R34 – Remote Training in Evidence-based Practices for Clinicians Who Work with Migrant Workers
Principal Investigators
Gino Aisenberg, PhD, Associate Professor, School of Social Work
Zoran Popović, PhD, Professor, Paul G. Allen School of Computer Science and Engineering
Patricia Areán, PhD, Professor, Department of Psychiatry & Behavioral Sciences
Patrick Raue, PhD, Professor, Department of Psychiatry & Behavioral Sciences
Project Description
This study is a partnership between The University of Washington’s School of Social Work and Paul G. Allen School of Computer Science and Engineering; The Social Work Department at Heritage University in Toppenish, Washington; and The Yakima Valley Farm Workers Clinic.
This study will expand and enhance training in evidence-based psychosocial interventions (EBPIs) by designing and testing a computerized training program that is based on adaptive training algorithms. We hypothesize that by simplifying training and supplementing classroom curriculum, we can enhance clinical ability to deliver treatment more competently, more quickly, and with a higher quality of care.
Clinical Trials number: NCT03515226
| Setting | Heritage University Department of Social Work in Toppenish, Washington, and Yakima Valley Farm Workers Clinic |
| Population | Undergraduate social work students and migrant workers receiving services |
Intervention and/or Implementation Strategy Designed or Redesigned
| Intervention | Computerized training program for evidence-based psychosocial interventions (tCBT) based on adaptive training algorithms |
| Implementation Strategy | Qualitative interviews with students and training experts, development and modification of computerized training program, and randomized controlled trial comparing enhanced computerized training to traditional methods |
Impact
Enhanced clinical ability to deliver treatment more competently, more quickly, and with higher quality of care by simplifying training and supplementing classroom curriculum for evidence-based psychosocial interventions
Designing the Intelligent Tutoring System
This short presentation, initially given at the 2021 International Symposium on Human Factors and Ergonomics in Health Care by Emily Friedman, outlines our design process for creating an intelligent tutoring system (ITS) that would supplement in-person learning of mental health professionals and improve competency in essential skills while being cost-effective and scalable.
Project Publications
Modernizing Training in Psychotherapy Competencies With Adaptive Learning Systems: Proof of Concept
Research on Social Work Practice 31(1); 2020 · Pubmed · Publisher
Authors
Brenna N. Renn, Patricia A. Areán, Patrick J. Raue, Eugene Aisenberg, Emily C. Friedman, Zoran Popović
Abstract
Purpose: This proof-of-concept study assessed the feasibility, acceptability, and effectiveness of an intelligent tutoring system (ITS) as a classroom adjunct to improve training bachelor of social work (BSW) students in client engagement strategies.
Methods: We codeveloped the ITS with 11 undergraduate students and pilot tested it with six BSW students enrolled in a class on telephone-based cognitive behavioral therapy (tCBT). Student competencies in tCBT were assessed by expert review of role-plays. We also examined time spent using ITS and relation with competency.
Results: The majority of students (81.8%) in Wave 1 and all of the students who submitted role-plays in Wave 2 passed the clinical skills role-play. Students advancing through the ITS more quickly had better tCBT competency ratings than those progressing more slowly.
Discussion: One of the most challenging aspects of training is how to competently deliver evidence-based practices. ITS has the potential to streamline and scale such training.