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An Evolutionary Bootstrapping Development Approach for a Mental Health Conversational Agent.

Authors :
HOUSEH, Mowafa
SCHNEIDER, Jens
AHMAD, Kashif
ALAM, Tanvir
Al-THANI, Dena
SIDDIG, Mohamed Ali
FERNANDEZ-LUQUE, Luis
QARAQE, Marwa
ALFUQUHA, Ala
SAXENA, Shekhar
Source :
Studies in Health Technology & Informatics; 2019, Vol. 262, p228-231, 4p, 1 Color Photograph
Publication Year :
2019

Abstract

Conversational agents are being used to help in the screening, assessment, diagnosis, and treatment of common mental health disorders. In this paper, we propose a bootstrapping approach for the development of a digital mental health conversational agent (i.e., chatbot). We start from a basic rule-based expert system and iteratively move towards a more sophisticated platform composed of specialized chatbots each aiming to assess and pre-diagnose a specific mental health disorder using machine learning and natural language processing techniques. During each iteration, user feedback from psychiatrists and patients are incorporated into the iterative design process. A survival of the fittest approach is also used to assess the continuation or removal of a specialized mental health chatbot in each generational design. We anticipate that our unique and novel approach can be used for the development of conversational mental health agents with the ultimate goal of designing a smart chatbot that delivers evidence-based care and contributes to scaling up services while decreasing the pressure on mental health care providers. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
09269630
Volume :
262
Database :
Complementary Index
Journal :
Studies in Health Technology & Informatics
Publication Type :
Academic Journal
Accession number :
137369831
Full Text :
https://doi.org/10.3233/SHTI190060