Developing an Implementation Model for ADHD Intervention in Community Clinics: Leveraging Artificial Intelligence and Digital Technology

• Published in: Cognitive and behavioral practice 2024-11, Vol.31 (4), p.482-497
• Main Authors: Sibley, Margaret H., Bickman, Leonard, Atkins, David, Tanana, Michael, Coxe, Stefany, Ortiz, Mercedes, Martin, Pablo, King, Julian, Monroy, Jessica M., Ponce, Teodora, Cheng, Jenny, Pace, Brian, Zhao, Xin, Chawla, Varun, Page, Timothy F.
• Format: Article
• Language: English
• Subjects: ADHD; artificial intelligence; community mental health; digital technology
• ISSN: 1077-7229
• DOI: 10.1016/j.cbpra.2023.02.001

•STAND is an evidence-based treatment for adolescent ADHD that focuses on engagement.•Provides a summary of the development of a community implementation model for STAND.•Features include use of artificial intelligence to monitor fidelity and digitizing clinician resources.•Pilot work in three community agencies suggests acceptability, feasibility, and fidelity to the model. Implementation of behavior therapy for ADHD faces challenges in community settings. We describe development of a community-based implementation model for adolescent ADHD behavior therapy (Supporting Teens’ Autonomy Daily; STAND) blended with Motivational Interviewing (MI). A stakeholder-engaged development approach is used based on the Exploration, Preparation, Implementation, Sustainment (EPIS) framework. Resulting model features include: (a) task-shifting supervision from experts to agency supervisors, (b) holding bi-weekly technical assistance drop-ins to provide training and implementation supports, (c) MI integrity monitoring and feedback by artificial intelligence (AI), (d) AI-generated metrics for STAND content fidelity, (e) digitizing resources (manual, worksheets, tips, videos) on a clinician dashboard, (f) creating visual displays of feedback using badges and graphs, and (g) adding a rapport-building session prior to manualized content. We conducted stakeholder focus groups (N = 32) and two pilot studies to evaluate the new STAND AI measurement tool and revised service-delivery model (N = 6 therapists, 7 youth and parents, 3 agency supervisors). Results revealed advantages and disadvantages of the model, supported the promise of a STAND AI fidelity measurement tool, and indicated initial feasibility, acceptability, and agency engagement in STAND’s community-based implementation model. We discuss future directions for continued iterative development and testing. Video examples are included as supplementary material.