Saturday, September 7, 2024
9/7/2024
Under-treatment of mental health problems remains a major issue in the US, especially for youth, people of color, and individuals with low incomes. Technology may help reduce disparities in and expand the reach of mental health services. However, the newest technologies, such as generative AI, remain fraught with perils such as hallucinations. Therefore, rather than using AI to directly interact with clients, we will harness generative AI to provide training to mental health support providers, with the ultimate goal of increasing accessibility of mental health services and improving mental health outcomes for those receiving care. The goal of this research project is to develop and evaluate an automated, scalable system for delivering experiential training to mental healthcare providers. Specifically, we propose to develop a multi-agent training environment to provide interactive and experiential training on the micro- skills and underlying common factors for both lay counselors and paraprofessionals. Our training environment consists of three components: Virtual Patient, Assessor Agents, and Trainer Agents. Our proposal has four aims. During Aim 1, we will develop and evaluate a set of LLM-based Virtual Patients (VPs) that (a) realistically depict a wide range of common clinical problems (e.g., depression, job-related stress, ADHD, and suicidality), (b) engage in coherent conversations with trainees, and (c) present typical counseling challenges, such as addressing resistance to sharing problems in depth. During Aim 2, we will develop an Assessor Agent capable of automatically assessing the micro-skills used by the trainee, as well as how the trainee accomplishes higher-level segment goals (common factors). During Aim 3, we will develop a Trainer Agent capable of interacting with trainees, the Assessor Agent module, and the Virtual Patient module to achieve optimal training goals. During Aim 4, we will recruit 7Cups supporters to use our multi-agent training environment to evaluate its impacts on the training outcomes. RELEVANCE (See instructions): This study will lead to the creation and evaluation of an innovative approach for delivering clinical common factors and micro-skills experiential training to lay and paraprofessional mental healthcare providers. Results from this study are likely to generalize to and inform the evolution of many online mental health services and offline mental health support settings, including, for example, training for volunteers staffing suicide hotlines, social workers, and nurses.
HHS’ Tracking Accountability in Government Grants System (TAGGS) website provides access to detailed descriptions of grants, loans, aggregated direct payments and other types of financial assistance awarded by the HHS Operating Divisions (OPDIVs) and the Office of the Secretary Staff Divisions (STAFFDIVs).
