Despite the pressure on schools to identify troubled students in order to prevent school violence, screening students for mental health problems still ranks as a very low priority within most school systems.
Some 20% of the school-age student population has been estimated to be in need of treatment for emotional and behavioral problems, according to a recent article in the Journal of School Psychology. But universal mental health screening is a responsibility few administrators have been willing to accept.
Not only is there a concern that schools don’t have the resources to meet students’ mental health needs, but also there is a sense that schools should be primarily focused on students’ academic development.
In the study, researchers focus on one of the major stumbling blocks to implementing universal mental health screening–choosing an effective and practicable screening tool. The researchers report on an expert panel’s selection of a handful of screening measures that have a track record in the literature. “The expert panel determined that there was an appropriate research base to support the use of these screening tools,” the researchers write.
“It is well known that teachers substantially underrefer students with behavior problems–particularly those with internalizing type problems and disorders,” the researchers report. Referrals of students for academic problems peak between grades 2 and 3, the researchers report, while referrals for behavior problems peak in grade 9, seven years later.
“It is strongly recommended that school systems adopt universal screening approaches that (a) allow for the mass screening and evaluation of all students in a school and that (b) move routine school practices away from a reactive and toward a more proactive posture in this vitally important area.”
The screening measures selected by the panel based on their review of the literature were:
- Systematic Screening for Behavior Disorders (SSBD),
- SSBD: Critical Events Index (CEI),
- SSBD Academic Engaged Time (AET),
- SSBD Peer Social Behavior (PSB),
- School Social Behavior Scale (SSBS),
- Revised Behavior Problem Checklist,
- Eyberg Child Behavior Inventory (ECBI); and
- Drummond’s Student Risk-Screening Scale (SRSS).
The optimal measure for school screenings, the panel concluded, was the Systematic Screening for Behavior Disorders (SSBD). The SSBD procedure (Walker & Severson, 1990) “was endorsed in the behavioral assessment literature and had been used in numerous studies to screen elementary-aged children for behavioral problems of an externalizing and internalizing nature,” the researchers report.
SSBD was selected because it distinguishes between internalizers and externalizers (e.g. depression vs. disruptive behavior), has multiple gating procedures (teacher ratings, school professional observations), has acceptability in the field of behavior disorders and has been tested with a national normative sample of upwards of 6,000 students, the researchers report.
Multiple gating results in better identification of at-risk students compared to the spontaneous referrals of teachers, the researchers report. Multiple gating identifies students through multiple agents, multiple settings and multiple forms of assessment. This builds in cross-checking and greater accuracy, the researchers write. Multiple gating is also more cost-effective in that the number of students at each level of screening is reduced as the intensity and the sensitivity of the screening process increases with each successive stage, the researchers write.
Another important advantage of these screening measures, the researchers report, is that students are rated on common behavioral criteria. The Student Risk Screening Scale (SRSS) provides a highly accurate and cost-efficient system for teacher judgments about students’ antisocial behavior, the researchers report. The SSRS consists of seven behavioral indicators of antisocial behavior identified from the extensive professional literature on this topic. Teachers assign a Likert rating (0-3) to each student in the class based on the seven behavioral criteria. The SSRS is highly recommended for use in initial screening to detect students with emerging antisocial behavior patterns, the researchers report.
The Child Behavior Checklist, the Social Skills Rating Scale and the Behavioral and Emotional Rating Scale are other measures that can be used to refer children who are demonstrating school adjustment and social skill problems, the researchers report. Each has a parent version that allows for cross-checking the assessment of the child’s behavior and skill levels. All of the selected measures represent a substantial improvement over the “‘wait to fail'” model of teacher referral that has traditionally been the practice in many public schools,” the researchers write.
Screening assessments should occur twice during the school year, the researchers recommend: Approximately one month to six weeks following the beginning of school to allow teachers time to become familiar with the behavioral characteristics of their students and at the beginning of the second semester to account for changes in students’ behavior patterns and to accommodate the transfer of new students into the school.
The expert panel’s review was part of a project funded by the Office of Special Education Programs (OSEP) in the fall of 2004 involving four national Behavior Research Centers and the National Behavior Research Coordination Center at Stanford Research Institute.
According to the researchers, some other emerging innovations in behavioral screening and early detection of at-risk students are:
• Analysis of schools’ office discipline referrals (ODRs)
• Screening on the basis of Responsiveness to Intervention (RTI)
• Screening for exposure to risk factors associated with destructive outcomes.
Referrals for discipline
Research indicates that the top 5% of elementary students with the most disciplinary referrals accounted for approximately 59% of total ODRs within a school while the top 5% of middle schoolers accounted for 40%of total ODRs. As a rule, students with 5 or more ODRs are considered at risk and those with 10 or more ODRs are considered chronic discipline problems, the researchers report.
School-Wide Information System (SWIS) is a web-based software system for recording, entering, organizing and reporting ODRs. While SWIS is highly efficient for identifying students with externalizing behavior problems, it does not detect those with internalizing disorders (e.g. depression, phobias, social isolation).
RTI can be used in screening for emotional and behavior disorders and determining eligibility for special education and related services based on response to interventions.
“RTI assumes that if a student demonstrates an inadequate response to the best interventions available, then that student can and should be eligible for additional assistance including more intense interventions, special assistance, or special education and related services,” the researchers write.
Most proponents of the RTI approach use a multi-tiered model of intervention with increasing intensity of services, the researchers report. RTI interventions are typically developed between school psychologists and school personnel through a problem-solving approach.
The principle of precipitating vs. predisposing factors is an important and useful concept for the screening-identification process, the researchers note. Predisposing factors typically include the child’s history and experiences while precipitating factors are often the stressful events in a child’s life. In contrast to a disease model, the researchers note that an “accident prevention” model may be the more helpful model of step-wise risk reduction.
An important step is for schools to define the purpose of screenings. Are they to prevent school failure and dropout, refer students to outside mental health services, or to help teachers accommodate students?
“Proactive, early screening to detect behaviorally at-risk students: Issues, approaches, emerging innovations, and professional practices” Journal of School Psychology Volume 45 2007 pp. 193-223.
Published in ERN April 2007 Volume 20 Number 4