Association for Behavior Analysis International

The Association for Behavior Analysis International® (ABAI) is a nonprofit membership organization with the mission to contribute to the well-being of society by developing, enhancing, and supporting the growth and vitality of the science of behavior analysis through research, education, and practice.


48th Annual Convention; Boston, MA; 2022

Event Details

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Symposium #61
CE Offered: PSY/BACB
Insurance-Funded Applied Behavior Analysis Intervention Amidst the COVID-19 Pandemic: Telehealth and Learner Outcomes
Saturday, May 28, 2022
12:00 PM–12:50 PM
Meeting Level 2; Room 258A
Area: AUT; Domain: Service Delivery
Chair: Valerie R. Rogers (The ABRITE Organization)
Discussant: Kendra B. Newsome (Fit Learning)
CE Instructor: Valerie R. Rogers, Ph.D.
Abstract: Though the COVID-19 pandemic has brought many challenges related to securing and maintaining access to applied behavior analysis (ABA) intervention for children with autism, it also brought forth an opportunity to evaluate changes in treatment modality, intensity or dose of treatment, and overall access to intervention on learner gains and outcomes. For many ABA agencies, insurance-funded medically necessary ABA has changed in many ways since the onset of the pandemic. This includes the uses of telehealth not only for supervisory practices, but also for direct intervention via the behavior technician. Moreover, with risks safely mitigated, the pandemic even resulted in increased access to treatment for some learners. Still, these changes require systematic evaluation. The current symposium addresses these needs. The first paper examines the outcomes achieved with the use of telehealth at the individual and group level across different types of learners receiving varying intensities of treatment. The second paper provides an analysis of outcome data for a sample of learners and discussed in relation to learner specific variables, barriers overcome, and treatment modalities. The symposium will conclude with a discussion of the two papers and recommendations for further outcome research.
Instruction Level: Intermediate
Keyword(s): Insurance-funded, Outcomes, Telehealth
Target Audience: Data analysis, familiarity with insurance-funded ABA services, familiarity with standardized assessments and skill acquisition data
Learning Objectives: At the conclusion of the presentation, participants will be able to: (1) describe at least 3 variables in need of investigation by behavior analysts related to learner outcomes from telehealth services; (2) describe the relationship between rates of skill acquisition, treatment modality, proportion of recommended treatment hours received, and learner variables including telehealth prerequisite skills; (3) describe at least 2 factors correlating with improved learner outcomes.
An Examination of Telehealth and the Outcomes Achieved Across Various Types of Learners
GINGER R. RAABE (The ABRITE Organization), Valerie R. Rogers (The ABRITE Organization), Janice Frederick (The ABRITE Organization)
Abstract: The importance of a research practitioner approach within the field of behavior analysis has never been more important than in the presence of the current context. The pandemic has created what might be considered a paradigm shift in the delivery of behavior analytic services. To sustain access to services, telepractice was explored sparking additional questions in need of investigation. Within the arena of autism treatment and medical necessity, behavior analysts are continuing to navigate changes put forth by the various funders and continued examination of the outcomes produced would benefit the clinicians and the children and families served. The shift towards telehealth at all levels of service delivery has created new questions to be explored. Is telehealth at the behavior technician level effective? For what type of learner is telehealth effective? Do learners make the same, less than or more gains with this new service mode? This presentation will address these questions and examine the outcomes that were achieved with the use of telehealth at the individual and group level across various types of learners with autism receiving various amounts of service delivery in this fashion. In addition, the discussion will focus on access and medical necessity.

Pandemic Silver Linings: An Investigation of Parameters Related to Individual Learner Outcomes for Insurance-Funded Applied Behavior Analysis Intervention

VALERIE R. ROGERS (The ABRITE Organization), Ginger R. Raabe (The ABRITE Organization), Janice Frederick (The ABRITE Organization)

The COVID-19 pandemic has changed the way insurance-funded intervention has been implemented for many learners with autism including modifications in treatment modality, intensity of treatment, and overall access to intervention. The pandemic provided rare treatment conditions for many learners and therefore necessitates ongoing investigation of the outcomes associated with these conditions. Examples of such conditions include learners receiving direct behavior technician intervention via telehealth and school aged children receiving comprehensive treatment programs given increased availability. The current paper provides a refined analysis of individual learner outcome data for a set of learners for whom barriers to accessing treatment were overcome. Specifically, outcome data for a sample of different learners receiving ABA insurance-funded treatment during the pandemic will be presented and discussed in relation to learner specific variables. An analysis of skill acquisition data in relation to variables such as age, modality of intervention, proportion of recommended treatment hours received, standardized assessment results, and treatment goals met will be presented across multiple participants. Results are discussed in terms of factors correlating with improved outcomes, removing common barriers to treatment, and providing support for insurance funded ABA treatment under these conditions. The need for additional outcome analyses and future research are discussed.




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