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Abstract
School systems are the primary providers for the increasing number of children with mental health needs. School-based universal screening offers a valuable way to identify children that would benefit from school-based mental health services. However, many existing screening systems rely on teacher ratings alone and do not incorporate student self-ratings. The current study evaluates the psychometric properties of the Social, Academic, and Emotional Behavior Risk Screener–Student Rating Scale (SAEBRS-SRS), a new 20-item multidimensional universal screener intended to provide assessment data on students’ social, academic, and emotional functioning. The SAEBRS-SRS complements the SAEBRS Teacher Rating Scale (TRS), which has previously demonstrated robust psychometric evidence. In the current study, data were collected from a racially and ethnically diverse sample of middle school students. Confirmatory factor analyses supported a bifactor structure consistent with the SAEBRS-TRS, with items corresponding to internally consistent Social, Academic, and Emotional Behaviors subscales, as well as an overall Total Behavior scale. The current analyses yield promising initial support for the development of the SAEBRS-SRS. Implications and the need for future research to provide additional psychometric evidence are discussed.
References
Section:
|
Bruhn, A. L., Woods-Groves, S., Huddle, S. (2014). A preliminary investigation of emotional and behavioral screening practices in K–12 schools. Education and Treatment of Children, 37, 611–634. doi:10.1353/etc.2014.0039 Google Scholar | Crossref | ISI | |
|
De Los Reyes, A., Augenstein, T. M., Wang, M., Thomas, S. A., Drabick, D. A., Burgers, D. E., Rabinowitz, J. (2015). The validity of the multi-informant approach to assessing child and adolescent mental health. Psychological Bulletin, 141, 858–900. doi:10.1037/a0038498 Google Scholar | Crossref | Medline | ISI | |
|
De Los Reyes, A., Thomas, S. A., Goodman, K. L., Kundey, S. M. A. (2013). Principles underlying the use of multiple informants’ reports. Annual Review of Clinical Psychology, 9, 123–149. doi:10.1146/annurev-clinpsy-050212-185617 Google Scholar | Crossref | Medline | ISI | |
|
DeMars, C. E. (2013). A tutorial on interpreting bifactor model scores. International Journal of Testing, 13, 354–378. doi:10.1080/15305058.2013.799067 Google Scholar | Crossref | |
|
DiStefano, C., Greer, F. W., Kamphaus, R. W. (2013). Multifactor modeling of emotional and behavioral risk of preschool-age children. Psychological Assessment, 25, 467–476. doi:10.1037/a0031393 Google Scholar | Crossref | Medline | ISI | |
|
Dowdy, E., Kim, E. (2012). Choosing informants when conducting a universal screening for behavioral and emotional risk. School Psychology Forum, 6, 1–10. Google Scholar | |
|
Drummond, T. (1994). The Student Risk Screening Scale (SRSS). Grants Pass, OR: Josephine County Mental Health Program. Google Scholar | |
|
Duchesne, S., Vitaro, F., Larose, S., Tremblay, R. E. (2008). Trajectories of anxiety during elementary-school years and the prediction of high school noncompletion. Journal of Youth and Adolescence, 37, 1134–1146. doi:10.1007/s10964-007-9224-0 Google Scholar | Crossref | ISI | |
|
Gignac, G. E. (2005). Revisiting the factor structure of the WAIS-R insights through nested factor modeling. Assessment, 12, 320–329. Google Scholar | SAGE Journals | ISI | |
|
Goodman, R. (1997). The Strengths and Difficulties Questionnaire: A research note. Journal of Child Psychology and Psychiatry, 38, 581–586. doi:10.1111/j.1469-7610.1997.tb01545.x Google Scholar | Crossref | Medline | ISI | |
|
Hu, L., Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 6, 1–55. doi:10.1080/10705519909540118 Google Scholar | Crossref | ISI | |
|
Jenkins, L. N., Demaray, M. K., Wren, N. S., Secord, S. M., Lyell, K. M., Magers, A. M., Tennant, J. (2014). A critical review of five commonly used social-emotional and behavioral screeners for elementary or secondary schools. Contemporary School Psychology, 18, 241–254. doi:10.1007/s40688-014-0026-6 Google Scholar | Crossref | |
|
Kahlberg, J. R., Lane, K. L., Driscoll, S., Wehby, J. (2011). Systematic screening for emotional and behavioral disorders at the high school level: A formidable and necessary task. Remedial and Special Education, 32, 506–520. Google Scholar | SAGE Journals | |
|
Kamphaus, R. W., DiStefano, C., Dowdy, E., Eklund, K., Dunn, A. (2010). Determining the presence of a problem: Comparing two approaches for detecting youth behavioral risk. School Psychology Review, 39, 395–407. Google Scholar | ISI | |
|
Kamphaus, R. W., Reynolds, C. R. (2007). BASC-2 Behavioral and Emotional Screening System manual. Bloomington, IL: Pearson. Google Scholar | |
|
Kilgus, S. P., Eklund, K., von der Embse, N. P., Taylor, C. N., Sims, W. A. (2016). Psychometric defensibility of the Social, Academic, and Emotional Behavior Risk Screener (SAEBRS) Teacher Rating Scale and multiple gating procedure within elementary and middle school samples. Journal of School Psychology, 58, 21–39. Google Scholar | Crossref | Medline | |
|
Kilgus, S. P., Sims, W. A., von der Embse, N. P., Riley-Tillman, T. C. (2015). Confirmation of models for interpretation and use of the Social and Academic Behavior Risk Screener (SABRS). School Psychology Quarterly, 30, 335–352. doi:10.1037/spq0000087 Google Scholar | Crossref | Medline | |
|
Kilgus, S. P., Sims, W., von der Embse, N.P., Taylor, C. (2016). Psychometric defensibility of the Social, Academic, and Emotional Behavior Risk Screener (SAEBRS) teacher rating scale. Assessment for Effective Intervention. doi: 10.1177/1534508415623269 Google Scholar | SAGE Journals | |
|
Kilgus, S. P., von der Embse, N. P. (2015). Social, Academic, and Emotional Behavior Risk Screener (SAEBRS). Minneapolis, MN: Theodore J. Christ & Colleagues. Google Scholar | |
|
Kline, R. B. (2011). Principles and practice of structural equation modeling (3rd ed.). New York, NY: Guilford Press. Google Scholar | |
|
Lane, K. L., Little, M. A., Casey, A. M., Lambert, W., Wehby, J., Weisenbach, J. L., Phillips, A. (2009). A comparison of systematic screening tools for emotional and behavioral disorders. Journal of Emotional and Behavioral Disorders, 17, 93–105. doi:10.1177/1063426608326203 Google Scholar | SAGE Journals | ISI | |
|
Marsh, H. W., Hau, K.-T., Grayson, D. (2005). Goodness of fit evaluation in structural equation modeling. In Maydeu-Olivares, A., McArdle, J. (Eds.), Contemporary psychometrics: A Festschrift for Roderick P. McDonald (pp. 275–340). Mahwah, NJ: Lawrence Erlbaum. Google Scholar | |
|
McIntosh, K., Ty, S. V., Miller, L. D. (2014). Effects of school-wide positive behavioral interventions and supports on internalizing problems current evidence and future directions. Journal of Positive Behavior Interventions, 16, 209–218. doi:10.1177/1098300713491980 Google Scholar | SAGE Journals | |
|
Muthén, L. K., Muthén, B. O. (1998–2013). Mplus (Version 7.1). Los Angeles, CA: Author. Google Scholar | |
|
Muthén, L. K., Muthén, B. O. (2011). Mplus user’s guide (6th ed.). Los Angeles, CA: Author. Google Scholar | |
|
Perou, R., Bitsko, R. H., Blumberg, S. J., Pastor, P., Ghandour, R. M., Gfroerer, J. C., Parks, S. E. (2013). Mental health surveillance among children—United States, 2005–2011. MMWR Surveillance Summary, 62(2), 1–35. Google Scholar | |
|
Raines, T. C., Dever, B. V., Kamphaus, R. W., Roach, A. T. (2012). Universal screening for behavioral and emotional risk: A promising method for reducing disproportionate placement in special education. The Journal of Negro Education, 81, 283–296. doi:10.7709/jnegroeducation.81.3.0283 Google Scholar | Crossref | |
|
Rapport, M. D., Denney, C. B., Chung, K. M., Hustace, K. (2001). Internalizing behavior problems and scholastic achievement in children: Cognitive and behavioral pathways as mediators of outcome. Journal of Clinical Child Psychology, 30, 536–551. doi:10.1207/S15374424JCCP3004_10 Google Scholar | Crossref | Medline | |
|
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. Urban Review, 34, 317–342. doi:10.1023/A:1021320817372 Google Scholar | Crossref | |
|
Smith, S. R. (2007). Making sense of multiple informants in child and adolescent psychopathology: A guide for clinicians. Psychoeducational Assessment, 25, 139–149. doi:10.1177/0734282906296233 Google Scholar | SAGE Journals | |
|
Steiger, J. H., Lind, J. C. (1980, May). Statistically based tests for the number of common factors. In Proceedings of the annual meeting of the Psychometric Society, Iowa City, IA. Google Scholar | |
|
Tabachnick, B. G., Fidell, L. S. (2013). Using multivariate statistics (6th ed.). Boston, MA: Allyn and Bacon. Google Scholar | |
|
Taylor, C., Allen, A., Kilgus, S., von der Embse, N., Garbacz, S. A. (2016). Development and validation of a parent version of the Social, Academic, and Emotional Behavior Risk Screener (SAEBRS). Manuscript submitted for publication. Google Scholar | |
|
von der Embse, N. P., Mata, A., Segool, N., Scott, E. C. (2014). Latent profile analysis of test anxiety: A pilot study. Journal of Psychoeducational Assessment, 32, 165–172. Google Scholar | SAGE Journals | |
|
von der Embse, N. P., Pendergast, 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. doi:10.1037/pas0000253 Google Scholar | Crossref | Medline | |
|
Zinbarg, R. E., Revelle, W., Yovel, I., Li, W. (2005). Cronbach’s α, Revelle’s β, and McDonald’s ωH: Their relations with each other and two alternative conceptualizations of reliability. Psychometrika, 70(1), 123–133. Google Scholar | Crossref | ISI |
