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.


50th Annual Convention; Philadelphia, PA; 2024

Event Details

Previous Page


Symposium #160
CE Offered: BACB — 
Effective Supervision Practices to Improve Quality Service Delivery
Saturday, May 25, 2024
5:00 PM–5:50 PM
Marriott Downtown, Level 5, Grand Ballroom Salon CD
Area: OBM/AUT; Domain: Applied Research
Chair: Santino LoVullo (LEARN Behavioral)
CE Instructor: Abigail Blackman, Ph.D.
Abstract: Effective supervision skills are crucial for all Board Certified Behavior Analysts (BCBAs). The Behavior Analyst Certification Board outlines the requirements for ethical supervision to be provided (BACB, 2023). Further, published research articles outline best practices in supervision for aspiring, newly certified, and tenured BCBAs (e.g., Sellers et al., 2016; Valentino et al., 2016). Despite the information available to BCBAs, there is a lack of integration of information on how to effectively engage in supervisory practices. The first talk of this symposium will focus on practices extended from clinical psychology and how they can be applied in behavior analytic practice (Lopez et al., in preparation). The second talk will focus on results of a survey that reveal that not all BCBAs are engaging in best practices for procedural integrity. Using the information gathered, the presenters will discuss how to overcome barriers BCBAs report in practice to make sound organizational processes (Colon et al., in preparation). The final talk will highlight data from organizations across the United States that shows ways to improve quality service delivery and decrease turnover by engaging in best practice supervision standards (Blackman et al., in preparation). All of the information provided will be geared toward how effective supervision will lead to higher quality service delivery for consumers served.
Instruction Level: Intermediate
Keyword(s): Processes, Quality, Supervision, Turnover
Target Audience: Intermediate - certified or aspiring BCBA/BCBA-D; clinical supervisors; organizational leaders
Learning Objectives: At the conclusion of the presentation, participations will be able to: (1) Attendees will describe the benefits of effective supervision; (2) Attendees will be able to discuss one way to evaluate needs at their organization; (3) Attendees will be able to describe three ways to analyze integrity data to make informed organizational decisions that impact quality and turnover.
Oranizational Processes to Support Best Practice Supervision
ANDY LOPEZ-WILLIAMS (NYSABA), Megan Brown (ADHD & Autism Psychological Services and Advocacy), Vilas Sawrikar (University of Edinburgh), Abigail Blackman (Behavior Science Technology)
Abstract: There continues to be an increase in the number of Board Certified Behavior Analysts (BCBA) who enter the field (BACB, 2023). Recent survey research suggests the BCBA turnover is occurring across organizations. There are a number of variables that contribute to BCBA turnover; however, the overarching trend was that there is a lack of support from upper management and ongoing learning opportunities to expand their skills (Blackman et al., under review). It is the organization’s responsibility to put processes in place to support their supervisors in engaging in best practice supervision, as this impacts provider skill, client outcomes, and retention. Taking information from clinical psychology literature, this presentation will outline the effects of and evolution of organizational processes at a mid-size organization on supervisor and provider skill. A discussion surrounding how each intervention was selected, why the processes evolved, and the use of data to guide those changes will be discussed.
Procedural Integrity Data Collection Practices
CANDICE COLÓN (LEARN ), Santino LoVullo (LEARN Behavioral), Abigail Blackman (Behavior Science Technology)
Abstract: Monitoring procedural integrity in clinical settings may entail: observation, data collection, progress tracking, data analysis, and feedback. In addition, throughout the course of procedural integrity monitoring, data analysis may indicate that modifications to the client’s plan may be necessary to support progress and/or that additional training is necessary to support the correct implementation of the planned intervention. In relation to ongoing support and training, there is an estimated turnover of 45-75% annually for technicians who provide direct applied behavior analysis (ABA) services (Molko, 2018; Sundberg, 2016) for clients diagnosed with autism. Such high turnover rates can affect client outcomes and success (Szczech, 2008) and may result from a lack of evidence-based initial and ongoing training procedures (DiGennaro Reed & Henley, 2015). Given the importance of procedural integrity to support the training process and quality of services, this presentation will share common barriers to its implementation that were found via a survey of BCBAs and discuss solutions to these barriers in an effort to facilitate consistent implementation of the procedural integrity monitoring process.

Large-Scale Procedural Integrity Data: Predictors of Turnover and Quality Service Deliver

ABIGAIL BLACKMAN (Behavior Science Technology), Tricia Glick (Behavior Science Technology), Troy Glick (Behavior Science Technology)

Organizational leaders should focus on creating sustainable systems to support their supervisors in providing high-quality supervision to staff. One of the behaviors that supervisors must engage in to effectively support their staff is collecting data on integrity. Integrity is the extent to which a procedure is implemented as designed (Gresham 2004; Sanetti & Kratchowill, 2009). Research has revealed a correlation between higher levels of integrity and greater clinical outcomes (e.g., quicker skill acquisition; e.g., DiGennaro Reed et al., 2007). Unfortunately, recent survey results revealed that these data are not often collected, tracked, or analyzed in practice. Therefore, this presentation will discuss: 1) how organizations can evaluate their current processes to determine their efficiency and make necessary changes (Diener et al., 2009; McGee & Crowley-Koch, 2019); 2) how and when organizations should collect procedural integrity data; and 3) how to analyze these data at the individual provider, team, and organization levels to impact provider performance and quality service delivery. Additionally, the benefits of aggregating and analyzing integrity data and how the data can be used to inform retention and training and development initiatives will be discussed.




Back to Top
Modifed by Eddie Soh