District Leadership Content
This article is designed for district administrators, MTSS coordinators, and school psychologists implementing system-wide behavior screening programs.
Why Universal Screening?
Just as we screen all students for reading difficulties, universal behavior screening identifies students who may need additional support before problems become severe.
The Case for Screening
- Early identification: Catch concerns in Tier 1 before Tier 3 is needed
- Resource allocation: Data-driven decisions about intervention staffing
- Equity: Systematic process reduces referral bias
- Prevention focus: Shift from reactive to proactive support
Screening Tools Overview
| Tool Type | Examples | Considerations |
|---|---|---|
| Teacher Rating Scales | SRSS, SAEBRS, SDQ | Quick, low cost, subjective |
| Office Discipline Referrals | ODR data from SWIS | Already collected, varies by school culture |
| Direct Behavior Rating | DBR-SIS | Repeated measurement, more training needed |
| Comprehensive Measures | BASC-3 BESS | Normed, validated, higher cost |
Implementation Timeline
Phase 1: Planning (Spring Before)
Select screening tool, establish decision rules, train staff, communicate with stakeholders
Phase 2: Fall Screening (Weeks 4-6)
Administer universal screener, analyze data, identify students for Tier 2/3 consideration
Phase 3: Winter Screening (January)
Re-screen all students, evaluate intervention effectiveness, adjust supports
Phase 4: Spring Screening (April-May)
Final screening, year-end data analysis, inform summer and fall planning
Establishing Decision Rules
Before screening, establish clear criteria for action:
Sample Decision Framework
- Low Risk: Continue Tier 1 supports, monitor at next screening
- Some Risk: Consider Tier 2 intervention, collect additional data
- High Risk: Immediate Tier 2/3 consideration, possible FBA referral
Screening Informs, Does Not Diagnose
Universal screening data identifies students who may need additional assessment or support. It is not diagnostic. Communicate this clearly to teachers and parents to prevent misunderstanding about screening results.
References
Lane, K. L., Oakes, W. P., Buckman, M. M., Lane, N. A., Lane, K. S., Fleming, K., Swinburne Romine, R. E., Sherod, R. L., Cantwell, E. D., & Chang, C.-N. (2024). New evidence of predictive validity of SRSS-IE scores with middle and high school students. Frontiers in Education, 8, 1251063. https://doi.org/10.3389/feduc.2023.1251063
Sugai, G., & Horner, R. H. (2020). Sustaining and scaling positive behavioral interventions and supports: Implementation drivers, outcomes, and considerations. Exceptional Children, 86(2), 120–136. https://doi.org/10.1177/0014402919855331
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. Journal of Applied Research on Children, 5(2), Article 4.
Ruble, L. A., McGrew, J. H., Wong, W. H., & Missall, K. N. (2018). Special education teachers' perceptions and intentions toward data collection. Journal of Early Intervention, 40(2), 177–191. https://doi.org/10.1177/1053815118771391
Blue-Banning, M., Summers, J. A., Frankland, H. C., Lord Nelson, L., & Beegle, G. (2004). Dimensions of family and professional partnerships: Constructive guidelines for collaboration. Exceptional Children, 70(2), 167–184. https://doi.org/10.1177/001440290407000203
Sheridan, S. M., Smith, T. E., Kim, E. M., Beretvas, S. N., & Park, S. (2019). A meta-analysis of family-school interventions and children’s social-emotional functioning: Moderators and components of efficacy. Review of Educational Research, 89(2), 296–332. https://doi.org/10.3102/0034654318825437
Lei, H., Cui, Y., & Chiu, M. M. (2016). Affective teacher-student relationships and students’ externalizing behavior problems: A meta-analysis. Frontiers in Psychology, 7, 1311. https://doi.org/10.3389/fpsyg.2016.01311
U.S. Department of Education. (2021). FERPA general guidance for parents and eligible students. https://studentprivacy.ed.gov/
Take Action
Put what you've learned into practice with these resources.
Key Takeaways
- Universal screening identifies students needing support before crisis
- Screening should occur at least three times per year (fall, winter, spring)
- Decision rules must be established before screening begins
- Screening data informs resource allocation, not individual diagnosis
- Teacher buy-in requires clear communication about purpose and use
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About the Author
Dr. Sarah Mitchell consists of former Special Education Teachers and BCBAs who are passionate about leveraging technology to reduce teacher burnout and improve student outcomes.
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