Enhancing the conversational agent with an emotional support system for mental health digital therapeutics

Abstract

As psychological diseases become more prevalent and are identified as the leading cause of acquired disability, it is essential to assist people in improving their mental health. Digital therapeutics (DTx) has been widely studied to treat psychological diseases with the advantage of cost savings. Among the techniques of DTx, a conversational agent can interact with patients through natural language dialog and has become the most promising one. However, conversational agents' ability to accurately show emotional support (ES) limits their role in DTx solutions, especially in mental health support. One of the main reasons is that the prediction of emotional support systems does not extract effective information from historical dialog data and only depends on the data derived from one single-turn interaction with users. To address this issue, we propose a novel emotional support conversation agent called the STEF agent that generates more supportive responses based on a thorough view of past emotions. The proposed STEF agent consists of the emotional fusion mechanism and strategy tendency encoder. The emotional fusion mechanism focuses on capturing the subtle emotional changes throughout a conversation. The strategy tendency encoder aims at foreseeing strategy evolution through multi-source interactions and extracting latent strategy semantic embedding. Experimental results on the benchmark dataset ESConv demonstrate the effectiveness of the STEF agent compared with competitive baselines.

ChatGPT as a coping mechanism for social isolation: An analysis of user experiences and perceptions of social support

“…Prior studies, such as the work of Valtolina and Hu (2021), have demonstrated the potential of AIbased conversational agents in providing social support and mitigating feelings of loneliness among older adults. This is further evidenced by the findings of Jones et al (2021), indicating the effectiveness of an AIbased conversational agent in reducing loneliness within a retirement community, and Wang et al (2023), highlighting the positive impact on individuals with mental health conditions.…”

Virtual Agents in DTx: Focusing on Usability and Therapeutic Effectiveness

“…Our study ventured into the relatively unexplored field of digital therapeutics (DTx), emphasizing the influence of a virtual agent on usability and therapeutic outcomes-a synergy suggested by prior research [6]. Through a month-long longitudinal study, we provided concrete data on how the agent's design features correlate with therapeutic efficacy and usability.…”

“…Particularly in DTx, where long-term use and digital therapeutic alliance, which can be referred to as the relationship between DTx and user, are crucial, the importance of agents is accentuated, given the fact that agents can boost digital alliance [5]. Furthermore, in the prevalent digital therapeutics field of mental healthcare, enhancing sociability to foster agent-user relationships and emotional support added a secondary benefit [6]. Numerous prior studies have thus provided insights into the design and role of agents in the digital healthcare field.…”