🤖 AI Summary
This study addresses the challenge of aligning patient self-reports with clinical intuition in intensive outpatient treatment for posttraumatic stress disorder (PTSD). Through a two-phase qualitative interview process, it gathers perspectives from U.S. veteran patients and prolonged exposure (PE) therapists, integrating three human-centered theoretical frameworks—distributed cognition, situated learning, and infrastructural inversion—to design and analyze a prototype clinical decision support system (CDSS) tailored for PTSD care. The research identifies key opportunities for CDSS application in session review and patient conceptualization, while also uncovering institutional and contextual barriers to its deployment within the Veterans Affairs healthcare system. Centered on alignment theory, the study proposes design principles to enhance the CDSS’s applicability and effectiveness in mental health clinical practice.
📝 Abstract
Psychotherapy delivery relies on a negotiation between patient self-reports and clinical intuition. Growing evidence for technological support of psychotherapy suggests opportunities to aid the mediation of this tension. To explore this prospect, we designed a prototype of a clinical decision support system (CDSS) for treating veterans with post-traumatic stress disorder in a Prolonged Exposure (PE) therapy intensive outpatient program. We conducted a two-phase interview study to collect perspectives from practicing PE clinicians and former PE patients who are United States veterans. Our analysis distills opportunities for a CDSS (e.g., offering homework review at a glance, aiding patient conceptualization) and larger challenges related to context and deployment (e.g., navigating Veterans Affairs). By reframing our findings through three human-centered perspectives (distributed cognition, situated learning, infrastructural inversion), we highlight the complexities of designing a CDSS for psychotherapists in this context and offer theory-aligned design considerations.