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

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.
Source :
Cognitive & Behavioral Practice; Nov2024, Vol. 31 Issue 4, p482-497, 16p
Publication Year :
2024

Abstract

• 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. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
10777229
Volume :
31
Issue :
4
Database :
Supplemental Index
Journal :
Cognitive & Behavioral Practice
Publication Type :
Academic Journal
Accession number :
180114712
Full Text :
https://doi.org/10.1016/j.cbpra.2023.02.001