Our evidenced-based methodology combines multiple areas of expertise to improve clinician capacity, simplify usability, and sustain quality in mental health treatments. Our aim is to create a collaborative and iterative environment, provide a strong foundation for every project, and establish a flexible, nonlinear framework that evolves as we learn from our progress over time.
We work to understand environmental factors, define the needs of everyone involved, and identify specific problems we want to solve.
We examine the information gathered during the discover phase, process this information, and brainstorm concepts for potential solutions.
We develop low-fidelity prototypes of our concepts, test these prototypes with users, and refine our concepts based on findings.
We develop high-fidelity prototypes, implement a pilot study, and rethink our approach based on its performance in a real-world setting.
Here are some examples of how DDBT has been applied to studies
Lessons Learned from Designing an Asynchronous Remote Community Approach for Behavioral Activation Intervention for Teens
Iterative redesign of a caregiver-mediated intervention for use in educational settings
Designing the Future of Children’s Mental Health Services
Modernizing Training in Psychotherapy Competencies With Adaptive Learning Systems: Proof of Concept
Parallel Journeys of Patients with Cancer and Depression: Challenges and Opportunities for Technology-Enabled Collaborative Care