scholarly journals Towards an Artificially Empathic Conversational Agent for Mental Health Applications: System Design and User Perceptions

10.2196/10148 ◽  
2018 ◽  
Vol 20 (6) ◽  
pp. e10148 ◽  
Author(s):  
Robert R Morris ◽  
Kareem Kouddous ◽  
Rohan Kshirsagar ◽  
Stephen M Schueller
Keyword(s):  
Mental Health ◽  
System Design ◽  
Conversational Agent ◽  
User Perceptions ◽  
Health Applications

scholarly journals Towards an Artificially Empathic Conversational Agent for Mental Health Applications: System Design and User Perceptions (Preprint)

2018 ◽  
Author(s):  
Robert R Morris ◽  
Kareem Kouddous ◽  
Rohan Kshirsagar ◽  
Stephen M Schueller
Keyword(s):  
Mental Health ◽  
Controlled Study ◽  
Conversational Agent ◽  
Conversational Agents ◽  
Human Capabilities ◽  
User Perceptions ◽  
Ethical Implications ◽  
System P ◽  
Mental Health Interventions ◽  
Health Applications

BACKGROUND Conversational agents cannot yet express empathy in nuanced ways that account for the unique circumstances of the user. Agents that possess this faculty could be used to enhance digital mental health interventions. OBJECTIVE We sought to design a conversational agent that could express empathic support in ways that might approach, or even match, human capabilities. Another aim was to assess how users might appraise such a system. METHODS Our system used a corpus-based approach to simulate expressed empathy. Responses from an existing pool of online peer support data were repurposed by the agent and presented to the user. Information retrieval techniques and word embeddings were used to select historical responses that best matched a user’s concerns. We collected ratings from 37,169 users to evaluate the system. Additionally, we conducted a controlled experiment (N=1284) to test whether the alleged source of a response (human or machine) might change user perceptions. RESULTS The majority of responses created by the agent (2986/3770, 79.20%) were deemed acceptable by users. However, users significantly preferred the efforts of their peers (P<.001). This effect was maintained in a controlled study (P=.02), even when the only difference in responses was whether they were framed as coming from a human or a machine. CONCLUSIONS Our system illustrates a novel way for machines to construct nuanced and personalized empathic utterances. However, the design had significant limitations and further research is needed to make this approach viable. Our controlled study suggests that even in ideal conditions, nonhuman agents may struggle to express empathy as well as humans. The ethical implications of empathic agents, as well as their potential iatrogenic effects, are also discussed.

Rewards in Mental Health Applications for Aiding with Depression: A Meta-analysis

2021 ◽  
pp. 197-206
Author(s):  
Stephanie Six ◽  
Maggie Harris ◽  
Emma Winterlind ◽  
Kaileigh Byrne
Keyword(s):  
Mental Health ◽  
Meta Analysis ◽  
Health Applications

scholarly journals Changes to the Psychiatric Chatbot Landscape: A Systematic Review of Conversational Agents in Serious Mental Illness: Changements du paysage psychiatrique des chatbots: une revue systématique des agents conversationnels dans la maladie mentale sérieuse

2020 ◽  
pp. 070674372096642
Author(s):  
Aditya Nrusimha Vaidyam ◽  
Danny Linggonegoro ◽  
John Torous
Keyword(s):  
Mental Health ◽  
Systematic Review ◽  
Bipolar Disorder ◽  
Mental Illness ◽  
Serious Mental Illness ◽  
Therapeutic Efficacy ◽  
Digital Tools ◽  
Conversational Agent ◽  
Conversational Agents ◽  
Diagnostic Quality

Objective: The need for digital tools in mental health is clear, with insufficient access to mental health services. Conversational agents, also known as chatbots or voice assistants, are digital tools capable of holding natural language conversations. Since our last review in 2018, many new conversational agents and research have emerged, and we aimed to reassess the conversational agent landscape in this updated systematic review. Methods: A systematic literature search was conducted in January 2020 using the PubMed, Embase, PsychINFO, and Cochrane databases. Studies included were those that involved a conversational agent assessing serious mental illness: major depressive disorder, schizophrenia spectrum disorders, bipolar disorder, or anxiety disorder. Results: Of the 247 references identified from selected databases, 7 studies met inclusion criteria. Overall, there were generally positive experiences with conversational agents in regard to diagnostic quality, therapeutic efficacy, or acceptability. There continues to be, however, a lack of standard measures that allow ease of comparison of studies in this space. There were several populations that lacked representation such as the pediatric population and those with schizophrenia or bipolar disorder. While comparing 2018 to 2020 research offers useful insight into changes and growth, the high degree of heterogeneity between all studies in this space makes direct comparison challenging. Conclusions: This review revealed few but generally positive outcomes regarding conversational agents’ diagnostic quality, therapeutic efficacy, and acceptability, which may augment mental health care. Despite this increase in research activity, there continues to be a lack of standard measures for evaluating conversational agents as well as several neglected populations. We recommend that the standardization of conversational agent studies should include patient adherence and engagement, therapeutic efficacy, and clinician perspectives.

scholarly journals 116: Effect of an automated conversational agent on postpartum mental health: A randomized, controlled trial

2020 ◽  
Vol 222 (1) ◽  
pp. S91
Author(s):  
Sanaa Suharwardy ◽  
Maya Ramachandran ◽  
Stephanie A. Leonard ◽  
Anita Gunaseelan ◽  
Athena Robinson ◽  
...  
Keyword(s):  
Mental Health ◽  
Randomized Controlled Trial ◽  
Controlled Trial ◽  
Conversational Agent ◽  
Randomized Controlled ◽  
Postpartum Mental Health

Robotic Emotion Monitoring for Mental Health Applications: Preliminary Outcomes of a Survey

2021 ◽  
pp. 481-485
Author(s):  
Marat Rostov ◽  
Md Zakir Hossain ◽  
Jessica Sharmin Rahman
Keyword(s):  
Mental Health ◽  
Health Applications

Presence-Inducing Media for Mental Health Applications

2015 ◽  
pp. 283-332 ◽  
Author(s):  
Giuseppe Riva ◽  
Cristina Botella ◽  
Rosa Baños ◽  
Fabrizia Mantovani ◽  
Azucena García-Palacios ◽  
...  
Keyword(s):  
Mental Health ◽  
Health Applications
Sign in / Sign up

Export Citation Format

Share Document