DARA: Development of a Chatbot Support System for an Anxiety Reduction Digital Intervention; Using Actor Network Theory to Analyze Digital Mental Health Interventions for Individuals of Low Socioeconomic Status
Lynch, Annabel, School of Engineering and Applied Science, University of Virginia
Barnes, Laura, EN-Eng Sys and Environment, University of Virginia
Ferguson, Sean, EN-Engineering and Society, University of Virginia
The prevalence of mental health conditions, such as anxiety and depression, has increased in the US in recent decades. Unfortunately, only about half of the US population suffering from these conditions will receive treatment. With this level of burden, treating people one-on-one in a traditional clinical setting will never meet the existing needs of mental illness intervention. People of low socioeconomic status (SES) are more likely to suffer from mental illness, as well as less likely to seek treatment due to lack of resources.
The spread of mobile and web-based technologies to address health priorities has evolved into a new field of digital mental health (DMH) interventions. The digital technologies targeted for mental illness treatments rely on symptom monitoring and self-engagement. Even though there is evidence that DMH interventions are associated with improved treatment outcomes, studies have not been able to show their full potential due to high attrition rates and common premature dropouts.
The technical thesis proposes a chatbot support system for an anxiety reduction digital intervention. MindTrails is a research program at UVA that provides free multi-session training programs for anxious individuals. It uses cognitive bias modification training to promote healthier, flexible thinking patterns. The capstone team partnered with MindTrails to address high attrition rates among participants. In efforts to increase engagement, the team assessed the feasibility of a conversational agent to assist users during training sessions. This conversational agent was developed due to previous shortcomings of human coaching and to better address the needs of anxious individuals.
The STS research expanded upon the work of my technical project. When exploring the field of digital mental health, I became excited about the increased accessibility and lower cost of
intervention options. This technology has the potential to treat under-served populations, particularly those of low socioeconomic status and those living in low-income countries. Digital mental health interventions cannot solve the global mental health crisis over night, but it is a step towards improving healthcare disparities. Low resource settings provide difficulties for administering digital treatments, but there have been successful outcomes. There was a great emphasis on sociocultural factors which showed increased trust through local providers and familiar delivery methods.
I thoroughly enjoyed my capstone and STS research this year. It’s fulfilling to see the social and ethical implications technology can provide to society. Mental health conditions can affect anyone, and everyone deserves the right to healthcare and proper treatment. We must be cognizant of disparities around us and take the opportunity to aid others when we can. The field still has much work to be done, but I looked forward to the growth and popularity of digital mental health technologies.
BS (Bachelor of Science)
Digital health, Mental health, Low SES, Low income, Actor network theory
School of Engineering and Applied Science
Bachelor of Science in Systems Engineering
Technical Advisor: Laura Barnes
STS Advisor: Sean Ferguson
Technical Team Members: Disha Patel, Aparna Ramanan, Rob Schwartz
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