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

arXiv: https://arxiv.org/abs/2401.03631 · HTML: https://mlsanity.com/paper/2401.03631/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 2 of its 12 references that are in the map.
- First posted on arXiv 8 Jan 2024.

## Builds on (most cited first, 2 of 2)

- [Human-AI Collaboration Enables More Empathic Conversations in Text-based Peer-to-Peer Mental Health Support](https://mlsanity.com/paper/2203.15144/) (2022)
- [Rasa: Open Source Language Understanding and Dialogue Management](https://mlsanity.com/paper/1712.05181/) (2017)

## Built on by (most cited first, 2 of 2)

- [RedditESS: A Mental Health Social Support Interaction Dataset -- Understanding Effective Social Support to Refine AI-Driven Support Tools](https://mlsanity.com/paper/2503.21888/) (2025)
- [AI Standardized Patient Improves Human Conversations in Advanced Cancer Care](https://mlsanity.com/paper/2505.02694/) (2025)

## Abstract (arXiv)

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.