Determining Effective Selection and Implementation of Function-Based Interventions in Schools Presented by Lauraine Allen, April Ard, Erin Dean, Michelle MacGregor, Alex Nalivaiko, Kelly Rulon, Amanda Skourtis & Claire Zandoli
Introduction & Literature Review • Students with severe emotional & behavioral issues nationwide: • whether or not they are eligible for special education services or experience full inclusion, will not demonstrate significant academic or behavioral progress over an entire academic year (Minahan& Rappaport, 2012). • will always make up 5% of the student body in our nation’s schools (Taylor-Green et. al, 1997). • make up over 50% of office referrals, which reduces instructional time and increases the likelihood of school dropout rates for this population (Arcia, 2006).
Foundations & IDEA • 1997 amendment of IDEA requires the use of functional behavioral assessments (FBA) and positive behavioral interventions and supports (PBIS) under certain circumstances for students with IEPs in schools. • IDEIA 2004 articulates the criteria for implementation of a positive behavior support plan for students with IEPs (Wright et. al, 2007). • FBA is an example of a functional based intervention that examines the antecedent, behaviors and the consequences to determine the reason of the behavior (Gresham, Watson, & Skinner, 2001).
Research Questions • What are the critical features of function-based intervention across setting events, antecedents, behavior and consequences? • What processes do experts and non-experts use in coming up with/developing behavioral interventions? • What are similarities and differences in the approach to identifying function-based intervention based on FBA information? • How can this information be used to provide better training in identifying function-based interventions?
Participants & Setting • Participants divided into two categories: seven “experts,” and eight “non-experts.” • Experts were defined as people who have published work in the field of positive behavior supports and were located throughout the country. • Non-experts were defined as people who currently work in the field of education and had some background in behavior support planning. • Participants signed a consent form then agreed to either complete an interview on the phone, via Skype or in person.
Measures • Interview tool: behavior pathway forms revised to include sample students and sample problem behaviors (vignettes), created by Chris Borgmeier, PhD. and Sheldon Lohman, PhD. • Participants filled out one “choice” vignette and one “open-ended” vignette. • Each pair of vignettes had a different function and problem behavior.
Interview tool Choice Open Ended
Procedures • Semi-structured interviews (approximately 30 minutes) which were recorded then transcribed by the researchers. • Participants were given two vignettes with different functions of behavior the day before the scheduled interview. • Participants were prompted by researchers to explain why they came up with or chose specific interventions as well as logic/reasoning for ruling out other interventions.
Trends in Data • A presence of “high performing” non-experts emerged when comparing correct responses across all of the data categories. • 2/8 non-experts answered all the questions correctly. Range of 14% correct to 100% correct responses. • Not a single expert scored 100% correct. Range of 71% correct to 86% correct responses.
Comparison of Experts & Non-Experts • There were a range of non-experts. • Found similarities among the higher scoring non-experts’ and experts’ approach and explanations for identifying interventions. • Non-experts who scored low didn’t identify function when determining interventions, while experts did. • Non-experts often went with interventions they have done before; what might have worked with other students. • “I’ve seen this work for teachers before.” • Had reasons for choosing interventions, but did not link to function of behavior & individual student needs.
Common Features of Experts & Higher Performing Non-Experts • Experts & higher scoring ‘non-experts’ used a common language & approach to identifying interventions that were based on function. • More direct responses and more streamlined approach to identifying interventions & ruling out interventions.
Critical Features of Interventions Identified by Participants • Experts talked a lot about the use of reinforcement to maintain behavior. • Non-experts didn’t link reinforcement to the alternate behavior, but focused more on long-term, desired behavior. • Interventions responding to problem behavior: • Greater focus on extinction vs. redirection to alternate behavior across both experts & non-experts.
Implications for Training • When training to identify antecedent interventions, it is necessary to explicitly link them to function. • Training needs to focus on concept of alternate behavior & reinforcement and redirection to alternate behavior.
Implications for Training, cont. • We can more effectively teach concepts and strategies for identifying function-based intervention • BUT there are still challenges to: • daily use and implementation. • implementation with staff who do not understand behavior from a functional perspective: • more punishment oriented. • Prefer to use same 2-3 interventions, rather than something new (and individualized).
Limitations • Small sample size. • After the analysis of data collection, researchers determined additional prompting of reasons for selecting interventions during semi-structured interviews was necessary.
Future Research • Use trends in processes and strategies ‘experts’ and high performing ‘non-experts’ used to identify function-based interventions to inform training methods. • Evaluate methods of training emerging professionals to identify function-based interventions for students.
In Conclusion • We found that identified experts in the field were more accurate and more likely to link their intervention choices to the given function. • Non-experts were less accurate and more likely to use interventions that they had previously implemented. • These findings suggest that future research and training need to focus on the concept of linking interventions explicitly to the function of behavior.
References Arcia, E. (2006). Achievement and enrollment status of suspended students: Outcomes in a large, multicultural school district. Education and Urban Society, 38(3), 359-369. Gresham, F. M., Watson, T. S., Skinner, C. H. (2001). Functional behavior assessment: Principles, procedures, and future directions. School Psychology Review, 30(2), 156-172. Taylor-Greene, S., Brown, D., Nelson, L., & Longton, J. (1997). School-wide behavioral support: Starting the year off right. Journal of Behavioral Education, 7, 99-112. Minahan, J. &. Rappaport, N. (2012). Be a behavior detective: Improving prospects for challenging students. Harvard Education Letter, 28(3). Retrieved from http://www.hepg.org/hel/article/534 Wright, D. B., Mayer, G. R., Cook, C. R., Crews, S. D., Kraemer, B. R., & Gale, B. (2007). A preliminary study on the effects of training using behavior support plan and quality evaluation guide (BSP-QE) to improve positive behavior support plans. Education and Treatment of Children, 30(3), 90-106.