, K., Bohnenkamp, J., Whitcomb, S., Raines, T. C., & Dowdy, E. (2023). A roadmap to equitable school mental health screening. Journal of School Psychology, 96, 57–74.
Murrieta, I., & Eklund, K. (2022). Universal screening to detect emotional and behavior risk among English language learners. School Psychology Review, 51(4), 441–453.
National Practitioner Advisory Group. (2019). Making SEL assessment work: Ten practitioner beliefs. Collaborative for Academic, Social, and Emotional Learning and the American Institutes for Research.
Okonofua, J. A., Paunesku, D., & Walton, G. M. (2016). Brief intervention to encourage empathic discipline cuts suspension rates in half among adolescents. Proceedings of the National Academy of Sciences, 113(19), 5221–5226.
Poppen, M., Sinclair, J., Hirano, K., Lindstrom, L., & Unruh, D. (2016). Perceptions of mental health concerns for secondary students with disabilities during transition to adulthood. Education and Treatment of Children, 39(2), 221–246.
Reinke, W. M., Stormont, M., Herman, K. C., Puri, R., & Goel, N. (2011). Supporting children’s mental health in schools: Teacher perceptions of needs, roles, and barriers. School Psychology Quarterly, 26(1), 1–13.
Romer, N., von der Embse, N., Eklund, K., Kilgus, S., Perales, K., Splett, J. W., Suldo, S., & Wheeler, D. (2020). Best practices in social, emotional, and behavioral screening: An implementation guide. Version 2.0. Retrieved from smhcollaborative.org/universalscreening
Romero, L. S., Scahill, V., & Charles, S. R. (2020). Restorative approaches to discipline and implicit bias: Looking for ways forward. Contemporary School Psychology, 24, 309–317.
Shi, Y., & Zhu, M. (2022). Equal time for equal crime? Racial bias in school discipline. Economics of Education Review, 88, 1–12.
Skiba, R. J., Horner, R. H., Chung, C., Rausch, M. K., May, S. L., & Tobin, T. (2011). Race is not neutral: A national investigation of African American and Latino disproportionality in school discipline. School Psychology Review, 40, 85–107.
Skiba, R. J., Michael, R. S., Nardo, A. C., & Peterson, R. L. (2002). The color of discipline: Sources of racial and gender disproportionality in school punishment. The Urban Review, 34, 317–342.
Skiba, R. J., Poloni-Staudinger, L., Gallini, S., Simmons, A. B., & Feggins-Azziz, R. (2006). Disparate access: The disproportionality of African American students with disabilities across educational environments. Exceptional Children, 72(4), 411–424.
Splett, J. W., Garzona, M., Gibson, N., Wojtalewicz, D., Raborn, A., & Reinke, W. M. (2019). Teacher recognition, concern, and referral of children’s internalizing and externalizing behavior problems. School Mental Health, 11, 228–239.
Splett, J. W., Trainor, K. M., Raborn, A., Halliday-Boykins, C. A., Garzona, M. E., Dongo, M. D., & Weist, M. D. (2018). Comparison of universal mental health screening to students already receiving intervention in a multitiered system of support. Behavioral Disorders, 43(3), 344–356.
van Oort, F. V. A., van der Ende, J., Wadsworth, M. E., Verhulst, F. C., & Achenbach, T. M. (2011). Cross-national comparison of the link between socioeconomic status and emotional and behavioral problems in youths. Social Psychiatry and Psychiatric Epidemiology, 46(2), 167–172.
Verlenden, J., Naser, S., & Brown, J. (2021). Steps in the implementation of universal screening for behavioral and emotional risk to support multi-tiered systems of support: Two case studies. Journal of Applied School Psychology, 37(1), 69–107.
von der Embse, N., Kim, E. S., Jenkins, A., Sanchez, A., Kilgus, S. P., & Eklund, K. (2021). Profiles of rater dis/agreement within universal screening in predicting distal outcomes. Journal of Psychopathology and Behavioral Assessment, 43, 632–645.
von der Embse, N., Kim, E. S., Kilgus, S., Dedrick, R., & Sanchez, A. (2019). Multi-informant universal screening: Evaluation of rater, item, and construct variance using a trifactor model. Journal of School Psychology, 77, 52–66.
von der Embse, N. P., Pendergast, L. L., Kilgus, S. P., & Eklund, K. R. (2016). Evaluating the applied use of a mental health screener: Structural validity of the social, academic, and emotional behavior risk screener. Psychological Assessment, 28, 1265–1275.
Wehmeyer, M. L., & Schwartz, M. (2001). Disproportionate representation of males in special education services: Biology, behavior, or bias? Education & Treatment of Children, 24, 28–45.
Wood, B. J., & Ellis, F. (2022). Universal mental health screening practices in Midwestern schools: A window of opportunity for school psychologist leadership and role expansion? Contemporary School Psychology. https://doi.org/10.1007/s40688-022-00430-8
Young, E. L., Sabbah, H. Y., Young, B. J., Reiser, M. L., & Richardson, M. J. (2010). Sex differences and similarities in a screening process for emotional and behavioral risks in secondary schools. Journal of Emotional and Behavioral Disorders, 18(4), 225–235.
Zakszeski, B., Ormiston, H. E., Nygaard, M. A., & Carlock, K. (2023). Informant discrepancies in universal screening as a function of student and teacher characteristics. Unpublished manuscript. Education & Human Development, University of Delaware.
Acknowledgements
Financial support was provided by the US Office of Elementary and Secondary Education Mental Health Professional Demonstration Grant #S184X190033, but the funding source had no such involvement in the study design, data collection, analysis andinterpretation of data, in writing the report, or in deciding to submit for publication.
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This work was supported by the US Office of Elementary and Secondary Education Mental Health Professional Demonstration Grant #S184X190033.
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Ormiston, H.E., Renshaw, T.L. Student Demographics as Predictors of Risk Placements via Universal Behavioral Screening. School Mental Health 15, 1076–1089 (2023). https://doi.org/10.1007/s12310-023-09603-z
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DOI: https://doi.org/10.1007/s12310-023-09603-z