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Computer Science > Human-Computer Interaction

arXiv:2401.03631 (cs)
[Submitted on 8 Jan 2024]

Title:Bridging the Skills Gap: Evaluating an AI-Assisted Provider Platform to Support Care Providers with Empathetic Delivery of Protocolized Therapy

Authors:William R. Kearns, Jessica Bertram, Myra Divina, Lauren Kemp, Yinzhou Wang, Alex Marin, Trevor Cohen, Weichao Yuwen
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Abstract:Despite the high prevalence and burden of mental health conditions, there is a global shortage of mental health providers. Artificial Intelligence (AI) methods have been proposed as a way to address this shortage, by supporting providers with less extensive training as they deliver care. To this end, we developed the AI-Assisted Provider Platform (A2P2), a text-based virtual therapy interface that includes a response suggestion feature, which supports providers in delivering protocolized therapies empathetically. We studied providers with and without expertise in mental health treatment delivering a therapy session using the platform with (intervention) and without (control) AI-assistance features. Upon evaluation, the AI-assisted system significantly decreased response times by 29.34% (p=0.002), tripled empathic response accuracy (p=0.0001), and increased goal recommendation accuracy by 66.67% (p=0.001) across both user groups compared to the control. Both groups rated the system as having excellent usability.
Comments: Accepted: AMIA Annual Symposium 2023. To appear as: Kearns W, Bertram J, Divina M, Kemp L, Wang Y, Marin A, Cohen T, Yuwen W. Bridging the Skills Gap: Evaluating an AI-Assisted Provider Platform to Support Care Providers with Empathetic Delivery of Protocolized Therapy. AMIA Annual Symposium Proceedings 2023. American Medical Informatics Association
Subjects: Human-Computer Interaction (cs.HC); Artificial Intelligence (cs.AI); Computation and Language (cs.CL); Information Retrieval (cs.IR); Machine Learning (cs.LG)
Cite as: arXiv:2401.03631 [cs.HC]
  (or arXiv:2401.03631v1 [cs.HC] for this version)
  https://doi.org/10.48550/arXiv.2401.03631

Submission history

From: William Kearns [view email]
[v1] Mon, 8 Jan 2024 02:23:17 UTC (542 KB)
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