Educators across the U.S. are reporting an alarming rise in behavioral disruptions among elementary school students over the last few years. Driven by the need to manage the increase in both volume and intensity of disruptive behaviors, schools are scrambling to provide adequate support resources to meet students’ behavioral and emotional needs.
Unfortunately, evidence suggests that current efforts are insufficient to manage the increase. The national student-to-counselor ratios, for example, are far below the levels recommended by the American School Counselor Association. In our own survey on behavioral disruptions, 69% of educators said that their schools support resources are currently “understaffed” or “severely understaffed.”
The most effective way to address the rising demand for support services is through better preventive efforts. However, identifying the right students at the right time is often difficult. Many students may show no signs of distress for a long time before acting out. At the same time, support resources are naturally directed towards those who do. With behavioral disruptions on the rise, support resources are inevitably used to respond to crises rather than prevent them.
Universal screening a highly effective method of identification
In order to support effective early identification and prevention, educators and psychologists, including the American Psychological Association (APA) and the National Association of School Psychologists (NASP)1, have long promoted the use of universal screening tools for behavioral and emotional issues.
These tools take the form of short questionnaires given to a variety of groups: teachers, students, and/or parents, allowing schools to evaluate large groups of students quickly and at scale (screening usually takes a few minutes per child). Each student receives a score indicating whether they may benefit from additional support. This form of screening gives educators an objective, evidence-based way of measuring which students may be at risk of exhibiting disruptive behavior in the future.
Misconceptions among educators hinder widespread adoption of best practice
Despite decades of evidence supporting the effectiveness and efficiency of universal screening in identifying students at risk, most U.S. districts are still relying on teacher referrals alone to identify the need for student support. In a 2018 survey, only about a third of District Leadership Forum districts (30%) reported using a universal screening tool, while a 2014 national sample puts the number at an even lower 12.6%.
There are two main reasons why many educators are reluctant to adopt universal screening measures: concern that instruments will identify too many students and stretch support resources even further, and fear that teachers will end up labeling students based on the results of the screening.
Decades of research have shown that universal screening tools do not overidentify students. The most commonly used screeners demonstrate high accuracy2 in identifying at-risk students, give very few false positives3, and identify a similar number of students compared to traditional teacher referrals. However, screeners identify students much earlier than referrals, giving schools the opportunity to intervene proactively.
Furthermore, teacher referrals tend to be more subjective and open to individual bias and are much more likely to focus on externalizing behavior (e.g., students acting out). While teacher referrals are still a valuable strategy for identifying students with behavioral or emotional issues, they work best when used alongside a universal screener, not instead of one.
The other most common concern is that identified students will be labeled as “problem kids” by teachers and peers. However, district administrators already screen students for many other indicators—reading, math, health, vision, etc.—without expressing similar hesitation. The fact that educators see emotional and mental health as an area where labeling might be more concerning likely reflects a broader societal stigma on mental health. Unfortunately, students and even teachers already label others in the classroom. Universal screening is a way to prevent labeling because it allows educators to help students early, long before they have acted out and given reasons for others around them to view them as “trouble.”
Careful planning ensures success of universal screening
There is no single “best” universal screening tool and districts should consider carefully the pros and cons of the many available. While we have provided a reference table with summary of the latest research on the most popular evidence-based screeners, we recommend that districts conduct their own review of existing tools in consultation with support specialists. Among the most important factors they should consider are cost, time to complete per student, availability in multiple languages, availability of additional assessment and analysis tools, and ease of administration.
Finally, although the choice of evidence-based tool will differ by district, there are a few common elements that we recommend districts follow when adopting universal screening. These include ensuring parental consent via an opt-in/opt-out process, screening more than once each school year, and training teachers on using the selected tool in advance. Taking these factors into account ensures proper and smooth administration of the screening and makes it both a resource-efficient and highly effective method of assessing and identifying the emotional and behavioral needs of young students.
Comparison of evidence-based universal screeners
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1National Association of School Psychologists. (2015). The importance of mental and behavioral health services
for children and adolescents (Position statement). Bethesda, MD: Author.
2Positive predictive values of most universal screeners range from 0.5 to 0.8. Positive predictive values identify proportion of correctly identified students from those identified at risk.
3Negative predictive values of most universal screeners range from 0.92 to 0.98. Negative predictive values identify proportion of correctly identified students of those not identified at risk.
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